diff --git a/docs/CREATING_CM.md b/docs/CREATING_CM.md new file mode 100644 index 00000000..2b81beba --- /dev/null +++ b/docs/CREATING_CM.md @@ -0,0 +1,65 @@ +# CREATING CM directories + +*** BY FAR THE SAFEST WAY IS TO USE QUICKSCRAPE *** + +Any other method is likely to lead to fies out of sync unless you are acreful with what you are doing. +However it can be sometimes useful to create CMDirs from single files. +This documentation may not have been thoroughly checked. + +## Input + +For a command: + +``` norma -i foo/bar/a12345.suffix -o plugh/xyzzy``` + +the system will create a CMDir of the form: + +``` plugh/xyzzy/a12345``` + +It will then use ```suffix``` to create either reserved files (e.g. ```fulltext.xml```) in the CMDir or reserved subdirectories +of the form: + +``` plugh/xyzzy/a12345/image``` + +to hold the images. As there can be several images (e.g. ```plugh/xyzzy/a12345.png``` ) we use the given names, such as: + +``` plugh/xyzzy/a12345/image/a12345.png``` + +This is verbose and also leads to a separate CMDir for each image. + +## File types + +The following suffixes are supported: + +### Single reserved files + +The CMDir is generated from the ```-o mydir``` parameter and the input baseNames ```(FilenameUtile.getBaseName())``` + +```mydir/bar``` is the CMDir. + +```foo/bar.xml``` is copied to ```mydir/bar/fulltext.xml``` +```foo/bar.html``` is copied to ```mydir/bar/fulltext.html``` +```foo/bar.pdf``` is copied to ```mydir/bar/fulltext.pdf``` +```foo/bar.epub``` is copied to ```mydir/bar/fulltext.epub``` +```foo/bar.txt``` is copied to ```mydir/bar/fulltext.txt``` + +### Image files + +```foo/bar.png``` is copied to ```mydir/bar/image/bar.png``` + +Analogous copies for: + ```gif```, ```jpg```, ```tif``` + +### Supplemental Data files + +```foo/bar.doc``` is copied to ```mydir/bar/supplement/bar.png``` + +Analogous copies for: + ```docx```, ```csv```, ```tex```, ```ppt```, ```pptx```, ... + +### SVG Data files + +```foo/bar.svg``` is copied to ```mydir/bar/svg/bar.svg``` + + + \ No newline at end of file diff --git a/examples/hocr-tesseract-ijsem-140.zip b/examples/hocr-tesseract-ijsem-140.zip new file mode 100644 index 00000000..cce1b2a2 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140.zip differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000026-0-000.pbm2.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000026-0-000.pbm2.png new file mode 100644 index 00000000..35d9f3ef Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000026-0-000.pbm2.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000026-0-000.pbm2.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000026-0-000.pbm2.png.hocr new file mode 100644 index 00000000..b4b1c774 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000026-0-000.pbm2.png.hocr @@ -0,0 +1,736 @@ + + + + + + + + + + + +
+
+

+ 100 + +

+
+
+

+ 0.02 + +

+
+
+

+ 67 + +

+
+
+

+ 81 + +

+
+
+

+ 71 + +

+
+
+

+ 68 A. kentL/Ckyensis NRRL 8—24129T (AY183357) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ A. rifamycinica DSM 46095T (AY083603) + +

+
+
+

+ + +

+
+
+

+ A. pretoriensis NRRL B-24133T (AY183357) + + A. vancoresmycina DSM 44592T (AJ508240) + +

+
+
+

+ + +

+
+
+

+ 93 7 A. lexingtonensis NRRL B-24131T (AY183358) + +

+
+
+

+ + +

+
+
+

+ 74 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 52 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 56 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ A. plumensis SBHS Strp1T (AY262825) + + 91 7 A. tolypomycina DSM 44544T (AJ508241) + + A. balhimycina DSM 44591T (AJ508239) + + A. mediterranei KCTC 1739T (AY125600) + + A. australiensis GY048T (AY183357) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 50 A. saalfe/densis HKI 0457T (DQ792500) + +

+
+
+

+ A. rubida 13.4T (AF222022) + +

+
+
+

+ A. albidoflavus NBRC 100337T (AB327251) + +

+
+
+

+ + +

+
+
+

+ 89 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 95 A. + + {A + +

+
+
+

+ 91 + +

+
+
+

+ + +

+
+
+

+ 857A. + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ A. benzoati/ytica DSM 43387T (AY957506) + + A. albidoflavus IMSNU 22139T (AJ252832) + +

+
+
+

+ 7 A. halotolerans N4-6T (DQOOO196) + +

+
+
+

+ A. echigonensis L02T (AB248535) + +

+
+
+

+ A. niigatensis LC11T (ABZ48537) + +

+
+
+

+ alba DSM 44262T (AF051340) + + coloradensis NRRL 3218T (AF051341) + +

+
+
+

+ A. azurea IMSNU 20053T (AJ400709) + +

+
+
+

+ keratiniphila subsp. nogabecina DSM 44586T (AJ508238) + + . keratiniphi/a subsp. keratiniphi/a DSM 44409T (AJ278496) + + Iurida DSM 43134T (AJ577997) + +

+
+
+

+ 88 i A + + 7 A. + + A. decaplanina DSM 44594T (AJ508237) + +

+
+
+

+ A. japan/ca MG417-CF17T (X77959) + +

+
+
+

+ 85 % A. orientalis IMSNU 20058T (AJ400711) + + 99 + +

+
+
+

+ A. regifaucium GY080T (AY129760) + +

+
+
+

+ 98 + +

+
+
+

+ + +

+
+
+

+ 72 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ A. nigrescens CSC17Ta-90T (DQ486888) + + A. minnesotensis 32U-2T (DQO76842) + +

+
+
+

+ A. jejuensis N7-3T (00000200) + + A. sulphurea DSM 46092T (AF051343) + +

+
+
+

+ A + +

+
+
+

+ + +

+
+
+

+ 100 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 58 + +

+
+
+

+ + +

+
+
+

+ . sacchari K24T (AF223354) + +

+
+
+

+ A. marina Ms392AT (EU329845) + + —A. palatopharyngis 1BDZT (AF479268) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 100 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ A. taiwanensis 0345M-7T (DQ160215) + + A. eurytherma NT202T (AJ000285) + + - A. methanol/ca IMSNU 20055T (AJ249135) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 100 A. thermof/ava N1165T (AF052390) + +

+
+
+

+ + +

+
+
+

+ A. fastidiosa IMSNU 20054T (AJ400710) + +

+
+
+

+ Prauserella rugosa DSM 43194T (AF051342) + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000109-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000109-0-000.pbm.png new file mode 100644 index 00000000..784f114c Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000109-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000109-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000109-0-000.pbm.png.hocr new file mode 100644 index 00000000..2d37d066 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000109-0-000.pbm.png.hocr @@ -0,0 +1,198 @@ + + + + + + + + + + + +
+
+

+ Roseobacter literal/s ATCC 49566T (X78312) + +

+ +

+ Sulfitobacter pontiacus ChLG 1OT (Y13155) + +

+ +

+ Nereida ignava 28M4T (AJ748748) + +

+ +

+ Octadecabacter arcticus 238T (U73725) + +

+ +

+ Phaeobacter ga/Iaeciensis BS107T (Y13244) + +

+ +

+ Mar/novum a/gico/a ATCC 51440T (X78315) + +

+ +

+ Thalassobius mediterraneus CECT 5383T (AJ878874) + +

+ +

+ Ruegeria at/antica IAM 14463T (D88526) + +

+ +

+ Pseudoruegeria aquimaris SW-255T (D0675021) + +

+ +

+ Sagittula stellata E-37T (U58356) + +

+ +

+ Antarctobacter heliothermus EL-219T (Y11552) + +

+ +

+ Roseovarius tolerans EL-172T (Y11551) + +

+ +

+ Roseivivax ha/oto/erans OCh 210T (D85831) + +

+ +

+ Roseivivax ha/odurans OCh 239T (D85829) + +

+ +

+ Salipiger mucosus A3T (AY527274) + +

+ +

+ Donghicola eburneus SW-277T (DQ667965) + +

+ +

+ Lutimaribacter saemankumensis SMK-117T (EU336981) + + Maritimibacter alkaliphilus HTC02654T (DQQ15443) + + Oceanicola nanhaiensis SSO11B1—20T (DQ414420) + +

+ +

+ 54-9 Oceanicola batsensis HTCCZSQ7T (AY424898) + + Ocean/cola marinus AZO-CT (DQ822569) + +

+ +

+ 95.7 Oceanicola granulosus HTC02516T (AY424896) + +

+ +

+ —+: Roseisalinus antarcticus EL-BST (AJ605747) + +

+ +

+ Ketogu/onicigenium vulgare DSM 4025T (AF136849) + +

+ +

+ Jannaschia helgolandensis Hel 1OT (AJ438157) + +

+ +

+ Loktane/la salsi/acus LMG 21507T (AJ440997) + +

+ +

+ Rhodobacter capsu/atus ATCC 1 1 166T (016428) + +

+ +

+ Stappia ste/Iu/ata IAM 12621T (D88525) + +

+
+
+

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

+
+
+

+ + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000117-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000117-0-000.pbm.png new file mode 100644 index 00000000..8d0720c4 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000117-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000117-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000117-0-000.pbm.png.hocr new file mode 100644 index 00000000..d6d1a882 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000117-0-000.pbm.png.hocr @@ -0,0 +1,124 @@ + + + + + + + + + + + +
+
+

+ Providencia sneebia AT (EU587095—EU587100) + +

+ +

+ Providencia sneebia A75 (EU587053—EU587058) + +

+ +

+ 52 Providencia sneebia A91 (EU587059—EU587064) + + 59! Providencia sneebia A102 (EU587071—EU58707G) + + 60l Providencia sneebia A101 (EU587065—EU587070) + +

+ +

+ 56 Providencia burhodogranariea BT (EU587101—EU587106) + + 10° Providencia burhodogranariea B97 (EU587083—EU587088) + + Providencia burhodogranariea B18 (EU587077—EU587082) + + Providencia burhodogranariea D (EU587113—EU587118) + + 100 Providencia burhodogranariea D37 (EU587089-EU587094) + + Providencia stuartii DSM 4539T (EU587024—EU587029) + + Providencia heimbachae DSM 3591T (EU587018—EU587023) + + Providencia a/ca/ifaciens DSM 30120T (EU587047—EU587052) + + Providencia rustigianii DSM 4541T (EU587030—EU587034) + + Providencia vermicola DSM 17385T (EU587041—EU587046) + + Providencia rettgeri DSM 4542T (EU587035—EU587040) + +

+ +

+ 100 Providencia rettgeri C (EU587107—EU587112) + + Proteus mirabi/is Hl4320 (AM942759) + +

+
+
+

+ Photorhabdus Iuminescens TTO1T (BX470251) + + Yersinia pest/s €092 (AL590842) + + 100 Erwinia carotovora subsp. atroseptica SCR|1043 (BX950851) + + 100 Escherichia coli K-12 MG1655 (UOOOQB) + +

+
+
+

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + +

+
+
+

+ 0.02 54 + +

+
+
+

+ 100 + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000158-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000158-0-000.pbm.png new file mode 100644 index 00000000..1256630a Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000158-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000158-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000158-0-000.pbm.png.hocr new file mode 100644 index 00000000..7b86db5a --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000158-0-000.pbm.png.hocr @@ -0,0 +1,224 @@ + + + + + + + + + + + +
+
+

+ + +

+
+
+

+ + +

+
+
+

+ Cytophaga hutch/hsom'iATCC 33406T (M58768) + +

+
+
+

+ 97 Pedobacter sat/tans DSM 1 2145T (AJ4381 73) + + E Sph/hgobacterium spl'r/T/vorum ATCC 33861 T (M587 7 8) + + 6‘ Sph/hgobacter/um thalpoph/Yum DSM 1 1 723T (AJ4381 77) + +

+
+
+

+ 100 Pedobacter lentus DS-4OT (EF4461 46) + + Pedobacler tem'co/a DS—45T (EF4461 47) + + Pedobacter aquatfl/s AR107T (AM1 1 4396) + + 97 $1: Pedobacter alluvionis NWER-II1 1T (EU030688) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 93 Pedobacter roseus CL—G P80T (D01 1 2353) + + —fl. Pedobacter sandarak/hus DS— 2 7T (D02352 2 8) + + Pedobacter borea/I's G-1T (EU030687) + + 65 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ Pedobacter suwonens/s 1 5—5 2T (D009 7 2 7 4) + + 553+: Pedobacz‘er nyac/(ens/s NWG-II14T (EU030686) + + Pedobacter hepar/hus DSM 2366T (AJ4381 7 2) + + Pedobacter afr/canus DSM 1 21 26T (AJ4381 71) + + 100 73 Pedobacter metabo/IpauperWBQ3-71 T (AM491 370) + + Pedobacter duraquae WBQ.1 —25T (AM491 368) + + Pedobacter caen/LMG 22862T (AJ786798) + + ‘00 Pedobacfer steyn/iWB2.3—45T (AM491372) + + —0 Pedobaoter g/hseng/lso/I'Gsoil 104T (AB245371) + + 62 100 Pedobacterpanac/lerrae Gsoil 042T (ABQ45368) + + Pedobacter terrae DS-57T (D0889723) + + Pedobacterp/lsc/um DSM 1 1 725T (AJ4381 74) + + Pedobacter hanfon/us WB3.3-3T (AM491 371 ) + + Pedabacter cg/ocon/I/s A3 7T (AJ4381 70) + + Pedobacfer h/Ma/ayens/s H HS 22T (AJ583425) + + Pedobacter westerhafens/s WBS.3—22T (AM491 369) + +

+
+
+

+ fiddobacter I'nsu/ae DS-39T (EF1 00697) + + Pedobacler koreensis WPCB1 89T (D0092871 ) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + + + +

+
+
+

+ + +

+
+
+

+ 96 + + —o + +

+
+
+

+ 0.01 + +

+
+
+

+ 51 + +

+
+
+

+ + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000174-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000174-0-000.pbm.png new file mode 100644 index 00000000..b78652c8 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000174-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000174-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000174-0-000.pbm.png.hocr new file mode 100644 index 00000000..0cce8bbf --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000174-0-000.pbm.png.hocr @@ -0,0 +1,66 @@ + + + + + + + + + + + +
+
+

+ ‘Rhodoplanes cryptolactis’ DSM 9987 (AB087718) + +

+
+
+

+ + + + + + + + + + + + +

+
+
+

+ Rhodoplanes roseus DSM 5909T (D25313) + + Rhodoplanes elegans A8130T (D2531 1) + +

+ +

+ Strain TUT3530T (AB087717) + +

+ +

+ Blastochlaris viridis ATCC 19567T(D25314) + + Blastochloris sulfoviridis DSM 729T (D86514) + + Rhodopseudomonas palustris ATCC 17001T(D25312) + +

+
+
+

+ Rhodoblastus acidophilus ATCC 25092T (M34128) + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000257-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000257-0-000.pbm.png new file mode 100644 index 00000000..5e672768 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000257-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000257-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000257-0-000.pbm.png.hocr new file mode 100644 index 00000000..54293153 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000257-0-000.pbm.png.hocr @@ -0,0 +1,652 @@ + + + + + + + + + + + +
+
+

+ + +

+
+
+

+ 0.0 + +

+
+
+

+ 59 + +

+
+
+

+ 1 + +

+
+
+

+ 84 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 96 Sphfngomonas yabuuchiae GTC 868T (ABO71955) + + Sphingomonas roseiflava MK341T (D84520) + + Sphingomonas parapaucimobilis IFO 15100T (D13724) + + Sphingomonas pseudosanguinis G1 ~2T (AM412238) + + Sphingomonas sanguinis IFO 13937T (D84529) + + 97 Sphingomonas paucimobilis GIFU 2395T (D16144) + + Sphingomonas adhaesiva GIFU 11458T (084527) + + Sphingomonas phyllosphaerae FA1 (AY563441) + + 100 Sphingomonas yunnanensis YIM 003T (AY894691) + + Sphingornonas desiccabi/is CP1DT (AJ871435) + + Sphfngomonas molluscorum An 18T (ABZ48285) + + Strain NxozY (DQ789172) + + - Sphingomonas pituitosa EDIVT (AJ243751) + + _LSphingomonas trueperi LMG 2142T (X97776) + + 99 Sphingomonas azotifigens NBRC 15497T (AB217471) + + 7 Sphingomonas panni 052T (AJ575818) + + 89 Sphingomonas mucosissima CP173-2T (AM229669) + + Sphingomonas dokdonensis DS-4T (DQ178975) + + Sphingomonas koreensis JSSZBT (AF131296) + + Sphingomonas soli T5-04T (AB166883) + + 91 Sphingomonas mali IFO 15500T (Y09638) + + 80 Sphingomonas pruni IFO 15498T (Y09637) + + Sphingomonas asaccharolytica IFO 15499T (Y09639) + +

+
+
+

+ 64 + + 99 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 74 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 95 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 71 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 100 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ Sphingomonas insu/ae DS-28T (EF363714) + + Sphingomonas abaci C42T (AJ575817) + +

+
+
+

+ [Sphingomonas aquatilis JSS7T (AF131295) + + 100 Sphingnmnnas melon/s DAPP-PG 224T (A3055863) + +

+
+
+

+ _‘_— Sphingomonas echinaides ATCC 14820T (ABO21370) + + 9 + +

+
+
+

+ 7 Sphingomonas oligophenolica 8213'r (ABO18439) + + Sphingomonas aemlata NW12T (AJ429240) + +

+
+
+

+ + +

+
+
+

+ 71 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 100 Sphingomonas aurantiaca MA101bT (AJ429236) + +

+
+
+

+ ‘39 Sphingomonas faeni MA—olkiT (AJ429239) + + Sphingomonas jaspsi TDMA-16T (A8264131) + +

+
+
+

+ + +

+
+
+

+ 53 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ Sphingomonas kaistensis PB56T (AY769083) + +

+
+
+

+ 96 + + 91 Sphingomonas haloaromaticamans A175T (X94101) + +

+
+
+

+ 91 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ Sphingomonas wittichii DSM 6014T (ABOZ1492) + + Sphingomonas fennica K101T (AJ009706) + + Sphingobium yanoikuyae NBRC 15102T (D13728) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 100—: Sphingobium herbicidovorans NBRC 16415T (ABO42233) + + 99 + +

+
+
+

+ Sphingobium chlorophenolicum ATCC 33790T (X87161) + + Sphingosinicella soli KSL-125T (DQOB7403) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 100 + +

+
+
+

+ Sphingosinicella microcystinivorans MDBZ (ABZ19940) + + 99 + +

+
+
+

+ Sphingosinicella xenopeptidilytica 3»2W4T (AY950663) + +

+
+
+

+ Novosphingobium rose IAM 14222T (013945) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 69 + +

+
+
+

+ + +

+
+
+

+ 89 + +

+
+
+

+ Novosphingobium capsulatum GIFU 11526T (D16147) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 99 Novosphingnbium subterraneum SMCC 30478T (U20773) + + Novosphingobium aromatic/vorans SMCC B0695 (U20755) + +

+
+
+

+ 99 Novosphingobium aromaticivorans SMCC F199T (U20756) + +

+
+
+

+ + +

+
+
+

+ Sphingopyxis terrae NBRC 15098T (D13727) + + Sphingopyxis macrogoltabida EY-1 (A8255383) + +

+
+
+

+ Sphingopyxis baekryungensis SW-150T (AY608604) + +

+
+
+

+ Erythrobacter Iongus DSM 6997T (AF465835) + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000265-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000265-0-000.pbm.png new file mode 100644 index 00000000..98860bcc Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000265-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000265-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000265-0-000.pbm.png.hocr new file mode 100644 index 00000000..73a97d48 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000265-0-000.pbm.png.hocr @@ -0,0 +1,114 @@ + + + + + + + + + + + +
+
+

+ Hymenobacter rigui WPCB131T (DQOBQBBQ) + + Hymenobacter Xinjiangensis X2-1gT (D0888329) + +

+
+
+

+ + + + + + + + + + +

+
+
+

+ Hymenobacter gel/purpurascens T><g1T (Y18836) + + Hymenobacter psychrotolerans Tibet—I |U1 1T (DQ177475) + + Hymenobacter aerophilus |/26—Cor1T (AJ276901) + + Hymenobacter actinosc/erus CCUG 39621T (Y17356) + + Hymenobacter chitinivorans Tx<31T (Y18837) + + Hymenobacter norwr'chens/s NS/50T (AJ549285) + + Hymenobacter roseosa/ivarius AA—718T (Y18833) + + Hymenobacter soli PB17T (AB251884) + + 86 '— Strain ZLB-3T (EU325941) + + 100 ‘— Hymenobacter ocellatus Myx 2105T (Y18835) + + Pant/beater actiniarum KMM 6156T (AY989908) + + Adhaeribacter aquaticus MBRG1.5T (AJ626894) + + Flavobacterium aquati/e ATCC 11947T (M62797) + +

+
+
+

+ 0.02 59 + +

+
+
+

+ 100 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + + + + + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000349-0-001.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000349-0-001.pbm.png new file mode 100644 index 00000000..0bdaa1c0 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000349-0-001.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000349-0-001.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000349-0-001.pbm.png.hocr new file mode 100644 index 00000000..276632cb --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000349-0-001.pbm.png.hocr @@ -0,0 +1,143 @@ + + + + + + + + + + + +
+
+

+ Anaerotruncus colihominis DSM 17241 T (AJ315980) + +

+
+
+

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

+
+
+

+ 73 + + Acetanaerobacterium elongatum AS 1.5012T (AY518589) + +

+
+
+

+ Hydrogenoanaerobacterium saccharovorans SW512T (EU158190) + +

+
+
+

+ 62 + + Hydrogenoanaerobacterium saccharovorans W72 (EU170433) + +

+
+
+

+ Clostridium methylpentosum DSM 5476T (Y18181) + +

+
+
+

+ Ruminococcus albus ATCC 27210T (L76598) + +

+ +

+ Ruminococcus flavefaciens ATCC 19208T (L76603) + +

+ +

+ Ruminococcus cal/idus ATCC 27760T (L76596) + +

+ +

+ Eubaoterium siraeum ATCC 29066T (L34625) + +

+ +

+ Anaerofi/um agile DSM 4272T (X98011) + +

+ +

+ Anaerofilum pentosovorans DSM 7168T (X97852) + + Faeca/ibacterium prausnitzii ATCC 27768T (AJ413954) + + Clostridium Ieptum ATCC 29065T (M59095) + +

+
+
+

+ ClostridIum sporosphaeroIdes ATCC 25781T (M591 16) + +

+
+
+

+ Clostridium cellulosi AS 1.1777T (L09177) + +

+
+
+

+ Clostridium butyricum ATCC 19398T (M59085) + +

+
+
+

+ 2% + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000364-0-002.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000364-0-002.pbm.png new file mode 100644 index 00000000..ca931e8b Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000364-0-002.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000364-0-002.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000364-0-002.pbm.png.hocr new file mode 100644 index 00000000..324c6b15 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000364-0-002.pbm.png.hocr @@ -0,0 +1,207 @@ + + + + + + + + + + + +
+
+

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

+
+
+

+ Human strain ADV244 (EF468686) + +

+ +

+ 100 Pyramidobacter piscolens W5455T (EU309492) + + Human strain ADV746 (EF468688) + +

+ +

+ Oral clone BA121 (AY005444) + +

+ +

+ Orangutan faecal clone orang2_aai66011 (EU462629) + + Sheep rumen clone 196.B09 (DQ308572) + +

+ +

+ Bovine rumen clone P5_M14 (EU382030) + +

+ +

+ Naked mole—rat faecal clone molerat_aai69f04 (EU463081) + + Swine intestine clone p—4292-4Wa3 (AF371930) + + Human strain ADV403 (EF468687) + +

+ +

+ Human strain RMA 14551 (DQ412722) + + Anaerobic digestor clone vadinBBO2 (U81658) + +

+
+
+

+ Hoatzin crop clone hoa61_11f11 (EU344711) + + 100 Oral strain E3_33 (AF481216) + +

+
+
+

+ Jonquete/la anthropi ADV 126T (EF436500) + +

+ +

+ 100 Dethiosu/fovibrio russensis DSM 12577 (AF234543) + + Dethiosulfovibrio peptidovorans DSM 11002T (U52817) + + Synergistes jonesii ATCC 49833T (L08066) + +

+ +

+ 100 Anaerobaculum mobile DSM 13181T (AJ243189) + + Anaerobacu/um thermoterrenum DSM 13490T (U50711) + + Thermovirga lien/'1' Ca560314T (DQ071273) + +

+ +

+ Thermanaerovibrio acidaminovorans DSM 6589T (AF071414) + + Aminomonas paucivovorans DSM 12260T (AFO72581) + + Aminobacterium colombiense DSM 12261T (AF069287) + + Aminobacterium mobile DSM 12262T (AFO73521) + +

+ +

+ 100 Oral clone W028 (AF125202) + +

+ +

+ Oral clone MCE3_120 (AF481215) + +

+
+
+

+ Oral clone D084 (AF125200) + + Oral clone BH007 (AY005447) + +

+
+
+

+ Oral clone MCE7_5 (AF481214) + + 92 Oral clone 33062 (AY005445) + +

+
+
+

+ 100 + +

+
+
+

+ 57 + +

+
+
+

+ + +

+
+
+

+ '—' 100 + + 0.05 + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000364-0-004.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000364-0-004.pbm.png new file mode 100644 index 00000000..db9336d3 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000364-0-004.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000364-0-004.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000364-0-004.pbm.png.hocr new file mode 100644 index 00000000..2f8d37ae --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000364-0-004.pbm.png.hocr @@ -0,0 +1,150 @@ + + + + + + + + + + + +
+
+

+ 68 + +

+
+
+

+ 83 + +

+
+
+

+ 100 + + 100 + +

+
+
+

+ 96 + +

+
+
+

+ 100 + + 98 + +

+
+
+

+ 77 + + 99 + +

+
+
+

+ 100 + + 97 + +

+
+
+

+ 71 98 + +

+
+
+

+ 100 + +

+
+
+

+ 99 + + 100 + +

+
+
+

+ 0.1 + +

+
+
+

+ Pyramidobacter piscolens W5455T (DU723069) + + ‘Aquifex aeolicus’ VF5 (AACO7677) + + Thermotoga maritime MSB8T (AAD36645) + + Synechocoocus elongatus PCC 6301T (BAD79413) + + Rhodopirellula baltica SH1T (CAD79269) + + Desulfovibrio desulfuricans G20 (ABB37883) + + Lactobacillus salivarius UCC118 (ABD99994) + + Streptococcus gordonii Challis (ABV1 1046) + + Bacillus subtilis 168 (CAB15547) + + Finegoldia magna ATCC 29328 (BAG08949) + + Chloroflexus aurantiacus J-10fl (ABY33776) + + Porphyromonas gingivalis W83 (AAQ65708) + + Bacteroides fragilis NCTC 9343T (CAH06724) + + Chlorobium tepidum TLST (AAM72469) + + Fusobacterium nucleatum ATCC 25586T (AAL93833) + + Bifidobacterium Iongum NCC2705 (AAN25218) + + Chlamydia trachomatis D/UW—3/CX (AAC68296) + + Opitutus terrae PBQO-1 (ACB74961) + + Treponema dent/cola ATCC 35405T (AAS12412) + + Caulobacter crescentus CB15 (AAK25030) + + Ochrobactrum anthropi ATCC 49188T (ABS13742) + + Ehrlichia chaffeensis ArkansasT (ABD45253) + + Bordetella pertussis Tohama | (CAE43285) + + Neisseria gonorrhoeae FA 1090 (AAW89680) + + Pseudomonas aeruginosa PA01 (AAGO7791) + + Haemophilus influenzae PittGG (ABROO457) + + Escherichia coli O157:H7 EDL933 (NP_285794) + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000406-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000406-0-000.pbm.png new file mode 100644 index 00000000..57a52686 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000406-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000406-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000406-0-000.pbm.png.hocr new file mode 100644 index 00000000..341f632a --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000406-0-000.pbm.png.hocr @@ -0,0 +1,322 @@ + + + + + + + + + + + +
+
+

+ 78 + +

+
+
+

+ 67 + + 54 + + 89 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 89 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 77 + +

+
+
+

+ + +

+
+
+

+ 68 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 77 + +

+
+
+

+ + +

+
+
+

+ 100 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 7 Paenibaci/Ius agar/devorans DSM 1355T (AJ345023) + +

+
+
+

+ L 33-4AT (A3265205) + +

+
+
+

+ MX2-3T (ABZGSZOG) + +

+
+
+

+ Paenibacil/us granivorans A30T (AF237682) + +

+ +

+ Paenibaci/Ius agarexedens DSM 1327T (AJ345020) + + Paenibaci/Ius alkaliterrae DSM 17040T (AY960748) + +

+ +

+ Paenibacil/us glycanilyticus DS-1T (ABO42938) + +

+
+
+

+ 7 Paenibacillus kobensis DSM 10249T (ABO73363) + +

+
+
+

+ + +

+
+
+

+ 100 + +

+
+
+

+ + +

+
+
+

+ Paenibacillus curd/anoiyticus DSM 10247T (AB073202) + + Paenibacillus favisporus GMP01T (AY208751) + +

+
+
+

+ Paenibacillus rhizosphaerae CECAP06T (AY751754) + +

+
+
+

+ + +

+
+
+

+ Paenibacillus lentimorbus ATCC 14707T (AFO71861 ) + +

+
+
+

+ + +

+
+
+

+ 100 + +

+
+
+

+ + +

+
+
+

+ Paenibacil/us thiaminolyflcus JCM 8360T (D78475) + +

+
+
+

+ + +

+
+
+

+ Paenibacil/us validus JCM 9077T (ABO73203) + +

+
+
+

+ + +

+
+
+

+ 100 + +

+
+
+

+ + +

+
+
+

+ Paenibacil/us naphtha/enovorans DSM 14203T (AF353681) + +

+
+
+

+ Aneur/nibaci/Ius aneurin/Iyticus DSM 5562T (X94194) + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000489-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000489-0-000.pbm.png new file mode 100644 index 00000000..8d3ef98d Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000489-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000489-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000489-0-000.pbm.png.hocr new file mode 100644 index 00000000..a08d2358 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000489-0-000.pbm.png.hocr @@ -0,0 +1,91 @@ + + + + + + + + + + + +
+
+

+ 100 G. agarilytica N02T (DQ784575) + +

+ +

+ G. chathamensis S18K6T (ABZ47623) + +

+ +

+ G. polaris LMG 21857T (AJ293820) + +

+ +

+ G. mesophi/a KMM 241T (AJ488501) + +

+ +

+ G. psychrophi/a 170T (DQOO7436) + + Strain E3T (EU183316) + +

+ +

+ G. punicea ACAM 611T(U85853) + + G. nitratireducens FR1064T (AY787042) + + 100 G. pallidu/a ACAM 615T (U85854) + + Alteromonas mac/eodii IAM 12920T (X82145) + +

+
+
+

+ + + + + + + + + + + + + + + + +

+
+
+

+ 0.01 + + 91 + +

+
+
+

+ + + + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000497-0-001.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000497-0-001.pbm.png new file mode 100644 index 00000000..15261991 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000497-0-001.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000497-0-001.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000497-0-001.pbm.png.hocr new file mode 100644 index 00000000..9c74ceab --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000497-0-001.pbm.png.hocr @@ -0,0 +1,202 @@ + + + + + + + + + + + +
+
+

+ + +

+
+
+

+ 94* + +

+
+
+

+ 52 + +

+
+
+

+ 97* + +

+
+
+

+ 90 + +

+
+
+

+ 0.005 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 61 + +

+
+
+

+ 54 + +

+
+
+

+ + +

+
+
+

+ S. griseus subsp. griseus IFO 13550 (ABO45866) + + S. fragil/s NRRL 2424T(AY999917) + + ‘8. vel/osus’ NRRL 8037 (X99942) + +

+
+
+

+ S. champavatii NRRL B-5682T (DQ026642) + + S. sampsonii ATCC 25495T (D63871) + +

+
+
+

+ + +

+
+
+

+ 71* + +

+
+
+

+ + + + +

+
+
+

+ 57 + +

+
+
+

+ ‘S. fungicidicus’ YHO4 (AW-336155) + + S. albidoflavus HD-109 (EF620361) + +

+
+
+

+ S. koyangensis VK-AESOT (AY079156) + + S. spinoverrucosus LMG 20321T (AJ781376) + + S. thermodiastaticus JCM 4840T (ABO18096) + + S9 albogriseo/us NRRL B-1305T (AJ494865) + + S. variegatus LMG 20315T (AJ781371) + + S. mashuensis DSM 40221T (X79323) + + S. kasugaensis NRRL B-24288T (AY999920) + +

+
+
+

+ + +

+
+
+

+ 98‘ + +

+
+
+

+ + +

+
+
+

+ 99* S. morookaense LMG 20074T (AJ781349) + +

+
+
+

+ s. lavenduligriseus NRRL 3—3173T (DQ442515) + + S. sodiiphilus YIM 80305T (AY236339) + + S. xiamenensis MCCC 1A01550T (EFO12099) + + S. carpaticus NRRL 846359T (DQ442494) + + 98" S. cheonanens/s VC-A46T (AY822606) + +

+
+
+

+ + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000521-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000521-0-000.pbm.png new file mode 100644 index 00000000..00515e4e Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000521-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000521-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000521-0-000.pbm.png.hocr new file mode 100644 index 00000000..dc80939d --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000521-0-000.pbm.png.hocr @@ -0,0 +1,144 @@ + + + + + + + + + + + +
+
+

+ 0.01 53 Rhizobium undico/a LMG 11875T (Y17047) + + Rhizobium vitis LMG 8750T (X67225) + + Rhizobium giardinii H152T (U86344) + + Rhizobium daejeonense KCTC 12121T (AY341343) + + Rhizobium rubi LMG 156T (X67228) + + Rhizobium radiobacter ATCC 19358T (AJ389904) + + Rhizobium lanymoorei AF3‘ 1 0T (230542) + + Rhizobium cellulosi/yticus ALA1OBZT (DQ855276) + + Rhizobium ga/egae ATCC 43677T(D11343) + + Rhizobium huautlense 802T (AF025852) + + Rhizobium loessense CCBAU 7190BT (AF364069) + + Rhizobium alamii YA834 (AF239242) + + Rhizobium alamii GBV016T (AM931436) + + Rhizobium alamii USDA 1920 (U89823) + + Rhizobium sul/ae |S123T (Y10170) + + Rhizobium indigoferae CCBAU 71 O42T (AF364068) + + Rhizobium yang/ingense SH 22623T (AF003375) + + Rhizobium gall/Cum R6025pT (U86343) + + Rhizobium mongolense USDA 1844T(U89817) + + Rhizobium hainanense I66T (U71078) + + Rhizobium etli CFN 42T (U28916) + + Rhizobium legummosarum USDA 2370T (U29386) + + Rhizobium tropici CIAT 899T (U89832) + + Rhizobium lusitanum P1 -7T (AY738130) + + Rhizobium rhizogenes ATCC 1 1325T (AY945955) + + Ensifer kostiensis LMG 19227T (AM181748) + + Ensifer kummerowiae CCBAU 71714T (AF364067) + + Sinorhizobium americanum CFNEI 156T (AF506513) + + Ensifer fredii LMG 6217T (X67231) + + Ochrobaotrum anthropi ATCC 49188T (CP000758) + +

+
+
+

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

+
+
+

+ + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000547-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000547-0-000.pbm.png new file mode 100644 index 00000000..1b4f1d33 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000547-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000547-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000547-0-000.pbm.png.hocr new file mode 100644 index 00000000..0ef94788 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000547-0-000.pbm.png.hocr @@ -0,0 +1,285 @@ + + + + + + + + + + + +
+
+

+ 0.01 + +

+
+
+

+ + + + + + + + + + + + + + +

+
+
+

+ + +

+
+
+

+ -l_— + +

+
+
+

+ 50 P. stutzeri CCUG 11256T (U26262) + +

+
+
+

+ 100 + +

+
+
+

+ -P. psychrotolerans C36T (AJ575816) + +

+ +

+ P. oleovorans IAM 1508T (D84018) + +

+ +

+ P. tuomuerensis 78-123T (D0868767) + +

+ +

+ 93 P. alcaliphila AL15—21T(ABO30583) + +

+ +

+ P. mendocina ATCC 25411T (M59154) + +

+ +

+ P. pseudoalcaligenes JCM 5968T (AB021379) + +

+ +

+ P. segetis FR1439T (AY770691) + +

+ +

+ P. borbari R—20821T(AM114527) + +

+ +

+ P. anguilliseptica NCMB 1949T (ABOZ1376) + +

+ +

+ P. guinea LMG 24017T (AM491811) + +

+ +

+ 99 P. peli R-20805T (AM114534) + +

+ +

+ P. flavescens B62T (U01916) + +

+ +

+ P. straminea IAM 1598T (D84023) + +

+ +

+ 99 P. argentinensis CH01T (AY691188) + +

+ +

+ 99 P. azotifigens 6H33bT (AB189452) + +

+ +

+ P. ind/ca |MT37T(AF302795) + +

+ +

+ P. thermotolerans CM3T (AJ31 1980) + +

+ +

+ P. ba/earica SP1402T (U26418) + +

+ +

+ P. resinovorans ATCC 14235T (ABOZ1373) + +

+ +

+ P. aeruginosa LMG 1242T (Z76651) + +

+ +

+ P, otitidis MCC10330T (AY953147) + +

+ +

+ P. alcaligenes IAM 12411T (D84006) + +

+ +

+ 78 P. nitroreducens IAM 1439T(D84021) + +

+ +

+ P. multiresinivorans ATCC 700690T (X96787) + +

+ +

+ P. jinjuensis Pss 26T (AF468448) + +

+ +

+ P. knackmussii B13T (AF039489) + +

+ +

+ P. citrone/lolis ATCC 13674T (ABOZ1396) + + 93 P. delhiensis RLD—1T(DQ339153) + +

+ +

+ P. xanthoman'na KMM 1447T (AB176954) + +

+
+
+

+ + +

+
+
+

+ 42 + +

+
+
+

+ + + + + + + + + + + + + + + + +

+
+
+

+ + + + + + + + + + + + + + + + + + + + + + + + +

+
+
+

+ + +

+
+
+

+ 37 + +

+
+
+

+ C. ostraviensis LMG 19434T (AJ493583) + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000588-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000588-0-000.pbm.png new file mode 100644 index 00000000..ffd956aa Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000588-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000588-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000588-0-000.pbm.png.hocr new file mode 100644 index 00000000..993f084c --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000588-0-000.pbm.png.hocr @@ -0,0 +1,200 @@ + + + + + + + + + + + +
+
+

+ + +

+
+
+

+ 76 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ Thermomonas fusca LMG 21737T (AJ519986) + +

+
+
+

+ 83 + +

+
+
+

+ + +

+
+
+

+ 5 Lysobacter gummosus ATCC 29489T (AB161361) + + 100 Lysobacter antibioticus DSM 2044T (ABO19582) + + Lysobacter capsici YCS194T (EF488749) + +

+
+
+

+ L ysobacter enzymogenes DSM 2043T (AJ298291 ) + + L ysobacrer niastensis GH41-7T (DQ462462) + +

+
+
+

+ L ysobacler daejeonensis DSM 17634T (DQ191 178) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 0.01 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 91 + +

+
+
+

+ + +

+
+
+

+ Lysobacter concretionis K007T (AB161359) + + 95 Lysobacter spongiicola KMM 329T (A8299978) + +

+ +

+ 66 ; Lysobacter def/uvii IMMIB APB-9T (AM283465) + + L ysobacter koreensis KCTC 12204T (AB166878) + +

+ +

+ Lysobacter niabensis GH34-4T (DQ462461) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ Lysobacter yangpyeongensis DSM 17635T (DQ191179) + +

+
+
+

+ 91 i + + 89 Lysabacter oryzae YC6269T (EU376963) + +

+
+
+

+ L ysobacter brunescens ATCC 29482T (AB161360) + +

+
+
+

+ + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000620-0-002.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000620-0-002.pbm.png new file mode 100644 index 00000000..943ce2ea Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000620-0-002.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000620-0-002.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000620-0-002.pbm.png.hocr new file mode 100644 index 00000000..0862fbc5 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000620-0-002.pbm.png.hocr @@ -0,0 +1,133 @@ + + + + + + + + + + + +
+
+

+ 99_— Desulfosporosinus orientis DSM 7493 (AJ493052) + + Desu/fltobacterium frappien' PCP—1T (U40078) + +

+ +

+ Dehalobacter restrictus PER—K23T (U84497) + +

+ +

+ Desulfotomaculum nigrificans NCIMB 8395T (X62176) + +

+ +

+ Peptococcus niger DSM 20475T (X55797) + +

+ +

+ Carboxydocella the/mautotrophica 4‘1T (AYO61974) + +

+ +

+ Thermincola carboxydiphi/a 2204T (AY603000) + +

+ +

+ Strain 1315T(EF542810) + +

+ +

+ Carboxydothermus ferrireducens .JW/AS—Y7T (U76363) + +

+ +

+ Carboxydothermus hydrogenofonnans 2-2901T rrsA (NC7007503) + +

+ +

+ 95 Carboxydothermus hydrogenofonnans 2-2901T rrsB (NC7007503) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + + + + + + + + + +

+
+
+

+ 0.05 + + |—‘ 98 Carboxydothermus hydrogenoformans 2-2901T rrsC (NC7007503) + +

+
+
+

+ 70 Carboxydothermus hydrogenoformans Z—290‘1T rrsD (N07007503) + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000695-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000695-0-000.pbm.png new file mode 100644 index 00000000..4c158a5e Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000695-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000695-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000695-0-000.pbm.png.hocr new file mode 100644 index 00000000..34af0f7d --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000695-0-000.pbm.png.hocr @@ -0,0 +1,362 @@ + + + + + + + + + + + +
+
+

+ 52_— Micrococcus luteus Ballarat (biovar Ill) (AJ409096) + + 63 Micrococcus flavus LW4T (DQ491453) + + 99 Micrococcus antarcticus T2T (AJ005932) + + 62 Micrococcus Iy/ae DSM 20315T (X80750) + + -Ci(ricoccus alkalito/erans YIM 70010T (AY376164) + + 52 100 Citricoccus mural/s 4-0T (AJ344143) + + Zhihengliuella ha/oto/erans YIM 70185T (DQ372937) + + 61 Anhrobacter sulfureus DSM 20167T (X83409) + + Arthrobacter protophormiae DSM 20168T (X80745) + + 67 —Ar1hrobacter nicotianae DSM 20123T (X80739) + + 0-01 78 —Arthrobacter uratoxydans DSM 20647T (X83410) + + 1—1 34 —Acaricomes phytoseiuli DSM 14247T (AJ812213) + + Hen/"bacterium salmoninarum ATCC 33209T (X51601) + + —Arthrobacter oxydans DSM 201 19T (X83408) + + 99 —Arthrobacter ilicis DSM 20138T (X83407) + + 98 —Arthrobacter nicotinovorans DSM 420T (X80743) + + Sinomonas flava CW 108T (EU370704) + + 100 * Sinomonas atrocyanea DSM 20127T (EU697388) + + 100 # Kocuria rosea DSM 20447T (X87756) + + 75 —Kocuria polaris CMS 760rT (AJ278868) + + 99 —Kocuria rhizophi/a DSM 11926T (Y16264) + + 91 Kocuria palustris DSM 11925T (Y16263) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ YanieI/a ha/otolerans YIM 70085T (AY228479) + + 62 —Nesterenkonia jeotgali JCS-241T (AY928901) + + Rothia aeria GTC 867T (ABO71952) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ Nocardia inohanensis IFM 0092T (AB092560) + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000737-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000737-0-000.pbm.png new file mode 100644 index 00000000..502b7258 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000737-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000737-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000737-0-000.pbm.png.hocr new file mode 100644 index 00000000..77c96de3 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000737-0-000.pbm.png.hocr @@ -0,0 +1,316 @@ + + + + + + + + + + + +
+
+

+ <r m + + o) o) + +

+
+
+

+ Similarity (%) + +

+
+
+

+ no I\ + + on 07 + +

+
+
+

+ co + + cu + +

+
+
+

+ m + + m + +

+
+
+

+ 100 + +

+
+
+

+ MW + +

+
+
+

+ 100 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 100 + +

+
+
+

+ + +

+
+
+

+ 52 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 58 + +

+
+
+

+ + +

+
+
+

+ 100 + +

+
+
+

+ 100 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 100 + +

+
+
+

+ 100 + + 100 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 73 + +

+
+
+

+ 99 + +

+
+
+

+ HJ039T + + UST040317—058T + + OSZ17T + + TF-27T + +

+ +

+ LT1 7T + +

+ +

+ ACEM 9T + + KMM 3597T + + KMM 3299T + + ACAM 591 T + + M7T + +

+ +

+ LMG 19866T + + M5 + +

+ +

+ PO10T + +

+ +

+ LT1 SaT + +

+ +

+ ATCC 8071 T + + M R—1 T + +

+ +

+ NCTC 10735T + + T147T + +

+ +

+ U141 7T + + CCTCC M 203093T + + ATCC 51 192T + +

+
+
+

+ S. spongiae DQ167234 + + S. irciniae DQ180743 + + S. denitrificans AJ311964 + + S. gaetbuli AY190533 + + S. donghaensis AY326275 + + S. o/Ieyana AF295592 + + S. pacifica AF500075 + + S. japonica AF145921 + + S. frigid/marina U85903 + + AM980877 + + S. livingstonensis AJ300834 + + AM980878 + + S. hafniensis A8205566 + + S. profunda AY445591 + + S. putrefaciens X82133 + + S. oneidensis AF005251 + + S. baltica AJ000214 + + S. glacia/ipiscico/a AB205571 + + S, morhuae A3205576 + + S. deco/orationis AJ609571 + + S. algae AF005249 + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000737-0-001.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000737-0-001.pbm.png new file mode 100644 index 00000000..6c507c27 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000737-0-001.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000737-0-001.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000737-0-001.pbm.png.hocr new file mode 100644 index 00000000..f9971b18 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000737-0-001.pbm.png.hocr @@ -0,0 +1,416 @@ + + + + + + + + + + + +
+
+

+ 73 S. bait/ca NCTC 10735T (A8231331) + + 88 S. hafniensis PO10T (AB208056) + + 0 02 88 S. putrefaciens ATCC 8071T (AFOO5669) + + S. glacialipiscico/a T147T (ABZ66200) + + S. morhuae U1417T (A3208062) + + S. deceleration/s CCTCC M 203093T (AJ609572) + + 100 S. oneidensis MR-1T (AEO14299) + + S. denitrificans 08217T (CP000302) + + 79 Strain M7T (EU702750) + + 100 S. frigidimarina ACAM 591T (AF014947) + + 97 S. livingstonensis NF22T (EU702751) + +

+ +

+ S. algidipisc/cola S13T (ABZ66202) + + 82 S. colwelliana ATCC 39565T (AB266207) + +

+ +

+ S. piezotolerans WP?)T (AM229308) + +

+ +

+ S. fidelis (AM229309) + + 93 S. marinintestina IK-1T (AB081763) + + 89 s. sairae SM2-1T (AB081768) + + 63 S. sohlegeliana HRKA1T (ABOB1766) + +

+ +

+ 65 72 S. halifaxensis HAW-EB4T (AY842131) + + 98 S. pea/eana ANG—SQ1T (AF014945) + + S. gel/dimarina ACAM 456T (AF014946) + + 100 S. hanedai ATCC 33224T (AFOO5693) + + S. sediminis HAW-EB3T (AY842130) + + 99 S. woodyi M332T (AF014944) + + S. atlantica HAW-E35T (AY842132) + + 78 S. canadensis HAW-E82T (AY842129) + +

+
+
+

+ S. psychrophila WP2T (AM229307) + + £8. benthica ATCC 43992T (AFO14949) + + 99 S. violacea (A8092340) + +

+
+
+

+ S. Ioihica PV-4T (CP000606) + + 35 s. algae ATCC 51192T (AF005686) + + 100 S. amazonensis SBZBT (AF005257) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 100 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 100 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 94 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 63 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 96 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000760-0-001.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000760-0-001.pbm.png new file mode 100644 index 00000000..4e8e0b1b Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000760-0-001.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000760-0-001.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000760-0-001.pbm.png.hocr new file mode 100644 index 00000000..ee246358 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000760-0-001.pbm.png.hocr @@ -0,0 +1,545 @@ + + + + + + + + + + + +
+
+

+ (a) 16S rRNA + + M. avium subsp. avium DSM 44155T (AJ536037) + +

+
+
+

+ + + + + + + + + + + + +

+
+
+

+ M. shimoidei ATCC 27962T (X82459) + +

+ +

+ M. heckeshornense S369T (AF174290) + + M. xenopi DSM 43995T (AJ536033) + + 54 M. batniense E347T (AJO12756) + +

+ +

+ M. celatum ATCC 51131T (L08169) + +

+ +

+ M. cookii ATCC 49103T (AF480598) + +

+ +

+ M. branderiATCC 51789T (AF480574) + +

+
+
+

+ KUM 060204T (AB370111) + + M. trivia/e ATCC 23292T (X88924) + +

+
+
+

+ M. hiberniae ATCC 49874T (X67096) + +

+ +

+ 99 M. nonchromogenicum ATCC 19530T (X52928) + + M. arupense AR30097T (DQ157760) + +

+ +

+ M. terrae ATCC 15755T (X52925) + +

+ +

+ M. kumamotonense CST 7247T (A8239925) + +

+ +

+ M. doricum DSM 44339T (AF264700) + +

+
+
+

+ Nocardia asteroides DSM 43757r (AF430019) + +

+
+
+

+ 0.01 + +

+
+
+

+ + + + + + + + + + + + + + + + + + + + + + + + + + +

+
+
+

+ (c) rpoB + +

+
+
+

+ 17 M. trivia/e DSM 44153T (AY544971) + +

+ +

+ M. shimoidei DSM 44152T (AY544962) + +

+ +

+ M. xenopi CIP 104035T (AY544979) + +

+ +

+ M. heckeshornense DSM 44428T (AY544922) + + M. botniense DSM 44537T (AY544891) + +

+ +

+ M. avium subsp. avium CIP 104244T (AY544887) + +

+
+
+

+ M. celatum CIP 106109T (AY544897) + + M. branderi CIP 104592T (AY544895) + +

+ +

+ KUM 060204T (AB370178) + +

+ +

+ M. kubicae CIP 106428T (AY544937) + +

+
+
+

+ M. doricum DSM 44339T (AY544906) + + M. interjectum DSM 44064T (AY544928) + +

+
+
+

+ M. cookii CIP 105396T (AY544904) + + M. conspicuum CIP 105165T (AY544903) + + Rhodococcus equi ATCC 10146 (AF057494) + +

+
+
+

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

+
+
+

+ 001 + +

+
+
+

+ (b) hsp65 + + M. trivia/e DSM 44153T (AF547883) + +

+
+
+

+ M. cookii CIP 105396T (AF547824) + + M. tuberculosis CIP 105795 (AF547885) + +

+
+
+

+ M. lacus DSM 44577T (AY438090) + + M. kansasii CIP 104589T (AF547849) + +

+
+
+

+ M. gastri CIP 104530T (AF547836) + + M. shimoidei DSM 44152T (AF547874) + + M. botn/‘ense DSM 44537T (AF547812) + +

+
+
+

+ M. celatum CIP 105109T (AF547817) + + M. branderi CIP 104592T (AF547815) + +

+
+
+

+ KUM 060204' (ABS7D171) + + M. terrae CIP 104321T (AF547879) + +

+
+
+

+ M. kumamotonense CST 7247T (A8239920) + +

+ +

+ M. doricum DSM 44339T (AF547826) + +

+ +

+ M. nonchromogen/‘cum DSM 44164T (AF547861) + + M. hiberniae DSM 44241T (AY438083) + +

+ +

+ M. arupense CCUG 39146 (DQ168662) + +

+
+
+

+ Nocardia asteroides ATCC 19247T (AY756513) + +

+
+
+

+ + + + + + + + + + + + + + + + + + + + + + +

+
+
+

+ 26 + +

+
+
+

+ 50 + +

+
+
+

+ + + + + + + + + + + + + + + + + + + + +

+
+
+

+ 0,01 + + (d) SOdA 39 M. cookii CIP 105396T (AY544815) + + M. branderi CIP 104592‘r (AY544810) + + 10 M. xenopi CIP 104035T (AY544878) + +

+ +

+ - M. heckeshornense DSM 44428T (AY544830) + + M. botm‘ense DSM 44537T (AY544806) + + M. lacus DSM 44577T (AY544841) + +

+ +

+ M. tuberculosis CIP 64.31T (AY544875) + +

+ +

+ 10 M. ulcerans CIP 105425T (AY544876) + +

+ +

+ M. marinum CIP 104528T (AY544845) + +

+ +

+ M. kansasii CIP 104589T (AY544838) + +

+ +

+ M. gastri CIP 104530T (AY544825) + +

+ +

+ M. szu/gai CIP 104532T (AY544867) + +

+ +

+ M. shimoidei DSM 44152T (AY544863) + +

+ +

+ M. conspicuum CIP 105165T (AY544814) + +

+ +

+ M. parascmfulaceum CIP 108112T (AY943181) + +

+
+
+

+ M. interjectum DSM 44064T (AY544835) + + M. parmense CIP 107385T (AY943182) + +

+
+
+

+ M. bohemicum CIP 105811T (AY544805) + + M. celatum CIP 106109T (AY544812) + +

+
+
+

+ KUM 060204T (AB370184) + + M. saskatchewanense CIP 108114T (AY943183) + +

+
+
+

+ Nocardia abscessus DSM 44432T (AY544981) + +

+
+
+

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

+
+
+

+ + +

+
+
+

+ 97 + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000794-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000794-0-000.pbm.png new file mode 100644 index 00000000..8195d16f Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000794-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000794-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000794-0-000.pbm.png.hocr new file mode 100644 index 00000000..370b6c36 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000794-0-000.pbm.png.hocr @@ -0,0 +1,98 @@ + + + + + + + + + + + +
+
+

+ Lewinella persica NBRC 102663T (ABBO‘IG‘IB) + + Lewinel/a agan’lytica SST-19T (AM286229) + + Lewinella antarctica IMCC3223T (EF554367) + + LewineI/a Iutea NBRC 102634T (AB301494) + + Lewine/la marina NBRC 102633T (ABSO1495) + + Lewinella cohaerens NBRC 102661T (ABBO1614) + + Lewinella nigricans NBRC 102662T (ABBO1615) + + Haliscomenobacter hydrossis ATCC 27775T (M58790) + + Aureispira marina 24T (AB245933) + +

+ +

+ Flexithrix dorotheae ATCC 23163T (AF039296) + + Persicobacter diff/uens ATCC 23140T (M58765) + + Flexibacter flexilis ATCC 23079T (M62794) + + FIectobaciI/us major ATCC 29496T (M62787) + + Sphingobacterium spirit/vorurn ATCC 33861T (M58778) + + Chitinophaga pinensis ACM 2034T (AF078775) + + Aequorivita antarctica SW49T (AY027802) + +

+ +

+ Flavobacterium aquati/e ATCC 11947T (M62797) + + Rhodothermus man'nus OKD7 (X95071) + +

+
+
+

+ + + + + + + + + + + + + + + + + + + + +

+
+
+

+ 0.05 + +

+
+
+

+ + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000802-0-002.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000802-0-002.pbm.png new file mode 100644 index 00000000..d6f9794b Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000802-0-002.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000802-0-002.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000802-0-002.pbm.png.hocr new file mode 100644 index 00000000..ea762aa3 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000802-0-002.pbm.png.hocr @@ -0,0 +1,87 @@ + + + + + + + + + + + +
+
+

+ 99 Thermobrachium celere JW/YL—N235T (X99238) + + Ca/oramatorindicus |ndiB4T (X75788) + +

+ +

+ ‘Ca/oramator uzoniensis’ JW/VK—KU2 (AF489534) + + Caloramator proteoc/asticus UT (X90488) + + Caloramator coo/haasi/ ZT (AF104215) + +

+ +

+ Caloramator viterbiensis JW/MS-VSST (AF181848) + + 100 Caloramator australicus RC3T (EU409943) + +

+ +

+ Caloramator fen/idus ATCC 43204T (L09187) + + Clostridium butyricum ATCC 19398T (M59085) + +

+
+
+

+ 0.02 + +

+
+
+

+ + + + + + + + + + + + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000851-0-002.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000851-0-002.pbm.png new file mode 100644 index 00000000..a9c8a980 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000851-0-002.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000851-0-002.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000851-0-002.pbm.png.hocr new file mode 100644 index 00000000..9383debd --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000851-0-002.pbm.png.hocr @@ -0,0 +1,155 @@ + + + + + + + + + + + +
+
+

+ Arcobacter butz/eri ATCC 49616T (AY621 1 16) + +

+ +

+ Helicobacter pylori NCTC 1 1637T (225741 ) + +

+ +

+ Wolinella succinogenes ATCC 29543T (M88159) + + Campy/obacter fetus subsp. fetus ATCC 27374T (LO4314) + + 100 Campy/obacter upsaliensis CCUG 14913T (L14628) + +

+ +

+ - Campy/obacter helveticus NCTC 12470T (U03022) + + Campy/obacter peloridis LMG 11251 (AF550632) + + Campy/obacter peloridis LMG 23910T (AM922331) + + Campy/obacterlari subsp. Iari CCUG 23947 (LO4316) + + Campy/obacter insulaenigrae NCTC 12927T (AJ620504) + + Campy/obacter/ari subsp. concheus LMG 11760 (AF550633) + + 1((2)21mpylobacter/ari subsp. concheus LMG 21009T (AM922330) + + 55 Campy/obacterjejuni subsp. doylei CCUG 24567T (L14630) + + 1(goampylobacz‘erjejuni subsp. jejuni ATCC 33560T (M59298) + + Campy/obacter coli ATCC 33559T (M59073) + +

+
+
+

+ Caminibacler hydrogeniphilus AM1 1 16T (AJ309655) + +

+
+
+

+ 10% 58 + +

+
+
+

+ + + + + + +

+
+
+

+ + +

+
+
+

+ 100 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + + + + + + + + + +

+
+
+

+ 97 55 + +

+
+
+

+ + +

+
+
+

+ 97 + +

+
+
+

+ 41 + +

+
+
+

+ 64 + +

+
+
+

+ + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000901-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000901-0-000.pbm.png new file mode 100644 index 00000000..580a06f1 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000901-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000901-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000901-0-000.pbm.png.hocr new file mode 100644 index 00000000..fce2136e --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000901-0-000.pbm.png.hocr @@ -0,0 +1,108 @@ + + + + + + + + + + + +
+
+

+ 0.05 + + I—l + +

+
+
+

+ 93 Antarctobacter heliathermus DSM 11445T(Y11552) + + Sagiltula stellata ATCC 700073T (US$356) + + 57 Donghicola eburneus SW—277T (DQ667965) + + Donghicola xiamenensis Y-2T (DQ120728) + + 99 Roseivivax halodurans JCM 10272T (D85829) + + Roseivivax halotolerans JCM 10271 F (D85831) + + 79 Salipiger mucosus LMG 22090T (AY527274) + + Leisingera methylohalidivorans DSM 14336T (AY005463) + + Phaeobacter gallaeciensis B81071 (Y13244) + + 100 Phaeobacter inhibens TST (AY177712) + + Marinovum algicola ATCC 51440" (X78315) + + Jannaschia helgalandensis DSM 1485 ST (AJ438 1 57) + + Ketogulonicigenium vulgare DSM 40251(AF136849) + + Oceanicola gramzlosus DSM 15982" (AY424896) + + 97 Roseisalinus antarcticus EL-SST (AJ605747) + + 0 Rhodobacter capsulafus ATCC 11166T (D16428) + + Marinasulfonomonas methylotropha PSCH4T (U62894) + + Nereida ignava ZSM4T (AJ748748) + + Oceanihulbus indoltfex DSM 148621(A1550939) + + Staleya guttiformis DSM11458T(Y16427) + + Sulfitobacter brevis DSM 11443T(Y16425) + + 68 53 SulfitobacterpontiacusDSM10014T(Y13155) + + 97 Raseobacter denitrificarzs DSM 7001T (M59063) + + 100 Roseobacler liloralis ATCC 49566T (X78312) + + Octadecabacter arcticus CIP 1067321(U73725) + + 90 Thalassobius gelatinovorusIAM12617T(D88523) + + 61 Roseovarius crassostreae CV919-312r (AF114484) + + Roseovarius nubinhibens DSM 15170" (AF098495) + + Roseovarius tolerans DSM 11457T(Y11551) + + Ruegeria atlanticaIAM14463T(D88526) + + 100 Silicibacter lacuscaeru/ensis DSM11314T(U77644) + +

+
+
+

+ 97 + +

+
+
+

+ .98 + +

+
+
+

+ 60 82 + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000935-0-005.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000935-0-005.pbm.png new file mode 100644 index 00000000..3e93d074 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000935-0-005.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000935-0-005.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000935-0-005.pbm.png.hocr new file mode 100644 index 00000000..1d947f3d --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000935-0-005.pbm.png.hocr @@ -0,0 +1,478 @@ + + + + + + + + + + + +
+
+

+ 94/100/1.00 + +

+
+
+

+ a: 100/100/1.00 + + b: 79/64/098 + + c: 73/65/099 + + d: —/—/— + +

+ +

+ e: 87/85/100 + + f: —/57/0.99 + +

+ +

+ g: 76/82/096 + +

+ +

+ h: 100/100/100 + + i: 76/75/073 + +

+
+
+

+ —/54/0,56 e + +

+
+
+

+ 61/54/062 + +

+
+
+

+ 100/97/1‘00 + +

+
+
+

+ 90/93/1 .00 + +

+
+
+

+ —/64/0.67 + + 92/87/1000 + +

+
+
+

+ 97/100/100 + +

+
+
+

+ 73/59/1 .00 + +

+
+
+

+ 57/—/0.88 + +

+
+
+

+ 72/—/0.91 + +

+
+
+

+ 100/100/1.00 + +

+
+
+

+ 87/92/095 Colpoda cucuI/us + +

+
+
+

+ 100/99/1 .00 + + —/—/0.54 + +

+
+
+

+ Colpoda Iucida + + Colpoda inflata + +

+
+
+

+ a Colpoda magna + +

+
+
+

+ 87/92/100 + +

+
+
+

+ Colpoda minima + +

+
+
+

+ b Bresslaua vorax + + C Colpoda henneguyi + +

+
+
+

+ 80/63/039 + +

+
+
+

+ Bresslauides discoideus + +

+
+
+

+ h Chain—forming colpodid + + d Colpoda steinii + +

+
+
+

+ _/_/_ + +

+
+
+

+ Mykophagophrys terricola + + Pseudop/atyoph/ya nana + + f Colpoda aspera + +

+
+
+

+ Grossglockneriida + +

+
+
+

+ Hausmanniella discoidea + +

+
+
+

+ I/siella palustris + +

+
+
+

+ Notoxoma parabryoph/yides + +

+
+
+

+ Barde/ie/Ia pu/chra + +

+
+
+

+ 89/75/099 HAVOmat-euk43 + +

+
+
+

+ 100/100/1.00 LKM53 + +

+
+
+

+ PAA1OAU2004 + +

+
+
+

+ Cyrtolophosis mucicola Brazil + +

+ +

+ Cyrtolophosis mucicola Austria + +

+ +

+ h Aristerostoma sp. ATCC 50986 + +

+ +

+ Aristerostoma marinum + + Bursaria sp. 2 A + +

+
+
+

+ 100/100/1.00 + +

+
+
+

+ 80/91/100 + +

+
+
+

+ 94/92/100 Bursaria sp. 2 B + +

+
+
+

+ Bursaria sp. 1 + +

+
+
+

+ Pseudocyrtolophosis alpestris + +

+
+
+

+ I Bryophryida + +

+
+
+

+ Cyrtolophosidida | + +

+
+
+

+ Bursariomorphida + +

+
+
+

+ Bursaria truncate/Ia + +

+
+
+

+ —/62/0.92 + +

+
+
+

+ 100/100/1.00 + +

+
+
+

+ 100/100/1‘00 + + 87/76/080 + + h + + 100/100/1.00 + +

+
+
+

+ B/yometopus atypicus I + +

+
+
+

+ Bryometopus pseudochilodon + +

+
+
+

+ Bryometopus sphagni + + Ottowph/ya dragescoi + + Sorogena stoianovitchae + + Platyophrya sp. + + Platyophrya vorax + + Sagittaria sp. + + PIatyophrya-Iike sp. + +

+
+
+

+ 100/100/100 Rostmphyra sp_ + +

+
+
+

+ 96/82/100 + +

+
+
+

+ 99/75/1 .00 + +

+
+
+

+ 10 changes + +

+
+
+

+ Furgasonia blochmanni + +

+
+
+

+ Obe/trumia georgiana + +

+
+
+

+ Coleps hirtus + + Prorodon teres + +

+
+
+

+ OrthodoneI/a apohamatus + + Pseudomicrothorax dub/us + +

+
+
+

+ :Bryometopida + +

+
+
+

+ Sorogenida + +

+
+
+

+ :Cyrtolophosidida II + + I + +

+
+
+

+ I + + : NASSOPHOREA + + I + +

+
+
+

+ PROSTOMATEA + +

+
+
+

+ Colpodida + +

+
+
+

+ VEIGOd‘IOO + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000943-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000943-0-000.pbm.png new file mode 100644 index 00000000..b978a8ee Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000943-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000943-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000943-0-000.pbm.png.hocr new file mode 100644 index 00000000..349b433e --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000943-0-000.pbm.png.hocr @@ -0,0 +1,360 @@ + + + + + + + + + + + +
+
+

+ 2% + +

+
+
+

+ 100 + +

+
+
+

+ 100 + +

+
+
+

+ Desulfovibrio dechloracetivorans ATCC 700912T (AF230530) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 88 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 50 100 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 77 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 100 + +

+
+
+

+ 7 Desulfovibrio caledoniensis’ SEBR 7250 (U53465) + +

+
+
+

+ 7 Desulfovibrio aespoeensis DSM 10631T (X95230) + +

+
+
+

+ Desulfovibrio tunisiensis R322T (EF577029) + +

+
+
+

+ —Desulfovibrio halophilus DSM 5663T (X99237) + +

+
+
+

+ Desulfovibrio brasiliensis‘ DSM 15816 (AJ544687) + +

+
+
+

+ Desulfovibrio hydrothermalis DSM 14728T (AF458778) + + ~ Desulfovibrio gracilis DSM 16080T (U53464) + +

+
+
+

+ + +

+
+
+

+ 100 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 100 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ Desulfovibrio capillatus’ DSM 14982 (AY176773) + +

+
+
+

+ Desulfovibrio indonesiensis DSM 15121T (AJ621884) + +

+
+
+

+ Desulfovibrio giganteus DSM 4370 (AF418170) + +

+
+
+

+ + +

+
+
+

+ 7O 95 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 82 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 92 + +

+
+
+

+ Desulfovibrio fairfieldensis’ ATCC 70045 (U42221) + +

+ +

+ Desulfovibrio vulgaris subsp. vulgaris DSM 644T (DQ826728) + + Desulfovibrio psychrotolerans DSM 19430T (AM418397) + +

+ +

+ Desulfovibrio alaskensis NCIMB 13491T (AJ404226) + +

+
+
+

+ Desulfotomaculum halophilum DSM 11559T (U88891) + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000968-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000968-0-000.pbm.png new file mode 100644 index 00000000..1c962671 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000968-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000968-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000968-0-000.pbm.png.hocr new file mode 100644 index 00000000..ac47ebf2 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000968-0-000.pbm.png.hocr @@ -0,0 +1,218 @@ + + + + + + + + + + + +
+
+

+ + +

+
+
+

+ 0.01 + +

+
+
+

+ 86 + +

+
+
+

+ 52 + +

+
+
+

+ + +

+
+
+

+ 100 + +

+
+
+

+ Dye/la koreensis B84T (AY884571) + +

+
+
+

+ + +

+
+
+

+ Strain CSS-BZ'r (AM939778) + +

+
+
+

+ + +

+
+
+

+ Dye/Ia ginsengisoli Gsoil 3046T (ABZ45367) + +

+
+
+

+ + +

+
+
+

+ 86* + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ Frateun'a aurantia DSM 6220T (AJO10481) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ *1 Dye/la japan/ca XD53T (AB110498) + +

+
+
+

+ + +

+
+
+

+ Dye/la yeojuensis R2A16-10T (DQ181549) + + 55 + +

+
+
+

+ X' | + +

+
+
+

+ + +

+
+
+

+ Rhodanobacter Iindaniclasticus RP5557T + + (AF039167) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ Fulvimonas so/i LMG 19981T (AJ311653) + +

+
+
+

+ Aquimonas voraii GPTSA 20T (AY544768) + +

+
+
+

+ Dokdone/la koreensis DS—123T (AY987368) + +

+
+
+

+ Silanimonas lenta 25-4T (AY557615) + +

+
+
+

+ Xanthomonas campestris LMG 568T (X95917) + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000984-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000984-0-000.pbm.png new file mode 100644 index 00000000..194592c9 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000984-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000984-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000984-0-000.pbm.png.hocr new file mode 100644 index 00000000..a37c25b8 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000984-0-000.pbm.png.hocr @@ -0,0 +1,102 @@ + + + + + + + + + + + +
+
+

+ 0.01 + +

+
+
+

+ 84 A. histidinolovorans DSM 20115T (X83406) + + 96 A. nicotinovorans DSM 420T (X80743) + +

+ +

+ A. ureafaciens DSM 20128T (X80744) + + A. aurescens DSM 20116T (X83405) + +

+ +

+ A. citreus DSM 20133T (X80737) + + A. chlorophenolicus A—6T (AF102267) + +

+
+
+

+ + + + + + + + + + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 92 Strain Sphe3'r (AM176541) + + EH A, polychromogenes DSM 20136T (X80741) + + 93 A. oxydans DSM 20119T (X83408) + + A. globiformis DSM 20124T (M23411) + + 100 A. pascens DSM 20545T (X80740) + +

+
+
+

+ Mycobacterium smegmatis ATCC 19420T + +

+
+
+

+ + +

+
+
+

+ (AY457078) + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000984-0-001.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000984-0-001.pbm.png new file mode 100644 index 00000000..296b46d6 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000984-0-001.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000984-0-001.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000984-0-001.pbm.png.hocr new file mode 100644 index 00000000..a1310343 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.000984-0-001.pbm.png.hocr @@ -0,0 +1,148 @@ + + + + + + + + + + + +
+
+

+ + +

+
+
+

+ 0.02 + +

+
+
+

+ 84 + +

+
+
+

+ A. oxydans ATCC 14358T (AF214789) + + A. polychromogenes ATCC 15216T (AF214785) + + Strain Sphe3T (AM931439) + + A. aurescens ATCC 13344T (AF214793) + + A. histidinolovorans ATCC 11442T (AF214788) + +

+
+
+

+ 98 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 51 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 72 + +

+
+
+

+ + +

+
+
+

+ 59 A. ureafaciens ATCC 7562T (AF214782) + + A. globiformis ATCC 8010T (AF214780) + + 68 A. pascens ATCC 13346T (AF214786) + +

+
+
+

+ A, nicotianae ATCC 15236T (AF214792) + + A. sulfureus ATCC 19098T (AF214787) + + A. citreus ATCC 11624T (AF214781) + +

+
+
+

+ Mycobacterium mon‘okaense CIP 105393T + + (AY859691) + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001123-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001123-0-000.pbm.png new file mode 100644 index 00000000..925c6ac6 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001123-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001123-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001123-0-000.pbm.png.hocr new file mode 100644 index 00000000..b4c323bb --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001123-0-000.pbm.png.hocr @@ -0,0 +1,377 @@ + + + + + + + + + + + +
+
+

+ 1% + +

+
+
+

+ + +

+
+
+

+ 100 + +

+
+
+

+ + +

+
+
+

+ B. ubonensis LMG 20358T (AY780511) + + B. vietnamiensis LMG 10929T (AF143774) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ B. anthina LMG 20980T (AF456059) + + B. multivorans LMG 16660 (AF143774) + + B. do/osa LMG 18943T (AF323971) + + 66— B. cepac/a LMG 1222T (AF143786) + + —B. pyrrocinia LMG 14191T (AF143794) + +

+ +

+ B. Genocepacia IIIB LMG 16659 (AF143783) + + B. stabi/is LMG 14294T (AF456031) + + 78. semina/is LMG 24067T (AM748102) + + —B. cenocepacia IIIC LMG 19239 (AM748105) + + B. cenocepacia IIIA LMG 16656T (whole genome) + + —B. cenocepacia IIID LMG 21461 (AF456021) + +

+ +

+ B. diffusa LMG 24065T (AM748103) + +

+ +

+ 53—719.].3tens LMG 24064T (AM922300) + + —B. ambifaria LMG 19182T (AF323985) + + B. arbor/s LMG 24066T (AM748095) + + B. meta/lice LMG 24068T (AF456103) \ \ + + B. contaminans LMG 23361T (AF456121) + + - B. Bantam/Hans R—20938 (AM905035) + + *B, contaminans R-13528 (AF456073) + + B. contaminans R-18442 (AM905034) > + + E)“ B. contaminans R-18428 (AM905037) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + + + +

+
+
+

+ + +

+
+
+

+ + + + + + + + + + + + + + + + +

+
+
+

+ Hm! + +

+
+
+

+ 76 B. contaminans R-9896 (AM905036) + + B. contaminans LMG 16227 (AM922301) + + B. contaminans LMG 23253 (AM922303) + + B. contaminans LMG 23255 (AM922302) + + B. Iata LMG 6860 (AF456069) + + - B. lata LMG 6992 (AF456008) + + 3 5 B. lata LMG 6863 (AF456019) > + + B. lata LMG 22485T (whole genome) + + 5 B. lata LMG 6993 (AF456124) + + *8. lata R—18628 (AF456087) + + {(8. lata R-9940 (AF456011) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ J\ + + V + + MUOXQL + +

+
+
+

+ + +

+
+
+

+ "#391 + +

+
+
+

+ JK + +

+
+
+

+ 3 + +

+
+
+

+ + +

+
+
+

+ B. lata R-3211 (AF456078) + + 53 50 B. lata R-23139 (AM905032) > + + 8. lata LMG 14095 (AF456016) + + B. lata R-15816 (AM905033) / + +

+
+
+

+ ||H7091 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ B. xenovorans LMG 21463T (AJ544489) + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001123-0-003.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001123-0-003.pbm.png new file mode 100644 index 00000000..f814edc6 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001123-0-003.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001123-0-003.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001123-0-003.pbm.png.hocr new file mode 100644 index 00000000..86ec50a0 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001123-0-003.pbm.png.hocr @@ -0,0 +1,270 @@ + + + + + + + + + + + +
+
+

+ 100 + +

+
+
+

+ 100 + +

+
+
+

+ Cupriavidus metallidurans CH34T + + B. xenovorans LB400T + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 100 + +

+
+
+

+ + +

+
+
+

+ —B. phytofirmans PsJNT + +

+
+
+

+ B. phymatum STM815T + +

+
+
+

+ —B. thai/andensis E264T + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 100 + +

+
+
+

+ 0.1 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 100 + +

+
+
+

+ + +

+
+
+

+ 109 + +

+
+
+

+ + +

+
+
+

+ 100 + +

+
+
+

+ + +

+
+
+

+ 4[ B. pseudomal/ei 1710b + + 100 B. mal/ei NCTC 10247 + +

+
+
+

+ B, multivorans ATCC 17616T + +

+
+
+

+ B. dolosa AU0158T + +

+
+
+

+ B. ambifan'a AMMDT + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 100 + +

+
+
+

+ + +

+
+
+

+ B. vietnamiensis G4 + + B. cenocepacia J2315T + +

+
+
+

+ + +

+
+
+

+ 100 + +

+
+
+

+ + +

+
+
+

+ B. [are 383T + + 10° B. contaminans SAR-1 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001149-0-003.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001149-0-003.pbm.png new file mode 100644 index 00000000..298d11f5 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001149-0-003.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001149-0-003.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001149-0-003.pbm.png.hocr new file mode 100644 index 00000000..3d81d54c --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001149-0-003.pbm.png.hocr @@ -0,0 +1,268 @@ + + + + + + + + + + + +
+
+

+ L. pyrrhocoris n + +

+
+
+

+ L. pod/ipaevi = m + +

+
+
+

+ :la...o..oou...o.anuaxenic59L] + + jun-uuua =L.jaderae sp.nov. + +

+
+
+

+ Wallaceina spp. + +

+
+
+

+ ...................Leptomonas Sp. C4 + +

+
+
+

+ + + + +

+
+
+

+ m = L. neopamerae sp. nov. + +

+
+
+

+ ‘B. miridarum’ + + L. bifurcata . . + + j C. l. thermophI/a, ‘C, deaneI’U) + +

+
+
+

+ Jill + +

+
+
+

+ ] Paraleishmania + + ] L. (Viannia) + + L. (Leishmania) + + J L. farce/es = n + + ]m + +

+
+
+

+ L. acus = + + :l . Eu. Iggy. 127AL = C. abscondita sp. nov. + + . . . . 331:: .ax. 119YS = C. insperata sp. nov. + +

+
+
+

+ + +

+
+
+

+ ' ' ax. 128$| = C. permixta sp. nov. + + ] + + C. acanthocepha/i + + ‘Leptomonas’sp. P + + C. fascicu/ata + +

+
+
+

+ E + +

+
+
+

+ B. triatomae - B. leptocoridis + + clade including typing units + +

+
+
+

+ B. triatomae 9'17' 1943' 25' 28'30’ + +

+
+
+

+ + +

+
+
+

+ 33, 34, 37, 39, 44, 45 + +

+
+
+

+ ......... env.127AL-A + +

+
+
+

+ -------env.59Ll + +

+
+
+

+ - o o - aenv.1288l + + env. 127AL-B + +

+
+
+

+ .B. Ieptocoridis em, 119YS + + 00-00-000... 0 . + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ ................:::::.:::::::: :::::::'..... Herpetomonas sp. Tom + +

+
+
+

+ 1 L. seymouri + +

+
+
+

+ H. muscarum, H. megaseliae + + H. pessoai + +

+
+
+

+ 3 + +

+
+
+

+ P— H. roitmani, Herpetomonas sp. TCCZ63, + + ‘C. oncopelti’al), C. deanei (II) + +

+
+
+

+ J + +

+
+
+

+ costaricensis + + L. col/osoma + +

+
+
+

+ Phytomonas spp. + +

+
+
+

+ B. culicis m + +

+
+
+

+ .........Q.¢n.qopelti.(|)........-Leptomonas sp. me + +

+
+
+

+ T. cruzi + + Trypanosoma spp. + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001149-0-004.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001149-0-004.pbm.png new file mode 100644 index 00000000..e5d3ee4a Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001149-0-004.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001149-0-004.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001149-0-004.pbm.png.hocr new file mode 100644 index 00000000..8f92c34e --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001149-0-004.pbm.png.hocr @@ -0,0 +1,172 @@ + + + + + + + + + + + +
+
+

+ + +

+
+
+

+ Leptomonas pod/ipaevi + + 59L| = L. cf. podlipaevi + +

+
+
+

+ 95/80/87 34EC = L. jaderae sp. nov. + + 96/98/98 Le tomo7nsaZRs: :Lerfpame’ae sp- nov. + + 66/56/62 p y , + + Leptomonas pyrrhocor/s + +

+
+
+

+ 127AL = Crithidia abscondita sp. nov. + + Leishmania major + +

+
+
+

+ 92/66/88 Leishmania infantum + + 100/100/100 Leishmania tarentolae + + Leishmania braziliensis + + Leptomonas costaricensis + + Egg/V51 ‘Blastocrithidia miridarum’ + + ‘Leptomonas’ sp. P + + Crithidia luciliae + + Crithidia fasciculata C + + 71/98/79 Leptomonas acus + +

+
+
+

+ Leptomonas tarcoles + + 100l99/99 | ‘Crithidia deanei’ATCC 30255 + +

+
+
+

+ Leptomonas blfurcata + + 119YS = Crithidia insperata sp. nov. + + 100 Wallaceina brevicu/a + + Wallaceina inconstans + + ‘Leptomonas’ sp. Cfm + + 64/ 1 00/90 1285' = Cairhiéieeemixtafinzmax: .............................................. .. + +

+
+
+

+ ‘Crithidia oncope/ti’ ATCC 30264 + + 100 Herpetomonas sp. TCC263 + + Crithidia deanel ATCC 30969 + + 55/*/86 Herpetomonas roitmani + + Leptomonas Iactosovorans + + 100/88/98 37EC = L. cf. Iactosovo'rans H + + Herpetomonas pessoal + + Herpetomonas muscarum + +

+
+
+

+ Phytomonas sp. EM1 + +

+
+
+

+ 56/*/* + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 100 Phytomonas sp. P + + Phytomonas serpens + + 98 Crithidia oncopelti ATCC 12982 + +

+
+
+

+ Blastocrimidia culicis + + Leptomonas collosoma + + Sergeia pod/ipaevi + + 100 Trypanosoma brucei + + Trypanosoma cruzi + + Bodo saltans + +

+
+
+

+ 0.05 + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001149-0-005.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001149-0-005.pbm.png new file mode 100644 index 00000000..08a738f8 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001149-0-005.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001149-0-005.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001149-0-005.pbm.png.hocr new file mode 100644 index 00000000..910067c9 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001149-0-005.pbm.png.hocr @@ -0,0 +1,300 @@ + + + + + + + + + + + +
+
+

+ 100/1 0/100 + +

+
+
+

+ + +

+
+
+

+ Leishmania amazonensis + + Leishmania major + +

+
+
+

+ + + + + + + + + + + + + + + + +

+
+
+

+ + +

+
+
+

+ 68/82/52 Leishmania guyanensis + + I Leishmania tarentolae + + 66/56/62 Leishmania donovani + + : Endotrypanum monterogeii + + 85/61/79 Leptomonas acus + + g Leptomonas tarooles + + 5 4 /* [58 Cr/thidia fascicu/ata + + 3 Wallaceina inconstans + + 83/ 1 00/893 Wallace/n3 brevicu/a + + 99/100/100 Leptomonas pod/ipaevi 5 + + 63/86/67 ' 59L| = L. cf. podlipaevi g L 2 + +

+
+
+

+ 34EC = Leptomonasjaderae sp. nov. + + 73BR = Leptomonas neopamerae sp. nov.5 + + Leptomonas bifurcata 2 + + ‘Crithidia deanei‘ATCC 30255 + + ‘Blastocrithidia miridarum’ + + Leptomonas costaricensis + + Trypanosomatid G755 + + ‘Leptomonas' sp. Cfm + + Leptomonas seymouri + +

+
+
+

+ 128$l = Crithidia permixta sp. nov. + + 127AL = Crithidia abscondita sp. nov. + + 119YS = Crithidia insperata sp. nov. + +

+
+
+

+ Phytomonas serpens 1G + + Phytomonas sp. EM1 P + +

+
+
+

+ + + + + + + + + + + + + + + + + + +

+
+
+

+ 54/75} + + 63/81/65 S + +

+
+
+

+ 51/*/55 + +

+
+
+

+ + + + + + + + + + +

+
+
+

+ + +

+
+
+

+ 100/100/100 Phytomonas sp. HART1 + + 88/77/76 100/100/100 Zerpetomonas sp: TOG-263 + + erpetomonas rortmam + + 100/99/100 Crilhidia deanei ATCC 30969 + +

+
+
+

+ 100/100/100 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 1 00/1 00/1 00 + + Herpetomonas muscarum :l + + Herpetamonas ztiplika + + 97/86/80 Blastecrithidia triatomae + + Leptomonasjaculum + + Serge/a pad/ipaevi + +

+
+
+

+ + +

+
+
+

+ Leptomonas col/osoma + +

+
+
+

+ —{—— Trypanosoma sce/opori + + 99/100/97 lepanosoma avium + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 0,01 + +

+
+
+

+ Bode sa/tans + +

+
+
+

+ ‘Crithidia oncope/ti’ATCC 30264 + +

+
+
+

+ Crithidia oncope/ti ATCC 12982 + + BIastocrithid/a oulicis + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001172-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001172-0-000.pbm.png new file mode 100644 index 00000000..b79a8189 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001172-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001172-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001172-0-000.pbm.png.hocr new file mode 100644 index 00000000..73ebc98a --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001172-0-000.pbm.png.hocr @@ -0,0 +1,138 @@ + + + + + + + + + + + +
+
+

+ 2 % L. fabifermentans LMG 24284T (AM905388) + + L. plantarum JCM 1149T(D79210) + + g(L.pem‘osus JCM 1558T(D79211) + + L. paraplantarum DSM 10667T (AJ306297) + + L. algidus JCM 10491T (ABO33209) + + L. saerimneri GDA154T (AY255802) + + L. acidipiscis F560-1T (ABOZ3836) + + L. aviarius DSM 20655T (M58808) + + L. salivarius ATCC 1 1741 T (AF089108) + + L. mali DSM 20444T (M58824) + + L. cacaonum LMG 24285T (AM905389) + + L. nagelii LuEwT(Y17500) + + L. satsumensis NRIC 0604T (AB154519) + + L. murinus DSM 20452T (M58826) + + L. animalis DSM 20602T (M58807) + + L. equi YIT 0455T (ABO48833) + + L. agilis DSM 20509T (M58803) + + L. ruminis DSM 20403T (M58828) + + L. delbrueckii DSM 20074T (M58814) + +

+
+
+

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + +

+
+
+

+ + +

+
+
+

+ 100 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ dn016 Lummun/d '7 + +

+
+
+

+ dnmfi snymyns '7 + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001172-0-001.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001172-0-001.pbm.png new file mode 100644 index 00000000..45cf927d Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001172-0-001.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001172-0-001.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001172-0-001.pbm.png.hocr new file mode 100644 index 00000000..647736e3 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001172-0-001.pbm.png.hocr @@ -0,0 +1,167 @@ + + + + + + + + + + + +
+
+

+ 10% + +

+
+
+

+ + +

+
+
+

+ L. fabifermentans LMG 24284T (AM922294) + +

+
+
+

+ L. plantarum LMG 6907T (AM087714) + + E L. paraplantarum LMG 16673T (AM087727) + + L. pentosus LMG 10755T (AM087713) + + L. delbrueckii LMG 6412T (AM087689) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ b) + +

+
+
+

+ L. saerimneri LMG 22087T (AM087717) + +

+ +

+ L. ruminis LMG 10756T (AM087756) + +

+ +

+ L. equi LMG 21748T (AM087740) + +

+ +

+ L. aviarius LMG 10753T (AMO87737) + +

+ +

+ L. agilis LMG 9186T (AM087734) + +

+ +

+ L. anima/is LMG 9843T (AM087679) + +

+ +

+ L. murinus LMG 14189T (AMO87760) + +

+ +

+ L. acidipiscis LMG 19820T (AM087762) + + L. a/gidus LMG 19872T (AM263504) + + L. salivarius LMG 9477T (AM087721) + + L. mali LMG 6899T (AM087746) + +

+ +

+ L. nage/ii LMG 21593T (AMO87708) + +

+ +

+ L. cacaonum LMG 24285T (AM922295) + + L. sarsumensis LMG 22973T (AM087769) + + L. de/brueckii LMG 6412T (AM087689) + +

+
+
+

+ + + + + + + + + + + + + + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001180-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001180-0-000.pbm.png new file mode 100644 index 00000000..72bba0c1 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001180-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001180-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001180-0-000.pbm.png.hocr new file mode 100644 index 00000000..4b0fe5c4 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001180-0-000.pbm.png.hocr @@ -0,0 +1,320 @@ + + + + + + + + + + + +
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 82.5 + +

+
+
+

+ 73. + +

+
+
+

+ + +

+
+
+

+ Pseudoalteromonas haloplanklis ATCC 14393T (X67024) + +

+
+
+

+ + +

+
+
+

+ l + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 100 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 95.4 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 86.4 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 100 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 100 + +

+
+
+

+ + +

+
+
+

+ + + + +

+
+
+

+ Psychromonas antarctica DSM 10704T (Y14697) + +

+
+
+

+ Colwellia psychrerythraea ATCC 27364T (AF001375) + +

+
+
+

+ Thalassamonas viridans DSM 13754T (AJ294748) + +

+
+
+

+ Pseudidiomarina salinarum [Idiomarina salinarum] ISL-52T (EF486355) + +

+
+
+

+ Pseudidiomarina homiensis [Idiomarina homiensis] PO-M2T (DQ342238) + +

+
+
+

+ Pseudidiomarina sediminum (3121T (EF212001) + +

+
+
+

+ 89.5 + +

+
+
+

+ Pseudidiamarina taiwanensis PIT 1 T (DQl 18948) + + Pseudidiomarina tainanensis PINlT (EU423907) + +

+
+
+

+ 100 + + Pseudidiomarina marina PIMlT (EU423908) + +

+
+
+

+ Idiomarinafimtislapidosi LMG 22169T (AY526861) + + ldiomarina baltica OSl45T (AJ440214) + + Idiomarina zobellii KMM 231T (AF052741) + +

+
+
+

+ Idiomarina seasinensis CL-SP19T (AY635468) + +

+
+
+

+ Idiomarina abyssalis KMM 227T (AF052740) + +

+
+
+

+ Idiomarina ramblicola LMG 22170T (AY526862) + +

+
+
+

+ + +

+
+
+

+ 99.4 + +

+
+
+

+ 7 Idiomarina loihiensz's LZ-TRT (AF 288370) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 0.01 + +

+
+
+

+ Oceanimonas doudoroflii ATCC 27123T (AB019390) + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001230-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001230-0-000.pbm.png new file mode 100644 index 00000000..4f6eb45e Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001230-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001230-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001230-0-000.pbm.png.hocr new file mode 100644 index 00000000..c68ae690 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001230-0-000.pbm.png.hocr @@ -0,0 +1,196 @@ + + + + + + + + + + + +
+
+

+ 91 + +

+
+
+

+ 100 + +

+
+
+

+ 81 + +

+
+
+

+ A. radioresistens CCM 3588T (EU477112) + +

+
+
+

+ A. baylyi ADP1 (EU477155) + +

+
+
+

+ 100 + +

+
+
+

+ 100 + +

+
+
+

+ 100 + +

+
+
+

+ 100 + +

+
+
+

+ 2% + +

+
+
+

+ A. ursingii NIPH 137T (EU477105) + + A. towneri CCM 7201T (EU477154) + + A. tandoii CCM 7199T (EU477152) + + A. gerneri CCM 7197T (EU477151) + + Genomic sp. 10 LMG 1003 (= ATCC 17924) (EU477116) + + Genomic sp. 11 LMG 988 (= ATCC 11171) (EU477117) + + Genomic sp. 15TU LUH 1090 (EU477119) + + A. lwoffii CCM 5581T (EU477111) + + A. bouvetii CCM 7196T (EU477150) + + A. schind/eri NIPH 1034T (EU477128) + + A. junii CCM 2376T (EU477110) + + Genomic sp, 6 LMG 1026 (= ATCC 17979) (EU477115) + + A. haemolyticus CCM 2358T (EU477109) + + 100 A. ca/coaceticus ATCC 23055T (EU477149) + + Genomic sp. ‘Between 1 and 3’ LUH 1469 (EU477122) + + Genomic sp. 3 LMG 1035 (= ATCC 19004) (EU477114) + + 97 A. baumannii ATCC 19606T (EU477108) + + Genomic sp. ‘Close to 13TU’ LUH 1472 (EU477126) + + 80 Genomic sp. 13TU LMG 993 (= ATCC 17903) (EU477118) + + A. tjernbergiae CCM 7200T (EU477153) + + Genomic sp. 16 ATCC 17988 (EU477135) + + Genomic sp. 1SBJ LUH 1729 (EU477133) + + ‘A, venetianus‘ ATCC 31012 (EU477136) + + Genomic sp. 17 LUH 1736 (EU477134) + + gyllenbergii LUH 1737 (EU477121) + + gyllenbergii LUH 5809 (EU477131) + + gyllenbergii NIPH 2150T (EU477148) + + gyllenbergii LUH 1740 (EU477127) + + gyllenbergii LUH 6541 (EU477144) + + gyllenbergii NIPH 230 (EU477106) + + gyllenbergii LUH 1741 (EU477158) + + gyllenbergii RUH 3064 (EU477145) + + .gyllenbergii NIPH 2353 (EU477156) + + A. parvus NIPH 384T (EU477107) + + Genomic sp. 14BJ LUH 1726 (EU477147) + + Genomic sp. 13BJ/14TU ATCC 17905 (EU477132) + + A. johnsoni/ LMG 999T (EU477113) + + beijerinckii RUH 2762 (EU477139) + + beijerinckii NIPH 838T (EU477124) + + . beijerinckii LUH 9424 (EU477157) + + beijerinckii LUH 5692 (EU477146) + + beijerinckii LUH 4561 (EU477120) + + . beijerinckii RUH 2879 (EU477140) + + . beijerinckii LUH 4738 (EU477123) + + . beijerinckii LUH 4771 (EU477125) + + . beijerinckii LUH 3340 (EU477129) + + . beijerinckii LUH 6214 (EU477130) + + beijerinckii RUH 2371 (EU477137) + + beijerinckii RUH 2560 (EU477138) + + beijerinckii LUH 3146 (EU477141) + + beijerinckii LUH 7834 (EU477142) + + . beijerinckii LUH 8896 (EU477142) + +

+
+
+

+ >>>>>>>>> + +

+
+
+

+ >>>>>>>>>>>>>>> + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001230-0-001.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001230-0-001.pbm.png new file mode 100644 index 00000000..8b44d3d9 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001230-0-001.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001230-0-001.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001230-0-001.pbm.png.hocr new file mode 100644 index 00000000..3509f569 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001230-0-001.pbm.png.hocr @@ -0,0 +1,322 @@ + + + + + + + + + + + +
+
+

+ + +

+
+
+

+ A. towneri AB 1110T (AF509823) + +

+
+
+

+ Acinetobactergenomic sp. 15TU 151a (293448) 1% + + if A. radioresistens 17694T (293445) + + 100 ‘A. venetianus’ RAG-1 (AJ295007) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ A. jun/i LMG 998T (AM410704) + + A. gerneri 9A01T (AF509829) + + fl— A. baumannii ATCC 19606T (293435) + +

+ +

+ Acinetobactergenomic 5p. 13TU ATCC 17903 (293446) + + A. ursingii NIPH 137T (AJ275038) + + JEAcmetobacter genomic 5p. 10 ATCC 17924 (293443) + +

+ +

+ Acinetobacter genomic 5p. 11 DSM 590 (X81659) + + A. tjernbergiae 7N16T (AF509825) + +

+ +

+ —A. tandoii 4N13T (AF509830) + + _‘_—A. bouvetii 4B02T (AF509827) + +

+ +

+ A. johnsonii ATCC 179091 RUH 2231T: (293440) + +

+ +

+ A. haemolyticus ATCC 17906T, RUH 22157: (293437) + + 100 A. beijerinckii NIPH 838T (AJ626712) this study + +

+ +

+ A. beijerinckii LUH 6214 (M303013) this study + +

+ +

+ Acinetobacter genomic 5p. 16 ATCC 17988 (293451) + + Acinetobacter genomic sp. 1SBJ 79 (293452) + +

+ +

+ A. schind/eri NIPH 1034T (AJ278311) + + A. pan/us NIPH 384T (AJ293691) + +

+
+
+

+ Acinetobactergenomic sp. 17 942 (293454) + + A. gyllenbergii LUH 1737 (AJ293692) this study + +

+
+
+

+ 100 A. gyllenbergii LUH 1740 (AJ293693) this study + +

+ +

+ A. gyllenbergii NIPH 2150T (AJ293694) this study + +

+ +

+ Acinetobacter genomic sp. 14BJ 382 (293453) + + Acinetobactergenomic Sp. 1BBJ/14TU ATCC 17905 (293447) + +

+
+
+

+ _I: A. lwoffii ATCC 17925 (Z93441) + +

+
+
+

+ Acinetobacter genomic species 6 ATCC 17979 (293439) + +

+ +

+ A. baylyi CCM 7195T (AM410709) + +

+ +

+ Acinetobacter genomic sp. ‘close to 13TU’ 10090 (293449) + +

+ +

+ Acinetobacter genomic sp. ‘between 1 and 3' 10095 (293450) + +

+ +

+ A. calcoaceticus DSM 30006T (X81661) + +

+ +

+ Acinetobacter genomic sp. 3 ATCC 17922 (293436) + +

+ +

+ 100 Alkanindiges iI/inoisensis MVAB Hex1T (AF513979) Psychrobacterimmobm‘s + +

+
+
+

+ I ATCC 43116T (U39399) + + 100 Moraxe/Ia Iacunata ATCC 17967T (AF005160) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + + + + + + + + + + + + + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + + + + + + + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001248-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001248-0-000.pbm.png new file mode 100644 index 00000000..fb8ac5d2 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001248-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001248-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001248-0-000.pbm.png.hocr new file mode 100644 index 00000000..dbcfb35f --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001248-0-000.pbm.png.hocr @@ -0,0 +1,116 @@ + + + + + + + + + + + +
+
+

+ 90 B. brevis DSM 30T (AB101593) + +

+ +

+ 45 B. formosus DSM 9885T (AB112712) + +

+ +

+ 51 B. choshinensis DSM 8552T (AB112713) + + B. reuszeri DSM 9887T (AB112715) + +

+ +

+ B. parabrevis IFO 12334T (D78463) + +

+ +

+ B. agri DSM 6348T (AB112716) + +

+ +

+ B. Iimnophilus DSM 6472T (AB112717) + + B. centrosporus DSM 8445T (AB112719) + +

+ +

+ B. invocatus LMG 18962T (AF378232) + +

+
+
+

+ + + + + + + + + + + + + + + + + + + + + + + + +

+
+
+

+ 99 B. panacihumi C17 (EU383032) + +

+ +

+ B. borstelensis DSM 6347T (AB112721) + +

+ +

+ B. levickii LMG 22481T (AJ715378) + +

+ +

+ B. thermoruber DSM 7064T (AB112722) + + B. laterosporus DSM 25T (AB112720) + +

+ +

+ B. ginsengisoli Gsoil 3088T (ABZ45376) + + Aneurinibacillus aneurinilyticus DSM 5562T + + (AB112724) + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001354-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001354-0-000.pbm.png new file mode 100644 index 00000000..a31caaaa Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001354-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001354-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001354-0-000.pbm.png.hocr new file mode 100644 index 00000000..aa9440b3 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001354-0-000.pbm.png.hocr @@ -0,0 +1,98 @@ + + + + + + + + + + + +
+
+

+ Arthrobacter globiformis DSM 20124T (M2341 1) + + Agromyces ramosus DSM 43045T (X77447) + + 87 Pseudoclavibacter helvo/us DSM 20419T (X77440) + + Gu/osibacter molinativorax 0N4T (AJ306835) + + Leucobacter komagatae IFO 15245T (AB007419) + +

+
+
+

+ 67 Frondicola australicus DSM 17894T (DQ525859) + + 99 Frigoribacterium faeni 801 T (Y18807) + + CIav/bacter michiganensis DSM 46364T (X77435) + + 56 Subterco/a frigoramans K265T (AF224723) + +

+
+
+

+ Mycetocola saprophi/us CM-01 T (ABO12647) + + Yonghaparkia alkaliphila KSL—113T (DQ256087) + + 100 Microce/Ia putealis CV-2T (AJ717388) + + Rathayibacter rathayi DSM 7485T (X77439) + + Labedella gwakjiensis JCM 14008T (DQ533552) + + 36 Cryobacterium psychrophi/um JCM 1463T (D45058) + + Cunobacterium citreum DSM 20528T (X77436) + + 100 Agreia bicolorata VKM Ac-1804T (AF159363) + + 38 Agreia pratensis DSM 14246T (AJ310412) + + 72 Subtercola boreus K300T (AF224722) + + Strain AHU1810 (AB378302) + + 100 Strain AHU1791T (AB378301) + + 61 Plantibacter flavus DSM 14012T (AJ310417) + + Okibacterium friti/lariae VKM Ac—2059T (AB042094) + + 100 Rhodoglobus vestalii LV3T (AJ459101) + + E Salinibacterium amurskyense KMM 3673T (AF539697) + + Microterricola vlrldarii KV—677T (A3282862) + + Leifsonia aquatica DSM 20146T (X77450) + + 0-01 Agrococcus jenensis DSM 9580T (X92492) + +

+
+
+

+ I—I Microbacterium Iacticum DSM 20427T (X77441) + + 100 Microbacterium sch/eiferi IFO 15075T (ABOO4723) + +

+
+
+

+ 65 + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001362-0-002.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001362-0-002.pbm.png new file mode 100644 index 00000000..bdb07af2 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001362-0-002.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001362-0-002.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001362-0-002.pbm.png.hocr new file mode 100644 index 00000000..ab1ca466 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001362-0-002.pbm.png.hocr @@ -0,0 +1,131 @@ + + + + + + + + + + + +
+
+

+ Ha/obacillus halophilus DSM 2266T (X62174) + + Marinococcus ha/ophi/us DSM 20408T (X90835) + + SporalactobaciI/us inu/inus ATCC 15538T (M58838) + + Exiguobacterium aurantiacum NCDO 2321T (X70316) + + Aneurinibacillus aneurinilyticus DSM 5562T (X94194) + + Brevibaci/lus brevis JCM 2503T (D78457) + +

+ +

+ Paenibacillus polymyxa IAM 13419T(D16276) + + Alicyc/obaciI/us acidoterrestris DSM 3922T (AJ133631) + + SulfobaciI/us thermosu/fidooxidans AT-1T (X91 080) + + Mechercharimyces asporophorigenens YM11-542T (AB239532) + + Mechercharimyces mesophilus YM3-251T (AB239529) + +

+ +

+ Shimazuella kribbensis A 9500T (ABO49939) + +

+ +

+ Seinonella peptonophila KCTC 9740T (AF138735) + + Thermof/avomicrobium dichotomicum KCTC 3667T (AF138733) + + Thermoactinomyces intermedius ATCC 33205T (AJ251775) + + Thermoactinomyces vulgaris KCTC 9076T (AF138739) + +

+ +

+ Laceye/Ia putida KCTC 3666T (AF138736) + +

+ +

+ Laceyella sacchari NCIMB 11367T (AJ251777) + +

+ +

+ Desmospora activa IMMIB L-1269T (AM940019) + +

+ +

+ 73 PIanifi/um fimeticola HO165T(A3088364) + +

+ +

+ Planifilum fulgidum 500275T (A8088362) + +

+ +

+ 100 Planifi/um yunnanense LA5T (DQ119659) + +

+
+
+

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

+
+
+

+ 2‘0 % + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001420-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001420-0-000.pbm.png new file mode 100644 index 00000000..c9996573 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001420-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001420-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001420-0-000.pbm.png.hocr new file mode 100644 index 00000000..8cebf9f7 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001420-0-000.pbm.png.hocr @@ -0,0 +1,260 @@ + + + + + + + + + + + +
+
+

+ 0.005 + +

+
+
+

+ 75 + +

+
+
+

+ 5‘1 + + 100 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 85 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 67 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 98 + +

+
+
+

+ + +

+
+
+

+ 73 + +

+
+
+

+ + +

+
+
+

+ P. chlororaphis IAM 12354T (084011) + + P. fluorescens DSM 50090T (276662) + + P. syringae LMG 1247T (276669) + +

+
+
+

+ P. putida DSM 291T (276667) + +

+
+
+

+ _|_—P. parafu/va AJ 2129T (ABO60132) + + P. p/ecoglossicida FPC 951T (AB009457) + +

+
+
+

+ P. nitroreducens IAM 1439T (084021) + +

+
+
+

+ P. stutzeri IAM 12668T (D84024) + +

+
+
+

+ P. aeruginosa LMG 1242T (276651) + +

+
+
+

+ P. Iuteo/a IAM 13000T (D84002) + + P. pohangensis H3—R18T (D0339144) + + P. pachastreI/ae KMM 330T (AB125366) + +

+
+
+

+ 99 + +

+
+
+

+ + +

+
+
+

+ Strain 83-3T (EU286805) + + ‘P. denitriflcans‘ IAM 12023 (ABOZ1419) + + P. pertucinogena IFO 14163T (AB021380) + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001461-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001461-0-000.pbm.png new file mode 100644 index 00000000..86401253 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001461-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001461-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001461-0-000.pbm.png.hocr new file mode 100644 index 00000000..faf2ae42 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001461-0-000.pbm.png.hocr @@ -0,0 +1,148 @@ + + + + + + + + + + + +
+
+

+ 0,02 + +

+
+
+

+ Halomonas aquamarina DSM 30161T (AJ306888) + + Halomonas meridiana DSM 5425T (AJ306891) + + Halomonas magadiensis 21 MIT (X92150) + + Halomonas variabilis DSM 3051T (AJ306893) + + Halomonas sulfidaeris Esulfide1T (AF212204) + + Halomonas venusta DSM 4743T (AJ306894) + + Halomonas hydrothermalis Slthf2T (AF212218) + + Halomonas desiderata FB2T (X92417) + + Halomonas campisalis ATCC 700597T (AF054286) + +

+ +

+ Halomonas halmophi/a ATCC 19717T (AJ306889) + + Halomonas eurihalina ATCC 49336T (X87218) + + Halomonas elongata ATCC 33173T (X67023) + + Halomonas ha/ophila DSM 4770 T (M93353) + + Halomonas organivorans G-16.1T (AJ616910) + + Chromoha/obacter sa/exigens DSM 3043T (AJ295146) + + Chromoha/obacter israe/ensis ATCC 43985T (AJ295144) + + Chromohalobacter canadensis ATCC 43984T (AJ295143) + + Chromoha/obacter marismon‘ui ATCC 17056T (X87219) + +

+ +

+ 71 Halomonas marisflavi SW32T (AF251 143) + + Halomonas indalinina CG2.1T (AJ427627) + + Halomonas avicenniae MWZaT (DQ888315) + + Strain A10T (AM941746) + + Modicisalibacter tunisiensis LIT2T (DQ641495) + + Cobetia marina DSM 4741T (AJ306890) + + Carnimonas nigrificans CTCBS1T (Y13299) + + Ha/otalea alkali/enta AW—7T (DQ421388) + + Zymobacter palmae ATCC 51623T (AF211871) + +

+
+
+

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

+
+
+

+ 98 + +

+
+
+

+ + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001479-0-001.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001479-0-001.pbm.png new file mode 100644 index 00000000..db6bc1e8 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001479-0-001.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001479-0-001.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001479-0-001.pbm.png.hocr new file mode 100644 index 00000000..1b77a1b2 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001479-0-001.pbm.png.hocr @@ -0,0 +1,168 @@ + + + + + + + + + + + +
+
+

+ 7 + +

+
+
+

+ 0.01 + +

+
+
+

+ 87 + +

+
+
+

+ 88 + + 85 + +

+
+
+

+ 89 + +

+
+
+

+ 99 + +

+
+
+

+ 93 + +

+
+
+

+ A. Iuteof/uorescens IFO 13057T (U49008) + + A. coeru/ea IFO 14679T (U49002) + + A. verrucospora IFO 14100T (U49011) + + A. citrea IFO 14678T (U49001) + + A. glauciflava AS41202T (AF153881) + + A. macra IFO 14102T (U49009) + + A. madurae JCM 7436T (U58527) + + A. formosensis JCM 7474T (AF002263) + +

+
+
+

+ A. pellet/er] JCM 3388T(AF163119) + + 100 A. cremea subsp. cremea JCM 3308T(AF134067) + +

+
+
+

+ A. cremea subsp. rifamycini IFO 14183T(U49003) + + A. catellat/spora AS41522T (AF154127) + +

+
+
+

+ A. livida JCM 3387T (AF163116) + + A. yumaensis JCM 3369T (AF163122) + +

+
+
+

+ A. vinacea JCM 3325T (AF134070) + + A. Viridis IFO 15238T (D85467) + +

+
+
+

+ Thermomonospora sun/eta JCM 3096T + + A. umbrina JCM 68377 (AF163121) (AF002262) + + A. echinospora IFO 14042T (U49004) + + A. spadix JCM 3146T (AF163120) + + Spiri/Iospora rubra JCM 6875T(AF163123) + + A. fibrosa ATCC 49459T (AF1631 14) + + A. nitrit/genes DSM 44137T (AYO35999) + + Spiri/lospora albida IFO 12248T (D85498) + + A. Iatina DSM 43382T (AY035998) + + A. rugatobispora IFO 14382T (U49010) + + A. fulvescens IFO 14347T (U49005) + + A. atramentaria IFO 14695T(U49000) + + 100 A. rubrobrunea IFO 14622 (AF134069) + + A. viridi/utea IFO 14480T (D86943) + + BC 44T-5T (EF116925) + + A. oligospora ATCC 43269T (AF163118) + +

+
+
+

+ 99 + +

+
+
+

+ A. hibisca JCM 9627T (AF163115) + + A. kijaniata IFO 14229T (U49006) + +

+
+
+

+ Actinocora/lia herbida IFO 15485T (D85473) + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001503-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001503-0-000.pbm.png new file mode 100644 index 00000000..15ebb3a8 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001503-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001503-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001503-0-000.pbm.png.hocr new file mode 100644 index 00000000..91e0e642 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001503-0-000.pbm.png.hocr @@ -0,0 +1,166 @@ + + + + + + + + + + + +
+
+

+ 0.01 + +

+
+
+

+ 97 + +

+
+
+

+ 100 + +

+
+
+

+ 96 + + 53 + +

+
+
+

+ 91 + +

+
+
+

+ 99 + +

+
+
+

+ 88 + +

+
+
+

+ 100 + +

+
+
+

+ 73 A. gerencseriae DSM 6844T (X80414) + +

+
+
+

+ 51 A. israelii CIP 103259T (X82450) + + A. massiliensis 4401292T (EF558367) + + 57 A. on'cola CCUG 46090T (AJ507295) + + 81 A. dental/s R18165T (AJ697609) + + 82 A. ruminicola B71T (DQO72005) + +

+
+
+

+ A. denticolens NCTC 11490T (X80412) + + A. catuli CCUG 41709T (AJ276805) + + A. howe/lii NCTC 11636T(X80411) + + A. slackii CCUG 32792T (AJ234066) + +

+
+
+

+ 1. A. bowdenii CCUG 37421T (AJ234039) + +

+
+
+

+ A. naeslundii DSM 43013T (X53226) + + 100 A. viscosus DSM 43327T (M33908) + + A. urogenitalis CCUG 28744 (AJ243893) + + A. Davis NCTC 11535T (X81061) + + A. radicidentis CCUG 36733T (AJ251986) + + A. graevenitzii CCUG 27294T (AJ540309) + + A. nasicola CCUG 46092T (AJ508455) + + A. hongkongensis HKU8T (AF433168) + + A. marimammalium CCUG 41710T (AJ276405) + + A. canis CCUG 41706T (AJ243891) + + A. radingae APL1T (X78719) + + A. georgiae DSM 6843T (X80413) + + A. odontolyticus CCUG 20536T (AJ234040) + + A. cardiffensis CCUG 44997T (AJ421779) + + A. vaccimaxillae R10176T (AJ427451) + + A. tun'censis APL10T (X78720) + + A. funkei CCUG 42773T (AJ404889) + + A. hyovaginalis NCFB 2983T (X69616) + + A. suimastitidis CCUG 3927GT (AJ277385) + + A. coleocanis CCUG 41708T (AJ249326) + + A. europaeus CCUG 32789 N (AM084230) + +

+
+
+

+ + +

+
+
+

+ A. neuii subsp. anitratus DSM 8577T (AM084229) + + 100 A. neuii subsp. neuii DSM 85761(AM084228) + + Varibaculum cambn'ense CCUG 44998T (AM084231) + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001529-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001529-0-000.pbm.png new file mode 100644 index 00000000..1cbac7f3 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001529-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001529-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001529-0-000.pbm.png.hocr new file mode 100644 index 00000000..6580046c --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001529-0-000.pbm.png.hocr @@ -0,0 +1,164 @@ + + + + + + + + + + + +
+
+

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

+
+
+

+ Pedobactcr afficanus DSM 12126T (AJ438171) + + Pedobacter caeni LMG 22862T (AJ786798) + + Pedobacter panaciterrae Gsoil 042T (ABZ45368) + + Pedobacter hepal‘irzus DSM 2366T (AJ438172) + + Pedobacter ginsengiso/i Gsoil 104T (AB24537I) + + Pedobacter insulae DS-39T (EF100697) + +

+
+
+

+ 100 Splzingobaclerium antarcticum 6BlY (AJ 576248) + + Pedabacter piscium DSM 1 1725T (AJ438174) + +

+
+
+

+ Pedobacter cryocom‘tis DSM 14825T (AJ438170) + + Pedobacter lzimalayensis HHSZ2T (A.1583425) + + edabacter aquatilis ARlO7T (AMI 14396) + + Pedobacter roseus CL-GP80T (DQl 12353) + + Pedobacter suwonensz’s 15-52T (DQ097274) + + Pedobacrer sandarakinus DS-27T (DQ235228) + + Pedabacrer terrico/a DS-45T (EF446147) + + Pedobacter lentus DS-40T (EF446146) + + Pedobacter (laechungensis Dae 13T (AB267722) + + Pedobacter salrans DSM 12145T (AJ438173) + +

+ +

+ Olivibacter itius AW-6T (DQ421387) + + Parapedobacler koreensis Jipl4T (DQ680836) + + Pseudosphingobacterium domesticum DC-186T (AM407725) + +

+
+
+

+ Sphingobuclerium daejeonense '1'R6-04T (ABZ49372) + + Sphingobactcrium mizumii DSM 11724T(AJ438175) + + phl’ngobacterium composri 4M24T (EF 122436) + + Sphingobacterl’um spiritivomm DSM 2582T (AJ459411) + + Sphingobaclerhtmfaecium DSM 11690'1 (AJ438176) + + Sphingobacterium I‘halpophi/um DSM 11723T (AJ438177) + +

+ +

+ 98 Sphingobacterium multivorum 1AM 14316T(A13100738) + + Bacteroides fragilis DSM 2151T (AB050106) + +

+
+
+

+ 0.02 + +

+
+
+

+ 100 + +

+
+
+

+ 86 + +

+
+
+

+ + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001537-0-001.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001537-0-001.pbm.png new file mode 100644 index 00000000..c04865c5 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001537-0-001.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001537-0-001.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001537-0-001.pbm.png.hocr new file mode 100644 index 00000000..63de0b1d --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001537-0-001.pbm.png.hocr @@ -0,0 +1,271 @@ + + + + + + + + + + + +
+
+

+ 0.02 + +

+
+
+

+ Desulfuromonas acetexigens DSM 1397T (U23140) + + Desulfuromonas michiganensis’ BB1 (AF357915) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ Desulfuromonas Chloroethenica TT4BT (U49748) + + Pelobacter carbinolicus Gra Bd1T (X79413) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ Pelobacter acetylenicus WoAcy 1T (X70955) + + Pelobacter venetianus DSM 2394T (U41562) + + Desulfuromonas palm/tatis SDBY1T (U28172) + + Geoalkalibacter ferr/hydriticus 2-0531T (DQ309326) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ Geoalkalibacter subterraneus Red1T (EU182247) + + Geobacterpelophilus Dfr2T (U96918) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ Geobacterpickeringii G13T (DQ145535) + +

+ +

+ Geobacter sulfurreducens PCAT (U13928) + +

+ +

+ Geobacter hydrogenophilus H-2T (U28173) + +

+ +

+ » Geobactergrbiciae TACP-2T (AF335182) + +

+ +

+ Geobacter metal/ireducens GS-15T (L07834) + +

+ +

+ Geothermobacter ehrlichii 88015T (AY155599) + + Desulfuromonas acetoxidans DSM 684T (M26634) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ Desulfuromonas thiophila N227T (Y11560) + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001552-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001552-0-000.pbm.png new file mode 100644 index 00000000..56ebe098 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001552-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001552-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001552-0-000.pbm.png.hocr new file mode 100644 index 00000000..e4167840 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001552-0-000.pbm.png.hocr @@ -0,0 +1,63 @@ + + + + + + + + + + + +
+
+

+ Alcanivorax borkumensis 8K2T (Y12579) + +

+
+
+

+ + + + + + + + + + +

+
+
+

+ 0-01 Alcanivorax jadensis T9T (AJOO1150) + +

+
+
+

+ Alcanivorax hongdengensis A-11-3T (EU438901) + + Alcanivorax venustensis |SO4T (AF328762) + + Alcanivorax balearicus MAC L04T (AY686709) + +

+ +

+ 100 Alcanivorax dieselo/ei B—5T (AY683537) + +

+
+
+

+ Pseudomonas fluorescens IAM 12022T (D84013) + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001651-0-001.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001651-0-001.pbm.png new file mode 100644 index 00000000..38945c51 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001651-0-001.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001651-0-001.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001651-0-001.pbm.png.hocr new file mode 100644 index 00000000..b8238fb0 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001651-0-001.pbm.png.hocr @@ -0,0 +1,198 @@ + + + + + + + + + + + +
+
+

+ Mesorhizobium chacoense PR5T (AJ278249) + + 0 10 Pseudaminobacter salicylatoxidans BN12T (AF072542) + + ' Mesorhizobium mediterraneum DSM 11555T (L38825) Rhizobiales + +

+
+
+

+ + +

+
+
+

+ PhyI/obacterium Ieguminum ORS 1419T (AY785323) + + Ensifer terangae LMG 7834T (X68388) + +

+ +

+ Roseobacter litora/is ATCC 49566T (X78312) + + Ruegeria gelatinovorans IAM 12617T (D88523) + + Roseovarius Iolerans DSM 11457T (Y11551) + +

+ +

+ Silicibacterlacuscaerulensis DSM 11314T (U77644) + + Roseivivax ha/odurans OCh 239T (D85829) + + Paracoccus denitrificans ATCC 17741T (Y16927) + + . Rhodobacter sphaeroides DSM 158T (X53855) + + Pseudovibrio ascidiaceicola NRBC 100514T (AB175663) + + Pseudovibrio denitrificans DN34T (AY486423) + + Nesiotobacter exalbescens LA33BT (AF513441) + + Stappia aggregate IAM 12614T (D88520) + + Stappia stellulata IAM 12621T (D88525) + + Kordiimonas gwangyangensis GW14-5T (AY682384) + + Parvularcula bermudensis HTCC2503T (AF544015) + + Asticcacaulis excentricus ATCC 15261T (ABO16610) + + Caulobacter vibrioides DSM 9893T (AJ227754) + + Brevundimonas diminuta ATCC 11568T (M59064) + + Sphingomonas paucimobilis ATCC 29837T (U37337) + + Zymomonas mobilis ATCC 10988T (AF281031) Sphingomonada/es + + Blastamonas ursinco/a KR-99T (Y10677) + + Craurococcus roseus NS13OT (D85828) + + Paracraurococcus ruber N889T (D85827) + + Roseomonas aquatica TR53T (AM231587) + + Raseococcus thiosulfatophilus RB-3T (X72908) + + . Acetobacler orienta/is 21 F-2T (A3052706) + + Kozakia baliensis Yo-3T (A8056321) + + Gluconobacter oxydans NRBC 14819T (AB178433) + + Tistrella mobilis IAM 14872.r (ABO71665) + + Rhodovibrio sodomensis DS1T (M59072) + + Azospin'llum Iipoferum ATCC 29707T (M59061) + + Magnetospirillum gryphiswaldense DSM 6361T (Y10109) + + Rhodospira trueperi ATCC 700224T (AJ001276) + + Roseospira goensis .JA135T (AM283537) + + Rhodaspiril/urn rubrum ATCC 11170T (CP000230) + + . Thalassospira xiamensis M-5T (AY189753) + + Thalessospira Iucentensis DSM 14000T (AM294944) + + Thalassospira profundimaris WP021 1T (AY186195) + + Terasak/e/la pusiI/a IFO 13613T (AB006768) _ + + Strain KOPRI 13522 (DQ167245) + + Kiloniella Iaminariae LD81T (AM749667) + + Orientia tsutsugamushi KarpT (AFO62074) + + Rickettsia prowazekii Breian (M21789) Rickettsia/es + + Wo/bachia pipientis (U23709) + + Hyphomicrobium indicum NBRC 14233T (AB159513) + + Vibrio chagasii R-3712T (AJ316199) + + Escherichia coli W31 10 (AP009048) + + Pseudoalteromonas maricaloris KMM 636T (AF144036) _ + +

+
+
+

+ Rhodobacterales + +

+
+
+

+ Kordiimonada/es + + ‘Parvu/arculales’ + +

+
+
+

+ I + + Caulobactera/es + +

+
+
+

+ I III” + +

+
+
+

+ I I + +

+
+
+

+ Rhodospirillales + +

+
+
+

+ I l + +

+
+
+

+ Outgroup + +

+
+
+

+ + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001677-0-001.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001677-0-001.pbm.png new file mode 100644 index 00000000..bb2dc2bc Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001677-0-001.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001677-0-001.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001677-0-001.pbm.png.hocr new file mode 100644 index 00000000..6cb13a9b --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001677-0-001.pbm.png.hocr @@ -0,0 +1,134 @@ + + + + + + + + + + + +
+
+

+ Methanolobus bombayensis B-1T (U20148) + + 68/71/73 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 82,70,54 Methanolobus tinder/us DSM 2278T(M59135) + +

+
+
+

+ + + + + + + + + + + + + + + + + + +

+
+
+

+ + +

+
+
+

+ 88/80/80 Methanolobus vulcani PL-12/MT(U20155) + +

+
+
+

+ Methanolobus + +

+
+
+

+ 100,100,97 Methanolobus profundi MobMT (AB370245) + +

+
+
+

+ Methanolobus taylorii GS-16T(U20154) + +

+
+
+

+ 66/59/50 . T + + Methanolobus oregonen3/s WAL1 (U20152) + +

+
+
+

+ + +

+
+
+

+ Methanohalophilus mahii DSM 5219T(M59133) + +

+
+
+

+ 57/56/51 + + Methanococcoides methylutens DSM 2657T(M59127) + +

+
+
+

+ Methanosarcina barkeri DSM 800T(AJO12094) + +

+
+
+

+ 0,02 + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001685-0-001.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001685-0-001.pbm.png new file mode 100644 index 00000000..db529a33 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001685-0-001.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001685-0-001.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001685-0-001.pbm.png.hocr new file mode 100644 index 00000000..de50ab7b --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001685-0-001.pbm.png.hocr @@ -0,0 +1,120 @@ + + + + + + + + + + + +
+
+

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

+
+
+

+ 0.005 + +

+
+
+

+ Dugane/la violaceinigra YIM 31327T(AY376163) + +

+
+
+

+ Mass/lie albidiflava 45T (AY965999) + + Naxibacter alkalitolerans YIM 31775T (AY679161) + + Telluria mixta ACM 1762T (X65589) + + Janthinobacterium agaricidamnosum W1r1’:T (Y08845) + + Aquaspin'llum arcticum IAM 14963T (ABO74523) + + Herminiimonas glaciei UMB49T (EU489741) + + Ultramicrobacterium ISSDS-831 (EF620474) + + Janthinobacterium sp. Marseille (CP000269) + + 100 Ultramicrobacterium Um1 (AY387012) + + Ultramicrobacterium HI-G4 (DQ205303) + + Ultramicrobacterium ND5 (ABOOB506) + + Herm/niimonas saxobsidens N81 1T (AM493906) + + Herminiimonas arsenicoxydans ULPAs1T (AY728038) + + Herminiimonas aquatilis CCUG 36956T (AM085762) + + Herminiimonas fonticola S-94T (AY676462) + + 100 HerbaspiriI/um Iusitanum PIS—12T (AF543312) + + Herbaspin'llum hiltneri N3T (DQ150563) + + Herbaspirillum rhizosphaerae UMS-37T (DQ188986) + + Collimonas fungivorans TerfiT (AJ310394) + + Paucimonas Iemoignei LMG 2207T (X92555) + + Oxalicibacterium flavum LMG 21571T (AY061962) + + Oxalobacter form/genes OXBT (U49757) + + Undibacterium pigrum CCUG 49009T (AM397630) + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001693-0-001.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001693-0-001.pbm.png new file mode 100644 index 00000000..df4e89d6 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001693-0-001.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001693-0-001.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001693-0-001.pbm.png.hocr new file mode 100644 index 00000000..c9a85dce --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001693-0-001.pbm.png.hocr @@ -0,0 +1,485 @@ + + + + + + + + + + + +
+
+

+ 80 + +

+
+
+

+ 0.01 + +

+
+
+

+ 100 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 100 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 100 + +

+
+
+

+ + +

+
+
+

+ + + + + + + + + + + + +

+
+
+

+ _— Methy/obacterium zatmam'i NCIMB 12243T (L20804) + + Methylobacterium podarium FM4T (AF514774) + + Methy/obacterium chloromethanicum CM4T (AF198624) + +

+ +

+ Methy/obacterium Iusitanum RXMT (AY009403) + +

+ +

+ LMethy/obacterium populi BJ001T (AY251818) + + Methylobacterium thiocyanatum ALL/SCN-PT (U58018) + +

+ +

+ Methy/obacterium aminovorans CCM 4612T (AJ851086) + +

+ +

+ Methy/obacterium extorquens JCM 2802T (D32224) + +

+ +

+ Methylobacterium rhodes/anum JCM 2810 (D32228) + +

+ +

+ Methylobacterium suomiense F20T (AY009404) + +

+ +

+ Methy/obacterium salsuginis MRT (EF015478) + +

+ +

+ Methylobacterlum dichloromethanicum DM4T (AF227128) + +

+ +

+ Methylobacterium rhodinum JCM 2811T (D32229) + +

+ +

+ 99 Methylobacterium adhaesivum AR27T (AM040156) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ Methy/obacterium iners 53173-33T (EF174497) + +

+
+
+

+ Methylobacterium organophilum JCM 2833T (D32226) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ Methy/obacterium jeotgali SZROGl-QT (DQ471331) + +

+
+
+

+ + +

+
+
+

+ 59 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ Methy/obacterium h/spanicum GP34T (AJ635304) + + 52 Methy/obacterium aero/atum 54133-11T (EF174498) + +

+ +

+ 64 Methy/obacterium mesophi/icum JCM 2829T (D32225) + + 86 Methylobacterium fujisawaense DSM 5686T (AJ250801) + +

+ +

+ 85 Methylobacterium radioto/erans JCM 2831T (D32227) + + Methylobacterium phyllosphaerae CBMB27T (EF126746) + + 54 Methylobacterium oryzae CBMBZOT (AY683045) + +

+ +

+ Methylobacterium variabi/e GR3T (AJ851087) + + 7 Methy/obacterium aquat/cum GR16T (AJ635303) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 88 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 100 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ Methy/obacterium platani PMBOZT (EF426729) + +

+
+
+

+ Methy/obacterium isbi/iense AR24T (AJ888239) + +

+
+
+

+ Methylobacterium nodulans ORS 2060T (AF220783) + + Methylorhabdus multlvorans DM13T (AF004845) + + Albibacter methy/ovorans DM10T (AF273213) + +

+
+
+

+ Methylopi/a capsu/ata |M1T (AF004844) + +

+
+
+

+ Methy/ocystis parvus OBBPT (M29026) + + Methy/osinus trichosporium OBSbT (M29024) + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001719-0-001.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001719-0-001.pbm.png new file mode 100644 index 00000000..c2364202 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001719-0-001.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001719-0-001.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001719-0-001.pbm.png.hocr new file mode 100644 index 00000000..ddb1f99f --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001719-0-001.pbm.png.hocr @@ -0,0 +1,130 @@ + + + + + + + + + + + +
+
+

+ 6m + +

+
+
+

+ + +

+
+
+

+ 1000 + +

+
+
+

+ —Clostridium hungatei ATCC 700212T (AF020429) + +

+
+
+

+ -Clostridium termitidis DSM 5396 (X71854) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ ooo + + Clostridium cellobioparum DSM 1351T (X71856) + +

+
+
+

+ + +

+
+
+

+ 1000 + +

+
+
+

+ Clostn'dium papyroso/vens DSM 2782T (X71852) + +

+
+
+

+ CDT-1T (A3267266) + +

+
+
+

+ 726 Clostridium josui FERM P-9684T (ABO11OS7) + +

+
+
+

+ 1000 + + Clostridium cellu/o/yflcum ATCC 35319T (X71847) + +

+
+
+

+ —Acetivibrio cellu/o/yticus ATCC 33288T (L35516) + +

+
+
+

+ + +

+
+
+

+ —C/ostridium aldrichii DSM 6159T (X71846) + + Clostridium thermoce/lum DSM 1237T (L09173) + +

+
+
+

+ Bacillus subtilis NCDO 1769T (X60646) + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001743-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001743-0-000.pbm.png new file mode 100644 index 00000000..181e643e Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001743-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001743-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001743-0-000.pbm.png.hocr new file mode 100644 index 00000000..e4769f4b --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001743-0-000.pbm.png.hocr @@ -0,0 +1,670 @@ + + + + + + + + + + + +
+
+

+ 100 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 78 + +

+
+
+

+ 100 + +

+
+
+

+ Cel/u/omonas flavigena NCIMB 8073T (X79463) + + Ce/lu/omonas ce/Iasea DSM 20118T (X83804) + +

+
+
+

+ 100 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ SB + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 79 + +

+
+
+

+ + +

+
+
+

+ 99 + +

+
+
+

+ 96 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 99 + +

+
+
+

+ + +

+
+
+

+ 100 + +

+
+
+

+ 98 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ Microbacterium sch/eiferi DSM 20489T (Y17237) + + Microbacterium lacticum DSM 20427T (X77441) + + Microbacterium quuefaciens DSM 20638T (X77444) + +

+
+
+

+ Plantibacter flavus DSM 14012T (AJ310417) + + Okibacterium friti/Iariae VKM Ac—ZOSQT (ABO42094) + + Agrococcus jenensis DSM 9580T (X92492) + +

+
+
+

+ Leffson/a poae VKM Ac—1401T(AF116342) + +

+
+
+

+ Leifsonia aquatica DSM 20146T (X77450) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ Leucobacter komagatae IFO 15245T (AJ746337) + +

+
+
+

+ Subtercola boreus K300T (AF224722) + +

+
+
+

+ —1_ + +

+
+
+

+ 100 Leifsonia rubra CMS 76rT (AJ438585) + + Pseudoc/avibacter he/volus DSM 20419T (X77440) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 0.01 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 97 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 100 + +

+
+
+

+ + +

+
+
+

+ 100 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ Agreia bico/orata VKM Ac—1804T (AF159363) + + Salinibacterium amurskyense KMM 3673T (AF539697) + + Rhodoglobus vesta/ii LV3T (AJ459101) + +

+
+
+

+ Rathayibacter tritici DSM 7486T (X77438) + + Rathayibacter rathayi DSM 7485T (X77439) + +

+
+
+

+ Rathayibacter toxicus JCM 9669T (D84127) + + Curtobacterium citreum DSM 20528T (X77436) + +

+
+
+

+ - Mycetoco/a tolaasinivorans CM—05T (ABO12646) + + Mycetoco/a lacteus CM-10T (AB012648) + + Mycetocola saprophi/us CM-01T (ABO12647) + +

+
+
+

+ Clavibacter michiganensis P 250/01 (AJ310416) + + Subterco/a frigoramans K265T (AF224723) + + Frigoribacterium faeni 801 T (Y18807) + +

+
+
+

+ 100 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ Mlcroce/la putealis CV2T (AJ717388) + + Microcella alkaliphila AC4rT (AJ717385) + + Yonghaparkia alkaliphi/a KSL-113T (D0256087) + +

+
+
+

+ Labede/Ia gwakjiensis KSW2-17T (D0533552) + + Cryobacterium psyohrophi/um DSM 4854T (AJ544063) + +

+
+
+

+ + +

+
+
+

+ 100 + +

+
+
+

+ + +

+
+
+

+ 69 + +

+
+
+

+ + +

+
+
+

+ 89 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ ‘Candidatus Planktoluna difficilis’ MWH-7Well8 (AM939566) + +

+
+
+

+ ‘Candidatus Aquiluna rubra’ MWH-Dar4 (AJ565416) + + ‘Candidatus Limnoluna rubra’ MWH-EgelM2-3 (AM943659) + + ‘Candidatus Flaviluna lacus’ MWH-Creno3D3 (AM939567) + + ‘Candidatus Rhodoluna lacicola‘ MWH-Ta8 (AM182889) + +

+
+
+

+ + +

+
+
+

+ 87 + +

+
+
+

+ + +

+
+
+

+ ‘Candidatus Rhodoluna limnophila’ MWH-VicMua1 (AJ565417) + + ‘Candidatus Rhodoluna planktonica’ MWH-Dar1 (AJ565415) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001768-0-001.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001768-0-001.pbm.png new file mode 100644 index 00000000..34e45e05 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001768-0-001.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001768-0-001.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001768-0-001.pbm.png.hocr new file mode 100644 index 00000000..99994029 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001768-0-001.pbm.png.hocr @@ -0,0 +1,298 @@ + + + + + + + + + + + +
+
+

+ 0.01 + +

+
+
+

+ 88 + +

+
+
+

+ 99 + +

+
+
+

+ Vibrio proteolyticus ATCC 15338T (X74723) + + Vibrio nere/s ATCC 25917T (X74716) + +

+ +

+ Vibrio diabolicus HE8OOT (X99762) + +

+ +

+ Vibrio brasiliensis LMG 20546T (AJ316172) + + Vibrio tubiashii ATCC 19109T (X74725) + +

+ +

+ Vibrio coral/iilyticus LMG 20984T (AJ440005) + + Vibrio neptun/us LMG 20536T (AJ316171) + + Vibrio oriental/'3 ATCC 33934T (X74719) + +

+ +

+ Vibrio cholerae CECT 514T (X76337) + +

+
+
+

+ + + + + + + + + + + + + + + + +

+
+
+

+ 56 + +

+
+
+

+ 85 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ Vibrio hollisae LMG 21416 (AJ514910) + +

+
+
+

+ terovibrio coralii LMG 22228T (AJ842343) + + ND1-1T (A3285018) + +

+
+
+

+ Salinivibrio costicola subsp. alca/iphi/us DSM 16359T (AJ640132) + + Sal/nivibrio costico/a subsp. cost/cola NCIMB 701T (X95527) + +

+
+
+

+ Salinivibrio cost/bola subsp. val/ismon‘is DSM 8285T (AF057016) + + 97 Salin/vibrio proteolyticus AF—2004T (D0092443) + +

+
+
+

+ Escherichia coli ATCC 1 1775T (X80725) + +

+
+
+

+ fl: + +

+
+
+

+ En + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + + + + + + + +

+
+
+

+ 56 + +

+
+
+

+ + +

+
+
+

+ 100 + + 100 + +

+
+
+

+ 66 + +

+
+
+

+ + +

+
+
+

+ Aeromonas biva/v/um 868ET (DQ504429) + +

+
+
+

+ + +

+
+
+

+ 99 + +

+
+
+

+ Psychromonas antarct/ca DSM 10704T (Y14697) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 100 + +

+
+
+

+ Aestuariibacter halophi/us JCZO43T (AY207503) + +

+
+
+

+ Pseudoa/teromonas bacteriolytica IAM 14595T(D89929) + + 62 —Pseudoalteromonas halop/anktis ATCC 14393T (X67024) + +

+
+
+

+ + +

+
+
+

+ Pseudoalteromonas piscicida IAM 12932T (AF297959) + + 10° Pseudoalteromonas mar/caloris LMG19692T(AF144036) + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001784-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001784-0-000.pbm.png new file mode 100644 index 00000000..21793490 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001784-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001784-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001784-0-000.pbm.png.hocr new file mode 100644 index 00000000..bcb44b53 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001784-0-000.pbm.png.hocr @@ -0,0 +1,126 @@ + + + + + + + + + + + +
+
+

+ 55 Xanthomonas sacchan' LMG 471T (Y10766) + +

+ +

+ Xanthomonas melonis LMG 8670T (Y10756) + + Xanthomonas campestris LMG 568T (X95917) + + Pseudoxanthomonas broegbemensis B1616/1T (AJO12231) + + Stenotrophomonas maltophi/ia LMG 958T (X95923) + +

+ +

+ X ylel/a fastidiosa ATCC 35879T (AF192343) + +

+ +

+ Luteimonas mephitis B1953/27.1T (AJ012228) + +

+ +

+ Lysobacter enzymogenes DSM 2043T (AJ298291) + + Lysobacter antibioticus DSM 2044T (ABO19582) + + Fulvimonas soli LMG 19981T (AJ311653) + +

+ +

+ Dye/Ia japonioa XD53T (AB110498) + +

+ +

+ Dye/Ia koreensis BB4T (AY884571) + +

+ +

+ Frateuria aurantia IFO 3245T (ABOQ1194) + + Rhodanobacter ginseng/soli GR17—7T (EF166075) + + Rhodanobacter spathiphylli B39T (AM087226) + + Rhodanobacter terrae GP18—1T (EF166076) + + Rhodanobacter lindaniclasticus RP5557T (AFO39167) + + Rhodanobacter thiooxydans LCSZT (A8286179) + + Rhodanobacter fu/vus Jip2T (AB100608) + +

+ +

+ 64 Rhodanobacter ginsenosidimutans Gsoil 3054T (EU332826) + + Escherichia coli ATCC 11775T (X80725) + +

+
+
+

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001792-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001792-0-000.pbm.png new file mode 100644 index 00000000..ae4b1d36 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001792-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001792-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001792-0-000.pbm.png.hocr new file mode 100644 index 00000000..c73ee9aa --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001792-0-000.pbm.png.hocr @@ -0,0 +1,146 @@ + + + + + + + + + + + +
+
+

+ onsen/ed Indels In gyrase A + + ATP synthase beta and + +

+
+
+

+ ribosomal protein 52 and + + 100/99/100 Clostrldium botulinum A strain ATCC 3502 + +

+
+
+

+ Clostridium botulinum F strain Langeland + + “30/38/58 71/78/7 Closfridium tetani + + ClostrId/um kluyven + + Clostridium acetobutylicum + + Clostridium beijerinckii + + 100/94/99 100/9moo Clostridium perfringens ATCC 13124T + + 100/100/94 Clostridlum perfringens SM101 + + Clostrldiurn pelfringens 13 + + Clostridium phytofermentans + + Clostridium diffici/e + + 100/59/100 ‘AIka/iphi/us oremlandii’ + + 100/96“ 00 ‘A/kaliphilus metal/iredigens’ + + Clostridium thermocellum + + 9 81/82 Caldicelluloslruptor saccharolytlcus + + 100/55/100 Thermoanaerobacter pseudethanollcus + + Thermoanaerobacter tengcongensis + + Symbiobacterium thermophilum + + Desulfitobacterium hafniense + + “JO/51,— womwg M Syntrophomonas wolfei + + —— oorel/a thermoacetlca + + 81/-/- Carboxydothermus h ydrogenoformans + + 99/73/85 ‘Desulfotomaculum reducens’ + + 100/99/100 Ureap/asma parvum + + Mycop/asma mycoides + +

+
+
+

+ + +

+
+
+

+ aa conserved inse + +

+
+
+

+ in phosphoglycerate 100/97/100 + + dehydrogenase + +

+
+
+

+ + +

+
+
+

+ 79/60/99 + +

+
+
+

+ + +

+
+
+

+ 100/93/93 Lactobacillus johnsonii + + 100/96l62 Staphylococcus aureus + + 100/99/100 Bacillus subti/is + +

+
+
+

+ + +

+
+
+

+ Mycobacterium tuberculosis + + Streptomyces coelicolor + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001800-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001800-0-000.pbm.png new file mode 100644 index 00000000..b86b1418 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001800-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001800-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001800-0-000.pbm.png.hocr new file mode 100644 index 00000000..15d28447 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001800-0-000.pbm.png.hocr @@ -0,0 +1,400 @@ + + + + + + + + + + + +
+
+

+ 54 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + + + + + + + + + + + + + +

+
+
+

+ 41 + +

+
+
+

+ 82 + +

+
+
+

+ + + + + + + + + + + + + + +

+
+
+

+ 55 + +

+
+
+

+ + +

+
+
+

+ 59 + +

+
+
+

+ 11 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 63 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 99 + +

+
+
+

+ Clyplococcus sp. AA-090.4 (AY188363) + + Cryptococcus flavescens L146 (EF116912) + + Cryptococcus flavescens HB1043 (AJ509857) + + Cryptococcus flavescens CBS 942Y (A8085796) + + Cryptococcus sp. HX-2006a (DQ333277) + + Cryptococcus sp. HB1122 (AM039434) + + Cryptococcus flavescens TJY36-3 (EU301625) + + Cryptococcus flavescens JCM 9909 (AB085807) + + Cryptacoccus flavescens GGO (ABO16233) + + Cryptococcus flavescens RT 3.513 (AY731784) + + 32 Cryptococcus flavescens CBS 6473 (AF487885) + + Cryptococcus flavescens HB1178 (AM160631) + + Cryptococcus flavescens J075.4 (AY188361 ) + + Cryptococcus flavescens 8602-048 (EF068213) + + Cryptococcus Iaurentii GS42A (DQ862855) + + Cryptococcus Iaurentii KSNZ (EF635635) + +

+
+
+

+ Cryptococcus flavescens M155 (EU386716) + + Cryptococcus sp. CBS 8372 (AF444707) + + Cryptococcus flavescens SM3$07 (EF460580) + + Cryptococcus laurentii CBS 8645 (ABOB7253) + + Cryptococcus terrestris C107DX4-Y11 (EF599104) + + Cryptococcus sp. CABSSO (EU427438) + + Cryptococcus terrestris Ep11c (EU200780) + +

+
+
+

+ Cryptococcus Iaurentif 8H3 (EF644463) + + Cryptococcus flavescens DGR1 (EU441902) + +

+
+
+

+ Cryptococcus terrestris CJDX4 Y23T (EF370393) + +

+
+
+

+ Cryplococcus 5p. CBS 8366 (AF444702) + + j. Cryptococcus sp. CBS 8358 (AF444698) + + Cryptococcus aureus CBS 3181 (A3085795) + + 86 Cryptococcus aureus HN4.9 (EU304246) + + 95 Bullera japonica CBS 2013T (AF444760) + + —l Cryptococcus sp. KCTC 17079 (AF459695) + +

+
+
+

+ epep SUGOSGAQIJ snooooold/Uo + +

+
+
+

+ Cryptococcus flavescens FK2 (EF644446) + +

+
+
+

+ + +

+
+
+

+ Cryptococcus Ierrestris 56e (EU340251 ) + +

+
+
+

+ Cryptococous sp. CAB 579 (EU427439) + +

+
+
+

+ apep 3111891191 snoooomd/flo + +

+
+
+

+ epep meme '3 + +

+
+
+

+ 80 AuriculibuI/er sp. B|111 (EU200788) + +

+
+
+

+ + +

+
+
+

+ 53 + +

+
+
+

+ Auriculibuller fuscus PYCC 5690T (AF444762) + +

+
+
+

+ Auriculibuller fuscus ZIM 609 (AM748525) + + Auriculibuller fuscus PYCC 5740 (AF444761) + +

+
+
+

+ 5 + +

+
+
+

+ Bullera pseudoalba CBS 72271 (AF075504) + +

+
+
+

+ 100 Cryptococcus cellulolyticus CBS 82941 (AF075525) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ Cryptococcus Iaurentii CBS 139T (AFO75469) + + Cryptococcus Iaurentii CBS 7140 (AY315663) + +

+
+
+

+ Cryplocaccus rajaslhanensis 15LT (AM262324) + +

+
+
+

+ 58 + + 99 Cryptococcus rajasthanensis 3-C1 (AM262981) + +

+
+
+

+ + +

+
+
+

+ 0.02 + +

+
+
+

+ Cryptacoccus carnescens CBS 973T (A3085798) + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001800-0-001.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001800-0-001.pbm.png new file mode 100644 index 00000000..0fd8b6af Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001800-0-001.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001800-0-001.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001800-0-001.pbm.png.hocr new file mode 100644 index 00000000..f880c517 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001800-0-001.pbm.png.hocr @@ -0,0 +1,433 @@ + + + + + + + + + + + +
+
+

+ 100 + +

+
+
+

+ 99 + +

+
+
+

+ Cryplococcus sp. AA-090,4 (AY188363) + + Cryptococcus flavescens 660 (ABO16234) + +

+
+
+

+ + + + + + +

+
+
+

+ Cryptococcus flavescens J075.4 (AY188361) + + Cryptococcus flavescens CBS 6474 (EF056305) + + Cryptococcus flavescens CBS 8359 (EF056302) + + Cryptococcus spA P225 (AJ345008) + + Cryptococcus flavescens CBS 942r (ABD35046) + + Clyptococcus flavescens HB 1178 (AM160631) + + Cryptococcus flavescens JCM 9910 (ABOB5804) + + Clyptococcus flavescens CBS 101036 (EF056308) + + Cryptococcus flavescens CBS 4919 (EF056303) + + Cryptococcus flavescens JCM 9911 (A8085805) + + Cryptococcus flavescens JCM 9912 (A8085806) + +

+
+
+

+ 88 Cryplococcus flavescens L146 (EF126368) + +

+
+
+

+ + +

+
+
+

+ Cryptococcus flavescens CBS 6475 (EF056308) + + Basidiomycete yeast sp. DX-2006N (DQ447764) + + Cryptoooccus flavescens JCM 9909 (A8085803) + + Tremella/es sp. LM339 (EF060658) + + Tremellales sp. LM333 (EF060652) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 46 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 70 + +

+
+
+

+ + +

+
+
+

+ 85 + +

+
+
+

+ 67 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 2 + +

+
+
+

+ + +

+
+
+

+ Cryptococcus aureus JCM 5945 (AB085802) + + 58 Aureobasidium pullulans HN2,3 (DQ680843) + +

+
+
+

+ + +

+
+
+

+ + + + + + + + +

+
+
+

+ Tremel/a/es spA LM47 (EF060429) + + TremelIa/es sp, LM48 (EF060430) + +

+
+
+

+ + +

+
+
+

+ 80 + +

+
+
+

+ + +

+
+
+

+ Cryptacoccus f/avescens m155 (EF648006) + + 20‘— Cryptococcus flavescens m158 (EF648007) + +

+
+
+

+ TremeIIa/es sp. LM629 (EF060913) + +

+ +

+ 2 Cryptococcus flavescens CBS 4926 (EF056304) + + Tremella/es sp. LM651 (EF060935) + + Cryptococcus sp. CBS 8372 (EU340250) + +

+
+
+

+ + + + +

+
+
+

+ Cryptococcus terrestris Ep11c (EU200781 ) + + Cryptococcus terrestris 56s (EU340250) + +

+
+
+

+ Cryptococcus aureus NRRL Y-30215 (EF056299) + + Cryptococcus aureus CBS 318T (AB035045) + + 70 Cryptococcus aureus G7A (DQ640764) + +

+
+
+

+ Treme/lales spA LM613 (EF060898) + +

+
+
+

+ epep sneme '9 + +

+
+
+

+ Cryptococcus aureus NRRL Y—30213 (EF056298) + +

+
+
+

+ Cryplococcus 5p. CBS 8366 (AF444393) + +

+
+
+

+ 100 Cryptococcus 5p. CBS 8358 (AF444387) + +

+
+
+

+ Cryptococcus flavescens NRRL Y-30216 (EF056300) + +

+
+
+

+ + +

+
+
+

+ Cryptococcus terrestris C107DX4 Y11 (EU4991B7) + + Cryptococcus terrestris CJDX4 Y23Y (EU200782) + +

+
+
+

+ epelo sueoseAey SHOOOOOJd/DO + +

+
+
+

+ epep S/JJSGJJQJ SHOOOOOJd/UQ + +

+
+
+

+ 99 Cryptacoccus Iaurenlii CBS 139T (AF410468) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 0.01 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ Culptocaccus rajasthanensis 15LT (AM262325) + + Cryptococcus anemochoreius CBS 10258T (DQS30986) + +

+
+
+

+ 64 Bullera pseudaalba CBS 7227' (AF444399) + + 100 Cryptoooccus cellulolyticus CBS 8294Y (AF444442) + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001826-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001826-0-000.pbm.png new file mode 100644 index 00000000..cab94811 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001826-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001826-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001826-0-000.pbm.png.hocr new file mode 100644 index 00000000..70ab8169 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001826-0-000.pbm.png.hocr @@ -0,0 +1,124 @@ + + + + + + + + + + + +
+
+

+ ' I + +

+
+
+

+ 95 Aestuariibacter saleXigens J02042T (AY207502) + + Aestuariibacter halophilus JCZO43T (AY207503) + + Glaciecola polaris LMG 21857T(AJ293820) + + GIacieco/a punicea ACAM 611T(U85853) + + Salinimonas chungwhensis BHO30046T (AY553295) + + Alteromonas addita R1 OSW1 3T (AY682202) + + 100 Alteromonas mac/eodii IAM 12920T (X82145) + + 89 I—Bowmane/Ia denitrificans BD1T (DQ343294) + +

+ +

+ 100 LBowmaneIIa pacifica W3-3AT (EU440951) + +

+ +

+ Agarivorans albus MKT106T (A8076561) + +

+
+
+

+ + + + + + + + + + +

+
+
+

+ 55 + +

+
+
+

+ 71 + +

+
+
+

+ 100 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 55 Colwellia psychroerythraea ACAM 55OTT(AF001375) + + 100 Thalassomonas viridans CECT 5083T (AJ294748) + + Oceanimonas doudoroffii ATCC 27123T (ABO19390) + + 5EFerrimonas balearica DSM 9799T (X93021) + + 93 + +

+
+
+

+ Shewane/la putrefaciens ATCC 8071T (X82133) + + Escherichia coli ATCC 1 1775T (X80725) + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001909-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001909-0-000.pbm.png new file mode 100644 index 00000000..495607a1 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001909-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001909-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001909-0-000.pbm.png.hocr new file mode 100644 index 00000000..6c953d0a --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001909-0-000.pbm.png.hocr @@ -0,0 +1,178 @@ + + + + + + + + + + + +
+
+

+ 64.8 + +

+
+
+

+ o I + + o\ + +

+
+
+

+ 72. + +

+
+
+

+ 84.6 + +

+
+
+

+ 85.8 + + 51.8 + +

+
+
+

+ 95.6 99.9 + +

+
+
+

+ 74.9 + +

+
+
+

+ 71.7 + +

+
+
+

+ 100.0 + +

+
+
+

+ 99.6 + +

+
+
+

+ 100.0 + +

+
+
+

+ 100.0 Porphyromonas gu/ae ATCC 51 700T (AF208290) + +

+
+
+

+ Porphyromonas gingiva/is ATCC 33277T (L1 6492) + + Porphyromonas crevioricanis ATCC 55563T (D0677836) + + Porphyromonas cansu/ciVPB 4875T (X76260) + + Porphyromonas catoniae ATCC 51 270T (X82823) + + Porphyromonas macacae ATCC 331 41 T (L16494) + + Porphyromonas somerae ATCC BAA-1 230T (AY968205) + + Porphyromonas leI/I'i ATCC 29147T (L16493) + + Porphyromonas bennonis WAL 19266T (EU414673) + + Porphyromonas cangingiva/fs VPB 4874T (X76259) + + Porphyromonas canoris VPB 4882 (X76261) + + 100.0 ‘Porphyromonas can/3’ JCM 10100 (ABOS4799) + + 100'0 Porphyromonas gingivicanis ATCC 55562T (D0677835) + + Porphyromonas circumdentaria NCTC 1 2469T (L26102) + + Porphyromonas endodonta/r's ATCC 35406T (AY253728) + + 100.0 Porphyromonas uenonis ATCC BAA—906T (AY57051 4) + + Porphyromonas asaccharo/ytica ATCC 25260T (L16490) + + Tannere/la forsythia ATCC 43037T (A8035460) + + Tannerella forsythia RMA 8464 (D034491 7) + + Parabacteroides distasonis JCM 5825T (EU136681) + + Bacteroides fragi/is DSM 2151T (AB050106) + + Bacteroides theta/otaomicron ATCC 291 48T (L1 6489) + + 100.0 Bacteroides pyogenes JCM 6294T (EU136683) + + Bacteroides tectus JCM 10003T (EU136689) + + Prevote/la me/aninogenica ATCC 25845T (AY323525) + + Alist/pes finegoldiiANH 2437T (AJ518874) + + Alistipes putredinis ATCC 29800T (L1 649 7) + +

+
+
+

+ 100.0 + +

+
+
+

+ 100.0 + +

+
+
+

+ 100.0 + +

+
+
+

+ 100.0 + +

+
+
+

+ 100.0 + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001925-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001925-0-000.pbm.png new file mode 100644 index 00000000..d217b64d Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001925-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001925-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001925-0-000.pbm.png.hocr new file mode 100644 index 00000000..ba0bd32e --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001925-0-000.pbm.png.hocr @@ -0,0 +1,98 @@ + + + + + + + + + + + +
+
+

+ 100 Leifsonia aquatica DSM 2014GT (X77450) + +

+ +

+ Leifsonia naganoensis DB103T (AB028941) + +

+ +

+ Le/fsonia shinshuensis DB102T (A3028940) + +

+ +

+ Leifsonia xyli subsp‘ cynodontis JCM 9733T (ABO16985) + + Leifsonia poae VKM Ac-1401T (AF116342) + +

+ +

+ Okibacterium frit/"I/ariae DSM 15271T (AM410675) + + Leifsonia ginsengi wged1 1T (DQ473536) + +

+ +

+ Leifsonia kribbensis MSL-13T (EF466129) + + Leifsonia bigeumensis MSL—27T (EF466124) + + Sal/n/bacterium amurskyense KMM 3673T (AF539697) + + Leifsonia aurea CMS 81yT (AJ438586) + + Rhodoglobus vestalii LV3T (AJ459101) + +

+ +

+ 100 Leifsonia rubra CMS 76rT (AJ438585) + +

+
+
+

+ + + + + + + + + + + + + + + + + + +

+
+
+

+ 80 + +

+
+
+

+ 0,005 + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001958-0-001.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001958-0-001.pbm.png new file mode 100644 index 00000000..54b17990 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001958-0-001.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001958-0-001.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001958-0-001.pbm.png.hocr new file mode 100644 index 00000000..244db661 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001958-0-001.pbm.png.hocr @@ -0,0 +1,344 @@ + + + + + + + + + + + +
+
+

+ 0,02 + +

+
+
+

+ + +

+
+
+

+ as + +

+
+
+

+ Clostridium sulfatireducens 38-1 (AY943861) + +

+
+
+

+ + + + + + + + + + + + + + + + +

+
+
+

+ Clostridium amygdaI/‘num DSM12857T (AY353957) + + Clostridium boliviensis E-1 (AY943862) + +

+
+
+

+ se + +

+
+
+

+ Clostridium indolis DSM 755T (Y18184) + +

+ +

+ Clostridium methoxybenzovorans DSM 12182T (AF067965) + + Clostridium saccharolyticum DSM 2544T (Y18185) + +

+ +

+ Clostridium sphenoides ATCC 19403T (ABO75772) + +

+ +

+ m Clostridium celerecrescens DSM 5628T(X71848) + +

+ +

+ 9E Clostridium algidixylanolyticum DSM 12273T(AF092549) + +

+
+
+

+ Clostridium xylanolyticum DSM 6555T(X76739) + +

+
+
+

+ + +

+
+
+

+ mu + +

+
+
+

+ Clostridium aerato/erans DSM 5434T (X76163) + + Closm'dium hathewayi DSM 13479T (AJ311620) + + Clostridium aldenense CCUG 52204T (DQ279736) + + w Clostridium bolteae WAL16351T (AJ508452) + +

+ +

+ { Clostridium closm'dioforme ATCC 25537T (M59089) + + Clostridium Citroniae CCUG 52203T (DQZ79737) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ Clostridium asparagiforme DSM 15981T (AJ582080) + +

+
+
+

+ + +

+
+
+

+ 1_E,OICIostridium IavalenseCCRl-9842T(EF564277) + + Clcstridium IavalenseCCRl -9929 (EF564278) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 54 + +

+
+
+

+ Clostridium symbiosum ATCC 14940T(M59112) + + Clostridium aminophilum FT (L04165) + +

+
+
+

+ Clostridium pmteoc/asticum ATCC 51982T (U37378) + + Clostridium coccoides DSM 2088T (M59090) + + Clostridium glycyrrhizini/yticum ZM35T (AB233029) + +

+
+
+

+ + + + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + + + + + +

+
+
+

+ Clostridium orotioum ATCC 13619T (M59109) + +

+ +

+ Clostridium nexile DSM 1787T (X73443) + +

+ +

+ Clostridium hy/emonae DSM 15053T(A8023972) + +

+ +

+ Clostridium fusiformis CM973 (AF028349) + +

+ +

+ Clostridium scindens DSM 5676T (Y18186) + + m Clostridium jejuense DSM 15929T (AY494606) + +

+ +

+ —|:Clostridium xylanovorans DSM 12503T(AF116920) + +

+
+
+

+ 57 Clostridium aminova/erfcum DSM 1283T (X73436) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ ma + +

+
+
+

+ Clostridium phytofermenlans ATCC 700394T (AF020431) + + Clostridium populeti ATCC 35295T (X71853) + +

+
+
+

+ + +

+
+
+

+ 93 Clostridium polysaccharolyticum DSM 1801T (X77839) + + Clostridium herbivorans DSM 14428T (L34418) + + Clostridium fimetarium DSM 9179T (AF126687) + + Propionigenium modestum Gra Succ 2T (X54275) + +

+
+
+

+ Fusobacterium nucleatum ATCC 25586T (AJ133496) + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001966-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001966-0-000.pbm.png new file mode 100644 index 00000000..9f0be5b4 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001966-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001966-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001966-0-000.pbm.png.hocr new file mode 100644 index 00000000..b971b2b6 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001966-0-000.pbm.png.hocr @@ -0,0 +1,120 @@ + + + + + + + + + + + +
+
+

+ Granulicatella adiacens GIFU 12706T (D50540) + + Ablotrophla defectiva GIFU 12707T (D50541) + + Facklamla homlnls ATCC 700628T (Y10772) + + Aerococcus viridans ATCC 1 1563T (M58797) + + Aerococcus urinae NCFB 2893T(M77819) + + Staphylococcus lntermedlus ATCC QQGBST (D83369) + + Staphylococcus sch/elferl CD22-1 (D83372) + + Staphylococcus hyicus ATCC 1 1249T (D83368) + + Staphylococcus gallinarum ATCC 35539T (D83366) + + Staphylococcus fells FD21-2 (D83365) + + _|: Gemella haemolysans ATCC 10379T (L14326) + + Gems/la sangulnls 2045—94T (Y13364) + + Gems/la morblllorum ATCC 27824T (L14327) + + Gemella cuniculiM60449l99l1T(AJ251987) + + Gemella bergerl617-93T (Y13365) + + Gemella asaccharolytica WAL 1945JT (EU427463) + + Gems/la palaticanis M663-98—1 T (Y17280) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001990-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001990-0-000.pbm.png new file mode 100644 index 00000000..89d57640 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001990-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001990-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001990-0-000.pbm.png.hocr new file mode 100644 index 00000000..9d32ec7c --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.001990-0-000.pbm.png.hocr @@ -0,0 +1,415 @@ + + + + + + + + + + + +
+
+

+ Enterovibrio coralii 9I2b (AM942729) (a) 163 rRNA + + Enterovibrio coralii 9I5b (AM942730) + + Enterovibrio coralii 11/2a (AM942732) + + Enterovibrio coralii 10/6 (AM942731) + + Enterovibrio coralii 9/2a (AM942728) + + Enterovibrio coralii 9/1c (AM942727) + + Enterovibrio coralii 9I1a (AM942726) + + Enterovibrio coralii 8/13 (AM942725) + + Enterovibrio coralii LMG 22228T (AJ842343) + +

+ +

+ 77 Enterovibrio nigricans DAI 1-1-5T (AM942722) + + 100 Enterovibrio nigricans DAI 1-1-4 (AM942723) + + Enterovibrio nigricans 8/6b (AM942724) + +

+ +

+ 65 Enterovibrio norvegicus LMG 19839T (AJ316208) + + 100 Enterovibrio norvegicus LMG19840 (AJ316207) + + Enterovibrio norvegicus LMG 19842 (AJ437193) + + Enterovibrio calviensis RE35F/12T(AF118021) + +

+ +

+ Grimontia hollisae LMG 17719T (AJ514909) + +

+
+
+

+ + + + + + + + + + + + + + + + + + + + +

+
+
+

+ 1% + +

+
+
+

+ 100 + +

+
+
+

+ Enterovibrio coralii 10l6 (AM942058) (c) rpoD + + Enterovibrio coralii 9I5b (AM942057) + + Enterovibrio coralii 9I1c (AM942054) + +

+
+
+

+ + + + + + + + + + + + + + + + +

+
+
+

+ + +

+
+
+

+ 5% + +

+
+
+

+ 99 + +

+
+
+

+ Enterovibrio coralii 9I2a (AM942055) + +

+ +

+ Enterovibrio coralii 9I2b (AM942056) + +

+ +

+ Enterovibrio coralii 9I1a (AM942053) + +

+ +

+ 100 Enterovibrio coralii 8/13 (AM942052) + +

+ +

+ Enterovibrio coralii 11/23 (AM942059) + +

+ +

+ Enterovibrio coralii CAIM 912T (AM942051) + + Enterovibrio nigricans 8/6b (AM942050) + +

+ +

+ Enterovibrio nigricans DAI 1-1-4 (AM942049) + +

+ +

+ 99 Enterovibrio nigricans DAI 1-1-5T (AM942048) + + Enterovibrio norvegicus CECT 7288T (AM942062) + + Enterovibrio calviensis DSM 14347T (AM942047) + + Grimontia hollisae CECT 5069T (AM942061) + +

+ +

+ Vibrio cholerae CECT 514T (AM942060) + +

+
+
+

+ 76 + +

+
+
+

+ + +

+
+
+

+ Vibrio cholerae CECT 514T (X76337) + +

+
+
+

+ Enterovibrio coralii CAIM 912T (AM942063) (b) recA + + Enterovibrio coralii 8/13 (AM942064) + +

+ +

+ Enterovibrio coralii 9/1a (AM942065) + +

+ +

+ Enterovibrio coralii 9/2a (AM942066) + +

+ +

+ Enterovibrio coralii 9/2b (AM942068) + +

+ +

+ 100 Enterovibrio coralii 9I1c (AM942067) + +

+ +

+ Enterovibrio coralii 9l5b (AM942069) + +

+ +

+ Enterovibrio coralii 10l6 (AM942070) + +

+ +

+ Enterovibrio coralii 11l2a (AM942071) + +

+ +

+ 63 Enterovibrio norvegicus CECT 7288T (AM942075) + + 100 Enterovibrio norvegicus R-3717 (AJ842350) + + Enterovibrio norvegicus LMG 19840 (AJ842349) + + Enterovibrio calviensis DSM 14347T (AM942077) + + Enterovibrio nigricans 8/6b (AM942074) + + Enterovibrio nigricans DAI 1-1-4 (AM942073) + +

+ +

+ 100 Enterovibrio nigricans DAI 1-1-5T (AM942072) + + Grimontia hollisae CECT 5069T (AM942076) + +

+
+
+

+ + + + + + + + + + + + + + + + + + + + + + + + + + +

+
+
+

+ 5% + +

+
+
+

+ Enterovibrio coralii 8/13 + +

+
+
+

+ + + + + + + + + + + + + + + + + + + + + + +

+
+
+

+ 5 % Enterovibrio coralii 9I2a + + Enterovibrio coralii 9I2b + + 100 Enterovibrio coralii 10l6 + + Enterovibrio coralii 9/1a + + 100 Enterovibrio coralii 9/1c + + 100 Enterovibrio coralii 9/5b + + Enterovibrio coralii 11l2a + +

+ +

+ Enterovibrio coralii CAIM 912T + +

+ +

+ 100 Enterovibrio nigricans DAI 1-1-5T + + Enterovibrio nigricans DAI 1-1-4 + + Enterovibrio nigricans 8/6b + +

+ +

+ Enterovibrio norvegicus CECT 7288T + + Enterovibrio calviensis DSM 14347T + +

+
+
+

+ Grimontia hollisae CECT 5069T + +

+
+
+

+ Vibrio cholerae CECT 514T (AM942078) + +

+
+
+

+ (d) Concatenated dataset + +

+
+
+

+ Vibrio cholerae CECT 514T + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002048-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002048-0-000.pbm.png new file mode 100644 index 00000000..d97215f8 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002048-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002048-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002048-0-000.pbm.png.hocr new file mode 100644 index 00000000..36720599 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002048-0-000.pbm.png.hocr @@ -0,0 +1,153 @@ + + + + + + + + + + + +
+
+

+ Sporolactobacillus kofuensis JCM 3419T (ABS74517) + + Sporo/actobacil/us laevo/acticus IAM 12321T (AB374516) + +

+ +

+ 100[ Sporo/actobacil/us nakayamae subsp. nakayamae JCM 3514T (AB374518) + + 76 _ Sporolactobacillus nakayamae su bsp. racemicus JCM 3417T (AB374519) + + Sporolactobaci/Ius terrae JCM 3516T (ABs74520) + + Sporolactobacillus putidus QC81-06T (AB374522) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 88 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 98 * Sporolactobacillus vineae SL1153 (EF581818) + + 100 Sporo/actobaciI/us vineae SL153T (EF581819) + + Sporolactobaci/Ius inulinus IFO 13595T (AB374521) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ Bacillus subtilis IAM 12118T (ABO42061) + +

+
+
+

+ 0.01 + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002048-0-001.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002048-0-001.pbm.png new file mode 100644 index 00000000..6f79c5f3 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002048-0-001.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002048-0-001.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002048-0-001.pbm.png.hocr new file mode 100644 index 00000000..8524aa17 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002048-0-001.pbm.png.hocr @@ -0,0 +1,102 @@ + + + + + + + + + + + +
+
+

+ 85 Sporolactobacillus kofuensis JCM 3419T (A8374524) + + Sporalactobacillus laevolacticus IAM 12321T (A8374523) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 100 Sporolactobaoillus nakayamae subsp. nakayamae JCM 3514T (A8374525) + + 100 Sporalactobacillus nakayamae subsp. racemicus JCM 3417T (ABS74526) + + 98 Sporolactobacillus terrae JCM 3516T (ABB74527) + + Sporolactobacillus inulinus IFO 13595T (ABS74528) + + Sporolactobacillus putidus QC81-06T (AB374529) + + Bacillus subtilis IAM 12118T (299104) + + 1—1 + +

+
+
+

+ 0.05 + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002113-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002113-0-000.pbm.png new file mode 100644 index 00000000..4b88d31b Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002113-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002113-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002113-0-000.pbm.png.hocr new file mode 100644 index 00000000..9ba2c352 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002113-0-000.pbm.png.hocr @@ -0,0 +1,163 @@ + + + + + + + + + + + +
+
+

+ Marinomonas primoryensis KMM 3633T (AB074193) + + Marinomonas polaris CK13T (AJ833000) + + Marinomonas pontica 46-16T (AY539835) + +

+ +

+ Marinomonas dokdonensis DSW10-10T (DQO11526) + + Marinomonas ushuaiensis U1T (AJ627909) + +

+
+
+

+ + + + + + +

+
+
+

+ 0.01 + +

+
+
+

+ 100 + +

+
+
+

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

+
+
+

+ 100 + + 100 Marinomonas mediterranea MMB-1T (AF063027) + + 33 Marinomonas communis LMG 2864T (DQO11528) + + Marinomonas vaga ATCC 27119T (X67025) + + 94 Marinomonas aquimarina 1 1SM4T (AJ843077) + +

+
+
+

+ + +

+
+
+

+ Marinomonas ostreistagni UST010306—043T (ABZ42868) + + Oceanobacter kriegii IFO 15467T (AB006767) + + Thalassolituus o/eivorans M | L-1 T (AJ431699) + +

+ +

+ Bermanella marisrubri RED65T (AY136131) + +

+ +

+ O/eispira antarctica RB-8T (AJ426420) + + Oceanospiri/Ium linum ATCC 1 1336T (M22365) + +

+ +

+ Oceanospir/Ilum maris ATCC 27509T (ABOO6771) + + Oceanospiri/lum beljerinckii IFO 15445T (ABOOG760) + + Oceanospiri/Ium multiglobuliferum IFO 13614T (ABOOB764) + + Neptunomonas naphthovorans NAG-2N-126T (AF053734) + + Neptuniibacter caesariensis MEDE)2T (AY1361 16) + +

+ +

+ Reinekea blandensis MED297T (DQ403810) + +

+ +

+ Reinekea marinisedimentorum DSM 15388T (AJ561121) + + Saccharospiri/Ium impatiens EL—105T (AJ315983) + +

+ +

+ KangleI/a koreensis SW-125T (AY520560) + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002220-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002220-0-000.pbm.png new file mode 100644 index 00000000..2de6edd5 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002220-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002220-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002220-0-000.pbm.png.hocr new file mode 100644 index 00000000..26663842 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002220-0-000.pbm.png.hocr @@ -0,0 +1,220 @@ + + + + + + + + + + + +
+
+

+ 56 + +

+
+
+

+ 002 + +

+
+
+

+ 99 + +

+
+
+

+ 84 + +

+
+
+

+ 100 + +

+
+
+

+ 100 + +

+
+
+

+ 100 + +

+
+
+

+ 74 + +

+
+
+

+ 100 + +

+
+
+

+ 100 + +

+
+
+

+ 96 + +

+
+
+

+ 100 + +

+
+
+

+ 100 + +

+
+
+

+ 50 + +

+
+
+

+ 100 + +

+
+
+

+ 100 + +

+
+
+

+ Haliea salexigens DSM 19537T (AY576769) + +

+
+
+

+ Strain CM41_15aT DSM19751T(EU161717) + +

+
+
+

+ Melitea salexigens DSM 19753T (AY576729) + +

+
+
+

+ Microbulbifer salipa/udis SM—‘l T (AF479688) + +

+
+
+

+ Microbulbifer hydrolyticus DSM 1 1525T (AJ608704) + +

+
+
+

+ Microbulb/fer elongatus DSM 6810T (AF500006) + +

+
+
+

+ Microbulbifer maritimus TF—1 7T (AY377986) + +

+
+
+

+ Cellvibrio japonicus NCIMB 10462T (AF452103) + +

+
+
+

+ CeI/vibrio mixtus ACM 2603 (AJ289160) + +

+
+
+

+ Pseudomonas pseudoalcaligenes LMG 1225T (276666) + +

+
+
+

+ Pseudomonas stutzeri DSM 7136 (AF063219) + +

+
+
+

+ Pseudomonas balearica LS401 (U26417) + +

+
+
+

+ Pseudomonas rhodesiae DSM 14020T (AF064459) + +

+
+
+

+ Pseudomonas grimontii CFML 97—514T (AF268029) + +

+
+
+

+ Acinetobacter bouvetii DSM 14964T (AF509827) + +

+
+
+

+ Moraxella equi ATCC 25576T (AF005184) + +

+
+
+

+ Psychrobacter aquaticus CMS 56T (AJ584833) + +

+
+
+

+ Alcanivorax venustensis DSM 13974T (AF328766) + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002287-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002287-0-000.pbm.png new file mode 100644 index 00000000..ff445d95 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002287-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002287-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002287-0-000.pbm.png.hocr new file mode 100644 index 00000000..484aa414 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002287-0-000.pbm.png.hocr @@ -0,0 +1,287 @@ + + + + + + + + + + + +
+
+

+ 100 94 T. pedis T183 (EF061270) + + 7'. pedis T354A (EF061267) + + 71 T. dent/cola ATCC 35405T (NC 002967) + + 97— T. putidum ATCC 700334T (AJ543428) + + ‘T. phagedenis‘ strain K5 (M57739) + + 87 ‘T. refringens‘ CIP 51.64 (AF426101) + + 100— ‘T. calligyrum’ CIP 64.40 (AF426100) + + 100 ‘T. vincentil" ATCC 700013 (AF033310) + + 100— T. medium ATCC 700293T (D85437) + + T. pallidum Nichols strain (NC_000919) + + T. brennaborense DSM 12168T (Y16568) + + 87 T. Iecithinolyticum ATCC 700332T (AJ131282) + + 100— T. maltophilum ATCC 51939T (X87140) + +

+ +

+ 99— T. berlinense ATCC BAA-909T (AY230217) + + 40 T. pectinovorum ATCC 33768T (AF302940) + + T. saccharophilum ATCC 43261T (M71238) + + ,9 T. bryantii ATCC 33254T (M57737) + + 51— T. porcinum ATCC BAA-908T (AY518274) + + 51 T. succinifaciens ATCC 33096T (M57738) + +

+ +

+ 59 T. amylovorum ATCC 700288T (Y09959) + + 65_— T. parvum ATCC 700770T (AF302938) + +

+ +

+ T. socranskii subsp. socranskii ATCC 35536T + + (AF033306) + +

+
+
+

+ 0 02 T. pedis T35523T (EF061268) + + ' A“ T. pedis GS19CB (EF061269) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002287-0-001.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002287-0-001.pbm.png new file mode 100644 index 00000000..8c0d638e Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002287-0-001.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002287-0-001.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002287-0-001.pbm.png.hocr new file mode 100644 index 00000000..8cd06ae9 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002287-0-001.pbm.png.hocr @@ -0,0 +1,218 @@ + + + + + + + + + + + +
+
+

+ 0.05 + +

+
+
+

+ 44 + +

+
+
+

+ 43 + +

+
+
+

+ 80 + +

+
+
+

+ 98 T. pedis T183 (EU754824) + +

+
+
+

+ sir. pedis GB19CB (EU754823) + + 10° T. pedis T35523T (EF061284) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ T. pedis T354A (EF061283) + + T. denticola ATCC 33521 (AJ277354) + + T. denticola ATCC 35405T (AJ277353) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 84 + +

+
+
+

+ ‘T. phagedenis’ Kazan 5 (M94015) + + T. medium ATCC 700293T (EF061285) + +

+
+
+

+ + +

+
+
+

+ 100 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 100 4| ‘7'. Vincentii’ATCC 35580 (EF061286) + + 99 ‘T. Vincentii’ D2A2 (EF061287) + + T. maltophilum ATCC 51939T (Y18889) + + T. lecithinolyticum ATCC 700332T(AJ277358) + + T. pallidum subsp. pallidum (AE000520) + +

+
+
+

+ + +

+
+
+

+ Serpulina hyodysenteriae CS (X63513) + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002295-0-001.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002295-0-001.pbm.png new file mode 100644 index 00000000..fd861437 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002295-0-001.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002295-0-001.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002295-0-001.pbm.png.hocr new file mode 100644 index 00000000..4d04c0b6 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002295-0-001.pbm.png.hocr @@ -0,0 +1,79 @@ + + + + + + + + + + + +
+
+

+ 0,02 + +

+
+
+

+ D—I + +

+
+
+

+ 73 C. esten‘heticum subsp. Iaramiense DSM 14884T (AJ506115) + +

+ +

+ 65 C1 estertheticum subsp‘ estherfheticum NCIMB 12511T (X68181) + + C. frigoris DSM 14204T (AJ506116) + +

+ +

+ C. lacusflyxe/lense DSM 14205T (AJ506118) + +

+ +

+ —‘C. algoriphilum’ 14D1 (AY117755) + +

+
+
+

+ + + + + + + + +

+
+
+

+ + +

+
+
+

+ _‘——C. bowmanii DSM 14206T (AJ506120) + + 55 Strain A121 T (D0296031) + + C. psychrophi/um A-1/C-an/lT (AJ297443) + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002352-0-001.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002352-0-001.pbm.png new file mode 100644 index 00000000..e4068b70 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002352-0-001.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002352-0-001.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002352-0-001.pbm.png.hocr new file mode 100644 index 00000000..08b24bb8 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002352-0-001.pbm.png.hocr @@ -0,0 +1,91 @@ + + + + + + + + + + + +
+
+

+ Paenibacillus polymyxa DSM 3ST (AJ320493) + + Paenibacillus elgii NBRC 100335T (AY090110) + +

+ +

+ Paenibacillus koreensis KCTC 2393T (AF130254) + + PaenibaciI/us ehimensis KCTC 3748T (AY116665) + +

+
+
+

+ Paenibaci/Ius soli KCTC 13010T (DQ309072) + + Paenibaci/lus chinjuensis DSM 15045T (AF164345) + +

+
+
+

+ + + + + + + + + + + + + + +

+
+
+

+ 000 + +

+
+
+

+ Paenibacillus validus DSM 3037T (078320) + +

+
+
+

+ Paenibacillus naphthalenovorans DSM 14203T (AF353681) + + Paenibacillus ginsengihumi KCTC 13141T (EF452662) + + Paenibacillus pueri b09i-3T (EU391 156) + +

+
+
+

+ 0-01 1000 2' Paenibacillus pueri b13i-1 (EU391155) + +

+
+
+

+ + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002378-0-001.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002378-0-001.pbm.png new file mode 100644 index 00000000..ae5109fa Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002378-0-001.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002378-0-001.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002378-0-001.pbm.png.hocr new file mode 100644 index 00000000..919fb9de --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002378-0-001.pbm.png.hocr @@ -0,0 +1,226 @@ + + + + + + + + + + + +
+
+

+ + +

+
+
+

+ 100 + +

+
+
+

+ + +

+
+
+

+ —|: + +

+
+
+

+ 83 + + 68 + +

+
+
+

+ 100 + +

+
+
+

+ 100 + +

+
+
+

+ Gemmata obscurig/obus DSM 5831T, AJ231191 + + Gemmata-Iike strain Schlesner 633, X81957 + + Gemmata-Iike strain JW11-2f5, AF239696 + + Gemmata—Iike strain JW3-8sO, AF239694 + + Gemmata—Iike strain Soil9, AF239698 + + Gemmata-Iike strain JW9—3f1,AF239697 + + Gemmata—Iike strain Cjuql4, AF239693 + + Gemmata—Iike isolate JW10—3f1 , AF239695 + + Strain A1 OT, AM162406 + + Isosphaera pal/ida DSM 96130, AJ231195 + + ‘Nostocoida Iimico/a |||’ Ben220, AF244748 + + ‘Nostocoida Iimico/a |||’ Ben223, AF244750 + + Singulisphaera acidiphila DSM 186581 AM850678 + + Blastopirellula marina DSM 36451 X62912 + + Pirel/u/a staleyi DSM 60681 X81946 + + Sch/esneria paludicola ATCC BAA-13931AM162407 + +

+
+
+

+ + + + + + + + + + + + +

+
+
+

+ + +

+
+
+

+ 100 + +

+
+
+

+ 98 + + 1 00 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ Planctomyces Iimnophilus DSM 3776T, X62911 + +

+
+
+

+ + +

+
+
+

+ —88[: Planctomyces bras/Iiensis DSM 53053 AJ231190 + + Planctomyces maris DSM 879W, AJ231184 + + iflandidatus Brocadia anammoxidans’, AF375994 + +

+
+
+

+ 83 'Candidatus Brocadia fulgida’, DQ459989 + + ‘Candidatus Anammoxoglobus propionicus‘, DQ317601 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 0.10 + +

+
+
+

+ 60 + + ‘Candidatus Kuenenia stuttganiensis’, AF375995 + +

+
+
+

+ + +

+
+
+

+ 100 ‘Candidatus Scalindua brodae’, AY254883 + + 99 E ‘Candidatus Scalindua sorokinii’, AY257181 + +

+
+
+

+ ‘Candidatus Scalindua wagneri’, AY254882 + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002394-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002394-0-000.pbm.png new file mode 100644 index 00000000..09fec912 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002394-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002394-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002394-0-000.pbm.png.hocr new file mode 100644 index 00000000..74df47e3 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002394-0-000.pbm.png.hocr @@ -0,0 +1,287 @@ + + + + + + + + + + + +
+
+

+ + +

+
+
+

+ 0.02 + +

+
+
+

+ 100 + +

+
+
+

+ + + + + + + + + + +

+
+
+

+ + +

+
+
+

+ Pseudoxanthomonas broegbernensis B1616/1T (AJ012231) + + Stenotrophomonas maltophilia ATCC 13637T (ABOO8509) + + Xanthomonas campestris LMG 568T (X95917) + +

+ +

+ Xylella fastidiosa PCE-FFT (AF192343) + +

+ +

+ Thermomonas haemolytica A50-7-3T (AJ300185) + +

+ +

+ Luteimonas composti CC—YY255T (DQB46687) + +

+
+
+

+ + + + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 85 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ —o + + 91 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 68 + +

+
+
+

+ + +

+
+
+

+ i + +

+
+
+

+ Luteimonas mephitis B1953/27.1T (AJ012228) + +

+ +

+ L ysobacter brunescens KCTC 12130T (AB161360) + +

+ +

+ Lysobacter panaciterrae Gsoil 068T (ABZ45359) + + Lysobacter niabensis GH34—4T (DQ462461) + +

+
+
+

+ —95+: + + L ysobacter yangpyeongensis GH19-3T (DQ191 179) + +

+
+
+

+ Lysobacter enzymogenes DSM 2043T (AJ298291) + + Lysobacter niastensis GH41-7T (DQ462462) + + Lysobacter koreensis Dae16T (AB166878) + + Lysobacter capsici YCS194T (EF488749) + +

+
+
+

+ oo Lysobacter gummosus KCTC 12132T (AB161361) + + 55 Lysobacter ant/bioticus DSM 2044T (ABO19582) + +

+
+
+

+ 69 + +

+
+
+

+ 100 + + 76 + +

+
+
+

+ Lysobacter daejeonensis GH1—9T (DQ191 178) + +

+
+
+

+ Lysobacter concretionis K007T (AB161359) + + fir;— Lysobacter defluvii IMM | B APB-9T (AM283465) + +

+
+
+

+ Lysobacter spongiico/a KMM 329T (A8299978) + + Aqu/monas voraii GPTSA 20T (AY544768) + + Dokdone/Ia koreensis DS-123T (AY987368) + + Frateuria aurantia NBRC 3245T (ABOQ1194) + + Fulvimonas soli LMG 19981T (AJ311653) + + Rhodanobacter Iindanic/asticus RP5557T (AF039167) + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002444-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002444-0-000.pbm.png new file mode 100644 index 00000000..e0f9adaa Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002444-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002444-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002444-0-000.pbm.png.hocr new file mode 100644 index 00000000..93943cd8 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002444-0-000.pbm.png.hocr @@ -0,0 +1,146 @@ + + + + + + + + + + + +
+
+

+ 98 + +

+
+
+

+ 76 + +

+
+
+

+ 0.02 + +

+
+
+

+ 73 + +

+
+
+

+ 86 + +

+
+
+

+ 100 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ Hymenobacter riguiWPCB131T (DQ089669) + +

+
+
+

+ + + + + + + + + + +

+
+
+

+ Hymenobacter Xinjiangensis X2-1gT(D0888329) + + Hymenobacter gelipurpurascens Txg1T(Y18836) + + Hymenobacter actinosc/erus CCUG 39621 T (Y1 7356) + + Hymenobacter aerophi/us |/26-Cor1 T (AJ276901) + + Hymenobacter roseosalivan‘us AA—718T(Y18833) + + Hymenobacter norwichensis NS/SOT (AJ 549285) + + Hymenobacter chitin/vorans Txc1 T (Y18837) + + Hymenobacter daecheongensis Dae14T (EU370958) + + Hymenobacter soli PB17T (AB251884) + +

+
+
+

+ K—Hymenobacter ocel/atus Txo1 T (Y18838) + +

+
+
+

+ 100 + +

+
+
+

+ Adhaeribacter aquaticus MBRG1.5T(AJ626894) + + Persicobacter diff/uens NCIMB 1402T (D12660) + + Reichenbachie/Ia agariperforans KMM 3525T (AB058919) + + Dyadobacter fermentans NS114T(AF137029) + + Rune/la slithyformis ATCC 2593GT (M62786) + + Flectobacil/us major ATCC 29496T (M62787) + + Flexibacter flex/[is ATCC 23079T (M62794) + + Cytophaga hutchinsonii DSM 1761 T (D12663) + + Sporocytophaga myxococcoides DSM 11118T (AJ310654) + + Pedobacter heparinus DSM 2366T (AJ438172) + + Sphingobacterium spiritivorum DSM 2582 (AJ459411) + + Flavobacterium aquatile ATCC 11947T (M62797) + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002451-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002451-0-000.pbm.png new file mode 100644 index 00000000..a90342eb Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002451-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002451-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002451-0-000.pbm.png.hocr new file mode 100644 index 00000000..d009b9df --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002451-0-000.pbm.png.hocr @@ -0,0 +1,160 @@ + + + + + + + + + + + +
+
+

+ 98* Salinicoccus iranensis QW6T (DQ767692) + + Saliniooccus luteus YIM 70202T (D0352839) + + Salinicoccus roseus DSM 5351T (X94559) + + Sal/nicoccus hispanicus DSM 5352T (AY028927) + + Salinicoccus siamensis PN1-2T (AB258358) + + Salinicoccus salsiraiae RH 1 T (00333949) + +

+ +

+ 100' Salinicoccus jeotgali 82R53-5T (DQ471329) + + Salinicoccus alkaliphilus T8T (AF275710) + +

+
+
+

+ Salinicoccus kunmingensis YIM Y15T (DQ837380) + + ‘Sa/inicoccus salitudinis‘ YIM-C678T(EF590121) + +

+
+
+

+ Salinicoccus halodurans W24T (D0989633) + + Salinicoccus albus YIM—Y21T(EF177692) + + Nosocomiicoccus ampullae TRF-1 T (EU240886) + + Jeotgalicoccus pinnipedialis CCUG 42722T (AJ251530) + + Jeotgalicoccus marinus JSM 076033T(EU583727) + + Jeotgalicoccus halotolerans YKJ-101T (AY028925) + + Jeotgalicoccus psychrophilus YKJ-1 15T (AY028926) + + Macrococcus bovicus L2T4T (Y15714) + +

+ +

+ Macrococcus carouselicus H8b16T(Y15713) + + Staphylococcus nepalensis CW1 T (AJ517414) + + Staphylococcus piscifermentans SK03T (Y15754) + + Carnobacterium pleistocenium FTR1T (AF450136) + + Enterococcus faecium ATCC 19434T (DQ411813) + +

+
+
+

+ Enterococcus mundti/ ATCC 4318GT (AF061013) + + Marinococcus halophi/us DSM 20408T (X90835) + +

+
+
+

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

+
+
+

+ 0,02 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 53* + + 67* + +

+
+
+

+ + +

+
+
+

+ 95p + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002469-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002469-0-000.pbm.png new file mode 100644 index 00000000..8c6fc5d6 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002469-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002469-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002469-0-000.pbm.png.hocr new file mode 100644 index 00000000..aced66d7 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002469-0-000.pbm.png.hocr @@ -0,0 +1,246 @@ + + + + + + + + + + + +
+
+

+ 98* + +

+
+
+

+ + + + + + + + + + + + + + + + + + + + +

+
+
+

+ Grad/[bacillus ha/oto/erans NNT (AF036922) + + Paraliobacillus ryukyuensis 015-7T (AB087828) + + Halobacillus Iocisa/is MSS-155T (AY190534) + + Ha/obaci/Ius Iitora/is SL-4T (X94558) + + ThalassobaciI/us devorans G—19.1T (AJ717299) + + Lent/bacillus salicampi SF-20T (AY057394) + + Virgibacillus dokdonensis DSW-1OT(AY822043) + + Virgibacillus pantathenticus NCDO 1765T (D78477) + + Virgibaci/Ius marismortui 123T (AJ009793) + + VirgibaciI/us halodenitriflcans ATCC 49067T(AB021186) + + Oceanobacil/us iheyensis HTE831T (ABO10863) + + Paucisa/ibacillus globu/us BZZT(AM114102) + + 70p Ornithinibacillus californiensis MB-9T (AF326365) + + £1: Salinibacillus kushneri 8-2T (AY321434) + + Salinibaci/lus aidingensis 25-7T (AY321436) + +

+ +

+ Sal/rhabdus euzebyi CVS14T (AM292417) + + Pontibacillus halophilus JSM 0763056T (EU583728) + + Pontibacil/us marinus BH030004T (AY603977) + +

+ +

+ 99’ Pontibacillus chungwhensis BH030062T (AY553296) + + 100‘ —P/anococcus rifietoensis MST (AJ493659) + + Planococcus maritimus TF-QT (AF500007) + + Saccharococcus thermophilus ATCC 43125T (X70430) + + Saccharococcus caldoxylosilyticus S1812T (AF067651) + + Geobaci/lus subterraneus 34T (AF276306) + + 100* Geabaci/lus stearothermophi/us NBRC 12550T(ABZ71757) + + Anoxybacillus voinovskiensis TH13T (AB110008) + + —Anoxybacillus sayderensis ABO4T (AF001963) + + Anoxybaci/lus flavithermus DSM 2641T (AF004589) + + Exiguobacterium undae L2T (AJ344151) + +

+
+
+

+ 0.01 65* + +

+
+
+

+ + +

+
+
+

+ 68m + +

+
+
+

+ 50 + +

+
+
+

+ 55 + +

+
+
+

+ + + + + + + + + + + + + + + + + + + + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 76 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002477-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002477-0-000.pbm.png new file mode 100644 index 00000000..8f2753f4 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002477-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002477-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002477-0-000.pbm.png.hocr new file mode 100644 index 00000000..6c521181 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002477-0-000.pbm.png.hocr @@ -0,0 +1,94 @@ + + + + + + + + + + + +
+
+

+ 0.05 + + I—l + +

+
+
+

+ 9 Antarctobacterheliothermus EL-219T (Y11552) + + Sagittula stellata E—37T (U58356) + + 31 Ketogulonicigenium robustum X6LT (AF136850) + + Oceanicola granulosus HTCC2516T (AY424896) + + 9 10 Roseisalinus antarcticus EL—88T (AJ605747) + + 10 Loktane/la fryxel/ensis LMG 22007T (AJ582225) + + Loktanella salsilacus LMG 21507T (AJ440997) + + 1" Loktanella vestfoldensis LMG 22003T (AJ582226) + + 9 Leisingera methylohalidivorans MBZT (AY005463) + + 91 Phaeobactergallaeciensis 133107T (Y13244) + + Marinovum algico/a ATCC 51440T(X78315) + + 8 Roseovar/us crassostreae CV919—3127(AF114484) + + 5 Roseovarius nubinhibens ISMT (AF098495) + + Roseovarius pacificus sp. nov. 81 -2T (DQ120726) + + 6 Roseovarius mucosus DFL-24T (AJ534215) + + =‘ Roseovarius tolerans EL—172T (Y11551) + + 9 Rose/vivax halodurans OCh 239T (D85829) + + Roseivivax haloto/erans OCh 210T (D85831) + + Salipiger mucosus A3T (AY527274) + + 87 Paracoccus denitrificans ATCC 17741T (Y16927) + + " Roseibium hamelinense OCh 368T (D85836) + + Rhodobacter ve/dkampiiATCC 35703T (D16421) + + SilicibacterIacuscaeru/ensis |T|—1157T (U77644) + + 10 Octadecabacterantarcticus307T(U14583) + + Octadecabacterarcticus 238T (U73725) + + Thalassobius gelatinovorus IAM 12617T (088523) + + 10 Roseobacterdenitrificans OCh 114T (LO1784) + + Roseobacterlitoralis ATCC 49566T (X78312) + + 9 :4 Sulfitobacterbrevis EL—162T (Y16425) + + Sulfitobacter mediterraneus CH-B427T (Y17387) + +

+
+
+

+ 8 SulfitobacterpontiacusChLG1OT(Y13155) + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002519-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002519-0-000.pbm.png new file mode 100644 index 00000000..1624e39b Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002519-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002519-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002519-0-000.pbm.png.hocr new file mode 100644 index 00000000..e4510773 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002519-0-000.pbm.png.hocr @@ -0,0 +1,332 @@ + + + + + + + + + + + +
+
+

+ + +

+
+
+

+ Escher/ma col/ATCC 1 1 775T (X80725) + + Comamanas {err/gene DSM 7099T (AJ420326) + +

+
+
+

+ 100— SuffereI/a parV/rubra YIT 1 1816T (AB300989) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ Sufferel/a wadsworthens/s WAL 7877 (L37785) + + Sufferel/a sfercor/can/s CCUG 47620T (AJ566849) + + Uncultured bacterium clone D093 (AY916355) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 77 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 100 Uncultured bacterium clone HuCA4 (AJ408960) + + 72 Parasuttere/la excrement/hominis YIT 1 1859T (AB370250) + + es Uncultured bacterium clone 014C-E5 (D0905669) + +

+
+
+

+ + +

+
+
+

+ 59 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 87 + +

+
+
+

+ 80 Uncultured bacterium clone RL304 aal73c05 (D0824230) + +

+
+
+

+ 10° Uncultured bacterium clone D769 (AY986364) + + Oxa/obacter form/genes OxBT (U 49 7 5 7) + + Burkho/der/Qa cepaC/a ATCC 25416T (U9692 7) + + DerX/a gummosa IAM 13946T (AB089482) + + Brack/e/la oed/pod/s LMG 19451 T (AJ277742) + +

+
+
+

+ + +

+
+
+

+ O/I'ge/Aa urethra/is ATCC 1 7960T (AF227163) + + £17 Pe/fslega europaea LMG 10982T (Y1 1890) + + Tay/ore/la eqw'gem'fa/Ils NCTC 1 1 1 84T (X68645) + +

+
+
+

+ + +

+
+
+

+ 99— + +

+
+
+

+ + +

+
+
+

+ 26 + +

+
+
+

+ ' Tetrath/bbacler kashm/rens/s WT001 T (AJ8644 70) + + Advene/Aa mcenata CCUG 45225T (AM944734) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 100 + +

+
+
+

+ Aloe/lgenes faeca/Ils ATCC 8750T (M22508) + +

+
+
+

+ + +

+
+
+

+ H'gmem‘whaga kul/ae K24T (AF28291 6) + +

+ +

+ Kersters/a gy/orum LMG 5906T (AY131 213) + +

+ +

+ 7 L— Achromobacfer xylosoxzdans DSM 10346T (Y1 4908) + + 97 Bordefel/a pefiuss/s ATCC 9797T (U04950) + +

+ +

+ 7 Caste//an/e//a defragrans 54PinT (AJ00544 7) + +

+ +

+ Pusfl/I'nvonas noertemann/i NCIMB 1 4020T (AY695828) + +

+
+
+

+ 0.1 + +

+
+
+

+ 33 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002576-0-001.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002576-0-001.pbm.png new file mode 100644 index 00000000..44c65b1e Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002576-0-001.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002576-0-001.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002576-0-001.pbm.png.hocr new file mode 100644 index 00000000..6b7afbb4 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002576-0-001.pbm.png.hocr @@ -0,0 +1,98 @@ + + + + + + + + + + + +
+
+

+ Roseovarius tolerans EL-1 7? (Y1 1551) + + Roseovarius mucosus DFL—24T (AJ534215) + + Roseovarius aestuariiSMK—122T(EU156066) + + Roseovarius nubinhibens ISMT (AF098495) + + Roseovarius crassostreae CV919-31 QT (AF1 14484) + + Roseovarius halotolerans HJ50T (EU431217) + + Silicibacter lacuscaerulensis |T|—1 1 57T (U77644) + + Si/icibacter pomeroyi DSS-3T (AF098491) + + Marinovum a/gico/a FF3T(X78315) + + Leisingera methy/ohalidivorans MBQT (AY005463) + + Phaeobacter gallaeciensis BS1 07T (Y1 3244) + + Salipiger mucosus A3T (AY527274) + + Donghicola eburneus SW-277T (D0667965) + + Roseobacter Iitoralis Och 149T (X78312) + + EESu/fitobacter pontiacus ChLG 10T (Y1 3155) + + 59 Sulfitobacter dubius KMM 3554T (AY1 801 02) + + Loktane/la vestfoldensis LMG 22003T (AJ582226) + +

+
+
+

+ \— Burkholderia cepacia ATCC 2541 6T (U96927) + +

+
+
+

+ + + + + + + + + + +

+
+
+

+ 0,02 + +

+
+
+

+ 57 96 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002592-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002592-0-000.pbm.png new file mode 100644 index 00000000..2b8ac480 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002592-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002592-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002592-0-000.pbm.png.hocr new file mode 100644 index 00000000..3ef82852 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002592-0-000.pbm.png.hocr @@ -0,0 +1,183 @@ + + + + + + + + + + + +
+
+

+ Planomicrobium glaciei 0423T (EU036220) + +

+ +

+ Planomicrobium chinense DX3-12T (AJ697862) + +

+ +

+ Planomicrobium mcmeekinii DSM 13963T (AF041791) + +

+ +

+ Planomicrobium alkanoc/asticum NCIMB 13489T (AF029364) + +

+ +

+ Planomicrobium koreense JGO7T (AF144750) + +

+ +

+ Planomicrobium psychrophilum CMS 530rT (AJ314746) + +

+ +

+ Planomicroblum okeanokoites IFO 12536T (D55729) + +

+ +

+ Planococcus stackebrandtii K22-03T (AY437845) + +

+ +

+ Planococcus antarct/cus CMS 260rT (AJ314745) + +

+ +

+ Planococcus kocurii DSM 20747T (X62173) + +

+ +

+ Planococcus maritimus TF-9T (AF500007) + +

+ +

+ Planococcus maitriensis S1T (AJ544622) + +

+ +

+ Planococcus columbae Pg EX1 1T (AJ966515) + +

+ +

+ 77 Planococous rifietoensis M8T (AJ493659) + +

+ +

+ Planococcus citreus NCIMB 1493T (X62172) + +

+ +

+ Sporosarcina aquimarina SW28T (AF202056) + +

+ +

+ Kurth/a zopfii NCIMB 9878T (X70321) + +

+ +

+ Lysinibacillus sphaericus IAM 13420T (D16280) + + Caryophanon latum NCIMB 9533T (X70314) + +

+ +

+ Bacillus subti/is NCDO 1769T (X60646) + +

+ +

+ Exiguobacterium aurantiacum NCDO 2321T (X70316) + +

+
+
+

+ + + + + + + + + + + + + + + + + + +

+
+
+

+ 0.01 + +

+
+
+

+ + +

+
+
+

+ + + + + + + + + + + + + + +

+
+
+

+ 80 + +

+
+
+

+ + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002618-0-001.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002618-0-001.pbm.png new file mode 100644 index 00000000..30994263 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002618-0-001.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002618-0-001.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002618-0-001.pbm.png.hocr new file mode 100644 index 00000000..6cbd995b --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002618-0-001.pbm.png.hocr @@ -0,0 +1,174 @@ + + + + + + + + + + + +
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ Filimonas lacunae YT21T (AB362776) + + 0-02 E Segetibacter koreensis Gsoil 664T (A3267478) + + Terrimonas lutea DYT (AB192292) + +

+
+
+

+ C Terrimonas ferruginea ATCC 13524T (M62798) + +

+
+
+

+ E Niaste/la yeongjuensis GR20—13T (DQ244076) + + Niaste/la koreensis GR20-1OT (DQ244077) + +

+
+
+

+ Chitinophaga terrae KP01T (AB278570) + + ‘E EChitinophaga ginsengisegetis Gsoil 040T (A8264798) + + Chitinophaga arvensico/a IAM 12650T (D12657) + +

+
+
+

+ Chitinophaga japonensis IFO 16041T (ABO78055) + + Chitinophaga skermanii CC-SG1BT (DQ062743) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ Chitinophaga sancti IFO 15057T (ABO78066) + + Chitinophaga pinensis ACM 2034T (AFO78775) + + ‘E % Chitinophaga ginsengisoli Gsoil 052T (AB245374) + + Chitinophaga filiformis IFO 15056T (AB078049) + + Saprospira grand/'5 ATCC 23119T (M58795) + + Haliscomenobacter h ydrossis ATCC 27775T (M58790) + +

+
+
+

+ Lewine/Ia cohaerens ATCC 23123T (AF039292) + + Flexibacter roseo/us IFO 16707T (ABO78063) + +

+
+
+

+ —¢:W'°’e””ber 'FO 166W (“3078065) + + Flexibacter erXi/is IFO 15060T (ABO78050) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ Flavobacterium aquatile ATCC 11947T (M62797) + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002626-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002626-0-000.pbm.png new file mode 100644 index 00000000..cc9ce677 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002626-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002626-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002626-0-000.pbm.png.hocr new file mode 100644 index 00000000..2995b7c7 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002626-0-000.pbm.png.hocr @@ -0,0 +1,114 @@ + + + + + + + + + + + +
+
+

+ 64 P. pal/ens AHN 10371T (Y13105) + +

+
+
+

+ 0 02 94 P. nigrescens ATCC 33563T (AF414833) + + |'—[ 69 P. intermedia ATCC 25611T (AF414821) + + Knuc 34 100 P. falsenii 04052T (AB429504) + +

+
+
+

+ P. disiens ATCC 29426T (L16483) + + P. corporis ATCC 33547T (L16465) + + P. pa/udivivens JCM 13650T (ABO78827) + + P. bivia ATCC 29303T (L16475) + + 100 P. amnii CCUG 53648T (AM422125) + + P. oulorum ATCC 43324T (L16472) + + P. salivae JCM 12084T (AB108826) + +

+
+
+

+ 96 P. on's ATCC 33573T (L16474) + + 58 P. macu/osa W1609T (EF534314) + + F’. veroralis ATCC 33779T (L16473) + + 100 P. melaninogenica ATCC 25845T (AY323525) + +

+
+
+

+ P. copn' JCM 13464T (AB064923) + + P. albensis DSM 11370T (AJ011683) + + P. multisaccharivorax JCM 12954T (ABZOO414) + + P. denta/is DSM 3688T (X81876) + + P. bergensis 94087913T (AY350613) + + 100 P. multiformis JCM 12541T(AB182483) + + P. denticola ATCC 35308T (AY323524) + + P. buccae ATCC 33574T (L16477) + + 77 P. baroniae E9.33T (AY840553) + + P. stercorea JCM 13469T (ABZ44774) + + ‘P. massiliensis’ Smarlab 121567 (AF487886) + + 63 P. oral/‘3 ATCC 33269T (L16480) + + P. marshii DSM 16973T (AF481227) + + 61 P. shahii JCM 12083T (AB108825) + + 100 P. Ioescheii ATCC 15930T (L16481) + + P. pleuritidis JCM 14110T (A8278593) + + 100 P. enoeca ATCC 51261T (AJ005635) + + P. nanceiensis AIP 261 .03T (AY957555) + + P. timonensis 4401737T (DQS18919) + + 100 P. buccalis ATCC 3531GT (L16476) + + P. ruminico/a ATCC 19189T (L16482) + + 100 P. brevis ATCC 19188T (AJ011682) + + P. bryantii DSM 11371T (AJ006457) + + P. tannerae ATCC 51259T (AJ005634) + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002642-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002642-0-000.pbm.png new file mode 100644 index 00000000..0accb6be Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002642-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002642-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002642-0-000.pbm.png.hocr new file mode 100644 index 00000000..f2e95e83 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002642-0-000.pbm.png.hocr @@ -0,0 +1,358 @@ + + + + + + + + + + + +
+
+

+ 1% + +

+
+
+

+ + +

+
+
+

+ Pseudoruegeria aqu/maris KCTC 12737T (DQ675021) + +

+
+
+

+ + +

+
+
+

+ 1 Ruegeria pomeroyi DSS-3T (AF098491) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 76 Ruegeria Iacuscaeru/ensis lTl-1157T (U77644) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ Ruegeria atlantica IAM 14463T (D88526) + +

+
+
+

+ 6 + +

+
+
+

+ + +

+
+
+

+ 7 + + 59 Ruegerl’a pelagia HTCCZ663T (DQ916141) + + ‘°° Ruegeria mob/[is CIP 109181T (A8255401) + +

+
+
+

+ 100 + +

+
+
+

+ Tha/assobius aestuarii ‘102049T (AY442178) + +

+
+
+

+ 77 Thalassobius mediterraneus CECT 5383T (AJ878874) + +

+
+
+

+ + +

+
+
+

+ Thalossobius gelatinovorans IAM 12617T (D88523) + +

+
+
+

+ + +

+
+
+

+ Roseobacter denitrificans Och 114T (M96746) + +

+
+
+

+ + +

+
+
+

+ 100 + +

+
+
+

+ 63 Roseobacter litoralis ATCC 49566T (X78312) + +

+
+
+

+ + +

+
+
+

+ Sulfitobacter pontiacus ChLG 1OT (Y17388) + +

+
+
+

+ + +

+
+
+

+ 5" Su/fitobacter delicatus KMM 3584T (AY180103) + +

+
+
+

+ 100 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ Su/fitobacter dubius KMM 3554T (AY180102) + +

+
+
+

+ + +

+
+
+

+ Rueger/‘a a/gico/a ATCC 51440T (X78315) + +

+
+
+

+ Phaeobacter arcticus 20188T (DQS14304) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 79 Phaeobactergallaeciensis BS1O7T(Y13244) + +

+
+
+

+ + +

+
+
+

+ —Phaeobacter inhibens LMG 22475T (AY177712) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 33 Phaeobacter daeponensis TF—218T (DQQ81486) + +

+
+
+

+ + +

+
+
+

+ 5" erhaeobacter caeruleus LMG 24370 (AM943631) + + 1D + +

+
+
+

+ + +

+
+
+

+ D Phaeobactercaeruleus LMG 24369T (AM943630) + +

+
+
+

+ 50 + +

+
+
+

+ Leisingera methylohalidivorans MBZT (AY005463) + +

+
+
+

+ 97 + +

+
+
+

+ Leisingera aquimarina LMG 24366T (AM900415) + +

+
+
+

+ + +

+
+
+

+ Stappia stel/u/ata IAM 12621T (D88525) + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002683-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002683-0-000.pbm.png new file mode 100644 index 00000000..c8cdba08 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002683-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002683-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002683-0-000.pbm.png.hocr new file mode 100644 index 00000000..cbce7954 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002683-0-000.pbm.png.hocr @@ -0,0 +1,157 @@ + + + + + + + + + + + +
+
+

+ 1 % + + Roseivivax halodurans Och 239T (D85829) + +

+
+
+

+ 10° Roseivivax ha/otolerans Och 210T(D85831) + + Oceanlcola batsensis HTCC 2597T (AY424898) + + 59 Oceanicola marinus Azo-cT (D0822569) + +

+
+
+

+ Shimia marina JCM 13038T (AY962292) + + Thalassobius aestuarii JCZO49T (AY442178) + + 93 Thalassobius mediterraneus CECT 5383T (AJ878874) + + Nautella italica LMG 24365T (AM904562) + + Nautella italica LMG 24364 (AM904563) + + 9 Nautella italica R-28753 (AM944522) + + n. Nautella italica R-25532 (AM944520) + + Nautella italica R-28717 (AM944521) + + Pseudoruegeria aquimaris KCTC 12737T (DQ675021) + +

+
+
+

+ 9 + + 9 + +

+
+
+

+ + +

+
+
+

+ 91 Ruegeria pelagia HT002663T (DQ916141) + + 50 10° Ruegeria mobilis CIP 109181T (A5255401) + +

+ +

+ 99 Ruegeria pomeroyi DSS-3T (AF098491) + + 64 Ruegeria atlantica IAM 14463T (D88526) + +

+
+
+

+ 95 Ruegerialacuscaerulensis ITI—1157T (U77644) + + Sulfitobacterlitoralis DSM 17584T (DQOQ7527) + + 99 Roseobacterdenitrificans Och114T (M96746) + +

+ +

+ 10" Roseobacter/itoralis ATCC 49566T (X78312) + + Roseovarius crassostreae DSM 16950T (AF114484) + + Thalassobacter stenotrophicus CECT 5294T (AJ631302) + +

+ +

+ Octadecabacterarcticus 238T (U73725) + + Jannaschia donghaensis DSW—17T (EF202612) + + 65 100 Jannaschia seosinens/s JCM 13035T(AY906862) + + 59 Jannaschia helgolandensis Hel 10T (AJ438157) + + 51 99 Jannaschia rubra CECT 5088T (AJ748747) + + Loktanel/a vestfoldensis LMG 22003T (AJ582226) + + 69 Roseisalinus antarcticus EL-88T (AJ605747) + + 100 Oceanicola granulosus HTCCZ516T (AY424896) + + Ruegeria algicola ATCC 51440T (X78315) + + Leisingera methylohalidivorans MBZT (AY005463) + + 93 Phaeobacterdaeponensis TF-218T (DQ981486) + + 54 Phaeobactergallaeciensis BS107T (Y13244) + +

+
+
+

+ 58 + +

+
+
+

+ 10° Phaeobacterinh/bens LMG 22475T (AY177712) + +

+
+
+

+ + +

+
+
+

+ Aeromonas hydrophila subsp. bestiarum + + ATCC 7966T (X74677) + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002691-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002691-0-000.pbm.png new file mode 100644 index 00000000..eca6a5d0 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002691-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002691-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002691-0-000.pbm.png.hocr new file mode 100644 index 00000000..d594eacb --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002691-0-000.pbm.png.hocr @@ -0,0 +1,177 @@ + + + + + + + + + + + +
+
+

+ 90 Planococcus citreus NCIMB 1493T (X62172) + +

+ +

+ 75 Planococcus rifietoensis M8T (AJ493659) + + Planococcus columbae PgEx1 1T (AJ966515) + + Planococcus maritimus TF-9T (AF500007) + + Planococcus maitriensis S1T (AJ544622) + +

+ +

+ _ Planococcus antarcticus CMS 260rT(AJ314745) + + fig/anacoccus kocurii NCIMB 629T (X62173) + +

+ +

+ _ Planococcus stackebrandtii K22—03T (AY437845) + +

+
+
+

+ _ P/anomicrobium psychrophi/um CMS 53orT (AJ314746) + +

+
+
+

+ + + + + + + + + + +

+
+
+

+ 75 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ _ Planomicrobium okeanokoites IFO 12536T (D55729) + + 100 , Planomicrobium chinense DX3—12T (AJ697862) + + _ P/anomicrobium koreense JG07T(AF144750) + + 54 _ P/anomicrobium mcmeekinii 823F2T (AFO41 791) + + _ P/anomicrobium alkanoc/asticum NCIMB 13489T (AF029364) + + 88 _ Bhargavaea cecembensis DSE10T (AM286423) + + 74 + +

+
+
+

+ Clade | [Bacillus Sp. (29 species)] + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 71 + + < Clade || [Geobaci/lus sp (1 7 species)] + +

+
+
+

+ PaenibaCi/lus polymyxa DSM 36T (AJ320493) + + Escherichia coli ATCC 1 1 775T (X80725) + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002725-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002725-0-000.pbm.png new file mode 100644 index 00000000..fe569e23 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002725-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002725-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002725-0-000.pbm.png.hocr new file mode 100644 index 00000000..fa969f23 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002725-0-000.pbm.png.hocr @@ -0,0 +1,114 @@ + + + + + + + + + + + +
+
+

+ 0.05 100 Spirosoma Iuteum M5-H2 (EF187349) + + 100 ‘00 Spirosoma Iuteum SPM-1OT (EF451726) + +

+
+
+

+ 94 Spirosoma spitsbergense SPM-9T (EF451725) + + Spirosoma rigui WPCB118T (EF507900) + + Spirosoma lingua/e DSM 74T (AM000023) + + Rudane/la Iutea DSM 19387T (EF635010) + +

+
+
+

+ Larkine/la insperata NCIMB 14103T (AM000022) + +

+
+
+

+ 100— Dyadobacter crustico/a DSM 16708T (AJ821885) + + Dyadobacter hamtensis JCM 12919T (AJ619978) + +

+
+
+

+ Rune/Ia slithyformis ATCC 29530T (M62786) + + Rune/la zeae ATCC BAA-293T (AF137381) + +

+
+
+

+ Arcice/la aquatica LMG 21963T (AJ535729) + + Flectobaci/Ius major DSM 103T (M62787) + + Flectobacillus lacus JCM 13398T (DQ112352) + +

+
+
+

+ + + + + + + + + + +

+
+
+

+ 100 + +

+
+
+

+ + +

+
+
+

+ + + + + + + + + + +

+
+
+

+ + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002741-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002741-0-000.pbm.png new file mode 100644 index 00000000..fcd4090b Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002741-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002741-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002741-0-000.pbm.png.hocr new file mode 100644 index 00000000..ff79c621 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002741-0-000.pbm.png.hocr @@ -0,0 +1,370 @@ + + + + + + + + + + + +
+
+

+ 100/100 + +

+
+
+

+ 99/1 00 + + 53/94 + +

+
+
+

+ 51/52 + +

+
+
+

+ 100/100 + + 63/100 + +

+
+
+

+ 53/74 + +

+
+
+

+ 95/100 + +

+
+
+

+ 95/100 + +

+
+
+

+ 100/92 + +

+
+
+

+ 82,94 100/100 + +

+
+
+

+ 95/100 + +

+
+
+

+ 100/99 91/69 + +

+
+
+

+ 81/100 + +

+
+
+

+ 76/— + +

+
+
+

+ 98/88 51/99 + +

+
+
+

+ 66/90 + +

+
+
+

+ 56/100E + +

+
+
+

+ 97/100 + +

+
+
+

+ 94/100 : + +

+
+
+

+ 69/— + + 70/— + +

+
+
+

+ 70/100 + +

+
+
+

+ Escherichia coli + + Shigella boydil + +

+
+
+

+ Salmonella enter/ca + + Erwin/a carotovora + +

+
+
+

+ Yerslnla pestis + +

+
+
+

+ Photorhabdus luminescens + + Wigglesworthia glossinidia + +

+
+
+

+ Buchnera aphid/cola + + ‘Ca. Baumannia cicadellinicola’ + +

+
+
+

+ Soda/ls gloss/nidius + + Haemophilus influenzae + +

+
+
+

+ ‘Mannhelmla succiniciproducens’ + +

+
+
+

+ Enterobacteriales + +

+
+
+

+ Pasteurellales + +

+
+
+

+ Pasteurella multocida + + Aeromonas hydrophila + + Aeromonas salmonicida + + Vibrlo fischeri + +

+
+
+

+ } Aeromonadales + +

+
+
+

+ Photobacterium profundum Vibriona/es + + Vibrio cholerae + + Shewanella oneidensis + + ldiomarina loihiensis + + Alteromonadales + +

+
+
+

+ Colwellia psychrerythraea + + Pseudoalteromonas haloplanktis + +

+
+
+

+ Oceanospirillum sp. + + Oceanobacter sp. + +

+
+
+

+ Hahella chejuensis + +

+
+
+

+ Chromohalobacter saleXIgens Oceanospiri/Iales + +

+
+
+

+ Marinabacter aquaeolei + +

+
+
+

+ Saccharophagus degradans + + Marinomonas sp. + + Pseudomonas fluorescens + + Pseudomonas syringae + +

+
+
+

+ Pseudomonas aeruginosa + + Alcanivorax borkumensis + +

+
+
+

+ Pseudomonadales + +

+
+
+

+ Acinetobacter sp. + + Psychrobacter arcticus + + Legione/la pneumophila + +

+
+
+

+ Coxiella burnetii + + Methy/ococcus capsulatus + + Alkali/imnicola ehrlichli + +

+
+
+

+ Legions/lakes + +

+
+
+

+ Methy/ococcales and + +

+
+
+

+ Chromatlales + + Nitrosococcus oceani + + Xanthomonas campestris + + X ylella fastidiosa xanthomonadales + + chhelobacter nodosus Card/obacteriales + +

+
+
+

+ Thiamicros ira cruno ena . . + + p g Th/otrlchales + +

+
+
+

+ + +

+
+
+

+ Francisella tularensis + +

+
+
+

+ Ca ulobacter crescentus + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002766-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002766-0-000.pbm.png new file mode 100644 index 00000000..f5914238 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002766-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002766-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002766-0-000.pbm.png.hocr new file mode 100644 index 00000000..6306f3b2 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002766-0-000.pbm.png.hocr @@ -0,0 +1,164 @@ + + + + + + + + + + + +
+
+

+ 100 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ Leptospira borgpetersen/i Mus 127 (AY631884) + + Leptospira we/lii CelledoniT (AY631877) + + Leptospira alexanderi A23 (AY996803) + + Leptosp/"ra santarosai LT 821T (AY631883) + + Leptospira noguchii CZ 2‘14T (AY631886) + + Leptospira interrogans RGAT (AY631894) + + Leptospira kirschneri 3522C)T (AY631895) + +

+ +

+ * Leptospira genomospecies 1 79601 (AY631881) + + ' Leptospira kmetyi Bejo-lso9T (AB279549) + +

+ +

+ Leptospira wolffii Khorat—HZT (EF025496) + +

+
+
+

+ 65 + +

+
+
+

+ + +

+
+
+

+ 100 + +

+
+
+

+ 100 + +

+
+
+

+ + +

+
+
+

+ Leptosp/ra broomi/ 5399T (AY796065) + +

+ +

+ Leptospira inadai 10T (AY631896) + +

+ +

+ Leptospira genomospecies 3 WaZ Holland (AY631897) + + Leptospira biflexa Patoc |T (AY631876) + +

+
+
+

+ i Leptospira fainei BUT EST (AY631885) + + 63 + +

+
+
+

+ 100 + +

+
+
+

+ L + +

+
+
+

+ I—I + + 0.02 + +

+
+
+

+ Leptospira wolbachii CDCT (AY631879) + + 1 Leptospira genomospecies 4 LT 11-33 (AY631888) + + 64 Leptospira genomospecies 5 Sao Paulo (AY631882) + + 84 Leptospira meyeri Iowa City FrogT (AY631878) + +

+
+
+

+ eptonema iI/in/ Habaki (AY996806) + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002808-0-001.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002808-0-001.pbm.png new file mode 100644 index 00000000..84653ed3 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002808-0-001.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002808-0-001.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002808-0-001.pbm.png.hocr new file mode 100644 index 00000000..acbc4e95 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002808-0-001.pbm.png.hocr @@ -0,0 +1,125 @@ + + + + + + + + + + + +
+
+

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

+
+
+

+ 75 Thiobacillus denitrificans ATCC 25259 (CPOOO116) + + Thiobacillus denitrificans ME16 (EU546130) + + Thiobacillus thioparus DSM 505T (M79426) + + Thiobacillus thioparus LV43 (AF005628) + +

+ +

+ Thiobacillus denitrificans NCIMB 9548 (AJ243144) + + Thiobacillus thiophilus D24TNT (EU685841) + +

+ +

+ Thiobacillus aquaesu/is (U58019) + +

+ +

+ “Thiobacillus p/umbophi/us' DSM 6690 (AJ316618) + + Methyloversatilis universal/s (AY436796) + + Denitratisoma oestradiolicum AcBE2—1T (AY879297) + + ‘Dech/oromonas aromat/ca' RCB (AY032610) + + Rhodocyc/us purpureus (M34132) + + Thiomonas delicate NBRC 14566T (ABZ45481) + + Halothiobacillus h ydrothermalis R3T (M90662) + +

+ +

+ Halothiobaci/Ius halophilus (U58020) + + Halothiobacillus neapolitanus DSM 581 (AF173169) + + Acidithiobacillus albertensis DSM 14366T (AJ459804) + + Acidithiobaci/lus ferrooxidans (A3039820) + +

+ +

+ AcidithiobaciI/us caldus DSM 8584T(Z29975) + +

+
+
+

+ 67 + +

+
+
+

+ Outgroup + +

+
+
+

+ 0.10 + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002816-0-001.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002816-0-001.pbm.png new file mode 100644 index 00000000..82b6b8f8 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002816-0-001.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002816-0-001.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002816-0-001.pbm.png.hocr new file mode 100644 index 00000000..57e50ddd --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002816-0-001.pbm.png.hocr @@ -0,0 +1,258 @@ + + + + + + + + + + + +
+
+

+ 91': Clostridium ghoni/ NCIMB 10636T (X73451) + +

+
+
+

+ ‘00 C/ostr/dium sorde/lii ATCC 9714T (ABO757 71) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 1—4 + + 0-0‘ <{51 Clostridium bifermentans ATCC 638T (X75906) + + 56 Clostridium bart/ettfi WAL 16138T (AY438672) + + C/ostridium irregulare DSM 2635T (X73447) + + 74 C/ostridium diff/tile ATCC 9689T (ABO75770) + + _ 56 C/ostridium mangenotii ATCC 25761 T (M59098) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 99 I: Peptostreptococcus anaerobius NCTC 1 1460T (AY326462) + + ‘00 Peptostreptococcus stomatis W2278T (DO160208) + +

+
+
+

+ Sporacetigenium mesophi/um ZLJ1 1 5T (AY682207) + +

+
+
+

+ 79 + +

+
+
+

+ —100:C/OSMd/le litora/e DSM 5388T (X77845) + + Eubacterium acidaminophi/um DSM 3953T (AFO7141 6) + +

+
+
+

+ + + + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 99—Acidaminobacter hydrogenoformans glu 65T(AF016691) + + Fusibacter pauc/vorans SEBR 421 1T (AF050099) + +

+ +

+ Geosporobacter subterraneus VN568T (D0643978) + +

+ +

+ Alkaliphi/us crotonatoxidans B1 1—2T (AF467 248) + +

+ +

+ Clostridium fe/sineum DSM 794T (X77851) + +

+ +

+ Natroninco/a histidinovorans 2—7940T (Y1671 6) + +

+ +

+ Clostridium stick/and/i SR (LO4167) + +

+ +

+ Proteocatella sphenisci PPP2T (AF450134) + +

+ +

+ Filifactor vi/losus DSM 1645T (AF53721 1) + +

+ +

+ Fi/I'factor aloe/s ATCC 35896T (AJ006962) + +

+
+
+

+ 87 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + + + + + + + + + +

+
+
+

+ + +

+
+
+

+ + + + + + + + + + +

+
+
+

+ 100 + +

+
+
+

+ 100 + +

+
+
+

+ + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002873-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002873-0-000.pbm.png new file mode 100644 index 00000000..c0ea48bc Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002873-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002873-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002873-0-000.pbm.png.hocr new file mode 100644 index 00000000..15e8ae49 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002873-0-000.pbm.png.hocr @@ -0,0 +1,250 @@ + + + + + + + + + + + +
+
+

+ 0.05 + +

+
+
+

+ + +

+
+
+

+ e7 Novosphingobium nitrogen/figens Y88T (DO448852) + + Novosphingobium stygiumlFO16085T(A8025013) + + gé‘: Novosphingobium aromaticivoranleO16084T(ABOQ5012) + + 5‘ Novosphingobium subterraneumlFO16086T(ABOQ5014) + + Novosphingobium capsulatum GIFU11526T(D16147) + + Novosphingobium taihuense T3—BQT (AY500142) + + Novosphingobium hassiacum W-51T(AJ416411) + + Novosphingobium lentum MT1 T (AJ303009) + + Novosphingob/um tardaugens ARI-1T (ABO70237) + + Novosphingobium indicum H25T (EF549586) + + Novosphingobium pentaromativorans USES-1 T (AF502400) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + + + + + + + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 81 + +

+
+
+

+ + +

+
+
+

+ 1oo[ Novosphingobium resinovorum NCIMB 8767T(EF029110) + + Novosphingobium subarcticum KF1T(X94102) + + Novosphingobium naphtha/enivorans TUT562T(AB177883) + + Novosphingobium rosa IAM 14222T(D13945) + + 100 Sphingomonas desiccab/Iis CP1DT(AJ871435) + + Sphingomonas dokdonensis DS-4T (D01 789 75) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 10° Sphingomonas ech/noides ATCC14820T(ABOQ1370) + + 74 Altereryth/obacter indicus MSSRF26T (DO399262) + + —Altererythrobacter Iuteolus SW—109T(AY739662) + + Altererythrobacter epoxidivorans JCS350T (00304436) + + 72 91 —Erythrobacter flavus SW-46T (AF500004) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ Erythrobacter longus OCh101T(L017B6) + + Porphyrobacter dokdonensis DSW—74T(DOO11529) + + 99 Porphyrobacter neustonens/s DSM 9434T (AB03332 7) + +

+
+
+

+ + +

+
+
+

+ 100 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002881-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002881-0-000.pbm.png new file mode 100644 index 00000000..e7ebfcc1 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002881-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002881-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002881-0-000.pbm.png.hocr new file mode 100644 index 00000000..ca0afff1 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002881-0-000.pbm.png.hocr @@ -0,0 +1,551 @@ + + + + + + + + + + + +
+
+

+ + +

+
+
+

+ 0.02 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 72 + +

+
+
+

+ 73 ‘Candidatus Devosia euplotis’ L|V5 (AJ548825) + + 1°04‘Candidatus Devosia euplotis’ co (AJ548823) + + _ ‘Candidatus Devosia euplotis’ CAMP4.4 (AJ548824) + + Devosia Iimi LMG 22951T (AJ786801) + + Devosia neptuniae J1 T (AF469072) + +

+
+
+

+ Devosia subaequoris HST3-14T (AM293857) + + Devosia riboflavina ATCC 9526T (D49423) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 98 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 99 + +

+
+
+

+ 100 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 96 + +

+
+
+

+ —. + +

+
+
+

+ + +

+
+
+

+ 75 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 100 + +

+
+
+

+ + +

+
+
+

+ o + + 99 Devosia soli GH2—10T (DQ303125) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ i ‘Devosia ginsengisolf Gsoil 326 (AB271045) + + 100 Devosia insulae DS-56T (EF012357) + + Devosia geojensis BD-c194T (EF575560) + + Cucumibacter marinus CL-GR60T (EF21 1830) + + Strain CL-SK30T (EF988631) + + Ancalomicrob/um adetum DSM 4722T (ABO95950) + +

+ +

+ 100 Angulomicrobium amanitiforme NCIMB 1785T (AJ535709) + +

+ +

+ A Angulomicrobium tetraedrale DSM 5895T (AJ535708) + +

+
+
+

+ Methylorhabdus multivorans DM13T (AF004845) + +

+
+
+

+ + +

+
+
+

+ 100 + +

+
+
+

+ + +

+
+
+

+ 100 i Blastochloris sulfoviridis DSM 729T (D86514 ) + +

+
+
+

+ + +

+
+
+

+ —o + + 96 + +

+
+
+

+ + +

+
+
+

+ —o + +

+
+
+

+ —o + +

+
+
+

+ Blastoch/oris viridis ATCC 19567T (D25314) + + Rhodoplanes elegans AS130T (D25311) + +

+
+
+

+ + +

+
+
+

+ 100 Rhodoplanes rose-us 941T (D25313) + + Prosthecomicrobium pneumaticum ATCC 23633T (ABO17203) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 100 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ —o + + 97 + +

+
+
+

+ + +

+
+
+

+ 100 '4+* Pedomicrobium americanum ACM 3090T (X97692) + +

+
+
+

+ Rhodomicrobium vannie/ii DSM 162T (M34127) + + 78 Hyphomicrobium chloromethanicum CM2T (AF198623) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 71 Hyphomicrobium facile IFAM H-526T (Y14309) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 7 Hyphomicrobium methylovorum KM 146T (Y14307) + + Hyphomicrobium denitrificans TK 0145T (Y14308) + +

+
+
+

+ + +

+
+
+

+ # Hyphomicrobium vulgare IFAM MC-750T (Y14302) + + Hyphomicrobium zavarzinii IFAM ZV-622T (Y14305) + + —. Hyphomicrobium aestuarii DSM 1564T (Y14304) + +

+ +

+ 7 Hyphomicrobium ho/landicum IFAM KB-677T (Y14303) + +

+
+
+

+ Filomicrobium fusiforme DSM 5304T (Y14313) + + Hyphomicrobium sulfonivorans S1T (AF235089) + +

+
+
+

+ Pedomicrobium manganicum ACM 3038T (X97691) + +

+
+
+

+ Pedomicrobium ferrugineum DSM 1540T (X97690) + +

+
+
+

+ + +

+
+
+

+ 100 Pedomicrobium australicum ATCC 43611T (X97693) + +

+
+
+

+ + +

+
+
+

+ Escherichia coli K12T (U00096) + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002899-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002899-0-000.pbm.png new file mode 100644 index 00000000..5aad8fad Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002899-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002899-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002899-0-000.pbm.png.hocr new file mode 100644 index 00000000..737fa19b --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002899-0-000.pbm.png.hocr @@ -0,0 +1,132 @@ + + + + + + + + + + + +
+
+

+ .—u 99 N. sienata IFM 10088T (AB121770) + +

+
+
+

+ 0'01 84 *L N. testacea JCM 12235T (AB192415) + + 97f fl— N. flavorosea JCM 3332T (246754) + + 79 N. carnea DSM 43397T (AF430035) + +

+
+
+

+ + +

+
+
+

+ + + + +

+
+
+

+ 100 N. jinanensis 04-5195T (DQ462650) + + * I— N. speluncae N2-11T(AM422449) + + N. brevicatena DSM 43024T (AF430040) + + N. cyriac/georgica D1627T (AF282889) + + L— N. abscessus IMMIB D—1592T(AF218292) + + N. asteroides DSM 43757T (AF430019) + + N. tha/‘Iandica IFM 10145T (AB126874) + + N. Xishanensis AS 4.1860T(AY333115) + + N. pseudobrasiliensis DSM 44290T (AF430042) + + fv P N. nova IFM 102657(AB162790) + + N. alba YIM 30243T (AY222321) + + 92 N. salmonicida DSM 40472T(AF430050) + +

+
+
+

+ f m + + v 100 + + f, m 99 N. cummidelens DSM 44490T(AF430052) + +

+
+
+

+ fv m I N. soli DSM 44488T (AF430051) + +

+
+
+

+ + + + + + + + +

+
+
+

+ + +

+
+
+

+ 69 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002907-0-001.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002907-0-001.pbm.png new file mode 100644 index 00000000..ccf28e5d Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002907-0-001.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002907-0-001.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002907-0-001.pbm.png.hocr new file mode 100644 index 00000000..0727faaf --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002907-0-001.pbm.png.hocr @@ -0,0 +1,170 @@ + + + + + + + + + + + +
+
+

+ Kineosporia mikuniensis NBRC 16234T(ABB771 17) + + Kineosporia aurantiaca JCM 3230T (A8003931) + + Kineosporia succinea I-273T (A8003932) + + 861 VN05A0342 (AB377118) + + MVNOSAOM ST (AB377116) + + VN05A0351 (A3377119) + + Kineosporia rhizophi/a l-449T (ABOO3933) + + Kineosporia rhamnosa I-132T (A8003935) + + Kineococcus aurantiacus NBRC 15268T (X77958) + + _ Quadrisphaera granu/orum AGO19T(AY831385) + + Geodermatophi/us obscurus DSM 43162T (X92357) + + Frankia sp. (L41048) + + Sporichthya polymorpha NBRC 12702T(A8025317) + + PiI/me/ia terevasa DSM 43040T(X93190) + +

+
+
+

+ 0.01 + + Km + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 972 + +

+
+
+

+ 992 + +

+
+
+

+ + +

+
+
+

+ 522 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 800 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 979 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002915-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002915-0-000.pbm.png new file mode 100644 index 00000000..6af14390 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002915-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002915-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002915-0-000.pbm.png.hocr new file mode 100644 index 00000000..59b1a821 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002915-0-000.pbm.png.hocr @@ -0,0 +1,76 @@ + + + + + + + + + + + +
+
+

+ 96 B. gallinarum JCM 6291T (088191) + + 100 B. saeculare DSM 6531T (D89328) + + B. pullorum JCM 1214T(D86196) + + B. bifidum ATCC 29521 T (M84777) + + B. thermacidophilum subsp. porcinum P3-14T (AY148470) + + B. thermophilum ATCC 25525T (U10151) + + B. thermoacidophi/um subsp. thermoacidophi/um 36T (ABO16246) + + B. boum JCM 1211T(D86190) + + B. asteroides CCUG 24607T (EF187235) + + B. coryneforme ATCC 2591 1T (M58733) + + B. bombi BluCl/TPT (EU1 27549) + + B. tsurumiense OMB115T(A3241106) + + Parascardovia dentico/ens DSM 10105T (D89331) + + Scardovia inopinata DSM 10107T (D89332) + + Aeriscardovia aerophila T6T (AY1 74107) + +

+
+
+

+ Gardnerella vaginal/s ATCC 14018T (M58744) + + 0.1 + +

+
+
+

+ + + + + + + + + + + + + + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002915-0-001.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002915-0-001.pbm.png new file mode 100644 index 00000000..a36da84c Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002915-0-001.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002915-0-001.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002915-0-001.pbm.png.hocr new file mode 100644 index 00000000..b371853b --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002915-0-001.pbm.png.hocr @@ -0,0 +1,93 @@ + + + + + + + + + + + +
+
+

+ B. gallinarum JCM 6291 T (AY004279) + +

+ +

+ B. pullorum JCM 1214T (AYOO4278) + +

+ +

+ B. bifidum JCM 1255T (AYOO4280) + +

+ +

+ B. thermacidophi/um subsp. porcinum P3-14T (AY166561) + + B. boum JCM 1211T(AYOO4285) + +

+ +

+ B. thermoacidophi/um subsp. thermoacidophi/um AS 1.2282T (AY004276) + + B. thermophilum JCM 1 207T (AF240567) + +

+ +

+ B. coryneforme JCM 581 QT (AY004275) + +

+ +

+ B. ind/cum JCM 1302T (AF240574) + +

+ +

+ B. asteroides JCM 8230T (AF240570) + +

+ +

+ B. bombi BluCl/TPT (EU869281) + +

+ +

+ Aeriscardov/a aeriphi/a LMG 21 773T (AY339131) + + Parascardovia dentico/ens DSM 10105 T (AF240565) + + Gardnere/Ia vagina/is ATCC 1401 BT (AF240579) + +

+
+
+

+ + + + + + + + + + + + + + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002931-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002931-0-000.pbm.png new file mode 100644 index 00000000..b2910e71 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002931-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002931-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002931-0-000.pbm.png.hocr new file mode 100644 index 00000000..4d7a9ab3 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.002931-0-000.pbm.png.hocr @@ -0,0 +1,110 @@ + + + + + + + + + + + +
+
+

+ GraCi/ibaclllus haloto/erans NNT (AF036922) + + 100 Halobac/llus halophl/us NCIMB 9251T (X62174) + + L—l-lal;3bazcillus literal/s SL—4T (X94558) + + 74 Alkalibacillus ha/oalkaliphilus DSM 5271T (AJ238041) + + 100 Bacillus subtllis NCDO 1769T (X60646) + + I: Bacillus lichenilormls DSM 13T (X68416) + +

+
+
+

+ 71 Virgibacillus salexigens C-20MoT (Y11603) + +

+
+
+

+ + +

+
+
+

+ 55 100 Virgibacillus olivae E308T (DQ139839) + +

+
+
+

+ + +

+
+
+

+ Virgibacillus salarius SA»Vb1T (AB197851) + + I Virgibacillus marlsmortui 123T (AJ009793) + + 5‘ Virgibacillus proomii LMG 1237oT (AJO12667) + + 86? Virgibacillus pantothenticus NCDO 1765T (X60627) + + 87 991: Virgibacillus dokdonensis DSW—1OT(AY822043) + +

+
+
+

+ 100' Virgibacillus chiguensls NTU1O1T (EF101168) + + Virgibacillus halophilus 5B73CT (ABQ43851) + +

+
+
+

+ 100 Virgibacillus arcticus Hal 1T (EF675742) + + Virgibacillus necropolis LMG 19488T (N315056) + +

+
+
+

+ 53 + + 91 Virgibacillus carmonensis LMG 20964T (AJ316302) + +

+
+
+

+ Virgibacillus kekensis YIM—kkny16T (AY1 21439) + + Virgibacillus halodenitrificans ATCC 49067T (AB021186) + + Virgibacillus koreensis BH30097T (AY61601 2) + +

+
+
+

+ 0.02 + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003046-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003046-0-000.pbm.png new file mode 100644 index 00000000..23a0962a Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003046-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003046-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003046-0-000.pbm.png.hocr new file mode 100644 index 00000000..aa1a3326 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003046-0-000.pbm.png.hocr @@ -0,0 +1,96 @@ + + + + + + + + + + + +
+
+

+ 100 D. mumbaiensis CON—17(DQOO3135) + + 42 D. ficus CC—FR2—1OT(AY941086) + + ,—. 41 D. grand/s DSM 3963T(Y11329) + + 0-09 D. radiodurans DSM 20539T (Y1 1332) + + 48 87 D. indicus Wt/1aT(AJ549111) + + D. desert/VCD1 15T (AY876378) + + 27 73 D. hohokamensis KR-40T (AY743256) + + 95 i D. navajonesis KR—1 14T (AY743259) + + D. yunweiensis YIM 007T (D0344634) + + D. hopiensis KFl-140T (AY743262) + + 39 D. rad/opugnans ATCC 191727(Y11334) + + D. marmoris AA—63T (AJ585986) + + 99 D. frigens AA—692T (AJ585981) + + 21 56 D. saxicola AA-1444T (AJ585984) + + D. murrayiALT—1bT (Y13041) + + 80 D. geotherma/is ACE-3aT (Y13038) + + 80 D. apachensis KR-36T (AY743264) + + 100 D. proteolyticus DSM 20540T (Y1 1331) + + 40 ‘00 D. piscis saxT (D0683348) + + D. radiophi/us DSM 20551 T (Y1 1333) + + D. radiomo/lis PO-O4-20-132T (EF635404) + + 99 D. c/aud/onis PO—04—19—125T (EF635406) + + 92 D. altitudinis ME-o4-32T (EF635407) + + D. sonorensis KR-87T (AY743283) + + 36 D. maricopensis LB-34T (AY743274) + + 34 D. peraridi/itoris KR—200T (EF141348) + + 69 D. pimensis KR—235T (AY743277) + + 62 D. yavapaiensis KR-236T (AY743279) + + 60 D. papagonensis KR-241T (AY743280) + + 100 D. roseus TDMA-uv51T (ABQ64136) + + D. cellulosilyticus 551 161-15T (D0883809) + + 75 D. misasens/s TDMA-25T (AB264135) + + D. alpinitundrae ME—O4—04—52T (EF635408) + + Truepera radiovictr/X RO-24T (D0022076) + +

+
+
+

+ 16 + + 46 + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003053-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003053-0-000.pbm.png new file mode 100644 index 00000000..757c0a22 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003053-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003053-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003053-0-000.pbm.png.hocr new file mode 100644 index 00000000..d5b7da62 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003053-0-000.pbm.png.hocr @@ -0,0 +1,163 @@ + + + + + + + + + + + +
+
+

+ 0.1 0 + +

+ +

+ . Allochromatium minutissimum DSM 1376T(Y12369) + + Allochromatium vinosum DSM 180T (FM1 78268) + + Al/ochromatium warming/'1' DSM 1 73T (Y12365) + + Allochromatium renukae JA136T (AM399029) + + Thiocystis gelatinosa DSM 21 ST (Y1 131 7) + + Thiocystis minor DSM 1 78T (Y1 2372) + +

+ +

+ Thiocystis vio/acea DSM 207T (Y1 1315) + + Chromatium okeni/ DSM 169T (Y12376) + + Thiocapsa roseopersicina DSM 21 7T(Y12364) + + Thiocapsa rosea DSM 235T(FM178269) + +

+ +

+ Thiocapsa marina DSM 5653T (FM1 78270) + + Thio/amprovum pedioforme DSM 3802T (FM1 78271) + + Thiobaca trueperi BCHT (AJ404006) + + Thiorhodococcus mannito/iphagus WST (FM1 78272) + + Thiorhodococcus minor DSM 1 151 BT (Y1 1316) + + Thiorhodococcus bheemlic:usJA132T (AM282559) + + Thiorhodococcus drewsii DSM 15006T (FM1 78273) + + Thiorhodococcus kakinadensis JA13OT (AM282561) + +

+ +

+ o Marichromatium gracile DSM 203T (X93473) + +

+ +

+ o Marichromatium purpuratum DSM 1 591T (AJ224439) + + Marichromatium ind/cum JA100T (AJ543328) + + Mar/chromatium bheem/icum JA1 24T (AM180952) + + Ha/ochromatium glycol/cum 6340T (X93472) + + Ha/ochromatium sa/eXigens 631 OT (X98597) + + Halochromatium roseum JA134T (AM283535) + + Mghiohalocapsa marina JA142T (AM491592) + + Thiohalocapsa halophi/a DSM 6210T (AJ002796) + + Thiococcus pfennigii DSM 226T (Y12373) + + Thiof/avicoccus mobi/is 8321T (AJ010126) + + Thioa/ka/icoccus limnaeus A26T (AJ277023) + + Rhabdochromatium marinum DSM 5261T (X84316) + + Thiorhodovibrio Winogradskyi DSM 6702T (Y1 2368) + + Ectothiorhodospira shaposhnikovii DSM 243T (M591 51) + + Ha/orhodospira ha/ophila SL1T (M26630) + + Escherichia co/i ATCC 11775T (X80725) + +

+
+
+

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003061-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003061-0-000.pbm.png new file mode 100644 index 00000000..654bf000 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003061-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003061-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003061-0-000.pbm.png.hocr new file mode 100644 index 00000000..11a604ef --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003061-0-000.pbm.png.hocr @@ -0,0 +1,240 @@ + + + + + + + + + + + +
+
+

+ Pedobacter panaciterrae Gsoil 042T (ABZ45368) + + Pedobacter heparinus DSM 2366T (AJ438172) + + Pedobacter africanus DSM 12126T (AJ438171) + + Pedobacter caeni LMG 22862T (AJ786798) + + Pedobacter ginsengisoli Gsoil 104T (AB245371) + + Pedobacter insulae DS—39T (EF100697) + +

+
+
+

+ 100 Sphingobacterium antarcticum 6B1Y (AJ576248) + + Pedobacter piscium DSM 11725T (AJ438174) + +

+
+
+

+ 99 Pedobacter cryoconitis DSM 14825T (AJ438170) + + 98 Pedobacter hima/ayensis HHS 22T (AJ583425) + + Pedobacter aquatilis AR107T (AM114396) + + Pedobacter roseus CL—GP80T (DQ1 12353) + + ELEPedobacter suwonensis 15—52T (DQOQ7274) + + 68 Pedobacter sandarakinus DS—27T (DQ235228) + + Pedobacter composti TR6-06T (A8267720) + +

+
+
+

+ Pedobacter lentus DS—40T (EF446146) + + Pedobacter terrico/a DS—45T (EF446147) + +

+
+
+

+ + + + + + +

+
+
+

+ 0.02 + +

+
+
+

+ + +

+
+
+

+ 66 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 74 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 100 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ Pedobacter saltans DSM 12145T (AJ438173) + + 83 Olivibacter sitiensis AW-6T (DQ421387) + + 93 mbacmr koreensis Jip14T (D0680836) + + |—Pseudosphingobacterium domesticum DC—186T (AM407725) + +

+ +

+ 100 Sphingobacter/um daejeonense TR6—04T (AB249372) + + 97 99 Sphingobacterium mizutaii DSM 11724T(AJ438175) + + Sphingobacterium composti 4M24T (EF122436) + + Sphingobacterium spiritivorum DSM 2582 (AJ459411) + + Sphingobacterium faecium DSM 11690T (AJ438176) + + 71 @hiflgobacterium thalpophilum DSM 11723T (AJ438177) + +

+ +

+ 98 Sphingobacterium multivorum IAM 14316T (AB100738) + +

+
+
+

+ Bacteroides fragilis DSM 2151T (A8050106) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003087-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003087-0-000.pbm.png new file mode 100644 index 00000000..a3cd7289 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003087-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003087-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003087-0-000.pbm.png.hocr new file mode 100644 index 00000000..9b003787 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003087-0-000.pbm.png.hocr @@ -0,0 +1,309 @@ + + + + + + + + + + + +
+
+

+ Clone SWPT5_aaaO4e11 * (EF100091) + + 836 Clone obob2_aaa03g05 * (EF096493) + + #661 ' Strain M11 BET '(AM747811) + +

+ +

+ 999 Clone C16_E16 * (AYQQQQQO) + +

+ +

+ Clone SWPT12_aaaO4fO4 * (EF098044) + +

+ +

+ #9:? Clone M3_f06_3 * (DOO15649) + +

+
+
+

+ #885 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ #999 + +

+
+
+

+ + +

+
+
+

+ Clone RL176_aah44cO5 (DO793846) + + Bacterium B7 * (DO789120) + +

+
+
+

+ 7B1 Asaccharobacter ce/afus doOST (A82661 02) + + #1000 + +

+
+
+

+ #1000 + +

+
+
+

+ + +

+
+
+

+ #1000 + +

+
+
+

+ Adlercreuz‘ZIla equalifac/ens FJ C—BQT (A8306661) + + Human intestinal bacterium SNU—Julong732 (AY310748) + + Eggedhe/la lenfa SECO—Mt75m2 (AY937880) + + Eggerthefla s/nensfls HKU14T (AY321958) + + Eggerthe/la hongkongenS/Ls HKU1OT (AY28851 7) + + Den/Yrobacter/ijm detox/ficans NPOH1T (U 43492) + + S/ac/(I'a eX/gua ATCC 700122T (AF101240) + + C/yptobacz‘er/ijm cum/m DSM 15641 T (ABO19260) + + Co/flhse/la aerofac/ens ATCC 25986T (A801 1816) + + Cor/bbacter/um g/amerans DSM 20642T (X79048) + + Atapob/um m/nutum NCFB 2751T (X67148) + + O/sene/la u/iATCC 49627T (AF292373) + + Eubaoler/i/m //'mosum ATCC 8486T * (M59120) + +

+
+
+

+ 316 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 995 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ #815 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ #950 #492 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ #1000 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ #893 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 0.1 + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003087-0-001.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003087-0-001.pbm.png new file mode 100644 index 00000000..991173be Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003087-0-001.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003087-0-001.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003087-0-001.pbm.png.hocr new file mode 100644 index 00000000..584a1a00 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003087-0-001.pbm.png.hocr @@ -0,0 +1,108 @@ + + + + + + + + + + + +
+
+

+ Heterogeneity + + 250 200 150 100 50 + +

+
+
+

+ O + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ Strain Mt1BBT + +

+
+
+

+ + +

+
+
+

+ Asacoharobacter ce/atus + + DS M 1 8 78 5T + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ Eggen‘he/la hongkongens/s + + DSM 1 61 OST + +

+
+
+

+ Eggert/Ie/Ia /enl‘a + + DS M 2 243T + +

+
+
+

+ + +

+
+
+

+ flee + +

+
+
+

+ + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003145-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003145-0-000.pbm.png new file mode 100644 index 00000000..7bf0d82d Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003145-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003145-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003145-0-000.pbm.png.hocr new file mode 100644 index 00000000..9a1e9625 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003145-0-000.pbm.png.hocr @@ -0,0 +1,163 @@ + + + + + + + + + + + +
+
+

+ 0.005 + + M. a/gicola DG893T (AY2581 10) + +

+
+
+

+ M. salsuginis SD—14BT (EF028328) + +

+ +

+ M. flavimaris SW-145T (AY517632) + +

+ +

+ M. lipolyticus SM19T (AY147906) + +

+ +

+ M. sediminum R65T (AJ609270) + +

+ +

+ M. maritimus CK 47T (AJ704395) + +

+ +

+ M. salicampi ISL-40T (EF486354) + +

+ +

+ M. gudaonensis SLO14BB1AT (DQ414419) + +

+ +

+ M. bryozoorum 50—1 1T (AJ609271) + +

+ +

+ M. segnicrescens 8801 1 B1-4T (EF157832) + +

+ +

+ M. koreensis DD-M3T (DQ325514) + +

+ +

+ M. santoriniensis NKSG1T (EU496088) + +

+ +

+ M. pelagius H8225T (DQ458821) + +

+ +

+ 100 M. hydrocarbonoclasticus ATCC 49840T (X67022) + + M. aquaeolei VT8T (AJOOO726) + +

+ +

+ M. daepoensis SW—156T (AY517633) + +

+ +

+ M. vinifirmus FB1T (DQ235263) + +

+ +

+ M. excel/ens KMM 3809T (AY180101) + + 57 M. litoralis SW—45T (AF479689) + + M. Iutaoensis T5054T (AF288157) + +

+
+
+

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

+
+
+

+ + +

+
+
+

+ + + + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003152-0-001.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003152-0-001.pbm.png new file mode 100644 index 00000000..75030ed3 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003152-0-001.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003152-0-001.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003152-0-001.pbm.png.hocr new file mode 100644 index 00000000..1b9d0da9 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003152-0-001.pbm.png.hocr @@ -0,0 +1,114 @@ + + + + + + + + + + + +
+
+

+ 100 + +

+
+
+

+ 0.05 + +

+
+
+

+ 100 Chelativorans oligotrophicus LPM-4T (EF457242) + + 56 Che/ativorans multitrophicus DSM 9103T(EF457243) + + BNC1 (NC_008254) + + Aminobacter aminovorans DSM 7048T (A101 1 759) + + 69 Aminobacter aminovorans DSM 6450 (AJ01 1762) + + 64 Aminobacter ciceronei IMB-1T (AF034798) + + 100 Aminobacter aganoens/s DSM 7051 T (AJO1 1760) + + 53 Aminobacter niigataensis DSM 7050T (AJO1 1 761) + + Aminobacter lissarensis CC495T (AF107722) + + Mesorhizobium chacoense PR5T (AJ278249) + + 9 Mesorhizobium Ciceri UPM-Ca7T (U07934) + + Mesorhizobium loti ATCC 33669T (D14514) + + 73 Mesorhizobium temperatum SDWO18T (AF508208) + + Mesorhizobium mediterraneum UPM-Ca36T (L38825) + + Mesorhizobium tianshanense A-1 BST (U71 O79) + + _ I Mesorhizobium huakuii NBRC 15243T (D13431) + + 65 Mesorhizob/um plur/farium LMG 1 1892T (Y14158) + + 72 Mesorhizobium septentriona/e SDW014T (AF508207) + + 100 Mesorhizobium amorphae ACCC 19665T (AFO41442) + + Mesorhizobium albiziae CCBAU 61 1 58T (D0100066) + + Mesorh/zobium thiogangeticum SJTT (AJ864462) + + 97 Pseudaminobacter defluvii THI O51T (D32248) + + 87 Pseudam/nobacter salicy/atoxidans BN1 2T (AFO72542) + + 100 Def/uvibacter lusatiensis DSM 1 1099T (AJ132378) + + Aquamicrobium def/uvii DSM 1 1603T (Y15403) + + 100 Sinorhizobium fred/i ATCC 35423T (D14516) + + S/norhizobium americanum CFNEI 156T (AF506513) + + Agrobacter/um tumefaciens C4 (AF508093) + + Rhizobium ga/egae ATCC 43677T (D1 1343) + + 100 Rhizobium tropici CIAT 899T (U89832) + + 100 Rhizobium leguminosarum ATCC 10004T (AY509899) + + Rhizobium et/i CFN 42 (U28916) + + 100 Azospiri/lum lipoferum ATCC 29707 (M59061) + + Azosp/ri/lum bras/lense ATCC 29145 (AY3241 10) + +

+
+
+

+ 98 + +

+
+
+

+ 89 + + 65 + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003160-0-001.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003160-0-001.pbm.png new file mode 100644 index 00000000..d0112c5a Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003160-0-001.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003160-0-001.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003160-0-001.pbm.png.hocr new file mode 100644 index 00000000..eaf0bec4 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003160-0-001.pbm.png.hocr @@ -0,0 +1,67 @@ + + + + + + + + + + + +
+
+

+ Mass spectral similarity (% matches) + + 0 10 20 30 4O 50 60 + +

+
+
+

+ |—l—l—l—l—l—L + +

+
+
+

+ binotii CIP 101303T + +

+ +

+ binotii CIP 102116 + + aerolatum CIP 107636T + + thalassium CIP 105728T + + testaceum CIP 104324T + + aurum CIP 103994T + + resistens CIP 107265T + + keratano/yticum CIP 103815T + + flavescens CIP 102401T + + laevaniformans CIP 100934T + + foliorum CIP 107137T + + halotolerans CIP 108071T + +

+
+
+

+ :::::::::::: + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003160-0-002.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003160-0-002.pbm.png new file mode 100644 index 00000000..ababf40b Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003160-0-002.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003160-0-002.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003160-0-002.pbm.png.hocr new file mode 100644 index 00000000..280f53f1 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003160-0-002.pbm.png.hocr @@ -0,0 +1,152 @@ + + + + + + + + + + + +
+
+

+ 0.01 + + |—| + +

+
+
+

+ Leucobacter komagatae NBRC 15245T (AB007419) + + 58 M. haloto/erans YIM 70130T (AY376165) + + M. binotii CIP 102116 (EU600175) + + 100 . binotii CIP 101303T (EF567306) + + 57 M. trichotheceno/yticum NBRC 15077T (ABOO4722) + + M. ha/ophi/um NBRC 16062T (ABOO4714) + + M. xylanilyticum SB-ET (AJ853908) + + M.hominis NBRC 15708T (ABOO4727) + + M. tha/assium NBRC 16060T (ABOO4713) + + .‘ M. terrae NBRC 15300T (AB004720) + + 100 M. ketosireducens NBRC 14548T (ABOO4724) + + 51 M. flavescens NBRC 15039T (ABOO4716) + + M. Iaevaniformans NBRC 14471T (AB007416) + + M. dextranolyticum DSM 8607T (ABOO7417) + + M. chocolatum NBRC 3758T (ABOO4725) + + 96 M. aurantiacum CIP 105730T( EU863415) + + 100 . kitamiense JCM 10270T (AB013907) + + 55 M. hatanonis FCC-01T (AB274908) + + M. aurum NBRC 15204T(ABOO7418) + + M. sch/eiferi NBRC 15075T (ABOO4723) + + M. koreense J853»2T (AY962574) + + M. lacticum NBRC 14135T (ABOO7415) + + M. flavum YM18-098T (AB286029) + + M. terrico/a KV»448T (ABZ34025) + + 100 M. deminutum KV-483T (A8234026) + + . pumilum KV-488T (AB234027) + + M. terregens NBRC 12961T (ABOO4721) + + M. Iacus A5552T (AB286030) + + 68 M. aoyamense KV-492T (A8234028) + + M. barkeri DSM 20145T (X77446) + +

+
+
+

+ M. gubbeenense CIP 107184T + +

+
+
+

+ 89 M. indicum BBH6T (AM158907) (EU863414) + + M. paludicola US15T (AJ853909) + + 97 M. marinilaous YM11-607T (A3286020) + +

+
+
+

+ M. ulmi LMG 20991T (AY062021) + + M. sediminicola YM1O-847T (A8286021) + + M. ginsengisoli Gsoil 259T (ABZ71048) + + M. imperiale NBRC 12610T (ABOO7414) + + 87 M. arborescens NBRC 3750T (ABOO7421) + + M. keratano/yticum NBRC 13309T (ABOO4717) + + M. resistens DMMZ 1710T (Y 14699) + + M, testaceum DSM 20166T (X77445) + + M. oleivorans DSM 16091T (AJ698725) + + M. aero/atum DSM 14217T (AJ309929) + + M. naton'ense ATCC BAA-1032T (AY566291) + + M. foliorum DSM 1296GT (AJ249780) + + M. phy/Iosphaerae DSM 13468T (AJ277840) + + M. hydrocarbonoxydans DSM 16089T (AJ698726) + + 95 M. esteraromaticum DSM 86099T (Y17231) + + M. arabinogalactanolyticum NBRC 14344T (ABOO4715) + + M. paraoxydans DSM 15019T (AJ491806) + + 82 M. saperdae NBRC 15038T (ABOO4719) + + M. quuefaciens DSM 20638T (X77444) + + 8 . maritypicum NBRC 15779T (AJ853910) + + 61 M. oxydans DSM 20578T (Y17227) + + M. Iuteolum NBRC 15074T (ABOO4718) + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003210-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003210-0-000.pbm.png new file mode 100644 index 00000000..b5746bea Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003210-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003210-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003210-0-000.pbm.png.hocr new file mode 100644 index 00000000..40c6a799 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003210-0-000.pbm.png.hocr @@ -0,0 +1,256 @@ + + + + + + + + + + + +
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 0.1 + +

+
+
+

+ Bergeyella zoohelcum ATCC 43767T (M93153) + + Capnocytophaga gingivalis ATCC 33624T (L14639) + + EM41T (EU443205) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 100 I g + + a Cellulophaga paelflca KMM 3664T (AB100840) + + 74 106% Cellulophaga a/gico/a IC166T (AF001366) + + 93 Cel/u/ophaga baltica NN01584OT (AJ005972) + + ECeIIu/ophaga fucico/a NNO15860T (AJ005973) + + 100 Cellulophaga Iytica ATCC 23178T (M62796) + + 90 Robiginitalea biformata HTCC2501T (AY424899) + + 62 Zeaxanthinibacter enoshimensis TD-ZE3T (A3264057) + + Vite/Iibacter v/adivostokensis KMM 3516T (ABO71382) + + 51 Costenonia aggregate KOPRI 13342T (DQ167246) + + 9 -FIage/limonas eckloniae DOKDO 007T(DQ191180) + + 9’8. Muricauda flavescens SW-62T (AY445073) + + 57 100 »* Muricauda ruestringensis B1T (AF218782) + + 92 7 Muricauda aquimarina SW-63T (AY445075) + + 100 Zobellia galactanivorans DSM 12802T (AF208293) + + 100 Zobellia uliginosa ATCC 14397T (M62799) + + 97 ‘QZobeI/ia russeI/ii LMG 22071T (AB121976) + + 66 Zobellia amurskyensis LMG 22069T (AB121974) + + 9—7' 97 Zobe/Iia laminariae KMM 3676T (AB121975) + + Maribacter polysiphoniae LMG 23671 T (AM497875) + + QEEMaribacter aquivivus KMM 3949T (AY271625) + + 98 Maribacter dokdonensis KCTC 12393T (AY960749) + + flan/beater palladensis LMG 21972T (AJ575643) + + 100 Arenibacter/atericius KMM 426T (AF052742) + + Flavobacterium aquatile ATCC 11947T (M62797) + + Salegentibacter catena HY1T (DQ640642) + + 68 # Gaetbulibacter saemankumensis KCTC 12379T (AY883937) + + 9—8. U/vibacter antarcticus |MCC3101T EF554364 + + WC ) + +

+
+
+

+ 0 U/vibacter Iitoralis KCTC 12104T (AY243096) + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003228-0-001.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003228-0-001.pbm.png new file mode 100644 index 00000000..6f467cdf Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003228-0-001.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003228-0-001.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003228-0-001.pbm.png.hocr new file mode 100644 index 00000000..b0a142f7 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003228-0-001.pbm.png.hocr @@ -0,0 +1,492 @@ + + + + + + + + + + + +
+
+

+ O 005 + +

+
+
+

+ 85 + +

+
+
+

+ 50 + +

+
+
+

+ 72 + +

+
+
+

+ 99 Planotelraspora mira NBRC 15435T (D85496) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 65 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ iPlanotelraspora silvatica TT 00-51T (AB112082) + +

+
+
+

+ iPlanotetraspora thailandica BCC 21825T (ABS70244) + +

+
+
+

+ Microbispora rosea NBRC 14044T (086936) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 76 + +

+
+
+

+ Microbispora chromogenes NBRC 14876T (U48989) + + Microtetraspora malaysiensis H47-7T (A8062383) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 94 + +

+
+
+

+ 99 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 78 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 74 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ iMicrotetraspora fusoa NBRC 13915T (U48973) + +

+ +

+ Microtetraspora glauca NBRC 14761T (U48974) + + Herbidospora cretacea NBRC 15474T (085485) + +

+ +

+ Streptosporangium [Herbidospora] claviforme DSM 44127T (X89940) + + Acrocarpospora corrugata NBRC 13972T (AB188150) + + iAcrocarpospora p/eiomorpha R-31T (ABOO6174) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 99 + +

+
+
+

+ + +

+
+
+

+ 96 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 83 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 89 + +

+
+
+

+ + +

+
+
+

+ iAcrocarpospora macrocephala NBRC 16266T (A8025318) + +

+
+
+

+ Nonomuraea pusi/la NBRC 14684T (D85491) + +

+
+
+

+ Nonomuraea angiospora NBRC 13155T (U48843) + +

+
+
+

+ 100 Planobispora Iongispora NBRC 13918T (D85494) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ Planobispora rosea JCM 3166T (A3028654) + +

+
+
+

+ + +

+
+
+

+ B7 + +

+
+
+

+ + +

+
+
+

+ 64 Planomonospora alba JCM 9373T (A3062381) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 71 + +

+
+
+

+ + +

+
+
+

+ Planomonospora sphaerica JCM 9374T (ABDGZSBZ) + + —Streptosporangium roseum DSM 4302‘]T (X89947) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 55 Streptosporangium violaceochromogenes DSM 43849T (X89951) + +

+
+
+

+ + +

+
+
+

+ Actinomadura madurae DSM 43067T (X97889) + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003244-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003244-0-000.pbm.png new file mode 100644 index 00000000..bd759fae Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003244-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003244-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003244-0-000.pbm.png.hocr new file mode 100644 index 00000000..23554463 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003244-0-000.pbm.png.hocr @@ -0,0 +1,265 @@ + + + + + + + + + + + +
+
+

+ 574 ~Psychromonas macrocephali JAMM 0415T (ABBO4806) + +

+
+
+

+ + +

+
+
+

+ 810 —Psychromonas aquimarina JAMM 0404T (ABSO4805) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 552. *Psychromonas ossibalaenae JAMM 0738T (AB304808) + +

+
+
+

+ + +

+
+
+

+ 572 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ Psychromonas ingrahamii 37T (U73721) + +

+
+
+

+ + +

+
+
+

+ 992 + +

+
+
+

+ + +

+
+
+

+ Psychromonas antarctica DSM 10704T (Y14697) + +

+
+
+

+ + +

+
+
+

+ 598 *Psychromonasjaponica JAMM 0394T (AB304804) + + Psychromonas agarivorans J42-3AT (ABs74544) + +

+ +

+ 1000 . + + Psychromonas agarlvorans 04OZ-AS15-7A (AB374545) + +

+
+
+

+ 58% Psychromonas marina 4—22T (AB023378) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 998 Psychromonas profunda 2825T (AJ416756) + +

+
+
+

+ Psychromonas Kaikoae JT7304T (AB052160) + +

+
+
+

+ + +

+
+
+

+ 1000 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ Psychromonas heitensis AK‘15-027T (AB365352) + +

+
+
+

+ + +

+
+
+

+ Psychromonas hadalis K41 GT (ABOQ4413) + +

+
+
+

+ + +

+
+
+

+ Psychromonas arctica Pull 5.3T (AF374385) + +

+
+
+

+ + +

+
+
+

+ Thalassomonas viridans DSM 13754T (AJ294748) + +

+
+
+

+ + +

+
+
+

+ Escherichia coli ATCC 11775T (X80725) + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003251-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003251-0-000.pbm.png new file mode 100644 index 00000000..6da90d08 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003251-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003251-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003251-0-000.pbm.png.hocr new file mode 100644 index 00000000..5875ec7f --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003251-0-000.pbm.png.hocr @@ -0,0 +1,147 @@ + + + + + + + + + + + +
+
+

+ 97* Salinicoccus iranensis QW6T (DQ767692) + + Salinicoccus Iuteus YIM 70202T (DQ352839) + + Sa/inicoccus rcseus DSM 5351T (X94559) + + Salinicoccus hispanicus DSM 5352T (AY028927) + + Salinicoccus siamensis PN1—2T (A8258358) + + Salinicoccus sa/siraiae F€H1T (00333949) + + Salinicoccus jeotgali 82R53—5T (DQ471329) + + Salinicoccus alkaliphilus T8T (AF275710) + + Salinicoccus kunmingensis YIM Y15T (DQB37380) + + Salinicoccus albus YIM-Y21T (EF177692) + + Jeotgalicoccus ha/oto/erans YKJ-1O1T (AY028925) + + Jeotga/icoccus psychrophi/us YKJ—115T (AY028926) + + Jeotga/icoccus pinnipedia/is CCUG 42722T (AJ251530) + + Macrococcus carouselicus H8b16T (Y15713) + +

+ +

+ 9f Macrococcus bovicus ATCC 51825T (Y15714) + + 100 Macrococcus lamae LMG 21713T (AY119687) + + Macrococcus caseolyticus ATCC 13548T (Y15711) + + Staphylococcus piscifermentans DSM 7373T (Y15754) + + Staphylococcus nepalensis DSM 15150T (AJ517414) + + Carnobacterium pleistocenium FTR1T (AF450136) + + Enterococcus faecium ATCC 19434T (DQ411813) + + Enterococcus mundtii ATCC 43186T (AF061013) + + Halobaci/Ius ha/ophilus NCIMB 2269T (X62174) + + Marinococcus albus DSM 20748T (X90834) + + Marinococcus halophilus DSM 20408T (X90835) + + Nesterenkonia Iutea YIM 70081T (AY588278) + +

+
+
+

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

+
+
+

+ 56 + +

+
+
+

+ 002 + + 71 + +

+
+
+

+ 50 + +

+
+
+

+ 100* + +

+
+
+

+ 98" + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003269-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003269-0-000.pbm.png new file mode 100644 index 00000000..57399da8 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003269-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003269-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003269-0-000.pbm.png.hocr new file mode 100644 index 00000000..8242dd85 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003269-0-000.pbm.png.hocr @@ -0,0 +1,136 @@ + + + + + + + + + + + +
+
+

+ 100* + + 0.01 + +

+
+
+

+ 59 + +

+
+
+

+ 100* + +

+
+
+

+ 73 + +

+
+
+

+ 62* + +

+
+
+

+ 94* + + 98* + + 100* + +

+
+
+

+ 99* + + P 100‘ + +

+
+
+

+ 99* + + 99p + +

+
+
+

+ 98p + +

+
+
+

+ 100, Salegentibacter mishustinae KMM 6049T (AY576653) + + Salegentibacter salegens ACAM 48T (M92279) + + Salegentibacter flavus Fg 69T (AY682200) + + Mesonia algae KMM 3909T (AF536383) + + Mesonia mob/[is KMM 6059T (DQ367409) + + 96* Psychroflexus sediminis YlM-C238T (EU 1 3571 5) + +

+
+
+

+ 1 00* Psychroflexus tropicus ATCC BAA-734T (AF513434) + +

+
+
+

+ 100* Psychroflexus gondwanensis ACAM 44T (M92278) + + |—Psychroflexus torquis ACAM 623T (U85881) + + Salinimicrobium catena HY’lT (DQ640642) + + Salinimicrobium Xinjiangense KCTC 12883T (EF520007) + + Salinimicrobium terrae YIM—C338T (EU135614) + + Gi/Iisia mitskevichiae KCTC 12261T (AY576655) + + Gillisia myxi/Iae UST050418—085T (D0202393) + + Gil/isia illustrilutea ACAM 1062T (AY694008) + + Psychroserpens mesophilus KOPRI 13649T (DQOO1321) + + Psychroserpens burtonensis ACAM 188T (U62913) + + Algibacter mikhai/ovii LMG 23988T (AM491809) + + Algibacter/ectus KMM 3902T (AY187689) + +

+
+
+

+ Myroides odoratus ATCC 4651T (M58777) + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003285-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003285-0-000.pbm.png new file mode 100644 index 00000000..ea3fe0d4 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003285-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003285-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003285-0-000.pbm.png.hocr new file mode 100644 index 00000000..a5ae3dc0 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003285-0-000.pbm.png.hocr @@ -0,0 +1,188 @@ + + + + + + + + + + + +
+
+

+ + + + + + + + + + + + + + + + + + + + + + + + +

+
+
+

+ S. faeni MA—olkiT (AJ429239) + +

+ +

+ 1000 s. aurantiaca MA1O1bT (AJ429238) + +

+ +

+ S. aero/ata NW12T (AJ429240) + +

+ +

+ S. aquatilis JSS7T (AF131295) + +

+ +

+ S. abaci C42T (AJ575817) + +

+ +

+ S. echinoides DSM 1805T (AJO12461) + + S. mali NBRC 15500T (Y09638) + +

+ +

+ S. pruni NBRC 15498T (Y09637) + +

+ +

+ S. asaccharo/ytica NBRC 15499T (Y09639) + + S, soli T5-04T (AB166883) + +

+ +

+ S. koreensis JSSZGT (AF131296) + +

+ +

+ S. adhaesiva GIFU 11458T (D16146) + +

+ +

+ S. dokdonensis DS-4T (DQ178975) + +

+ +

+ S. mucosissima DSM 17494T (AM229669) + + S. molluscorum KMM 3882T (ABZ48285) + + S. desiccabi/is DSM 18792T (AJ871435) + + s. pann/ 052T (AJ575818) + +

+ +

+ 982 S. azotifigens NBRC 15497T (ABZ17471) + + 00 S. trueperi LMG 2142T (X97776) + +

+ +

+ S. pituitosa EDIW (AJ243751) + +

+ +

+ S. japonica KC7T (AB428568) + +

+ +

+ S. sanguinis NBRC 13937T (D13726) + +

+ +

+ S. parapaucimobilis NBRC 15100T (D13724) + + S. paucimobilis GIFU 2395T (D16144) + +

+ +

+ S. roseif/ava MK341T (D84520) + +

+ +

+ S. wittichii DSM 6014T (ABOZ1492) + +

+
+
+

+ Burkho/deria cepacia ATCC 25416T + + (AF097530) + +

+
+
+

+ 0,02 + +

+
+
+

+ 959 + +

+
+
+

+ 975 + + 995 + +

+
+
+

+ 903 + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003293-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003293-0-000.pbm.png new file mode 100644 index 00000000..7d2076dc Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003293-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003293-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003293-0-000.pbm.png.hocr new file mode 100644 index 00000000..fd3c04a0 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003293-0-000.pbm.png.hocr @@ -0,0 +1,259 @@ + + + + + + + + + + + +
+
+

+ 98 92 + +

+
+
+

+ 77 _ AI/oiococcus otitis NCFB 2890T (X59765) + + 100 Do/osigranulum pigrurn NCFB 2975T (X70907) + + [— Atopost/pes suicloacalis PPC79T (AF445248) + + 96 78 Allofush's seminis CCUG 45438T (AJ410303) + + 100 Marini/actibacillus psychrotolerans M13-2T (A8083406) + +

+ +

+ Marinilactibaci/lus piezotolerans LT20T (AY485792) + + {l 98 r‘:AIkalibacterium psychrotolerans IDR2-2T (AB125938) + + Alka/ibaclerium olivapovliticus WW2-SN4aT (AF143511) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ Aka/(bacterium iburiense M3T (AB188091) + + Atopococcus tabaci CCUG 48253T (AJ634917) + + Lacticigenium naphtae MIC1-18T (AB430339) + + 1001:36mobacterium p/eistoceniurn FTR1T (AF450136) + + Carnobacterium alterfunditum ACAM 313T (L08623) + + 86—J— Carnobacterium viridans MPL-11T (AF425608) + + Carnobacterium inhibens K1 T (273313) + +

+
+
+

+ 95S Carnobacterium maltaromaticum DSM 20342T (M58825) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ Carnobacterium gal/inarum NCFB 2766T (X54269) + + Camobacterium divergens NCDO 2763T (X54270) + + 66 Carnobacterium funditum pf3T (886170) + + 71— Carnobacterium mobile NCFB 2765T (X54271) + + Desemzia incena DSM 20581T (Y17300) + + Trichococcus collinsii 37AN3’T (AJ306612) + + Trichococcus pategoniensis PmagG1T (AF394926) + + 76 Trichococcus pasteurii ATCC 35945T (L76599) + + Trichococcus pa/ustris DSM 9172T (AJ296179) + + Trichococcus floccu/iformis DSM 2094T (Y17301) + + Isobaculum melis CCUG 37660T (AJ302648) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + + + +

+
+
+

+ 100 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ Enterococcus faecalis JCM 5803T (ABO12212) + +

+
+
+

+ Streptococcus pyugenes JCM 5674T (AB023575) + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003327-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003327-0-000.pbm.png new file mode 100644 index 00000000..d33e8ae8 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003327-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003327-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003327-0-000.pbm.png.hocr new file mode 100644 index 00000000..9d48f20d --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003327-0-000.pbm.png.hocr @@ -0,0 +1,305 @@ + + + + + + + + + + + +
+
+

+ + +

+
+
+

+ 976 + +

+
+
+

+ 994 + +

+
+
+

+ I,— + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 1000 + +

+
+
+

+ 933 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 854 + +

+
+
+

+ 1000 + +

+
+
+

+ 1000 + +

+
+
+

+ 1000 + + PhyI/o + +

+
+
+

+ 915 Mesorhizobium metallidurans STM 2683T (AM930381) + +

+ +

+ 757 Mesorhizobium tianshanense A-1BST (AFO41447) + +

+ +

+ q‘4M1'asorh/zobfum temperatum SDWO18T (AF508208) + +

+ +

+ Mesorhizobium mediterraneum UPM-Ca36T (L38825) + +

+ +

+ 31' Mesorhizobium septentrionale SDW014T (AF508207) + +

+ +

+ Mesorhizobium amorphae LMG 18977T (AF041442) + +

+ +

+ 62,— Mesomizobium plurifarium LMG 11892T (Y14158) + +

+ +

+ —Mesorhizobium huakuii CCBAU 2609T (D12797) + +

+ +

+ 999 Mesorh/zobium Ioti LMG 6125T (X67229) + +

+ +

+ Mesorhizobium ciceri UPM-Ca7T (U07934) + +

+ +

+ Mesorhizobium chacoense Pr5T (AJ278249) + +

+ +

+ —Mesorhizobium albiziae CCBAU 61158T (DQ100066) + +

+ +

+ Mesorhizobium thiogangeticum SJTT (AJ864462) + +

+ +

+ Phy/lobaclerium trifo/ii PETPOZT (AY786080) + +

+ +

+ bacterium myrsinacearum STM 948T (AY785315) + + Sinorhizobium saheli LMG 7837T (X68390) + +

+ +

+ inorhizobium fred/i LMG 6217T (X67231) + +

+ +

+ —— Sinorhlzobium me/I'loti LMG 6133T (X67222) + +

+ +

+ Rhizoblum Ieguminosarum USDA 2370T (U29386) + +

+
+
+

+ + + + + + + + + + +

+
+
+

+ 80 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 21$ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ A + +

+
+
+

+ Rhizobium et/i CFN 42T (U28916) + + Rhizobium tropic] USDA 9030T (U89832) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ _|:Rhizobium ga/egae LMG 6214T (X67226) + + Agrobacterium tumefaciens NCPPB 2437T (D14500) + +

+
+
+

+ zorhizobium cau/inodans ORS 571 T (D11342) + + Bradyrhlzoblumjaponlcum LMG 6138T (X66024) + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003327-0-001.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003327-0-001.pbm.png new file mode 100644 index 00000000..db5736fe Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003327-0-001.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003327-0-001.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003327-0-001.pbm.png.hocr new file mode 100644 index 00000000..aecb3832 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003327-0-001.pbm.png.hocr @@ -0,0 +1,411 @@ + + + + + + + + + + + +
+
+

+ 7% + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 1000 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 784 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 994 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 01 + +

+
+
+

+ (b) + +

+
+
+

+ 959 + +

+
+
+

+ 767 Mesorhizobium metallidurans STM 3297 (AM930387) + + 993 Mesorhizobium metallidurans STM 3295 (AM930386) + + Mesorhizobium metallidurans STM 3294 (AM930385) + + Mesorhizobium metallidurans STM 3292 (AM930383) + + , Mesorhizobium metallidurans STM 3293 (AM930384) + + Mesorhizobium metallidurans STM 2683T (AM930382) + + 7 Mesorhizobium tianshanense USDA 3592T (AJ294368) + + 7 Mesorhizobium mediterraneum USDA 3392T (AJ294369) + + Mesorhizobium ciceri USDA 3383T (AJ294367) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 7 Mesorhizobium huakuf/ USDA 4779T (AJ294370) + + 7 Mesorhizobium amorphae ICMP 15022T (AY494816) + +

+
+
+

+ Mesorhizobium Ioti USDA 3471T (AJ294371) + + Mesorhizobium plurifarium ICMP 1364GT (AY494824) + + Mesorhizobium chacoense ICMP 14,587T (AY494825) + + Agrobacterium tumefaciens NCPPB 2437T (AJ294377) + +

+ +

+ Phyllobacterium myrsinacearum ATCC 43590T (AJ294365) + + Sinorhizob/‘um meliloti USDA 1002T (AJ294382) + +

+ +

+ Sinorhizobium saheli HAMBI 217 (AJ294380) + +

+ +

+ Azorhizob/‘um caulinodans USDA 4892T (AJ294363) + +

+ +

+ Bradyrhizobium japonicum DSM 30131T(AY591555) + +

+
+
+

+ 1000 Mesorhizobium metallidurans STM 3297 (AM930389) + + 753 Mesorhizobium metallidurans STM 3294 (AM930393) + + Mesorhizobium metallidurans STM 3292 (AM930392) + + Mesorhizabium metallidurans STM 3293 (AM930390) + + 840 Mesorhizobium metallidurans STM 3310 (AM930391) + + Mesorhizobium metallidurans STM 2683Y (AM930388) + + Mesorhizobium plurifar/um ORS 1032T (AY785350) + + Mesorhizobium mediterraneum USDA 3392T (AJ294391) + + 7 Mesorhizobium lianshanense USDA 3592T (AJ294392) + + Mesorhizobium huakuii USDA 4779T (AJ294394) + +

+
+
+

+ + + + + + +

+
+
+

+ 770 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 728 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 812 + +

+
+
+

+ Mesorhizobium chacoense STM 2154T (AY785351) + + Mesorhizobium ciceri USDA 3383T (AJ294395) + + Mesorh/zobium amorphae STM 291T (AY785352) + +

+ +

+ Mesorhizobium Ioti USDA 3471T (AJ294393) + + Sinorhizobium me/i/oti USDA 1002T (AJ294400) + + 7 Sinorhizobium saheli HAMBI 217 (AJ294399) + +

+
+
+

+ + +

+
+
+

+ 810 + +

+
+
+

+ + +

+
+
+

+ 859 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 7 Agmbacterium tumefaciens ORS 1351 T (AY785348) + + Phyllobacterium myrsinacearum ATCC 43590T (AJ294387) + +

+
+
+

+ + +

+
+
+

+ Bradyrhizobium japonicum USDA 6T (AJ294388) + +

+
+
+

+ 0.1 + +

+
+
+

+ Azorhizobium cau/inodans USDA 4892T (AJ294389) + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003368-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003368-0-000.pbm.png new file mode 100644 index 00000000..2db7920d Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003368-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003368-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003368-0-000.pbm.png.hocr new file mode 100644 index 00000000..52175170 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003368-0-000.pbm.png.hocr @@ -0,0 +1,113 @@ + + + + + + + + + + + +
+
+

+ Burkholderia cepacia B7aM (AB164394) + +

+ +

+ 100 Pe/omonas saccharophi/a DSM 654T (ABOZ1407) + + Roseate/es depolymerans 61 B2 (AB003625) + + Leptothrix mobilis Feox-1T (X97071) + +

+ +

+ Leptothrix cholodnii COM 1827 (X97070) + + Azohydromonas lata IAM 12599T (D88007) + +

+ +

+ Rubrivivax gelatinosus |L144 (ABO16167) + + Rubrivivax benzoati/yticus JA2T (AJ888903) + + 69 ‘Rubrivivax indolicus’ OU5 (AJ620346) + + Aquinco/a tertiaricarbonis L108 (DQ436455) + +

+ +

+ Gsoil 1005 (ABZ71046) + +

+ +

+ Strain 1a22T (EU542576) + +

+ +

+ |MCC1722 (DQ664241) + +

+ +

+ Ideone/la dechloratans ATCC 51718T (X72724) + + 8511 (AB049106) + +

+ +

+ 8513 (ABO49107) + +

+ +

+ 8508-1 (ABO49105) + +

+
+
+

+ + + + + + + + + + + + + + + + + + + + + + +

+
+
+

+ 0.01 + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003376-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003376-0-000.pbm.png new file mode 100644 index 00000000..64c8f2dc Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003376-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003376-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003376-0-000.pbm.png.hocr new file mode 100644 index 00000000..fbedc4e1 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003376-0-000.pbm.png.hocr @@ -0,0 +1,117 @@ + + + + + + + + + + + +
+
+

+ + + + + + + + + + + + + + + + + + + + + + +

+
+
+

+ N. Xinjiangensis DSM 15475T (AY226510) + +

+ +

+ N. aethiopica DSM 17733T (AY574575) + +

+ +

+ N. alba CAAS 252T (EU566871) + +

+ +

+ N. flava JCM 14814T (EF680886) + +

+ +

+ N. Iacusekhoensis JCM 11953T(AJ290397) + + N. halobia JCM 11483T (X80747) + +

+ +

+ N. ha/ophila YIM 70179T (AY820953) + +

+ +

+ N. Iutea YIM 70081T (AY588278) + +

+ +

+ N. halotolerans YIM 70084T (AY226508) + +

+ +

+ N. jeotgali .JG—241T (AY928901) + +

+ +

+ 35 N. sandarakina YIM 70009T (AY588277) + + Arthrobacter cumminsii DSM 10493T (X93354) + + Arthrobacter globiformis DSM 20124T (X80736) + + Arthrobacter wo/uwensis DSM 10495T (X93353) + + Streptomyces megasporus DSM 41476T (268100) + +

+
+
+

+ 001 + +

+
+
+

+ 100 + + 100 + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003384-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003384-0-000.pbm.png new file mode 100644 index 00000000..89f734e0 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003384-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003384-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003384-0-000.pbm.png.hocr new file mode 100644 index 00000000..a2bc9c34 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003384-0-000.pbm.png.hocr @@ -0,0 +1,390 @@ + + + + + + + + + + + +
+
+

+ 91 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 79 + +

+
+
+

+ 99 93 + +

+
+
+

+ 79 + +

+
+
+

+ + +

+
+
+

+ 99 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 99 Parapedobacter koreensis \Jip14T (DQ680836) + + Olivibacter sltiensis AW-GT (DQ421387) + + Sphingobacterium composti T5-12T (ABZ44764) + + Sphingobacterium mizutaii ATCC 33299T (M58796) + + Sphingobacterium daejeonense TRE5-04T (ABZ49372) + + Sphingobacterium spiritivorum DSM 2582 (AJ45941 1) + + 7 Sphingobacterium faecium DSM 11690T (AJ438176) + + —Sphingobacterium thalpophi/um DSM 11723T (AJ438177) + + Sphingobacterium multivorum OM—A8 (ABOZOZOS) + + Pedobacter sa/tans DSM 12145T (AJ438173) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 100 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 98 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ Mucilaginibacter daejeonensis Jip 101' (A3267717) + +

+
+
+

+ Muci/aginibacter paludis TPT56T (AM490402) + +

+
+
+

+ + +

+
+
+

+ 100 + + 100 + +

+
+
+

+ 9 + +

+
+
+

+ 88 70 + +

+
+
+

+ + +

+
+
+

+ 100 + + 91 + +

+
+
+

+ 100 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 97 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 95 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 100 + +

+
+
+

+ 100 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ Muci/aginibacter gracilis TPT18T (AM490403) + + Pedobacterlentus DS-40T (EF446146) + + Pedobacter terrico/a DS-45T (EF446147) + +

+ +

+ 75 Pedobacter tenae DS»57T (D0889723) + +

+ +

+ 5 Pedobacter roseus CL-GP80T (DQ112353) + +

+ +

+ —Pedobacter sandarakinus DS-27T (D0235228) + + Pedobacter aquatilis AR1O7T (AM1 14396) + + Pedobacter insulae DS-1 39T (EF100697) + +

+ +

+ 1 Pedobacter panaciterrae Gsoil 042T (ABZ45368) + + Pedobacter heparinus DSM 2366T(AJ438172) + +

+ +

+ *Pedobacter ginseng/'50” Gsoil 104T (ABZ45371) + +

+ +

+ —Pedobaoter himalayensis HHS 22T (AJ583425) + +

+ +

+ Bel/fella ballica BA1 (AJ564642) + +

+ +

+ Cyclobacterium marinum ATCC 43824 (M62788) + + Cytophaga hutchinsonii ATCC 33406T (M58768) + + Sporocytophaga myxococcoides DSM 11118T (AJ310654) + +

+ +

+ Flavobacterium aquatile ATCC 11947T (M62797) + +

+ +

+ Cellulophaga lytioa NBRC 16022 (AB032513) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ Bacteroides fragi/is DSM 2151T (ABOSO106) + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003400-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003400-0-000.pbm.png new file mode 100644 index 00000000..b31ebf8d Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003400-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003400-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003400-0-000.pbm.png.hocr new file mode 100644 index 00000000..e69e93fa --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003400-0-000.pbm.png.hocr @@ -0,0 +1,208 @@ + + + + + + + + + + + +
+
+

+ + +

+
+
+

+ I—l 42 + + 0.005 34 + +

+
+
+

+ 59 + +

+
+
+

+ Oceanico/a batsensis HTCC2597T (AY424898) + + —Oceanicola nanhaiensis SSO11B1-20T (DQ414420) + + Oceanicola marinus AZO-CT (DQ822569) + + 60 Oceanicola pacificus W11-ZBT (DQS59449) + + —Octadecabacter arcticus 238T (U73725) + + T Thalassobius gelatinovorus IAM 12617T (D88523) + + 59 75 Thalassobius aestuarii JC2049T (AY442178) + + 71 Thalassobius mediterraneus CECT 5383T (AJ878874) + + Jannaschia helgo/andensis Hel 1OT (AJ438157) + + Marinosulfonomonas methylotropha PSCH4T (U62894) + + 100 Ketogu/onicigenium vulgare DSM 4025T (AF136846) + + ‘Ketogulonicigenium robustum X6LT (AF136850) + + Oceanicola granulosus HTCCZS16T (AY424896) + + Roseisalinus antarcticus EL-88T (AJ605747) + + Roseicyclus mahoneyensis ML6T (AJ315682) + + Rhodovulum sulfidophilum DSM 1374T (D16423) + + Albidovulum inexpectatum FRR-10T (AF465833) + + Rhodobacter capsulatus CST (D16427) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003434-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003434-0-000.pbm.png new file mode 100644 index 00000000..1384adc9 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003434-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003434-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003434-0-000.pbm.png.hocr new file mode 100644 index 00000000..27608046 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003434-0-000.pbm.png.hocr @@ -0,0 +1,161 @@ + + + + + + + + + + + +
+
+

+ V. ezurae HDV1—1 (AY426982) + + V. ezurae HDS1-2 (AY426981) + + V. ezurae HDS1-1T (AY426980) + + V. neonatus HDD3—1T (AY426979) + + V. halioticoli IAM 14599 (AB000393) + + V. halioticoli IAM 14597 (ABOOO391) + + V. halioticoli IAM 14596T (AB000390) + + V. gal/icus CIP 107867 (AY257975) + + V. gal/icus CIP 107863T (AY257972) + + V. gall/Gus CIP 107865 (AY257973) + + V comitans GHG2-1T (D0922915) + + V. comitans NHM1—4 (D0922919) + + V. comitans NHG1-11 (DQ922918) + + V. superstes G3—29T (AY155585) + +

+ +

+ 51 V. superstes 63-11 (AY155583) + + 58 V. superstes B1—5 (AF519806) + + V. rarus RW22T (DQ914239) + + V. inusitatus RW14T (DQ922920) + + 94 v. inusitatus RW21 (DQ922921) + + 64 RD 15.11T(EF599161) + + CMJ 13.7 (EU541610) + + VB 16.3 (EU541611) + + 95 RD 265(EU541609) v. breoganiisp. nov. + + C 5.5 (EU541608) + + C 4.15 (EU931112) + + RD 232 (EU931113) + +

+
+
+

+ + + + + + + + + + +

+
+
+

+ + +

+
+
+

+ + + + + + + + + + + + + + + + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + + + + + +

+
+
+

+ 97 + +

+
+
+

+ + +

+
+
+

+ V. cholerae ATCC 14035T (X74695) + +

+
+
+

+ 0.005 + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003434-0-001.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003434-0-001.pbm.png new file mode 100644 index 00000000..dabca4b0 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003434-0-001.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003434-0-001.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003434-0-001.pbm.png.hocr new file mode 100644 index 00000000..911da5a7 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003434-0-001.pbm.png.hocr @@ -0,0 +1,368 @@ + + + + + + + + + + + +
+
+

+ RD 2G5 (EU541576) + + RD 282 (FJ214964) + + CMJ 13.7 (FJ214963) + + 001 RD 15.11T (EU541565) V. breoganiisp. nov. + + 61 05.5 (EU541575) + + 99 VB 16.3 (FJ214965) + + 95 c 4.15 (FJ214962) + + V superstes LMG 213st (EU541580) + + 100 V. comitans LMG 23416T (EU541577) + + V. inus/tatus LMG 23434T (EU541579) + + V. rarus LMG 23674T (EU541578) + + 74 89 _| V. ezurae LMG 19970T (AJ842600) + + 90 V. ezurae LMG 19979 (AJ842601) + + V. neonatus LMG 19973T (AJ842660) + + V. halioticoli LMG 19963 (AJ842619) + + 99 V haliot/co/i LMG 18542T (AJ842617) + + V. neonatus LMG 19976 (AJ842661) + +

+
+
+

+ V gall/Gus LMG 21330T (EU541581) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 99 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ V. cholerae LMG 21698 (AJ842573) + +

+
+
+

+ RD 15.11T (EU541585) + + CMJ 13.7 (FJ214959) + + 4% 5.5 (EU541595) + + c 4-15 (FJ214958) V. breoganii sp. nov + + RD 265 (EU541596) + + RD 2B2 (FJ214960) + + 98 VB 16.3 (FJ214961) + + V. comitans LMG 2341GT (EU541597) + + V. inusitatus LMG 23434T (EU541600) + + V. halioticoli LMG 18542T (EU871966) + + V. halloticoll LMG 19963 (AJ842432) + + 95 V. ezurae LMG 19970T (AJ842413) + + V. ezurae LMG 19979 (AJ842414) + + V. neonatus LMG 19976 (AJ842476) + + V. neonatus LMG 19978 (AJ842477) + + V. rarus LMG 23674T (EU541599) + + V. gallicus DSM 16639T (EU541601) + + V. proteolyticus LMG 3772T (AJ842499) + +

+
+
+

+ (b) 55 + + 45 + +

+
+
+

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + +

+
+
+

+ 0.02 100 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + + + +

+
+
+

+ (c) 78 RD 15.11T (EU541550) + + 68 C 5.5 (EU541552) + + 79 C 4.15 (FJ214954) + + RD 265 (EU541551) V. breoganii sp. nov. + + RD 232 (FJ214956) + + VB 16.3 (FJ214957) + + CMJ 13.7 (FJ214955) + + V. superstes LMG 21323T(EF601344) + + 100 V. superstes LMG 21319 (EF601348) + + V. comitans LMG 23416T (EU541553) + + 50 V. inusitatus LMG 23434T (EU541555) + + V rarus LMG 23674T (EU541554) + + V. ezurae LMG 1997GT (EF601309) + + V. ezurae LMG 19979 (EF601313) + + V haliotico/i LMG 19700 (EF601267) + + 95 fiV. halioticol/‘LMG 18542T (EF601260) + +

+
+
+

+ 100 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 100 + +

+
+
+

+ + +

+
+
+

+ + + + + + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 55 V. neonatus LMG 19978 (EF601312) + + 93 V. neonatus LMG 19973T(EF601310) + + V. gal/icus LMG 21330T (EF601347) + + V. cholerae LMG 21698 (EF601300) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003442-0-001.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003442-0-001.pbm.png new file mode 100644 index 00000000..788383d6 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003442-0-001.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003442-0-001.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003442-0-001.pbm.png.hocr new file mode 100644 index 00000000..4c74a8cd --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003442-0-001.pbm.png.hocr @@ -0,0 +1,212 @@ + + + + + + + + + + + +
+
+

+ 89 S. coerulescens NBRC 12758T (AB184122) + + S. abikoensis NBRC 12887 (AB249967) + + 81 S. ehimensis NBRC 13802 (AB184493) + + 53 S. Iuteoverficil/atus NBRC 3722 (AB184791) + + S. roseovertici/Iatus NBRC 15920 (AB184715) + + S. Iuteireticuli NBRC 13422T (AB249969) + + go 51 S. varsoviensis NRRL B-3589T (DQOZ6653) + + 55 S. sapporonensis NBRC 13823T (AB184508) + + 73 9 S. griseoverticil/atus NBRC 13420T (AB184862) + + S. Ii/acinus LMG 20059T (AJ781346) + + 98 S. hiroshimensis NBRC 12785T (AB184144) + + S. mobaraensis NBRC 13819T (AB184870) + + S. albulus IMC 8—0802 (ABOZ4440) + + S. mashuensis DSM 40221T (X79323) + + S. auratus NRRL 8097T (AJ391816) + + 99 S. nashvi/lensis NBRC 13064T (AB184286) + + S. mauvecolor LMG 20100T (AJ781358) + + S. Violascens NBRC 12920T (AB184246) + + S. cremeus JCM 4362T (AY999744) + + 51 S. yanii AS 4.1146T (ABO15854) + + 60 97 s. kurssanovii NBRC 13192T (AB184325) + + 99 S. graminofaciens LMG 19892T (AJ781329) + + 85 S. peucetius JCM 9920T (ABO45887) + +

+
+
+

+ 99 + +

+
+
+

+ 86 S. xantholiticus NBRC 13354T (AB184349) + + S. javensis B22P3T (AJ391833) + + 86 S. yogyakan‘ensis C4R3T (AJ391827) + + 78 S. hygroscopicus subsp. hygroscopicus NBRC 14015 (AB184566) + + S. hygroscopicus ATCC 14891 (AB217603) + +

+
+
+

+ S. violaceusniger ISP 5563T (AJ391823) + + S. sporocinereus LMG 20311T (AJ781368) + + 99 S. endus NRRL 2339T (AY999911) + + 4 S. roseisc/eroticus NBRC 13002T (AB184251) + + 99 s. ruber NBRC 14600T (AB184604) + + 82 S. rubiginosus NBRC 12913T (AB184241) + + S. spiralis NBRC 14215T (AB184575) + + S. poonensis NBRC 13485T (AB184437) + + 97 99 S. thermovu/garis NBRC 16609 (ABZ49975) + + S. thermogriseus NBRC 100772T (ABZ49980) + + 93 s. mexicanus CH-M-1035T (AF441168) + + 53 S. thermocarboxydovorans DSM 44296T (U94489) + + 50 S. nodosus ATCC 14899T (AF114036) + + S. koyangens/s VK—A60T (AY079156) + + 81 S. intermedius DSM 40372T (Z76686) + + S. variegatus NBRC 15462T (AB184688) + + S. aureoverticil/atus NRRL B—3326T (AY999774) + + 88 ‘S. nobi/is’ NBRC 13386 (AB184370) + + S. spectabilis NBRC 13424T (AB184393) + + S. spinoverrucosus LMG 20321T (AJ781376) + + S. indiaensis LMG 19961T (AJ781344) + + 52 57 S. f/avoviridis NBRC 12772T (AB184842) + + S. Iomondensis LMG 20088 (AJ781352) + + 76 5153 S. Iateritius NBRC 12788T (AY999855) + + S. griseoflavus LMG 19344T (AJ781322) + + S. almquistii NRRL B-1685T (AY999782) + + 49 S. violaceochromogenes NBRC 13100T (AY999867) + + 77 S. iakyrus NRRL-ISP 5482T (AJ399489) + + S. Iongispororuber NBRC 13488T (AB184440) + + S. albogriseolus NRRL B-1305T (AJ494865) + + S. armeniacus JCM 3070T (ABO18092) + + S. cacaoisubsp. cacaoi NBRC 12748T (AB184115) + + S. nanshensis SCSIO 01066T (EU589334) + + S. sodiiphi/us YIM 80305T (AY236339) + + 99 S. flocculus NBRC 13041T (AB184272) + + 88 s. rangoonensis NBRC 13078T (AY999859) + + 65 s. gibsonii NBRC 15415T (AB184663) + + 71 S. albus subsp. albus DSM 40313T (AJ621602) + + S. flavofuscus NRRL B-8036 (DQ026648) + + S. ferralitis SFOp68T (AY262826) + + S. guanduensis 701T AY876942) + +

+
+
+

+ 58 66 s. yeochonensis CN 32T (AF101415) + + 87 S. rubidus 13c15T (AY876941) + + 69 S. paucisporeus 1413T AY876943 + + S. yang/inensis 1307T AY876940 + +

+
+
+

+ + +

+
+
+

+ S. scabrisporus KM—4927T (A3030585) + + S. thermol/neatus DSM 41451T (Z6809?) + + 77 S. megasporus DSM 41476T (Z68100) + + 99 + +

+
+
+

+ S. macrosporus DSM 41449T (268099) + + 0.01 + + I—l + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003459-0-002.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003459-0-002.pbm.png new file mode 100644 index 00000000..9dc0417e Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003459-0-002.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003459-0-002.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003459-0-002.pbm.png.hocr new file mode 100644 index 00000000..57ca6736 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003459-0-002.pbm.png.hocr @@ -0,0 +1,270 @@ + + + + + + + + + + + +
+
+

+ + +

+
+
+

+ 0.005 + +

+
+
+

+ 78 + +

+
+
+

+ 99 M. Chubuense ATCC 27278T (AF480597) + + 51|:|: M. chlorophenolicum PCP—IT (X79094) + + 61 M. poriferae ATCC 35087T (AF480589) + +

+
+
+

+ M. psychrotolerans WA1 O1T (AJ534886) + + M. rhodesiae DSM 44223T (AJ429047) + + M. aichiense ATCC 27280T (X55598) + + L? M. bonickei W5998T (AYO12573) + +

+
+
+

+ + +

+
+
+

+ + + + + + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 76 M. neworleansense W6705T (AYO12575) + + M. porcinum CIP 105392T (AY457077) + + 77 L— M. peregrinum CIP 105382T (AY457069) + + 95 M. septicum ATCC 700731T (AY457070) + + M. conceptionense CIP 108544T (AY859684) + + M. fortuitum CIP 104534T (AY457066) + + M. farcinogenes NCTC 10955T (AY457084) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ M. houstonense Ho1asT (AYO12579) + + M. senegalense CIP 104941T (AY457081) + + Strain FI-06250T (EU605695) + +

+
+
+

+ + + + +

+
+
+

+ + +

+
+
+

+ M. bn'sbanense W6743T (AYO12577) + + M. mucogenicum ATCC 49650T (AY457074) + + 100 M. phocaicum CIP 108542T (AY859682) + +

+
+
+

+ M. gadium CIP 105388T (DQ473310) + +

+
+
+

+ _71|: M. barrassiae CIP 108545T (AY859685) + + M. goodiiATCC 700504T (AY457079) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ _i—— M. mageritense CIP 104973T (AY457076) + + 68 M. wolinskyiATCC 700010T (AY457083) + +

+
+
+

+ M. faIIaX ATCC 35219T (AF480600) + + M. brumae ATCC 51384T (AF480576) + +

+
+
+

+ + +

+
+
+

+ M. trivia/e ATCC 23292T (X88924) + + M. tuberculosis H37Ra (CPOOOG11) + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003509-0-001.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003509-0-001.pbm.png new file mode 100644 index 00000000..56889bc2 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003509-0-001.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003509-0-001.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003509-0-001.pbm.png.hocr new file mode 100644 index 00000000..17ae9a96 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003509-0-001.pbm.png.hocr @@ -0,0 +1,408 @@ + + + + + + + + + + + +
+
+

+ + +

+
+
+

+ 96 * Chromohalobacter beijerinckii ATCC 19372T (AB021386) + + Chromohalobacterjaponicus 43T (AB105159) + + 52 Chromohalobacter sarecensis LV4T (AY373448) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 0.01 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ Chromohalobacter nigrandesensis LTS-4NT (AJ277205) + + Chromohalobacter canadensis ATCC 43984T (AJ295143) + + Chromohalobacter marismortui ATCC 17056T (X87219) + + [ Chromohalobacter israelensis ATCC 43985T (AJ295144) + + Chromohalobacter salexigens DSM 3043T (AJ295146) + + * Halomonas euriha/ina ATCC 49336T (X87218) + + *Halomonas elongate ATCC 33173T (X67023) + + Halomonas ha/ophila DSM 4770T (M93353) + + Halomonas pacifica DSM 4742T (L42616) + + Halomonas ventosae A|12T (AY268080) + + 98 ¥ Halomonas halodenitrificans ATCC 13511T (L04942) + + 55 -Halomonas alimentaria YKJ-16T (AF211860) + + Halomonas cupida DSM 4740T (L42615) + + Halomonas kenyensis AIR-2T (AY962237) + + Halomonas campisa/is ATCC 700597T (AF054286) + + Halomonas campaniensis SAGT (AJ515365) + + 57 Halomonas muralis LMG 20969T (AJ320530) + + 95 SP8T (EU218533) + + —— Halomonas pantelleriensis AAPT (X93493) + + 87 —Halomonas kribbensis BH843T (DQ280368) + + 93 Halomonas anticariensis FP35T (AY489405) + + Halomonas desiderata FB2T (X92417) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 89 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 77 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ Halomonas marisflavi SW32T (AF251 143) + + * Halomonas indalinina CG2.1T (AJ427627) + +

+
+
+

+ —Ha/omonas av/cenniae MW2aT (D0888315) + + Z ymobacter palmae IAM 14233T (D14555) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003525-0-001.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003525-0-001.pbm.png new file mode 100644 index 00000000..eb883dab Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003525-0-001.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003525-0-001.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003525-0-001.pbm.png.hocr new file mode 100644 index 00000000..be0d14b3 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003525-0-001.pbm.png.hocr @@ -0,0 +1,140 @@ + + + + + + + + + + + +
+
+

+ 0.10 + +

+
+
+

+ 100 + +

+
+
+

+ 100 + +

+
+
+

+ 100 + +

+
+
+

+ 91 ‘Geobacter humireducens’ JW3 (AY187306) + + 54 Geobacter bremensis Dfr1T (U9691 7) + + Geobacter toluenoxydans TMJ1T (EU711072) + + 85 Geobacter chapel/6i 1 72T (U41561) + + 61 Pelobacter propionicus Ott Bd 1T (X70954) + + Geobacter pelophilus Dfr2T (U96918) + + 100 Geobacter grbiciae TACP-5T (AF3351 83) + + 99 Geobacter metallireducens (ES-15T (LO7834) + + Geobacter sulfurreducens PCAT (U 1 3928) + + ‘00 Desu/furornonas palm/tatis SDBY1T (U281 72) + + ‘00 Pe/obacter carbinolicus Gra Bd 1T (X79413) + +

+
+
+

+ Desu/furomonas acetoxidans DSM 684T (M26634) + + 74 Desulfosporosinus sp. S10 (AFO76527) + +

+
+
+

+ 97 Desu/fosporosinus sp. T1 (AFO76525) + + 96 Desu/fosporosinus hippei DSM 8344T (Y1 1571) + + 94 Desu/fosporosinus lacus STP1 2T (A1582757) + +

+
+
+

+ Desulfosporosinus orient/'5 DSM 765T (Y1 1570) + + 99 Deha/obacter restrictus TEA (Y101 64) + +

+
+
+

+ 99 Syntrophobotu/us glycol/Gus SIGIym (X99706) + + 92 Desu/fitobacterium hafniense PCP-1 (U40078) + + 71 Desu/fitobacterium hafniense DOB-2T (X94975) + + 63 Desu/fitobacterium chlororespirans 0023T (U68528) + + 50 Desu/fitobacterium deha/ogenans JW/IU-DC1T (L28946) + + 76 Desulfitobacterium meta/lireducens 853—15AT (AF297871) + + Desulfitobacterium aromaticivorans UKTLT (EU711071) + + 68 Desulfotomaculum kuznetsovii DSM 61 15T (Y1 1 569) + +

+
+
+

+ 97 Desu/fotomacu/um sp. 0x39 (AJ577273) + +

+
+
+

+ 100 + +

+
+
+

+ Desul/otomaculum acetoxidans DSM 771T (Y1 1566) + + Hydrogenobacter thermophi/us TK-6T (230214) + +

+
+
+

+ Thermocrinis ruber OC 1/4T (AJ005640) + + Aquifex pyrophilus Ko|5aT (M83548) + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003541-0-000.pbm.png b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003541-0-000.pbm.png new file mode 100644 index 00000000..c9aab033 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003541-0-000.pbm.png differ diff --git a/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003541-0-000.pbm.png.hocr b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003541-0-000.pbm.png.hocr new file mode 100644 index 00000000..93e7da84 --- /dev/null +++ b/examples/hocr-tesseract-ijsem-140/sourceimages/ijs.0.003541-0-000.pbm.png.hocr @@ -0,0 +1,243 @@ + + + + + + + + + + + +
+
+

+ 1% + +

+
+
+

+ A. towneriAB1110T (AF509823) + + Acinetobacter genomic species 15TU M 151a (293448) + + A. radioresistens ATCC 43998T (293445) + +

+
+
+

+ A. venetianus RAG-1T (AJ295007 + + 61A. venetianus LUH 4379 (AM909 51) + +

+
+
+

+ 21A. venetianus LUH 8758 (EU258609) + + 1054i. venetianus LUH 7437 (EU258610) + + A. venetianus LUH 5627 (EU258608) + +

+
+
+

+ A. ursingii LUH 3792T (AJ275038) + +

+ +

+ A. baylyi BzT (AM410709) + +

+ +

+ A. IwoffiiATCC 17925 (U10871) + + Acinetobacter genomic species 8 ATCC 17979 (293439) + + Acinetobacter genomic species close to 13TU 10090 (293449) + + Acinetobacter genomic species between 1 and 3 10095 (293450) + +

+ +

+ A. calcoaceticus DSM 30006T (X81661) + + Acinetobacter genomic species 3 ATCC 17922 (293436) + + Acinetobacter genomic species 10 ATCC 17924 (293443) + + Acinetobacter genomic species 11 ATCC 11171 (X81659) + + 9 A. baumanniiATCC 19606T (293435) + + Acinetobacter genomic species 13TU ATCC 17903 (293446) + +

+ +

+ A. gerneri 9A01T (AF509829) + + A. juniiATCC 17908T (293438) + +

+
+
+

+ A. parvus NIPH 384T (AJ293691) + + A. tjernbergiae 7N16T (AF509825) + + A. tandoii4N13T (AF509830) + +

+
+
+

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

+
+
+

+ + +

+
+
+

+ Acinetobacter genomic species 17 942 (293454) + + Acinetobacter genomic species 14BJ 382 (293453) + + A, schind/eri LUH 5832T (AJ278311) + + A. bouvetii 4B02T (AF509827) + +

+ +

+ A. johnsonii ATCC 17909T (293440) + +

+ +

+ A. haemo/yticus ATCC 17906T (293437) + + 4% Acinetobacter genomic species 16 ATCC 17988 (293451) + +

+ +

+ Acinetobacter genomic species 15BJ 79 (293452) + + Alkanindiges i/Iinoisensis GTI MVAB Hex1T (AF513979) + +

+
+
+

+ 100 + + J + +

+
+
+

+ Moraxe/la lacunata + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ Acinetobacter genomic species 13BJ/14TU ATCC 17905 (293447) + +

+
+
+

+ Psychrobacter immobilis ATCC 431 1ST (U39399) + + ATCC 17967T (AF005160) + +

+
+
+ + diff --git a/examples/hocr-tesseract-ijsem-140/tree-checking.xls b/examples/hocr-tesseract-ijsem-140/tree-checking.xls new file mode 100644 index 00000000..04ec9606 Binary files /dev/null and b/examples/hocr-tesseract-ijsem-140/tree-checking.xls differ diff --git a/examples/ijs.0.003566-0-000.pbm.png b/examples/ijs.0.003566-0-000.pbm.png new file mode 100644 index 00000000..79550c10 Binary files /dev/null and b/examples/ijs.0.003566-0-000.pbm.png differ diff --git a/examples/ijs.0.003566-0-000.pbm.png.hocr b/examples/ijs.0.003566-0-000.pbm.png.hocr new file mode 100644 index 00000000..6e71cb8a --- /dev/null +++ b/examples/ijs.0.003566-0-000.pbm.png.hocr @@ -0,0 +1,128 @@ + + + + + + + + + + + +
+
+

+ 95 Coral/ococcus coral/oides DSM 2259T (AJ81 1588) + + 59 Cora/lococcus coral/aides DSM 51547 (AJ81 1592) + + 96— Cora/Iococcus coral/aides DSM 52500 (AJ81 1612) + + 84 Cora/lococcus coral/aides DSM 51620 (AJ81 1608) + + Coral/ococcus coral/aides DSM 51408 (AJ81 1615) + + 99 54 Cora/lococcus coral/oides DSM 51433 (AJ81 1616) + + as Myxococcus stipitatus DSM 14675 (DO7681 18) + + - Myxococcus Iu/vus ATCC 25199T(DQ768117) + + 95 Myxococcus xanthus ATCC 25232T (DO7681 16) + + 97 Myxococcus flavescens DSM 4946T (DO768130) + + 10° Myxococcus virescens NBRC 100334T (AB218225) + + [Coral/ococcus] macrosporus DSM 14697T (AJ81 1623) + + 97 Cystobacter fuscus ATCC 25194T (M94276) + + 1_00 Archangium gephyra ATCC 25201T (DQ768106) + + Stigmata/la aurantiaca ATCC 25190T (DO768127) + +

+
+
+

+ 474‘? Coral/ococcus exiguus DSM 14696T (A181 1598) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 2 0/o + +

+
+
+ + diff --git a/examples/ijs.0.003616-0-000.pbm.png b/examples/ijs.0.003616-0-000.pbm.png new file mode 100644 index 00000000..08effd5e Binary files /dev/null and b/examples/ijs.0.003616-0-000.pbm.png differ diff --git a/examples/ijs.0.003616-0-000.pbm.png.hocr b/examples/ijs.0.003616-0-000.pbm.png.hocr new file mode 100644 index 00000000..2646197e --- /dev/null +++ b/examples/ijs.0.003616-0-000.pbm.png.hocr @@ -0,0 +1,94 @@ + + + + + + + + + + + +
+
+

+ 100* Carnimonas nigrificans CTCBS1T(Y13299) + + Modicisa/ibacter tunisiensis LIT2T (DQS41495) + + Marinospiril/um megaterium H7T (A8006770) + + Marinospirillum alka/iphilum Z4T (AF27571 3) + + Oceanospiri/Ium linum ATCC 11336T (M22365) + + Oceanospirillum beijerinckii IFO 15445T (AB006760) + + Marinimicrobium agarilyticum M18T (AY839870) + + Microbulbifer salipa/udis SM-1T (AF479688) + + Microbulbifer elongatus ATCC 10144T(ABOZ1368) + + Saccharospirillum salsuginis YlM-Y25T (EF177670) + + SaccharospiriI/um impatiens EL—105T (AJ315983) + + Reinekea blandensis MED297T (DQ403810) + + Reinekea marinisedimentorum DSM 15388T(AJ561121) + + Kangiel/a koreensis SW—125T(AY52056O) + +

+ +

+ Kangie/la aquimarina SW—154T (AY520561) + + Alcanivorax jadensis T9T (AJ001 150) + +

+ +

+ Sedimenticola selenatireducens AK4O H 1 T (A F432 1 45) + + Arhodomonas aquaeo/ei ATCC 49307T (M26631) + + Terasakiella pusi/Ia IFO 13613T(ABOO6768) + +

+
+
+

+ + + + + + + + + + + + + + + + + + + + + + + + + + +

+
+
+ + diff --git a/examples/ijs.0.003624-0-000.pbm.png b/examples/ijs.0.003624-0-000.pbm.png new file mode 100644 index 00000000..57dcd335 Binary files /dev/null and b/examples/ijs.0.003624-0-000.pbm.png differ diff --git a/examples/ijs.0.003624-0-000.pbm.png.hocr b/examples/ijs.0.003624-0-000.pbm.png.hocr new file mode 100644 index 00000000..8da187d4 --- /dev/null +++ b/examples/ijs.0.003624-0-000.pbm.png.hocr @@ -0,0 +1,219 @@ + + + + + + + + + + + +
+
+

+ 100 Virgibacillus chiguensis NTU—1 01 T (EF101 168) + +

+ +

+ Virgibaci/lus dokdonensis DSW-1 0T (AY822043) + +

+ +

+ Virgibaci/Ius pantothenticus IAM 1 1061T(D16275) + +

+ +

+ Virgibaci/lus proomii LMG 1 237OT (AJO1 2667) + +

+ +

+ Virgibacillus marismortui 1 2ST (A1009793) + +

+ +

+ 100 Virgibacillus olivae E308T(DO139839) + +

+ +

+ Virgibacillus sediminis YIM kkny3T (AY121430) + +

+ +

+ Virgibacillus salexigens C-2OM0T (Y1 1 603) + +

+ +

+ Virgibacillus kekensis YIM kkny1 6T (AY1 21439) + + Virgibacillus ha/odenitrificans DSM 10037T (AY5431 69) + +

+ +

+ Virgibaci/lus halophi/us 5B7SCT (AB243851) + + Virgibaci/Ius carmonensis LMG 20964T(AJ316302) + + 99 100 Virgibaci/lus necropolis LMG 19488T(A1315056) + +

+
+
+

+ Virgibacillus koreensis BH30097T (AY61 601 2) + + Halobacillus trueperi DSM 1O4O4T(AJ310149) + +

+
+
+

+ Halobaci/lus ha/ophi/us NCIMB 9251 (X62174) + + Gracilibacillus haloto/erans NNT (AF036922) + + Grad/[bacillus dipsosauri DD 1 T (X82436) + + Oceanobacil/us iheyensis HTE831 T (ABO10863) + + Oceanobacillus Chironomi T3944DT (DO298074) + + Marinibacillus marinus DSM 1297T (AJ237708) + + Jeotgalibacillus alimentarius YKJ-13T(AF281 158) + +

+
+
+

+ F’aenibaciI/us po/ymyxa NCDO 1 774T (X60632) + + AlicyC/obaci/lus acidocaldarius DSM 446T (X60742) + +

+
+
+

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

+
+
+

+ 0.02 + +

+
+
+

+ 59 + +

+
+
+

+ 64 + +

+
+
+

+ 54 + +

+
+
+

+ 94 + +

+
+
+

+ + +

+
+
+

+ + + + +

+
+
+

+ + +

+
+
+

+ 100 + + 86 + +

+
+
+

+ 66 + + 100 + +

+
+
+

+ + +

+
+
+ + diff --git a/examples/ijs.0.003640-0-001.pbm.png b/examples/ijs.0.003640-0-001.pbm.png new file mode 100644 index 00000000..fd468716 Binary files /dev/null and b/examples/ijs.0.003640-0-001.pbm.png differ diff --git a/examples/ijs.0.003640-0-001.pbm.png.hocr b/examples/ijs.0.003640-0-001.pbm.png.hocr new file mode 100644 index 00000000..bdc6e510 --- /dev/null +++ b/examples/ijs.0.003640-0-001.pbm.png.hocr @@ -0,0 +1,110 @@ + + + + + + + + + + + +
+
+

+ Nonomuraea pusilla IFO 14684T (D85491) + + Actinomadura alba YIM 45681T (DQ985164) + + Actinomadura yumaensis IMSNU 22167T (AJ293714) + + Actinomadura hal/ensis H647-1T (DQO76484) + + Actinomadura Iivida IMSNU 22191T (AJ293706) + + 100 —Actinomadura cate/latispora IFO 16341T (AF154127) + + Actinomadura rugatobispora IFO 14382T (U49010) + + 74 Actinomadura vinacea DSM 43765T (AF134070) + + 91 Actinomadura viridis DSM 43175T (AJ420141) + + 52 Actinomadura pelletieri IMSNU 22169T (AJ293710) + + Actinomadura macra NBRC 14102T (AB364594) + + Actinomadura cremea subsp. cremea JCM 3308T (AF134067) + + 99 Actinomadura cremea subsp. rifamycini IFO 14183T (U49003) + + 5 72 Actinomadura formosensis DSM 43997T (AJ420140) + + Actinornadura mexicana A290T (AF277195) + + Actinomadura citrea DSM 43461T (AJ420139) + + 92 Actinomadura glauc/flava IFO 14668T (AF153881) + + 53 Actinomadura luteof/uorescens IFO 13057T (U49008) + + 80 Actinomadura coerulea IFO 14679T (U49002) + + 65 Actinomadura verrucosospora IFO 14100T (U49011) + + Actinomadura madurae DSM 43067T (X97889) + + Actinomadura meyerae A288T (AY273787) + + Actinomadura napierensis BSOT (AY568292) + + 83 Act/nomadura lat/na DSM 43382T (AY035998) + + Actinomadura atramentaria DSM 43919T (AJ420138) + + 56 67 Actinomadura hibisca DSM 44148T (AJ420136) + + Actinomadura namibiensis DSM 44197T (AJ420134) + + 100 Actinomadura kijaniata DSM 43764T (X97890) + + Actinomadura oligospora ATCC 43269T (AF163118) + + Actinomadura keratinilytica WCC-2265T (EU637009) + + 100 Act/nomadura viridi/utea IFO 14480T (D86943) + + 100 Actinomadura rubrobrunea DSM 43750T (EU637008) + + Actinomadura rudentiformis DSM 44962T (DQ285420) + + 89 Actinomadura fulvescens DSM 439st (AJ420137) + + Actinomadura fibrosa ATCC 49459T (AF163114) + + 52 Actinomadura nitritigenes DSM 44137T (AY035999) + + Actinomadura umbrina JCM 6837T (AF163121) + + 55 Actinomadura echinospora DSM 43163T (AJ420135) + + Actinomadura spadix JCM 3146T (AF163120) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+ + diff --git a/examples/ijs.0.003699-0-000.pbm.png b/examples/ijs.0.003699-0-000.pbm.png new file mode 100644 index 00000000..5d4b2199 Binary files /dev/null and b/examples/ijs.0.003699-0-000.pbm.png differ diff --git a/examples/ijs.0.003699-0-000.pbm.png.hocr b/examples/ijs.0.003699-0-000.pbm.png.hocr new file mode 100644 index 00000000..35ab4dc9 --- /dev/null +++ b/examples/ijs.0.003699-0-000.pbm.png.hocr @@ -0,0 +1,214 @@ + + + + + + + + + + + +
+
+

+ Geobaci/lus kaustophi/us NCIMB 8547T (X60618) + + Geobacillus thermoleovorans ATCC 43513T (M77488) + + Geobac/l/us lituanious N—3T (AYO44055) + + ‘Geobaci/Ius za/ihae' T1 (AY166603) + + Geobaci/lus vulcan/ 33—1 T (A1293805) + + Geobaci/Ius gargensis GaT (AY193888) + + 94 Geobaci/lus thermocatenu/atus DSM 730T (226926) + + Geobaci/Ius stearothermophi/us NCDO 1 768T (X60840) + + 100 —Geobacillus jurass/cus D81T (AY31 2404) + + 99 Geobacil/us uzenensis UT (AF276304) + + _,— Geobaci/lus subterraneus 34T (AF276306) + + 90 Geobaci/lus thermodenitrificans DSM 465T (Z26928) + + Geobaci/lus ca/doxy/o/yticus 8181 T (AF067651) + + Geobaci/lus thermog/ucosidasius ATCC 43742T (X60641) + + Geobacillus toebii SK-1T (AF326278) + + Geabaci/Ius deb/[is TfT (AJ564616) + + Anoxybacil/us rupiensis DSM 1 71 27T (AJ879076) + + Geobacillus tepidamans GS5-97T (AY563003) + + 92 Anoxybaci/lus contaminans LMG 21881T (A1551 330) + + 80 iflybacfl/us voinovskiensis TH13T (AB1 10008) + + Anoxybacil/us amylo/yticus MR3CT (AJ618979) + + 54 [— Anoxybaci/lus kestanbolensis K4T (AY24871 1) + + 58 9’5 Anoxybacillus pushchinoensis K1 T (AJ010478) + + Anoxybaci/lus flavithermus DSM 2641T (Z26932) + + Anoxybaci/lus ayderensis ABO4T (AFOO1963) + + Anoxybacil/us kamchatkensis JW/VK-KG4T (AF510985) + + Strain DR01 (EU621359) + + Strain DR02 (EU621360) + + Strain DR04 (EU621362) + + 62 Anoxybaci/lus gonensis G2T (AY1 22325) + + Strain DRO3 (EU621361) + + 100 Geobacillus pal/idus DSM 3670T (Z26930) + + Bacillus subti/is NCDO 1769T (X60646) + +

+
+
+

+ + + + + + +

+
+
+

+ 69 + +

+
+
+

+ 76 + +

+
+
+

+ 1—1 87 + + 0.005 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + + + + + + + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 78 + +

+
+
+

+ + +

+
+
+

+ + + + + + + + + + +

+
+
+

+ + +

+
+
+

+ 100 + +

+
+
+

+ 83 + +

+
+
+ + diff --git a/examples/ijs.0.003723-0-000.pbm.png b/examples/ijs.0.003723-0-000.pbm.png new file mode 100644 index 00000000..5fe74530 Binary files /dev/null and b/examples/ijs.0.003723-0-000.pbm.png differ diff --git a/examples/ijs.0.003723-0-000.pbm.png.hocr b/examples/ijs.0.003723-0-000.pbm.png.hocr new file mode 100644 index 00000000..e911a6d3 --- /dev/null +++ b/examples/ijs.0.003723-0-000.pbm.png.hocr @@ -0,0 +1,214 @@ + + + + + + + + + + + +
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 0.005 + +

+
+
+

+ 100 + +

+
+
+

+ - Saccharothrix mutabi/is subsp. mutabi/is DSM 43853T (X76966) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 100 ' + + 70 Saccharothrix mutabi/is subsp. capreo/us DSM 40225T (X76965) + + , Saccharothrix espanaensis NRRL 15764T (AF114807) + + Saccharothrix texasensis NRRL B-161 34T (AF114814) + + CW Saccharothrix violaceirubra YU 692-1T (A8284261) + + * -—— Saccharothrix australiensis NRRL B-11239T (AF114803) + +

+
+
+

+ + +

+
+
+

+ 96 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ Saccharothrix algeriensis NRRL B-24137T (AY054972) + + Saccharothrix xinjiangensis NBRC 101911T (A8381939) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ Saccharothrix syringae NRRL B-16468T (AF114812) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ Saccharothrix coeruleofusca NRRL B-16115T (AF114805) + +

+
+
+

+ Saccharothn'x Iongispora NRRL B-16116T (AF1 14809) + +

+
+
+

+ Actinosynnema mirum NBRC 14064T(D85475) + +

+
+
+ + diff --git a/examples/ijs.0.003731-0-002.pbm.png b/examples/ijs.0.003731-0-002.pbm.png new file mode 100644 index 00000000..d4a894c5 Binary files /dev/null and b/examples/ijs.0.003731-0-002.pbm.png differ diff --git a/examples/ijs.0.003731-0-002.pbm.png.hocr b/examples/ijs.0.003731-0-002.pbm.png.hocr new file mode 100644 index 00000000..fc91e8b6 --- /dev/null +++ b/examples/ijs.0.003731-0-002.pbm.png.hocr @@ -0,0 +1,194 @@ + + + + + + + + + + + +
+
+

+ Bootstrap va|ue; Methanofollis formosanus ML15T (AY186542) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ . >90 % Methanofollis aquaemaris N2F9704T (AF262035) + + 70 (y Methanofollis ethanolicus HASUT (AB371073) + + O > ° E MethanofoI/is Iiminatans GKZPZT (Y16428) + +

+
+
+

+ Methanofollis tationis Chile 9T (AF095272) + + Methanoculleus bourgensis M82T (AF095269) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ Methanolacinia paynteri 62000T (AY196678) + + _ Methanomicrobium mobile BPT (M59142) + + N J‘ 100 %; MP, 0 Methanoplanus Iimicola M3T (M59143) + + 100 %- ML <50 % Methanogenium organophilum CVT (M59131) + + : Methanocalculus halotolerans SEBR 4845T (AF033672) + + Methanocorpusculum parvum XIIT (M59147) + +

+
+
+

+ ‘Methanosphaeru/a palustris’ E1 -90 (EU156000) + + Methanolinea tarda NOBI-1T (AB162774) + + ‘Candidatus Methanoregula boonei’ 6A8 (D0282124) + + Methanospirillum hungatei JF-1 T (M60880) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 0.10 + +

+
+
+

+ + +

+
+
+ + diff --git a/examples/ijs.0.003749-0-000.pbm.png b/examples/ijs.0.003749-0-000.pbm.png new file mode 100644 index 00000000..cc611c95 Binary files /dev/null and b/examples/ijs.0.003749-0-000.pbm.png differ diff --git a/examples/ijs.0.003749-0-000.pbm.png.hocr b/examples/ijs.0.003749-0-000.pbm.png.hocr new file mode 100644 index 00000000..b41503b0 --- /dev/null +++ b/examples/ijs.0.003749-0-000.pbm.png.hocr @@ -0,0 +1,202 @@ + + + + + + + + + + + +
+
+

+ 002 + +

+
+
+

+ 47 + +

+
+
+

+ 59 A, cryaerophi/us CCUG 17801T (L14624) + + 75 A. cryaerophilus CCUG 17802 (AY314755) + + 99 A. skirrowiiCCUG 10374T (L14625) + + _{ A. cibarius LMG 21996T (AJ607391) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 100 + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 100 A. ciban'us LMG 21997 (AJ607392) + + I— A. butzleri CCUG 34397 (DQ464343) + + 100 L A. butzleri ATCC 4961 ST (AY621 1 1 6) + + A. nitmfigilis CCUG 15893.r (L14627) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 72 + +

+
+
+

+ + +

+
+
+

+ 100 A. nitrofigilis F2173 (EU106661) + + A. halophilus LA31BT (AF513455) + + A. mytili T234 (FJ156092) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 100 A. mytili F2075Y (eusegsm) + + 58 A. mytili F2026 (EU669906) + +

+
+
+

+ + +

+
+
+

+ Campy/abacter fetus subsp fetus ATCC 27374T (L04314) + +

+
+
+ + diff --git a/examples/ijs.0.003814-0-002.pbm.png b/examples/ijs.0.003814-0-002.pbm.png new file mode 100644 index 00000000..f5a75b8a Binary files /dev/null and b/examples/ijs.0.003814-0-002.pbm.png differ diff --git a/examples/ijs.0.003814-0-002.pbm.png.hocr b/examples/ijs.0.003814-0-002.pbm.png.hocr new file mode 100644 index 00000000..ef8b7d62 --- /dev/null +++ b/examples/ijs.0.003814-0-002.pbm.png.hocr @@ -0,0 +1,290 @@ + + + + + + + + + + + +
+
+

+ 0.1 + +

+
+
+

+ Archangium gephyra Ar 91 (AJ233912) + + 77 _L— Melittangium alboraceum Me b7 (AJ233907) + + Cystobacter bad/Us DSM 14723T (DQ768108) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 98 + +

+
+
+

+ + +

+
+
+

+ 74 + +

+
+
+

+ 66 + +

+
+
+

+ + +

+
+
+

+ + + + + + + + +

+
+
+

+ + +

+
+
+

+ Stigmate/Ia erecta BICC 8613 (DQ491071) + + 100 —| + +

+ +

+ 97 Stigmata/la hybrida DSM 14722T (DQ768129) + + Myxococcus xanthus DSM 435 (AJ233929) + + Pyxidicoccus fal/ax DSM 14698T (DQ768123) + +

+
+
+

+ + +

+
+
+

+ + + + + + +

+
+
+

+ + +

+
+
+

+ 68 + +

+
+
+

+ + +

+
+
+

+ 95 Cora/Iococcus exiguus DSM 14695T (AJ811598) + + Myxococcus fu/vus NBRC 100070 (ABZ18209) + + Myxococcus stipitatus NBRC 100069 (ABZ18208) + + Phaselicystis flava NOSO-1 (AJ233948) + + 99 Phase/icystis flava SBK0001T (EU545827) + + Byssovorax cruenta DSM 14553T (AJ833647) + + Sorangium cellulosum So ce26 (AF387629) + + Sorangium cellulosum So ce56 (AJ316014) + + Sorangium cellulosum 800157-2 (DQ256394) + + 87Soremgium cellulosum 809881 (AF467672) + + Sorangium cellulosum 809721—1 (AY032880) + + Sorangium cellulosum 300089—1 (AYO79453) + + 54 Sarangium cellulosum 809735-22 (AF467675) + + .1: Chondromyces lanuginosus Sy t2T (AJ233939) + + 79 Chondromyces robustus Cm a13T (AJ233942) + +

+
+
+

+ 51 + +

+
+
+

+ } Phaselicystidaceae + +

+
+
+

+ Po/yangiaceae + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ “Ll: Chondromyces crocatus Cm 06 (M94275) + +

+ +

+ 63 JahneI/a thaxteri Pl t3 (AJ233943) + + Kof/eria flava Pl vt1T (AJ233944) + + Enhygromyxa salina SMK-1-3 (AB097591) + + Plesiocystis pacifica SIR-1T (AB083432) + + ‘Nannocystis aggregans’ Na 31 (AJ233945) + + 10° Nannocystis exedens Na e571 (AJ233947) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ Cora/lococcus coral/aides DSM 2259T (DQ768120) + +

+
+
+

+ V + + eeeuuazoeqozslfg + +

+
+
+

+ J + + N + +

+
+
+

+ V + + aeeuybuwog + +

+
+
+

+ + +

+
+
+

+ Y + + eBeU/JS/(oouueN + +

+
+
+

+ J + +

+
+
+ + diff --git a/examples/ijs.0.003822-0-000.pbm.png b/examples/ijs.0.003822-0-000.pbm.png new file mode 100644 index 00000000..024fea01 Binary files /dev/null and b/examples/ijs.0.003822-0-000.pbm.png differ diff --git a/examples/ijs.0.003822-0-000.pbm.png.hocr b/examples/ijs.0.003822-0-000.pbm.png.hocr new file mode 100644 index 00000000..f8d29022 --- /dev/null +++ b/examples/ijs.0.003822-0-000.pbm.png.hocr @@ -0,0 +1,80 @@ + + + + + + + + + + + +
+
+

+ Desulfovibrio putealis DSM 16056T (AY574979) + + 66 + +

+
+
+

+ + + + + + +

+
+
+

+ Desulfovibrio carbinoliphi/us D41T (DQ186200) + + Desu/fovibr/o fructosivorans JJT (AF050101) + + Desulfovibrio marrakechensis EMSSDQ4Y (AM947130) + +

+ +

+ Desu/fovibrio alcoholivorans DSM 5433T (AF053751) + + gr Desu/fovibrio magnet/Gus RS-1T (D43944) + +

+ +

+ Desu/fovibrio carbinolicus DSM 3852T (AY626035) + + Desulfovibr/o burk/nensis HDvT (AF053752) + + Desu/fovibrio sulfodismutans ThA<201T (Y17764) + + Desulfovibrio inopinatus HHQ 20T (AF177276) + +

+
+
+

+ + +

+
+
+

+ + +

+
+
+

+ 0.01 + +

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Sulfurimonas gotlandica sp. nov., a chemoautotrophic and psychrotolerant epsilonproteobacterium isolated from a pelagic redoxcline, and an emended + description of the genus Sulfurimonas

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  1. Klaus Jürgens1
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  1. 1IOW Leibniz Institute for Baltic Sea Research Warnemuende (IOW), Germany +
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  3. 2Royal Netherlands Institute of Sea Research (NIOZ), Yerseke, Netherlands +
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  5. 3Arbeitsbereich Medizinische Biologie und Elektronenmikroskopisches Zentrum (EMZ), Universität Rostock, Germany +
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  1. Correspondence
    Matthias Labrenz matthias.labrenz{at}io-warnemuende.de
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    Present address: Center for Microbial Oceanography: Research and Education, SOEST, University of Hawaii at Manoa, Honolulu, HI 96822, USA. +

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    § Present address: Robert Koch Institute, Berlin, Germany. +

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Abstract

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A psychro- and aerotolerant bacterium was isolated from the sulfidic water of a pelagic redox zone of the central Baltic Sea. + The slightly curved rod- or spiral-shaped cells were motile by one polar flagellum or two bipolar flagella. Growth was chemolithoautotrophic, + with nitrate or nitrite as electron acceptor and either a variety of sulfur species of different oxidation states or hydrogen + as electron donor. Although the bacterium was able to utilize organic substances such as acetate, pyruvate, peptone and yeast + extract for growth, these compounds yielded considerably lower cell numbers than obtained with reduced sulfur or hydrogen; + in addition, bicarbonate supplementation was necessary. The cells also had an absolute requirement for NaCl. Optimal growth + occurred at 15 °C and at pH 6.6–8.0. The predominant fatty acid of this organism was 16 : 1ω7c, with 3-OH 14 : 0, 16 : 0, 16 : 1ω5c+t and 18 : 1ω7c present in smaller amounts. The DNA G+C content was 33.6 mol%. As determined in 16S rRNA gene sequence phylogeny analysis, + the isolate belongs to the genus Sulfurimonas, within the class Epsilonproteobacteria, with 93.7 to 94.2 % similarity to the other species of the genus Sulfurimonas, Sulfurimonas autotrophica, Sulfurimonas paralvinellae and Sulfurimonas denitrificans. However, the distinct physiological and genotypic differences from these previously described taxa support the description + of a novel species, Sulfurimonas gotlandica sp. nov. The type strain is GD1T ( = DSM 19862T = JCM 16533T). Our results also justify an emended description of the genus Sulfurimonas. +

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    These authors contributed equally to this study. +

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    The GenBank/EMBL/DDBJ accession number for the 16S rRNA gene sequence of strain GD1T is AFRZ01000001 (804671..806178), locus_tag SMGD1_rRNA3. +

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This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted + use, distribution, and reproduction in any medium, provided the original work is properly cited. +

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Deep-sea vents are among the most productive marine systems on Earth. The discovery of these primarily chemoautotrophic environments, + in 1977, has been followed by an appreciation of the remarkable physiological and phylogenetic diversity of their endosymbiotic + and often thermophilic inhabitants, most commonly species of the class Epsilonproteobacteria. Moreover, deep-sea vent chemolithoautotrophs are thought to be representatives of the earliest biological communities on + Earth (see the review by Nakagawa & Takai, 2008). Indeed, many epsilonproteobacteria are globally ubiquitous in oxygen-deficient and sulfide-rich marine and terrestrial + ecosystems, which accommodate their predominantly auto- to mixotrophic lifestyles (Campbell et al., 2006). A number of studies have verified the significant role of epsilonproteobacteria in biogeochemical cycles, particularly + those which are sulfur-dependent, as is the case in deep-sea hydrothermal fields (Nakagawa et al., 2005; Campbell et al., 2006), sulfidic cave springs (Engel et al., 2004) and autotrophic episymbiotic associations (Suzuki et al., 2006). In the suboxic to sulfidic transition zones of aquatic pelagic redox zones, high dark CO2 fixation rates, mainly due to the activities of epsilonproteobacterial chemolithoautotrophs, have been determined, for instance, + in the Black Sea and the Baltic Sea (Grote et al., 2008; Glaubitz et al., 2010; Jost et al., 2008). +

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The Baltic Sea is among the largest brackish basins of the world, with periodically anoxic conditions in its bottom waters. + In the region known as the Baltic Proper there are a number of such areas, including the Gotland Deep, where at depths below + 50–60 m a stable halocline separates the water column into an upper oxygenated layer and underlying oxygen-deficient and anoxic/sulfidic + layers (Lepland & Stevens, 1998; Neretin et al., 2003), in which high dark CO2 fixation rates have been reported (Jost et al., 2010). +

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In stimulation experiments (Labrenz et al., 2005; Brettar et al., 2006), quantitative 16S rRNA PCR (Labrenz et al., 2004), catalysed reporter deposition–fluorescence in situ hybridization (CARD-FISH; Grote et al., 2007) and microautoradiography (MICRO)-CARD-FISH (Grote et al., 2008) analyses, as well as 16S rRNA stable isotope probing (RNA-SIP; Glaubitz et al., 2009), the epsilonproteobacterial ‘Uncultured Helicobacteraceae G138eps1/GD17’ subgroup was shown to account for up to 30 % of the total cell numbers in pelagic redox zones of the central + Baltic Sea. The abundance of these bacteria highlights the importance of chemolithoautotrophic denitrification, which was + convincingly demonstrated to be the major N-loss process in water columns with a sulfide–nitrate interface (Brettar & Rheinheimer, 1991; Hannig et al., 2007; Jensen et al., 2009), catalysed by the GD17 group as potential key organisms for this process. According to its 16S rRNA phylogeny, the ‘Uncultured + Helicobacteraceae G138eps1/GD17’ subgroup belongs to the genus Sulfurimonas, which comprises mesophilic, facultatively anaerobic, chemolithoautotrophic species originating from deep-sea hydrothermal + and marine sulfidic environments (Takai et al., 2006). In previous work (Grote et al., 2012) we described the isolation of strain Gotland Deep 1 (GD1T), a close phylogenetic relative (16S rRNA similarity of 95.7 %) and thus representative of the Baltic Sulfurimonas ‘Uncultured Helicobacteraceae G138eps1/GD17’ subgroup. Selected genomic and physiological data suggested an ecological role for GD1T, especially with respect to its sulfide detoxification ability (Grote et al., 2012). Here, we expand on previous work by presenting the taxonomic characteristics of GD1T. Our results form the basis of an emended description of the genus Sulfurimonas. +

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Strain GD1T was isolated from a pelagic redox zone of the Gotland Deep in the central Baltic Sea during a research cruise on board the + RV Alkor in May 2005 (57° 19.2′ N 20° 03′ E). Water was collected in a free-flow bottle attached to a CTD-rosette from a depth of + 215 m. The in situ temperature was 6 °C, the salinity 13 practical salinity units (PSU), and the sulfide concentration 11 µM. Directly on board, + 100 µM KNO3 and 100 µM Na2S2O3 were added to the water samples, which were then incubated in the dark at 10 °C under anoxic conditions. For further isolation + and cultivation in the laboratory, a modified version of artificial brackish water medium (ABW) (Bruns et al., 2002) was used, consisting of 95 mM NaCl, 11.2 mM MgCl2 . 6H2O, 2.3 mM CaCl2 . 2H2O, 2.0 mM KCl, 6.4 mM Na2SO4, 192 µM KBr, 92 µM H3BO3, 34 µM SrCl2, 92 µM NH4Cl, 9 µM KH2PO4 and 16 µM NaF, buffered with 10 mM HEPES (pH 7.3). For anaerobic cultivation, the medium was boiled, bubbled with N2 for 30 min, and then autoclaved under anoxic conditions. Subsequently, anoxic and sterile-filtered 0.1 % (v/v) of the trace + element solution SL10 (Widdel et al., 1983), 0.2 % (v/v) of a 10-vitamin solution (Balch et al., 1979), 0.02 % (v/v) of a selenite–tungstate solution (Widdel & Bak, 1992), and 2–5 mM NaHCO3 were added. The standard medium ABW+nitrate+thiosulfate (ABW+NS) was prepared by the variable addition of 10 mM KNO3 and 10 mM Na2S2O3, with the final concentration depending on the experiment. A pure culture was acquired by the dilution to extinction method + and was cryopreserved at −80 °C in glycerol for long-term storage. +

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Morphological, physiological, and metabolic characteristics were, for the most part, analysed as described earlier (Grote et al., 2012). For these analyses, strain GD1T was cultivated in triplicate for 7–10 days at 15 °C in the dark. Growth was usually measured by counting 4′,6′-diamidino-2-phenylindol + (DAPI) stained cells, observed using epifluorescence microscopy, or by flow cytometric determinations of SYBR-Green I (Molecular + Probes) stained cells (Labrenz et al., 2007) at the end of the experiment. Sulfurimonas denitrificans DSM 1251T was used as the reference strain in the cultivation experiments. +

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Isolate GD1T is a motile, Gram-reaction-negative, slightly curved or spirilla-shaped bacterium typically with one polar flagellum (Fig. 1a, b), but in some cases two flagella at opposite poles (Fig. 1c). Cell width was rather constant (mean = 0.66 µm, sd = 0.083 µm, n = 112) whereas cell length, i.e. from pole to pole, was variable (mean = 2.1 µm, sd = 0.54 µm, n = 112). The cells had a positive chemotactic response to nitrate (Grote et al., 2012). Under optimal conditions in ABW+NS medium the cell doubling time of strain GD1T was 13 h. Cells in older cultures tended to form aggregates. Growth at temperatures in the range of 4–40 °C was investigated, + with highest cell numbers obtained between 4 and 20 °C and optimal growth at 15 °C (Grote et al., 2012). Thus, isolate GD1T is the first psychrotolerant species within the genus Sulfurimonas, in which all member species at the time of writing are mesophilic (Table 1). +

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Fig. 1.
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Fig. 1. + +

Cell morphology of spirilla-shaped cells of strain GD1T cultivated on ABW+NS medium. (a) Fluorescence microscopy of 4′,6′-diamidino-2-phenylindol (DAPI) stained cells. (b) Transmission + electron microscopy of a bacterium with one flagellum and (c) of a bacterium with two flagella (indicated by arrows), both + negatively stained with phosphotungstic acid. +

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Table 1. + Differential characteristics between strain GD1T and species of the genus Sulfurimonas + +

Taxa: 1, Sulfurimonas gotlandica sp. nov. GD1T; 2, Sulfurimonas denitrificans DSM 1251T (data from this study; Timmer-ten Hoor, 1975; Brinkhoff et al., 2005); 3, Sulfurimonas paralvinellae GO25T (Takai et al., 2006); 4, Sulfurimonas autotrophica OK10T (Inagaki et al., 2003). nd, Not determined; +, positive; −, negative. +

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To obtain media with different pH values, the pH of a 20 ml subsample from the anoxic ABW+NS was adjusted to pH 6.0, 6.5, + 6.7, 6.9, 7.1, 7.5, 8.0, 8.4 and 9.0 by the addition of the appropriate amount of 0.1M HCl. For the experimental setup, the + corresponding amount of 1 M HCl was added to the media preparations, which were then inoculated. After 14 days of incubation, + the pH was measured. At an initial pH of 6.5–8.4, it remained constant (±0.02) throughout the experiment whereas below and + above this range it decreased by about 0.18–0.25 pH units. Optimal growth occurred over a wide pH range (6.7–8.0) but no growth + occured at pH 6.0 and 8.4. The NaCl requirement was determined by cultivation in ABW+NS containing the following salt concentrations + [NaCl (g l−1)/MgCl2 . 6H2O (g l−1)]: 0/0, 0/0.50, 2.50/0.38, 5.00/0.75, 7.50/1.13, 10.00/1.50, 12.50/1.88, 15.00/2.25, 17.50/2.63 and 20.00/3.00. The isolate + had an absolute requirement for NaCl and grew best with between 10 and 20 g NaCl l−1; the upper limit for growth was not further determined. No growth was observed in media without added NaCl, in contrast to + Sulfurimonas denitrificans DSM 1251T, which grew equally well without NaCl and at all NaCl concentrations tested (Table 1). +

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To identify the electron donors sustaining chemoautotrophic growth of isolate GD1T, ABW medium containing 5 mM nitrate was supplemented with sulfite (1 mM), sulfide (10 µM, 20 µM, 100 µM) or elemental sulfur + (1 mM). Hydrogen utilization was assessed by bubbling ABW+NS with forming gas (N2/H2, 95 : 5) for several hours prior to inoculation and cultivation. Strain GD1T was able to use all of the tested electron donors as an energy source for growth although growth was inhibited by sulfide + concentrations >20 µM (Grote et al., 2012). This observation is in accordance with in situ activities of chemoautotrophic micro-organisms in pelagic Gotland Deep redox zones, where dark CO2 fixation rates are significantly reduced at environmental sulfide concentrations >20 µM (Jost et al., 2010). As electron acceptors, nitrate (100 µM, 2 mM, 5 mM, 10 mM), nitrite (600 µM, 2 mM) (Grote et al., 2012), manganese(IV) oxide (200 µM), manganese(III) acetate dihydrate (2.4 mM), iron(III) chloride hexahydrate (5 mM), fumarate + (100 µM) and oxygen (4 % saturation, approx. 12 µmol O2 l−1) were tested in ABW containing 5 mM thiosulfate. For the oxygen experiment, the oxygen content in fully oxygenated ABW+thiosulfate + was measured with an optode (POF-PSt3; PreSens) and the appropriate amount of oxygen was then mixed with anoxic ABW+thiosulfate + to achieve the desired amount of saturation. However, only nitrate and nitrite served as electron acceptors during growth + of the bacterium. +

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Although the manganese and iron concentrations tested may have been too high and thereby suppressed cell growth, previous + thiosulfate/manganese stimulation experiments with Baltic Sea water samples containing lower metal concentrations similarly + failed to reveal active manganese-reducing species of the genus Sulfurimonas (Labrenz et al., 2005). Sulfurimonas autotrophica is likewise unable to reduce ferrihydrite (Inagaki et al., 2003), which further supports the lack of direct participation of strain GD1T in the Mn/Fe-shuttle (Neretin et al., 2003) of Baltic pelagic redox zones. It also cannot be excluded that strain GD1T is able to grow in medium with an oxygen concentration below 4 %, given that the genome of this bacterium includes a gene + encoding a putative cbb3-type cytochrome c oxidase with the potential to mediate aerobic respiration (Grote et al., 2012). If aerobic respiration could occur at very low oxygen concentrations, it was beyond the scope of our experimental design. + The oxygen sensitivity of strain GD1T was examined in detail, using ABW+NS with oxygen saturations of 0.5, 3, 5, 10, 20, 30, 40 and 50 %. Compared to oxygen-free + conditions, oxygen concentrations ≥20 % reduced or inhibited the growth of this strain whereas oxygen concentration ≤10 % + had no such effect (Grote et al., 2012). Thus, the oxygen tolerance of strain GD1T is similar to that of aerobic Sulfurimonas autotrophica OK10T (Table 1). Based on our current knowledge, we consider strain GD1T to be an aerotolerant representative of the genus Sulfurimonas. +

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Chemolithoautotrophic growth was directly confirmed in ABW+NS containing 14C-bicarbonate followed by a combination of fluorescence in situ hybridization and microautoradiography (MICRO-CARD-FISH) (Grote et al., 2012). As electron donor (in ABW+5 mM KNO3) alone or as electron donor and sole carbon source (in NaHCO3-free ABW+5 mM KNO3) the following compounds were tested: (a) glucose (0.1 mM), (b) a mixture of lactate, malate, fumarate, succinate, glycerine + and glucose (abbreviated as mix 4) (100 µM), (c) yeast extract (0.01 mg l−1), (d) pyruvate (100 µM), (e) acetate (100 µM), (f) fumarate (100 µM), (g) alcohol mix (butanol, ethanol, methanol, propanol; + 100 µM) (Grote et al., 2012) and (h) an amino acid mix (0.1 mM) consisting of (g l−1): β-alanine 0.466, l-arginine 0.872, l-asparagine 0.750, l-cysteine 0.606, l-glutamine 0.730, l-glutamic acid 0.736, glycine 0.376, isoleucine 0.656, l-leucine 0.656, l-methionine 0.746, l-phenylalanine 0.826, l-serine 0.526, l-threonine 0.596, l-valine 0.586, l-proline 0.576, l-tryptophan 1.022, l-histidine 0.776, l-lysine 0.822, l-tyrosine 0.906 and l-asparagine 0.666. +

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In the presence of 2 mM NaHCO3, the growth of isolate GD1T was promoted with formate, acetate, yeast extract, pyruvate and the amino acid mix as electron donors. However, maximal cell + numbers were usually more than a magnitude less than those reached with thiosulfate/nitrate-containing medium, as shown in + Fig. 2(a) for pyruvate, which was also used in radiotracer experiments aimed at confirming the capability of strain GD1T to use organics as electron donor. In those experiments, CO2 production was measured following the addition of 16 kBq [2-14C]pyruvate (specific activity 0.6 GBq mmol−1) to cultures grown solely on pyruvate or on thiosulfate/pyruvate. After 24 h or 72 h of incubation, CO2 was degassed by the acidification of cell-free medium and trapped in ethanolamine. In nitrate/pyruvate medium, the growth + of strain GD1T was accompanied by elevated CO2 production (Fig. 2b). The simultaneous incorporation of [2-14C]pyruvate into GD1T cells was much less pronounced, but its uptake and contribution to biomass production were clearly determined + in thiosulfate/nitrate/pyruvate medium, where total cell numbers were also higher than those reached in thiosulfate/nitrate + medium (Fig. 2a), but the difference was not statistically significant (unpublished data). By contrast, in NaHCO3-free medium strain GD1T was unable to use any of the organics offered simultaneously as electron donor and carbon source (Fig. 2a). It has long been recognized that even heterotrophic bacteria may require CO2 for growth (Dehority, 1971), e.g. in anaplerotic reactions (Alonso-Sáez et al., 2010). Similar findings were reported for Nitrobacter hamburgensis, which requires atmospheric CO2 or the addition of sodium carbonate for mixotrophic growth (in the presence of NO2) on d-lactate (Starkenburg et al., 2008). The authors of that study suggested that CO2 fixation served as a reductant sink necessary to maintain cellular redox balance. The physiological background for the growth + of isolate GD1T on organics is thus far unclear. In other species of the genus Sulfurimonas, organic substance utilization is variable. For example, in a similar experiment Sulfurimonas denitrificans was able to use formate, fumarate, yeast extract and the alcohol mix as electron donors (Table 1). The ability of this bacterium to oxidize formate was proposed in a genome analysis, which identified a formate dehydrogenase + complex (Sievert et al., 2008). Homologues of genes involved in glycolysis and proteolysis are also present in the genome of strain GD1T (Grote et al., 2012), whereas Sulfurimonas autotrophica (Inagaki et al., 2003; but tested without bicarbonate supplementation to the organic medium) and Sulfurimonas paralvinellae (Takai et al., 2006) are unable to grow on organic compounds. In conclusion, although under specific circumstances organic compounds enhance + the growth of some species of the genus Sulfurimonas, members of this genus characteristically grow chemolithoautotrophically. +

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Fig. 2.
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Fig. 2. + +

Impact of pyruvate on the growth of isolate GD1T. Error bars indicate the standard deviation of three independent replicates for each assay. (a) Growth on media with different + substrate combinations: 1, NaHCO3, S2O32-, NO3; 2, NaHCO3, S2O32-, NO3, pyruvate; 3, NaHCO3, pyruvate; 4, pyruvate; 5, ABW without further supplements. The relative enrichment factor describes the increase of cell + numbers after 7 days of incubation compared to the initial cell numbers after inoculation at day 0 (6.1×105 ml−1). (b) 14CO2 production and [14C]pyruvate incorporation after 24 h and 72 h of incubation. Media: 1, NaHCO3, S2O32-, NO3, [14C]pyruvate; 2, NaHCO3, NO3, [14C]pyruvate. P, pyruvate incorporation; CO2, CO2 production. +

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Total fatty acids and phospholipid-derived fatty acids were extracted as described by Sasser (1990) and Boschker (2004), respectively, and analysed by gas chromatography with a flame-ionization detector on a non-polar HP-5ms column (Agilent). + The dominant cellular fatty acid of strain GD1T was 16 : 1ω7c, with 3-OH 14 : 0, 16 : 0, 16 : 1ω5c+t, and 18 : 1ω7c detected in lower amounts. This fatty acid profile is comparable to those of other species of the genus Sulfurimonas but most similar to that of Sulfurimonas denitrificans (Table 1). This may reflect the fact that strain GD1T and Sulfurimonas denitrificans were cultivated on ABW+NS under identical conditions. However, a high percentage of C16 : 0 and one or both of the monounsaturated + C16 and C18 fatty acids has also been described in other members of the class Epsilonproteobacteria, such as Nitratifractor salsuginis and Sulfurovum lithotrophicum (Suzuki et al., 2005). Accordingly, this combination may be a general characteristic of these epsilonproteobacteria. +

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The DNA guanine-plus-cytosine (G+C) content of strain GD1T was determined to be 33.6 mol%, as calculated by analysis of the whole genome (Grote et al., 2012). +

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To establish the closest relatives of strain GD1T based on 16S rRNA sequencing, preliminary searches in the EMBL Data Library were performed with the program fasta (Pearson & Lipman, 1988). Closely related sequences were retrieved from GenBank and aligned and analysed with the newly determined sequence, within + the program arb (Ludwig et al., 2004). Sequences for analysis were reduced to unambiguously alignable positions using group-specific filters. For phylogenetic + analyses, three different trees were calculated using the neighbour-joining, parsimony and maximum-likelihood (Phyml) algorithms + based on nearly full-length 16S rRNA sequences (approx. 1400 bp). For neighbour-joining, the Jukes–Cantor-correction was applied. + Shorter sequences were gradually inserted into the reconstructed tree without changing the topology. Sequence searches of + the EMBL database (latest: 2013-05-14) revealed that our isolate is related to the epsilon class of the phylum Proteobacteria (data not shown). In a pairwise analysis, it displayed highest (93.7–94.2 %) 16S rRNA gene sequence similarity to species + of the genus Sulfurimonas and to the Baltic ‘Uncultured Helicobacteraceae G138eps1/GD17’ subgroup (95.7 %). Lower levels of relatedness (≤91 % sequence similarity) were determined for the other examined + species belonging to the epsilon class of the phylum Proteobacteria. +

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An unrooted tree reconstructed using the neighbour-joining method showed the phylogenetic position of the novel bacterium, + strain GD1T, amongst the members of the class Epsilonproteobacteria (Fig. 3). Treeing analyses confirmed it to be a member of the genus Sulfurimonas, forming a stable cluster with the ‘Uncultured Helicobacteraceae G138eps1/GD17’ subgroup. This cluster is specifically detected by the SUL90 16S rRNA gene probe, originally developed to + be 100 % complementary to the G138eps1/GD17 target site (Grote et al., 2007). +

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Fig. 3.
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Fig. 3. + +

Unrooted tree showing phylogenetic relationships of isolate GD1T and closely related members of the class Epsilonproteobacteria. The tree was reconstructed using the neighbour-joining method and was based on a comparison of approximately 1400 nt. Solid + squares indicate that the corresponding nodes (or groups) were recovered in neighbour-joining, maximum-parsimony and maximum-likelihood + methods. Branching points supported by two algorithms are marked by an open square. The following strains were used as an + outgroup (not shown): Antarctobacter heliothermus EL-219T, Sagittula stellata E-37T, Roseovarius tolerans EL-172T, Roseovarius nubinhibens ISMT and Roseovarius mucosus DFL-24T. Bar, 1 substitution per 10 nt. +

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There is no precise correlation between percentage 16S rRNA sequence divergence and species delineation, but it is generally + recognized that divergence values ≥3 % are significant (Stackebrandt & Goebel, 1994). However, it is pertinent to note that the phylogenetic separateness of strain GD1T is strongly supported by phenotypic considerations. For instance, this novel bacterium is distinguishable from other species + of the genus Sulfurimonas by its psychrotolerance and energy metabolism (Table 1). Additional characteristics useful in differentiating Baltic isolate GD1T from related organisms are shown in Table 1. Based on phenotypic and genetic evidence, we propose the classification of strain GD1T as a representative of a novel species of the genus Sulfurimonas: Sulfurimonas gotlandica sp. nov. +

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Emended description of the genus Sulfurimonas

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The description is based on that by Takai et al. (2006). Cells are Gram-negative and morphologically variable. Straight to slightly short rods, elongated rods and spiral in different + growth phases and under different growth conditions. Psychrotolerant to mesophilic and aerotolerant to facultatively anaerobic. + Do not always require NaCl for growth. Optimal growth occurs chemolithoautotrophically with sulfide, S0, thiosulfate and H2 as electron donors, and with nitrate, nitrite and O2 as electron acceptors, using CO2 as a carbon source. Supplementation of bicarbonate can enable growth on organic substances, but yields much lower cell numbers + compared to growth on reduced sulfur or hydrogen. Potential ecological niches are deep-sea hydrothermal environments and benthic + or pelagic marine to brackish transition zones from oxic to anoxic/sulfidic environments. The type species is Sulfurimonas autotrophica (Inagaki et al. 2003). +

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Description of Sulfurimonas gotlandica sp. nov. +

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Sulfurimonas gotlandica (got.lan′di.ca. N.L. fem. adj. gotlandica pertaining to the Gotland Deep, the basin in the central Baltic Sea from which the organism was first isolated). +

+ +

Gram-negative, slightly curved or spirilla-shaped cells. Motile by one polar flagellum or two flagella at opposite poles. + Cells exhibit a positive chemotactic response to nitrate. Cell sizes are 0.66±0.083×2.1±0.54 µm. Cells have a tendency to + aggregate at older stages. Psychro- and aerotolerant. The temperature range for growth is 4–20 °C. Optimal growth occurs at + 15 °C and pH 6.7–8.0. The cells have an absolute requirement for NaCl. Chemolithoautotrophic growth occurs with H2, HS, S0 and thiosulfate. Supplementation of bicarbonate can enable growth on formate, acetate, yeast extract, pyruvate or amino acid + mix, but yields much lower cell numbers compared with growth on reduced sulfur or hydrogen. Sulfide concentrations of more + than 20 µM inhibit, but up to 10 % of oxygen in the medium does not influence growth. Dominant cellular fatty acid is 16 : 1ω7c, with 14 : 0, 16 : 0, 16 : 1ω5c+t, and 18 : 1ω7c present in smaller amounts. +

+ +

The type strain is GD1T ( = DSM 19862T = JCM 16533T), isolated from water of a pelagic redox zone of the central Baltic Sea. The G+C content of the type strain is 33.6 mol%. +

+ +
+
+
+ +

Acknowledgements

+ +

We thank the captain and the crew of the RV Alkor. We gratefully acknowledge the skilful technical assistance of Bärbel Buuk. Michael Hannig helped during the isolation procedure. + We thank the Deutsche Forschungsgemeinschaft (DFG) for grants LA 1466/4-1 and LA 1466/4-2. +

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References

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+ + \ No newline at end of file diff --git a/examples/ijsem-quickscrape/ijsem-mounce-OLD-scraper/http_ijs.sgmjournals.org_content_63_Pt_11_4141.full/fulltext.pdf b/examples/ijsem-quickscrape/ijsem-mounce-OLD-scraper/http_ijs.sgmjournals.org_content_63_Pt_11_4141.full/fulltext.pdf new file mode 100644 index 00000000..07da41b7 Binary files /dev/null and b/examples/ijsem-quickscrape/ijsem-mounce-OLD-scraper/http_ijs.sgmjournals.org_content_63_Pt_11_4141.full/fulltext.pdf differ diff --git a/examples/ijsem-quickscrape/ijsem-mounce-OLD-scraper/http_ijs.sgmjournals.org_content_63_Pt_11_4141.full/results.json b/examples/ijsem-quickscrape/ijsem-mounce-OLD-scraper/http_ijs.sgmjournals.org_content_63_Pt_11_4141.full/results.json new file mode 100644 index 00000000..50ce3e4f --- /dev/null +++ b/examples/ijsem-quickscrape/ijsem-mounce-OLD-scraper/http_ijs.sgmjournals.org_content_63_Pt_11_4141.full/results.json @@ -0,0 +1,96 @@ +{ + "publisher": { + "value": [ + "Society for General Microbiology" + ] + }, + "journal": { + "value": [ + "International Journal of Systematic and Evolutionary\n Microbiology" + ] + }, + "title": { + "value": [ + "Sulfurimonas gotlandica sp. nov., a chemoautotrophic and psychrotolerant epsilonproteobacterium isolated from a pelagic redoxcline, and an emended description of the genus Sulfurimonas" + ] + }, + "authors": { + "value": [ + "Matthias Labrenz", + "Jana Grote", + "Kerstin Mammitzsch", + "Henricus T. S. Boschker", + "Michael Laue", + "Günter Jost", + "Sabine Glaubitz", + "Klaus Jürgens" + ] + }, + "date": { + "value": [ + "11/01/2013" + ] + }, + "doi": { + "value": [ + "10.1099/ijs.0.048827-0" + ] + }, + "volume": { + "value": [ + "63" + ] + }, + "issue": { + "value": [ + "Pt 11" + ] + }, + "firstpage": { + "value": [ + "4141" + ] + }, + "abstract": { + "value": [ + "\n \n  Next Section\n Abstract\n \n A psychro- and aerotolerant bacterium was isolated from the sulfidic water of a pelagic redox zone of the central Baltic Sea.\n The slightly curved rod- or spiral-shaped cells were motile by one polar flagellum or two bipolar flagella. Growth was chemolithoautotrophic,\n with nitrate or nitrite as electron acceptor and either a variety of sulfur species of different oxidation states or hydrogen\n as electron donor. Although the bacterium was able to utilize organic substances such as acetate, pyruvate, peptone and yeast\n extract for growth, these compounds yielded considerably lower cell numbers than obtained with reduced sulfur or hydrogen;\n in addition, bicarbonate supplementation was necessary. The cells also had an absolute requirement for NaCl. Optimal growth\n occurred at 15 °C and at pH 6.6–8.0. The predominant fatty acid of this organism was 16 : 1ω7c, with 3-OH 14 : 0, 16 : 0, 16 : 1ω5c+t and 18 : 1ω7c present in smaller amounts. The DNA G+C content was 33.6 mol%. As determined in 16S rRNA gene sequence phylogeny analysis,\n the isolate belongs to the genus Sulfurimonas, within the class Epsilonproteobacteria, with 93.7 to 94.2 % similarity to the other species of the genus Sulfurimonas, Sulfurimonas autotrophica, Sulfurimonas paralvinellae and Sulfurimonas denitrificans. However, the distinct physiological and genotypic differences from these previously described taxa support the description\n of a novel species, Sulfurimonas gotlandica sp. nov. The type strain is GD1T ( = DSM 19862T = JCM 16533T). Our results also justify an emended description of the genus Sulfurimonas.\n \n \n " + ] + }, + "fulltext_html": { + "value": [ + "http://ijs.sgmjournals.org/content/63/Pt_11/4141.full" + ] + }, + "fulltext_pdf": { + "value": [ + "http://ijs.sgmjournals.org/content/63/Pt_11/4141.full.pdf" + ] + }, + "supplementary_material": { + "value": [] + }, + "figure": { + "value": [ + "http://ijs.sgmjournals.org/content/63/Pt_11/4141/F1.small.gif", + "http://ijs.sgmjournals.org/content/63/Pt_11/4141/F2.small.gif", + "http://ijs.sgmjournals.org/content/63/Pt_11/4141/F3.small.gif" + ] + }, + "figure_caption": { + "value": [ + "Fig. 1. \n \n Cell morphology of spirilla-shaped cells of strain GD1T cultivated on ABW+NS medium. (a) Fluorescence microscopy of 4′,6′-diamidino-2-phenylindol (DAPI) stained cells. (b) Transmission\n electron microscopy of a bacterium with one flagellum and (c) of a bacterium with two flagella (indicated by arrows), both\n negatively stained with phosphotungstic acid.\n \n \n \n ", + "Fig. 2. \n \n Impact of pyruvate on the growth of isolate GD1T. Error bars indicate the standard deviation of three independent replicates for each assay. (a) Growth on media with different\n substrate combinations: 1, NaHCO3, S2O32-, NO3−; 2, NaHCO3, S2O32-, NO3−, pyruvate; 3, NaHCO3, pyruvate; 4, pyruvate; 5, ABW without further supplements. The relative enrichment factor describes the increase of cell\n numbers after 7 days of incubation compared to the initial cell numbers after inoculation at day 0 (6.1×105 ml−1). (b) 14CO2 production and [14C]pyruvate incorporation after 24 h and 72 h of incubation. Media: 1, NaHCO3, S2O32-, NO3−, [14C]pyruvate; 2, NaHCO3, NO3−, [14C]pyruvate. P, pyruvate incorporation; CO2, CO2 production.\n \n \n \n ", + "Fig. 3. \n \n Unrooted tree showing phylogenetic relationships of isolate GD1T and closely related members of the class Epsilonproteobacteria. The tree was reconstructed using the neighbour-joining method and was based on a comparison of approximately 1400 nt. Solid\n squares indicate that the corresponding nodes (or groups) were recovered in neighbour-joining, maximum-parsimony and maximum-likelihood\n methods. Branching points supported by two algorithms are marked by an open square. The following strains were used as an\n outgroup (not shown): Antarctobacter heliothermus EL-219T, Sagittula stellata E-37T, Roseovarius tolerans EL-172T, Roseovarius nubinhibens ISMT and Roseovarius mucosus DFL-24T. Bar, 1 substitution per 10 nt.\n \n \n \n " + ] + }, + "license": { + "value": [ + "\n This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted\n use, distribution, and reproduction in any medium, provided the original work is properly cited.\n \n " + ] + }, + "copyright": { + "value": [ + "Copyright ©\n \t\t2015 International Union of Microbiological Societies\n \t\n " + ] + } +} \ No newline at end of file diff --git a/examples/ijsem-quickscrape/ijsem-mounce-OLD-scraper/http_ijs.sgmjournals.org_content_63_Pt_11_4174.full/DC1 b/examples/ijsem-quickscrape/ijsem-mounce-OLD-scraper/http_ijs.sgmjournals.org_content_63_Pt_11_4174.full/DC1 new file mode 100644 index 00000000..2266e827 --- /dev/null +++ b/examples/ijsem-quickscrape/ijsem-mounce-OLD-scraper/http_ijs.sgmjournals.org_content_63_Pt_11_4174.full/DC1 @@ -0,0 +1,358 @@ + + + + + Supplementary material + + + + + + + + + + + +
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Arthrobacter siccitolerans sp. nov., a highly desiccation-tolerant, xeroprotectant-producing strain isolated from dry soil +

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+

Arthrobacter siccitolerans sp. nov., a highly desiccation-tolerant, xeroprotectant-producing strain isolated from dry soil +

+
+
    + + +
  1. M. Manzanera
  2. +
+
    +
  1. Institute for Water Research, and Department of Microbiology, University of Granada, Granada, Spain
    +
  2. +
+
    +
  1. Correspondence
    M. Manzanera manzanera{at}ugr.es
  2. +
+
+
+ +

Abstract

+ +

A novel desiccation-tolerant, xeroprotectant-producing bacterium, designated strain 4J27T, was isolated from a Nerium oleander rhizosphere subjected to seasonal drought in Granada, Spain. Phylogenetic analysis based on 16S rRNA gene sequencing placed + the isolate within the genus Arthrobacter, its closest relative being Arthrobacter phenanthrenivorans Shep3 DSM 18606T, with which it showed 99.23 % 16S rRNA gene sequence similarity. DNA–DNA hybridization measurements showed less than 25 % + relatedness between strain 4J27T and Arthrobacter phenanthrenivorans DSM 18606T. The DNA base composition of strain 4J27T was 65.3 mol%. The main fatty acids were anteiso C15 : 0, anteiso C17 : 0, C16 : 0 and iso C16 : 0 and the major menaquinone was MK-9 (H2). The peptidoglycan type was A3α with an l-Lys–l-Ser–l-Thr–l-Ala interpeptide bridge. The bacterium tested positive for catalase activity and negative for oxidase activity. Phylogenetic, + chemotaxonomic and phenotypic analyses indicated that the desiccation-tolerant strain 4J27T represents a novel species within the genus Arthrobacter, for which the name Arthrobacter siccitolerans is proposed. The type strain is 4J27T ( = CECT 8257T = LMG 27359T). +

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    A supplementary figure and a supplementary table are available with the online version of this paper.

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+

This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted + use, distribution, and reproduction in any medium, provided the original work is properly cited. +

+
+

The genus Arthrobacter, first defined by Conn & Dimmick (1947), belongs to the class Actinobacteria and includes Gram-stain-positive coryneform bacteria with aerobic metabolism and little or no acid production from glucose. + Species of the genus Arthrobacter contain lysine in the peptidoglycan and have a DNA G+C content ranging from 59 mol% to 66 mol% (Keddie et al., 1986; Jones & Keddie, 1992). These bacteria typically take the shape of rods in younger cultures and cocci in older cultures (Keddie et al., 1986), depending on their growth rate and nutritional conditions (Germida & Cassida, 1980). The transition to this coccoid-like + state has been shown to require manganese (Germida & Cassida, 1980). The small coccoid-like state has been described as being + the most stable form. Due to their pleomorphic and heterogeneous appearance, strains of species of the genus Arthrobacter were originally grouped with the Corynebacteria (Keddie et al., 1986). +

+

In response to changing extracellular osmolarity such as desiccation or increased salinity some micro-organisms accumulate + small organic compounds (Brown, 1976; Arakawa& Timasheff, 1982). These compatible solutes act as protectants, which under laboratory conditions can also stabilize enzymes, DNA, cell membranes + and even whole cells against different kinds of stress, such as freezing, drying and heating (Brown, 1976; Yancey et al., 1982; Knapp et al., 1999; Manzanera et al. 2002, Narváez-Reinaldo et al., 2010, Julca et al., 2012). Our group has previously reported a new method for the isolation of desiccation-tolerant micro-organisms from dry soil + using organic solvents as selective agents (Manzanera et al., 2004a; Narváez-Reinaldo et al., 2010). Strain 4J27T displayed remarkably high tolerance to desiccation and produced excellent xeroprotectants for the dry stabilization of proteins + (lipase enzymes) and whole prokaryotic cells (Escherichia coli MC4100) compared with those when trehalose was used (Manzanera et al., 2004b; Narváez-Reinaldo et al., 2010). Among the 10 different xeroprotectants tested, the best results were observed with S4J27-D (composed of trehalose, glutamine + and glucose), a synthetic mixture derived from strain 4J27T (Narváez-Reinaldo et al., 2010). +

+

Here we describe the morphological, biochemical and phylogenetic characteristics of this desiccation-tolerant strain (4J27T), isolated from dry soil and with a remarkable potential for the dry stabilization of some biomaterials. On the basis of + the phylogenetic analysis of the 16S rRNA gene sequence together with physiological, chemotaxonomic and DNA–DNA hybridization + analyses we demonstrate that strain 4J27T represents a novel species of the genus Arthrobacter. +

+

Strain 4J27T was grown at 30 °C (±3 °C) in tryptone soya agar (TSA) plates and in tryptone soya broth (TSB) or M9 minimal medium (M6030; + Sigma). Arthrobacter phenanthrenivorans DSM 18606T was included in the study as reference. +

+

Strain 4J27T, the object of this study, had already been assigned to the genus Arthrobacter by partial analysis of its 16S rRNA gene sequence (GenBank accession number GU815139; Narváez-Reinaldo et al., 2010), which was compared with those in the EzTaxon-e server (http://eztaxon-e.ezbiocloud.net/, Kim et al., 2012). The nearly complete sequence of the 16S rRNA gene of strain 4J27T (approximately 1500 bp) was aligned with the sequences of closely related species of the genus Arthrobacter by using the clustal x 2 program (Larkin et al., 2007). A phylogenetic tree was inferred using the neighbour-joining (Saitou & Nei, 1987) and maximum-likelihood (Guindon & Gascuel, 2003) methods with the mega 5.0 software package (Tamura et al., 2011). Bootstrap analysis was based on 1000 resamplings (Felsenstein, 1985). The distances were calculated according to Kimura’s two-parameter model (Kimura, 1980). The resulting neighbour-joining tree obtained with Kimura’s two-parameter model is shown in Fig. 1 and the maximum-likelihood tree is shown in Fig. S1, available in IJSEM Online. +

+
+
Fig. 1.
View larger version: + +
+
+
Fig. 1. + +

Neighbour-joining phylogenetic tree based on 16S rRNA sequence comparisons of strain 4J27T and its 24 closest relatives. Streptomyces albus AS 4.164T was used as the outgroup. The numbers at bifurcations indicate how many times each species coincided in this position as + percentages and only values > 50% are shown. Bar, 0.01 changes per nucleotide position. +

+ +
+
+
+

The sequence corresponding to the 16S rRNA gene of strain 4J27T showed 99.23 % similarity to that of Arthrobacter phenanthrenivorans DSM 18606T. Phylogenetic analysis showed that strain 4J27T clearly belongs to the genus Arthrobacter, and its closest relative was Arthrobacter phenanthrenivorans DSM 18606T. +

+

DNA–DNA hybridization was carried out at the Deutsche Sammlung von Mikroorganismen und Zellkulturen (DSMZ; Braunschweig, Germany). + Cells of Artrhobacter phenanthrenivorans DSM 18606T and strain 4J27T were disrupted by using a French pressure cell (Thermo Spectronic) and the DNA of each strain in the crude lysate were purified + by chromatography on hydroxyapatite as described by Cashion et al. (1977). DNA–DNA hybridization was conducted as described by De Ley et al. (1970) with the modifications described by Huss et al. (1983) using a model Cary 100 Bio UV/VIS-spectrophotometer equipped with a Peltier-thermostat-regulated 6×6 multicell charger and + a temperature controller with in situ temperature probe (Varian). DNA–DNA hybridization of strain 4J27T with Arthrobacter phenanthrenivorans DSM 18606T resulted in a DNA–DNA relatedness value of 22.3 % (22.1 %), the value in parentheses being the result of measurements in + duplicate. On the basis of DNA–DNA reciprocal hybridization, strain 4J27T did not belong to the species Arthrobacter phenanthrenivorans according to the recommendations of a threshold value of 70 % DNA–DNA relatedness for the definition of bacterial species + (Wayne et al., 1987). Therefore strain 4J27T probably represents a novel species of the genus Arthrobacter. +

+

The G+C (mol%) content of the genomic DNA of strain 4J27T was analysed at the DSMZ. The dG and dT ratio was calculated according to the method of Mesbah et al. (1989). Species of the genus Arthrobacter have previously been described as Gram-stain-positive actinobacteria with high GC content (Keddie et al., 1986; Jones & Keddie ,1992), which typically have a DNA G+C content in the range of 59–66 mol% (Keddie et al., 1986). The DNA G+C content of strain 4J27T was 65.3 mol%, which was within the range shown by all members of the genus Arthrobacter and considered to have a high GC content (Keddie et al., 1986). +

+

Chemotaxonomic analyses were carried out by the Identification Service of the DSMZ. Peptidoglycans were isolated from strain + 4J27T and their structures analysed (Schleifer & Kandler, 1972). After derivatization according to the method of MacKenzie (1987) the approximate molar amino-acid ratio was determined by gas chromatography. Free amino groups within the peptidoglycan + were detected by labelling with 1-fluoro-2,4-dinitrobenzene (Schleifer, 1985). The peptidoglycan of strain 4J27T was composed of Ala, Ser, Thr, Glu and Lys at a molar ratio of 2.8 : 1.2 : 1.0 : 1.0 : 1.5. Two-dimensional TLC of the partial + hydrolysate (4 M HCl, 100 °C, 45 min) of the peptidoglycan revealed the presence of the peptides l-Ala–d-Glu, l-Lys–d-Ala, l-Lys–l-Ser, l-Lys–l-Ser–l-Thr, d-Ala–l-Lys–l-Ser–l-Thr, l-Ser–l-Thr and l-Ala–d-Ala. On the basis of these results it was concluded that strain 4J27T contains a type A3α peptidoglycan (Schleifer & Kandler, 1972) with an l-Lys–l-Ser–l-Thr–l-Ala interpeptide bridge (A11.23 DSMZ-Catalogue of strains, 7th edition, 2001), which is found in the more closely related + members of the genus Arthrobacter, according to the neighbour-joining phylogenetic tree, such as Arthrobacter chlorophenolicus, Arthrobacter oxydans, Arthrobacter polychromogenes, Arthrobacter sulfonivorans, Arthrobacter equi, Arthrobacter niigatensis, Arthrobacter phenanthrenivorans, Arthrobacter defluvii, Arthrobacter roseus and Arthrobacter scleromae (Borodina et al., 2002; Kodama et al., 1992; Westerberg et al., 2000; Reddy et al., 2002; Huang et al., 2005; Kim et al., 2008; Ding et al., 2009; Yassin et al., 2011). Strains containing a type A3α peptidoglycan make up a rather uniform group, although they do show a considerable number + of different types of interpeptide bridge. Most of these strains belong to the genus Arthrobacter and are distinguished by strictly aerobic growth and a complete life cycle (Conn & Dimmick, 1947; Schleifer & Kandler, 1972). +

+

Fatty-acid methyl esters were obtained from 40 mg cells of strain 4J27T scraped from Petri dishes by saponification, methylation and extraction using the methods of Miller (1982) and Kuykendall et al., (1988) with minor modifications. The fatty-acid methyl-ester mixtures were separated using the Sherlock Microbial Identification + System (MIS) (MIDI, Microbial ID). The main cellular fatty acids of the highly desiccation-tolerant strain 4J27T were, from highest to lowest, anteiso-C15 : 0, 41.20 %; anteiso-C17 : 0, 30.86 %; C16 : 0, 10.21 %; iso-C16 : 0, 6.61 %; iso-C15 : 0, 4.40 %; C18 : 0, 2.38 %; iso-C17 : 0, 1.79 %; iso-C14 : 0, 0.83 %; C14 : 0, 0.75 %; anteiso-C19 : 0, 0.61 % and iso-C18 : 0, 0.36 %. The fatty-acid composition of strain 4J27T was consistent with that of the genus Arthrobacter, with branched-chain fatty acid, antesio-pentadecanoic acid (anteiso-C15 : 0) predominating (Westerberg et al., 2000). +

+

Respiratory quinones were analysed as described by Tindall (1990a; b), using TLC and UV mass spectroscopy, and found menaquinone to be the sole quinone component. Analyses of the electron-transport + system (isoprenoid quinones) for strain 4J27T resulted in detection of MK9 (II-H2) 68 %; MK9 21 % and MK8 (II-H2) 11 %. +

+

To analyse the whole cell sugars of strain 4J27T, cells were hydrolysed in 0.5 M H2SO4 for 2 h at 100 °C. Sulfuric acid was removed by 20 % N,N-dioctylmethylamine in chloroform according to the method of Whiton et al. (1985). Sugars in the hydrolysate were analysed by TLC on cellulose plates according to the methods of Staneck & Roberts (1974). The whole-cell sugars of the isolated strain were galactose, glucose, mannose, ribose and rhamnose. +

+

Mobility was tested by stab-inoculating mannitol-mobility semi-solid agar (413782; Ultimed). This semi-solid agar medium enabled + us to analyse the nitrate reductase activity (capacity to reduce nitrate to nitrite) and catabolism of mannitol by using Griess–Ilosvay + A and B reagents. Oxidase activity was determined using 1 % w/v N,N,N′,N′-tetramethyl-p-phenylenediamine and catalase activity was determined by the production of bubbles from 3 % v/v. H2O2. Cells of strain 4J27T were identified as catalase-positive, oxidase-negative, nitrate reductase-negative and mannitol-positive. Arthrobacter phenanthrenivorans DSM 18606T. +

+

To characterize the growth of strain 4J27T at different temperatures, pH values and salinities, cultures were incubated at 150 r.p.m. in Luria–Bertani (LB) rich medium + (L3152; Sigma). Cell growth was monitored at different temperatures (5, 10, 15, 20, 25, 30, 35, 40, 45 and 50 °C), pH (3, + 5, 7, 9, 12 and 13) and NaCl concentrations (0, 0.2, 0.4, 0.6, 0.8, 1 and 1.2 M) by measuring the OD600 in triplicate at 0, 12 and 24 h using a UV-160A spectrophotometer (Shimadzu). Strain 4J27T grew best at 30 °C in LB medium. It was able to grow at 37 °C and 15 °C but not at 40 °C or 10 °C. The pH range for growth + was between 5 and 9 with optimum growth at pH 7. Strain 4J27T grew in NaCl concentrations ranging from 0 to 0.8 M but grew best at 0.2 M. This differed clearly from the most closely related + species, Arthrobacter phenanthrenivorans DSM 18606T, which was able to grow at 4 °C but not at pH 5. +

+

The following API kits were used for testing, API Coryne, API 20NE and API 20E (bioMérieux,). Each test was interpreted according + to the manufacturer’s instructions. Biolog tests were performed to investigate which compounds the strains in question could + use for respiration. A GP2 MicroPlate (Cat. No 1014; Biolog), containing 95 different carbon compounds, was used to test for + substrate oxidation. The chemistry of these plates is based on tetrazolium reduction, in response to metabolic processes such + as fermentation and oxidation. Tetrazolium reduction produced formazan in a variety of colours from dark blue to deep red + to orange, depending upon the original tetrazolium salt used as the substrate for the reaction. MicroPlates were inoculated + and interpreted according to the manufacturer’s instructions. The results were recorded after 12 h based on A585. Antibiotic susceptibility testing was performed using the disc-diffusion method in which the antibiotic diffuses away from + the disc in two dimensions, forming a concentration gradient that inhibits the growth of bacteria and causes an inhibition + zone (Piddock, 1990). The results were interpreted according to the criteria established for staphylococci in 1997 by the + National Committee for Clinical Laboratory Standards (2000). At the concentrations assayed, the inhibition zone caused by + streptomycin was 157 mm, rifampicin 347 mm, chloramphenicol 340 mm, kanamycin 150 mm and tetracycline 157 mm and thus it could + be concluded that strain 4J27T was susceptible to all the antibiotics tested. The phenotypic differences between strain 4J27T and closely related species are summarized in Table 1 and the physiological differences between strain 4J27T and its closest relative species Arthrobacter phenanthrenivorans DSM 18606T are summarized in Table S1. +

+
+
+
View this table: +
+
+
Table 1. + Differential characteristics between strain 4J27T and the type strains of the most closely related species of the genus Arthrobacter + +

Strains: 1, 4J27T; 2, Arthrobacter phenanthrenivorans DSM 18606T; 3, Arthrobacter niigatensis IAM 15382T; 4, Arthrobacter. defluvii DSM 18782T; 5. Arthrobacter equi DSM 23395T; 6. Arthrobacter chlorophenolicus DSM 12829T; 7. Arthrobacter polychromogenes DSM 20136T; 8. Arthrobacter oxydans DSM 20119T; 9. Arthrobacter scleromae JCM 12642T. Data of the reference species were taken from Kallimanis et al. (2009), Ding et al. (2009), Kim et al., (2008), Yassin et al. (2011), Westerberg et al. (2000), Schippers-Lammertse et al. (2009), Sguros (1955), Huang et al. (2005) and the present study. +, Positive; −, negative; nd, not determined; CFA, cellular fatty acid. +

+ +
+
+
+

The degree of tolerance to desiccation shown by strain 4J27T was compared with that of the previously described desiccation-tolerant bacteria Acinetobacter calcoaceticus PADD68 (Narváez-Reinaldo et al., 2010), the desiccation-sensitive strain Pseudomonas putida KT2440 (Manzanera et al., 2002) and the closely related Arthrobacter phenanthrenivorans DSM 18606T. A colony of a pure culture grown for 48 h of each strain, containing 107 to 109 cells, was suspended in 1 ml M9 minimal medium. Aliquots (100 µl) were placed on sterile Petri dishes and dried under a current + of sterile air for 24 h. The cells were then suspended in 1 ml sterile saline buffer, and serial dilutions of the cell suspension + were plated on TSA plates before and after drying. All such procedures were conducted at room temperature. The survival rate + was calculated in terms of c.f.u. ml−1 after drying compared with c.f.u. ml−1 before drying, expressed as a percentage. The assays were performed in triplicate accordingly to the protocol of Manzanera et al., 2002. Strain 4J27T showed the highest values of desiccation tolerance (31.58 %±6.9 %), which were significantly different from those of the + positive control, Acinetobacter calcoaceticus PADD68 (3.23 %±0.2 %) and more so from the closely related strain, Arthrobacter phenanthrenivorans DSM 18606T (1.5 %±0.41 %). As expected, the desiccation tolerance of the negative control, P. putida KT2440T, was below detectable levels. Therefore the closely related species Arthrobacter phenanthrenivorans DSM 18606T is considered to be desiccation-sensitive, due to its low degree of desiccation tolerance, in contrast to the novel strain, + which is considered to be a desiccation-tolerant strain. +

+

On the basis of phylogenetic analysis of its 16S rRNA gene sequence, together with physiological, chemotaxonomic and DNA–DNA + hybridization analyses, strain 4J27T is considered to represent a novel species of the genus Arthrobacter, for which the name Arthrobacter siccitolerans is proposed. +

+
+ + + +
+ +

Description of Arthrobactersiccitolerans sp. nov. +

+ +

Arthrobacter siccitolerans (sic.ci.to′le.rans. L. adj. siccus dry, L. part. adj. tolerans tolerating; N.L. part. adj. siccitolerans dry-tolerating). +

+ +

Cells are non-motile, non-spore-forming, Gram-positive, aerobic and rod-to-coccus-shaped. Colonies on TSA are convex, circular, + cream, opaque and usually 1–2 mm in diameter within 2 days at 30 °C. Catalase-positive, oxidase-negative and nitrate-reductase-negative + (no capacity to reduce nitrate to nitrite). Grows at temperatures from 15 to 35 °C, pH 5–9 and with 0–0.8 M NaCl in LB medium. + The peptidoglycan type is A3α (Schleifer & Kandler, 1972), with an l-Lys–l-Ser–l-Thr–l-Ala interpeptide bridge. The major cellular fatty acids are anteiso C15 : 0, anteiso C17 : 0, C16 : 0 and iso C16 : 0. The major menaquinone is MK9-(II-H2). The whole-cell sugars of the strain are galactose, glucose, mannose, ribose and rhamnose. It reduces nitrites to nitrogen. + Indole and acetoin (Voges–Proskauer) production are positive. According to the results from the API CORYNE, API 20NE and API + 20E strips, the following enzyme activities are detected: pirazinamidase, β-glucuronidase, β-galactosidase, α-glucosidase, + β-glucosidase (aesculin), β-galactosidase (p-nitrophenyl-β-d-galactopyranosidase). Assimilation of glucose, arabinose, mannose, mannitol, N-acetyl-glucosamine, maltose, potassium gluconate, + malate, trisodium citrate, inositol, sorbitol, rhamnose, sucrose, melibiose, amygdalin and arabinose are positive. The following + enzyme activities are not present: β-galactosidase (o-nitro-phenyl-β-d-galactopyranoside), arginine dihydrolase, lysine decarboxylase, ornithine decarboxylase, urease, tryptophan desaminase, gelatinase, + pyrrolidonyl arylamidase, alkaline phosphatase and N-acetyl-β-glucosaminidase. Production of H2S is negative and does not use citrate. In the Biolog GP2 MicroPlates the following substrates were used for respiration: + dextrin, inulin, l-arabinose, N-acetyl-d-glucosamine, N-acetyl-d-mannosamine, d-arbutin, cellobiose, d-fructose, d-galactose, d-galacturonic acid, α-d-glucose, gentiobiose, lactamide, l-lactic acid, lactulose, maltose, maltotriose, d-mannitol, d-mannose, melezitose, melibiose, 3-methyl glucose, α-methyl d-mannoside, palatinose, d-psicose, d-rafinose, l-rhamnose, d-ribose, salicin, d-sorbitol, sucrose, trehalose, turanose, xylitol, d-xylose, acetic acid, α-hydroxybutyric acid, β-hydroxybutyric acid, p-hydroxyphenylacetic acid, α-ketovaleric acid, l-malic acid, pyruvic acid, l-alaninamide, l-alanyl glycine, glycyl-l-glutamic acid, putrescine, glycerol, adenosine, 2′-deoxy adenosine, inosine, thymidine, uridine, thymidine-5′ monophosphate, + glucose-1-phosphate and d-l-α-glycerol phosphate. The following compounds were not used for respiration: α-cyclodextrin, β-cyclodextrin, glycogen, mannan, + Tween 40, Tween 80, amygdalin, d-arabitol, d-fructose, l-fucose, d-gluconic acid, myo-inositol, α-d-lactose, α-methyl-d-galactoside, β-methyl-d-galactoside, α-methyl-d-glucoside, β-methyl-d-glucoside, palatinose, propionic acid, l-alanine, l-asparagine, l-glutamic acid, l-pyroglutamic acid and l-serine, sedoheptulose, stachyose, d-tagatose, γ-hydroxybutyric acid, α-ketoglutaric acid, d-lactic acid methyl ester, d-malic acid, methyl pyruvate, mono-methyl succinate, succinamic acid, succinic acid, d-alanine, N-acetyl-l-glutamic acid, 2,3-butanediol, adenosine-5′-monophosphate, uridine-5′-monophosphate, fructose-6-phosphate and glucose-6-phosphate. + Susceptible to all the antibiotics tested: streptomycin, rifampicin, chloramphenicol, kanamycin and tetracycline. +

+ +

The type strain, 4J27T ( = CECT 8257T = LMG 27359T), was isolated from a Nerium oleander rhizosphere subjected to seasonal drought in Granada, Spain. The DNA G+C content of strain 4J27T is 65.3 mol%. +

+ +
+
+
+ +

Acknowledgements

+ +

We thank María de la Encarnación Olimpia Velázquez Pérez of the University of Salamanca for her useful discussions. This research + was funded by the Spanish Ministry of Science and Innovation under the aegis of research project P07-RNM-02588 and the Andalusian + Regional Government under the aegis of research project CTM2009-09270. M. M. received a Ramón y Cajal research grant from + the Ministry of Science and Innovation as well as support from European Regional Development Funds (EU). The authors also + thank J. Trout of the University of Granada Scientific Translation Service for revising their English text. +

+ +
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Prevotella jejuni sp. nov., isolated from the small intestine of a child with coeliac disease +

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+ +
+

Prevotella jejuni sp. nov., isolated from the small intestine of a child with coeliac disease +

+
+
    + + + + + + + + + +
  1. Sten Hammarström1
  2. +
+
    +
  1. 1Department of Clinical Microbiology, Immunology, Umeå University, SE-90187 Umeå, Sweden +
    +
  2. +
  3. 2CCUG – Culture Collection University of Gothenburg, Department of Clinical Bacteriology, Sahlgrenska University Hospital, + SE-41345 Göteborg, Sweden +
    +
  4. +
  5. 3Department of Infectious Diseases, Sahlgrenska Academy of the University of Gothenburg, SE-40530 Göteborg, Sweden +
    +
  6. +
  7. 4Department of Molecular Biology, Umeå University, SE-90187 Umeå, Sweden +
    +
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  9. 5Department of Clinical Sciences, Pediatrics, Umeå University, SE-90187 Umeå, Sweden +
    +
  10. +
+
    +
  1. Correspondence
    Maria E. Hedberg maria.hedberg{at}climi.umu.se Sten Hammarström sten.hammarstrom{at}climi.umu.se
  2. +
+
+
+ +

Abstract

+ +

Five obligately anaerobic, Gram-stain-negative, saccharolytic and proteolytic, non-spore-forming bacilli (strains CD3 : 27, + CD3 : 28T, CD3 : 33, CD3 : 32 and CD3 : 34) are described. All five strains were isolated from the small intestine of a female child + with coeliac disease. Cells of the five strains were short rods or coccoid cells with longer filamentous forms seen sporadically. + The organisms produced acetic acid and succinic acid as major metabolic end products. Phylogenetic analysis based on comparative + 16S rRNA gene sequence analysis revealed close relationships between CD3 : 27, CD3 : 28T and CD3 : 33, between CD3 : 32 and Prevotella histicola CCUG 55407T, and between CD3 : 34 and Prevotella melaninogenica CCUG 4944BT. Strains CD3 : 27, CD3 : 28T and CD3 : 33 were clearly different from all recognized species within the genus Prevotella and related most closely to but distinct from P. melaninogenica. Based on 16S rRNA, RNA polymerase β-subunit (rpoB) and 60 kDa chaperonin protein subunit (cpn60) gene sequencing, and phenotypic, chemical and biochemical properties, strains CD3 : 27, CD3 : 28T and CD3 : 33 are considered to represent a novel species within the genus Prevotella, for which the name Prevotella jejuni sp. nov. is proposed. Strain CD3 : 28T ( = CCUG 60371T = DSM 26989T) is the type strain of the proposed novel species. All five strains were able to form homologous aggregates, in which tube-like + structures were connecting individual bacteria cells. The five strains were able to bind to human intestinal carcinoma cell + lines at 37 °C. +

+ +
+
+ +
    +
  • +

    The GenBank/EMBL/DDBJ accession number for the 16S rRNA gene sequence of strain CD3 : 28T is JQ778983. +

    +
  • +
  • +

    One supplementary figure and three supplementary tables are available with the online version of this paper.

    +
  • +
+
+
+

This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted + use, distribution, and reproduction in any medium, provided the original work is properly cited. +

+
+

Coeliac disease (CD) is an immune-mediated enteropathy with a multifactorial aetiology. Early childhood infections have been + shown to be a risk factor for CD (Myléus et al., 2012). Also, the jejunal microbiota is considered to play a role in the pathogenesis of CD (Olivares et al., 2013). This is supported by epidemiological data from Sweden showing that childhood CD has features of an infectious disease with + a peak incidence between 1985 and 1996 in children younger than 2 years of age, a period referred to as ‘the Swedish CD epidemic’ + (Ivarsson et al., 2000). A similar increase in incidence was seen later, during 2001–2004 (Olsson et al., 2008; Namatovu, F. et al., unpublished data). After both peaks, incidence returned to normal. We have shown that CD patients born during ‘the Swedish + CD epidemic’ had a significant enrichment of mucosa-associated rod-shaped bacteria of the order Clostridiales, and genera Prevotella and Actinomyces in the jejunum (Forsberg et al., 2004; Ou et al., 2009). Recently, we characterized a novel species of a new genus, Lachnoanaerobaculum umeaense, that had been isolated from the jejunal mucosa of a child born during ‘the Swedish CD epidemic’ (Hedberg et al., 2012). We assumed that this bacterium corresponded to the prevalent bacteria of the order Clostridiales we had previously reported (Ou et al., 2009). To further characterize the microbiota of the small intestine of children with CD born during the first epidemic we have + now studied isolates of the genus Prevotella. +

+

At the time of writing, 48 species of the genus Prevotella have been described (Euzéby, 2013). The vast majority were isolated from humans, with the oral cavity being the main source (Dewhirst et al., 2010). However, Prevotella species have also been isolated from faeces (Hayashi et al., 2007), the female genital tract, skin and respiratory tract, and from the rumen and hindgut of non-human mammals (Alauzet et al., 2010). Until now, no species of the genus Prevotella from the human small intestine had been characterized. Species of the genus Prevotella are generally considered to be non-pathogenic or opportunistic pathogens. However, they have been shown to be involved in + serious infections, and virulence factors such as haemolysins, haemagglutinins, fimbrial adhesins, proteases and phospholipases + have been demonstrated in strains of several species (Alauzet et al., 2010). +

+

This study describes the phenotypic and genotypic characterization of strains CD3 : 27, CD3 : 28T and CD3 : 33, representing isolates of a novel species, CD3 : 32, probably a strain of Prevotella histicola (Downes et al., 2008), and CD3 : 34, probably a strain of Prevotella melaninogenica (Shah & Collins, 1990). Additionally, we describe the phylogenetic relationships between the five isolates and other members of the genus Prevotella, based upon comparative 16S rRNA gene sequence analyses. Moreover, the five isolates have been subjected to whole genome + sequencing (WGS) using 454 pyro-sequencing technology (GS Junior; Roche Diagnostics), and the sequences of the genes encoding + chaperonin 60 (cpn60) and DNA-directed RNA polymerase subunit-β (rpoB) have also been compared. +

+

The five strains were isolated from a biopsy of the proximal small intestine of a girl with CD, born in 1995, i.e. during + the 1985–1996 Swedish CD epidemic. She was on a gluten-free diet when the biopsy was taken at the Department of Paediatrics, + Umeå University Hospital, Umeå, in 2007. Informed consent was obtained from her parents. The study was approved by the local + Research Ethics Committee of the Faculty of Medicine (Um dnr: 96-304 and 04-156). The biopsy was weighed, homogenized and + serially diluted ten-fold in Fastidious Anaerobe Broth medium (Lab M) and immediately plated onto selective and non-selective + agar media. All Prevotella strains were primarily isolated on blood agar plates [Columbia Blood Agar Base (Acumedia), supplemented with 5 % defibrinated + horse blood]. P. histicola CCUG 55407T, P. melaninogenica CCUG 4944BT and Prevotella stercorea CCUG 55595T were obtained from the Culture Collection University of Gothenburg (CCUG; http://www.ccug.se). +

+

Pure cultures of the five strains grew well on blood agar plates and in Brucella broth (BBL) supplemented with vitamin K (1 + µg ml−1) and haemin (5 µg ml−1) under an anaerobic atmosphere (10 % H2, 5 % CO2 in N2) at 37 °C. +

+

Colony morphologies and the results of presumptive identification tests by diagnostic discs (Jousimies-Somer et al., 2002) were examined on blood agar plates after incubation for 3–5 days. None of the five strains grew in the presence of oxygen + and they should be considered strictly anaerobic. Growth was improved and pigmentation and haemolytic activity increased if + the atmosphere contained 10 % CO2 and 5 % H2 as compared with standard conditions. The appearance of the colonies of the five strains differed: isolate CD3 : 27 had circular, + raised, convex, weakly to moderately pigmented and strongly haemolytic colonies; CD3 : 28T and CD3 : 33 had circular, convex, weakly pigmented, weakly haemolytic colonies; CD3 : 32 had circular, slightly raised and + brown-reddish pigmented colonies with a shiny ‘wet’ appearance. Moreover, the centres of the colonies of CD3 : 32 were darker + than the outer part. Colonies of CD3 : 34 were similar to those of CD3 : 28T and CD3 : 33, but with a surface appearing ‘drier’ (Fig. S1 available in IJSEM Online). +

+

Light microscopy after Gram staining, dark field microscopy, scanning electron microscopy (SEM) and transmission electron + microscopy (TEM) were used to investigate cell morphologies. Cells of the five strains were rod-shaped, 0.7×0.8–2 µm in size, + occurring most often as short rods or as coccoid cells, with longer filamentous forms (>10 µm) seen sporadically. All five + strains were Gram-stain-negative and lacked spores. SEM revealed that all five strains, particularly if grown on agar medium, + as opposed to in liquid culture, formed large aggregates of bacterial cells connected to each other by multiple, thin, strait, + rod-shaped structures (Fig. 1a–c). Cells of strains CD3 : 27, CD3 : 28T and CD3 : 33 showed a similar degree of interconnectivity. Outer membrane vesicles were frequently observed. Analysis of + thin sections of the aggregates by TEM suggested that the rod-shaped structures were hollow, characterized as tubes connecting + cells to each other (Fig. 1d). +

+
+
Fig. 1.
View larger version: + +
+
+
Fig. 1. + +

Scanning electron micrographs showing surface structures of cells of P. jejuni, strains CD3 : 27 (a) and CD3 : 28T (b) and P. histicola strain CD3 : 32 (c). (d) Transmission electron micrograph of a cell of strain P. jejuni CD3 : 33; arrows indicate cross-section of the tube-like structures shown in (a)–(c) and arrowheads indicate outer membrane + vesicles. Bars, 0.2 µm (a, b, d); 1 µm (c). +

+ +
+
+
+

All five strains exhibited a temperature optimum for growth at 37 °C. The optimal pH for growth was 6–7 with reduced growth + at pH 5.5 and 7.5. Motility was not observed. All five strains were haemolytic and produced NH3. Growth on glucose as the sole carbon source yielded acetic acid, succinic acid and small amounts of isovaleric acid for + strains CD3 : 27, CD3 : 32 and CD3 : 34, and acetic acid and succinic acid for strains CD3 : 28T and CD3 : 33. +

+

The nucleotide sequences of the 16S rRNA genes of strains CD3 : 27, CD3 : 28T, CD3 : 33, CD3 : 32 and CD3 : 34 were determined by primer walking, covering the gene, and by cloning and sequencing of PCR + amplification fragments also covering the gene (Hedberg et al., 2012). These sequences were subsequently confirmed by genomic sequencing, allowing us to establish that there was only one copy + of the 16S rRNA gene per genome. Other 16S rRNA gene sequences for comparative analyses were retrieved from the NCBI database + (Sayers et al., 2010). Strains CD3 : 27, CD3 : 28T and CD3 : 33 shared >99.8 % 16S rRNA gene sequence similarity with each other and 98.1–98.3 % similarity with P. melaninogenica CCUG 4944BT (AY323525), P. histicola CCUG 55407T (AB547685), N 12-20 (EU126662), CD3 : 34 and CD3 : 32, and 97.3–97.7 % similarity with Prevotella veroralis CCUG 15422T (AY836507). Strain CD3 : 32 was related most closely to P. histicola (AB547685 and EU126662) showing >99.6 % sequence similarity. Strain CD3 : 34 showed 99.8 % sequence similarity to P. melaninogenica (AY323525 and NC-014370). Fig. 2 shows the phylogenetic tree reconstructed using the maximum composite likelihood model based on 16S rRNA gene sequences. + Strains CD3 : 27, CD3 : 28T and CD3 : 33 formed a separate group distinct from recognized species of the genus Prevotella while strain CD3 : 32 clustered with P. histicola and strain CD3 : 34 with P. melaninogenica. +

+
+
Fig. 2.
View larger version: + +
+
+
Fig. 2. + +

Phylogenetic tree based on 16S rRNA gene sequences showing the relationships between strains CD3 : 27, CD3 : 28T and CD3 : 33 and related species. The 16S rRNA gene sequence of Porphyromonas gingivalis ATCC 33277T served as an outgroup. Bar, 0.02 substitutions per nucleotide position. +

+ +
+
+
+

Genomic DNA–DNA reassociation analysis was carried out using the hybridization protocols described by Urdiain et al. (2008). Strain CD3 : 28T hybridized to a high level (95–112 %) with strains CD3 : 27 and CD3 : 33, confirming that these three strains belong to the + same species. The level of hybridization between strain CD3 : 28T and P. histicola CCUG 55407T, P. melaninogenica CCUG 4944BT, Prevotella scopos CCUG 57945T and P. veroralis CCUG 15422T was below 43 %. Levels of hybridization between strain CD3 : 28T and strains CD3 : 32 and CD3 : 34 were 49 and 59 % respectively. The level of hybridization between P. melaninogenica CCUG 4944BT and strain CD3 : 34 was high (104 %), while that between strain CD3 : 34 and strain CD3 : 28T was 51 %. P. melaninogenica hybridized to a low level (30 %) with P. histicola CCUG 55407T. The coefficient of variation was less than 5.5 %. As the genomic DNA hybridization values were well below 70 % for strains + CD3 : 27, CD3 : 28T and CD3 : 33 on the one hand and strains CD3 : 32 or CD3 : 34 on the other, the strains can be considered to represent different + species (Stackebrandt & Goebel, 1994). +

+

To shed further light on whether CD3 : 27, CD3 : 28T and CD3 : 33 should be considered as strains of the same novel species we compared the nucleotide sequences of the rpoB and cpn60 genes (Alauzet et al., 2010; Sakamoto & Ohkuma, 2010). Similarly, we compared strain CD3 : 32 with P. histicola and strain CD3 : 34 with P. melaninogenica. The rpoB and cpn60 (3810 and 1626 nt respectively) gene sequences were 100.0 % identical between strains CD3 : 27, CD3 : 28T and CD3 : 33. Sequence similarity between CD3 : 32 and P. histicola F0411 was 99.3 % for rpoB and 98.7 % for cpn60. Strain CD3 : 34 and P. melaninogenica CCUG 4944BT shared 98.3 % rpoB gene sequence similarity and 97.7 % cpn60 gene sequence similarity. +

+

The sizes of the genomes and the DNA G+C contents of the five strains were determined from WGS data (Table 1). Strains CD3 : 28T and CD3 : 33 had almost the same genome size, 3.81×106 and 3.80×106 bp, respectively, while CD3 : 27 had a size of 3.68×106 bp. The genome of strain CD3 : 32 had a size of 3.20×106 bp, larger than that of the closely related P. histicola F0411 (2.99×106 bp). The genome size of strain CD3 : 34 was 3.27×106 bp, about 102×103 bp larger than that of P. melaninogenica CCUG 4944BT. The DNA G+C contents of the strains grouped together, in that strains CD3 : 27, CD3 : 28T and CD3 : 33 had values of 41.7–41.8 mol%, CD3 : 32 and P. histicola F0411 had values of 41.1 and 41.2 mol%, respectively, and CD3 : 34 and P. melaninogenica CCUG 4944BT values of 40.7 and 41.0 mol%, respectively. +

+
+
+
View this table: +
+
+
Table 1. + Genome size and DNA G+C content of Prevotella jejuni sp. nov., and the other two Prevotella isolates from human small intestine compared with P. histicola and P. melaninogenica + +
+
+
+

Cellular fatty acid (CFA) methyl ester analyses were performed using a standardized protocol (http://www.ccug.se/pages/CFA_method_2008 and as detailed by Hedberg et al., 2012). Strains were grown anaerobically (10 % H2, 5 % CO2 in N2), using chocolate agar as culture medium at 37 °C, and harvested after 48 h. CFAs were extracted and saponified by mild alkaline + methanolysis and released fatty acids were methylated. CFAs were identified and quantified by GC (Hewlett Packard HP 5890). + Retention times of CFA peaks were converted to equivalent chain-length values and the relative amount (w/w) of each fatty + acid was expressed as a percentage of the total fatty acids in the profile of the respective strain (Table S1). The major + CFAs detected in strains CD3 : 27, CD3 : 28T, CD3 : 33, CD3 : 32 and CD3 : 34 were iso-C15 : 0, anteiso-C15 : 0, C16 : 0, C18 : 2ω6,9c/anteiso-C18 : 0 and iso-C17 : 0 3-OH. These five CFAs occurred in approximately the same relative amounts in the five strains with anteiso-C15 : 0 accounting for 38.5–42.5 % of the total CFAs. Interestingly, strains CD3 : 27, CD3 : 28T, CD3 : 33, CD3 : 32 and CD3 : 34 were more similar to each other than were CD3 : 32 to P. histicola CCUG 55407T or CD3 : 34 to P. melaninogenica CCUG 4944BT (Table S1). The similarities between the five jejunal isolates, although representing three different species, are perhaps + a reflection of the fact that they were isolated from the same organ of one individual. +

+

Analysis of metabolic and biochemical characteristics (rapid ID 32A, API 20A and APIZYM; bioMérieux) showed that the five + strains are saccharolytic and proteolytic (Table S2). Strains CD3 : 27, CD3 : 28T and CD3 : 33 demonstrated an almost identical pattern of biochemical characteristics. The only difference observed was that + strain CD3 : 33 had α-galactosidase activity, while the other two strains did not. CD3 : 32 and P. histicola CCUG 55407T showed an identical pattern of biochemical characteristics and the same was true for the comparison between CD3 : 34 and + P. melaninogenica CCUG 4944BT. Sialidase activity was detected using 2′-(4-methylumbelliferyl)α-d-N-acetylneuraminic acid as substrate (Moncla & Braham, 1989). All strains produced sialidase except CD3 : 32 and P. histicola CCUG 55407T. +

+

By disc diffusion it was shown that all five isolates and P. histicola CCUG 55407T were resistant to vancomycin (5 µg) but susceptible to kanamycin (1 mg), colistin (10 µg) (Oxoid) and bile (1000 µg) (Oxgall + tablets; Rosco Diagnostica), whereas P. melaninogenica CCUG 4944BT was resistant to vancomycin and kanamycin but susceptible to colistin and bile. P. stercorea CCUG 55595T was resistant to kanamycin and colistin but susceptible to bile and unexpectedly also susceptible to vancomycin (Jousimies-Somer et al., 2002). Because the bacteria were isolated from the small intestine adjacent to the bile duct, susceptibility to bile was investigated + further using an agar dilution technique. A stock solution containing 320 mM synthetic bile acids (taurocholate, 134.4 mM; + taurochenodeoxycholate, 83.2 mM; glycocholate, 70.4 mM; glycochenodeoxycholate, 32 mM) yielded final concentrations of 0.125–16 + mM bile acids in the assay. Interestingly, growth and haemolytic activity of all five jejunum isolates were stimulated at + low concentrations of bile (0.5–1.5 mM) compared with medium without bile, while growth was inhibited at higher bile concentrations + (2–8 mM). +

+

Susceptibility to penicillin G was tested using MIC Evaluator Strips (Oxoid). Strains CD3 : 32, CD3 : 34 and P. histicola CCUG 55407T were resistant (MIC >32 µg ml−1). The other strains were susceptible to penicillin G, with MICs ranging from 0.003 to 0.015 µg ml−1. According to the nitrocefin disc test (Remel), strains CD3 : 32, CD3 : 34 and P. histicola CCUG 55407T produce β-lactamase. WGS revealed the presence of the cfxA β-lactamase gene in strains CD3 : 32 and CD3 : 34, but not in P. histicola F0411, the only other P. histicola isolate that has been sequenced so far, or P. melaninogenica CCUG 4944BT. Strains CD3 : 32 and CD3 : 34 shared 100 and 99 % cfxA gene sequence similarity with Prevotella marshii CCUG 50419T, respectively. +

+

The abilities of strains CD3 : 27, CD3 : 28T, CD3 : 33, CD3 : 32, CD3 : 34, P. histicola CCUG 55407T and P. melaninogenica CCUG 4944BT to agglutinate human erythrocytes was investigated. Strains CD3 : 27, CD3 : 28T and CD3 : 33 strongly agglutinated human O and AB erythrocytes; there was no difference in the strength of the agglutination + reaction between the three strains, nor was there a difference in their ability to agglutinate AB versus O red blood cells. + Strain CD3 : 34 showed a weak agglutination reaction while strains CD3 : 32, P. histicola CCUG 55407T and P. melaninogenica CCUG 4944BT were negative. The finding that some strains of P. melaninogenica are able to weakly agglutinate red blood cells (Haraldsson et al., 2005) is in agreement with our results. +

+

To confirm that the five jejunal isolates were able to bind to intestinal epithelial cells, binding of PKH-2 fluorescence + dye-labelled bacteria to PKH-26 fluorescence dye-labelled intestinal epithelial cells was studied by flow cytometry (Hara-Kaonga & Pistole, 2007). Binding was evaluated after incubation at 37 °C and at 4 °C for 1 h. The cell lines were T84 (colon carcinoma), LS174T + (colon carcinoma), HT29 (small intestine-like carcinoma) and Int407 (fetal small intestine epithelial cells), all obtained + from the American Type Culture Collection (Rockville, MD). At 37 °C, all five isolates were able to bind to the four cell + lines with two exceptions: strains CD3 : 27 and CD3 : 28T did not bind to LS174T cells (Table S3). +

+

We conclude that strains CD3 : 27, CD3 : 28T and CD3 : 33 represent a novel species of the genus Prevotella, for which the name Prevotella jejuni sp. nov. is proposed, that CD3 : 32 is a strain of P. histicola and that CD3 : 34 is a strain of P. melaninogenica. The latter two jejunal isolates have larger genome sizes than the corresponding previously characterized strains. All five + jejunal isolates are able to bind to human intestinal epithelial cells. +

+
+ + + +
+ +

Description of Prevotella jejuni sp. nov. +

+ +

Prevotella jejuni (je.ju′ni. L. gen. n. jejuni of or from the jejunum, referring to the isolation of the type strain from the jejunum). +

+ +

The description is based on three strains isolated from the human jejunum. Cells are obligately anaerobic, non-motile, Gram-stain-negative + bacilli (0.7×0.8–2 µm). After 3–5 days of incubation on blood agar plates, colonies are 1–2 mm in diameter, circular, convex, + weakly to moderately pigmented and weakly to strongly haemolytic. The optimum conditions for growth are 37 °C and pH 6–7. + Acetic acid, succinic acid and small amounts of isovaleric acid are produced from glucose. NH3 is produced. Cells are saccharolytic and proteolytic and are able to ferment glucose, lactose, maltose, mannose, raffinose + and sucrose, but not arabinose, cellobiose, mannitol, melezitose, rhamnose, salicin, sorbitol, trehalose or xylose. Positive + for activity of β-galactosidase, β-galactosidase-6-phosphate, α-glucosidase, N-acetyl-β-glucosaminidase, α-fucosidase, sialidase, acid phosphatase, alkaline phosphatase, naphthol-AS-BI-phosphate, arginine + arylamidase, alanine arylamidase, leucine arylamidase and leucyl glycine arylamidase (Table S2). Gelatin is hydrolysed but + aesculin is not. Cells agglutinate human AB and O erythrocytes and bind to several human intestinal cell lines. The predominant + CFA is anteiso-C15 : 0, accounting for 42.5 % of the total CFA profile. +

+ +

The type strain is CD3 : 28T ( = CCUG 60371T = DSM 26989T), which was isolated from a biopsy of the small intestine of a child with CD. Strains CD3 : 27 ( = CCUG 60308) and CD3 : 33 + ( = CCUG 60311) are additional strains of this species. The DNA G+C content of the type strain is 41.7 mol%. +

+ +
+
+
+ +

Acknowledgements

+ +

Funding was provided by: the Swedish Research Council, Natural Sciences and Engineering Sciences (no. 2010-5669); the TORNADO-project + within the 7th framework program theme (grant agreement no. 222720-2); the Fund for Biotechnology-oriented Basic Science at + Umeå University; the County of Västerbotten; and the Medical Faculty of Umeå University. The funders had no role in study + design, data collection and analysis, decision to publish, or preparation of the manuscript. +

+ +
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References

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+ + \ No newline at end of file diff --git a/examples/ijsem-quickscrape/ijsem-mounce-OLD-scraper/http_ijs.sgmjournals.org_content_63_Pt_11_4218.full/fulltext.pdf b/examples/ijsem-quickscrape/ijsem-mounce-OLD-scraper/http_ijs.sgmjournals.org_content_63_Pt_11_4218.full/fulltext.pdf new file mode 100644 index 00000000..8cc6e132 Binary files /dev/null and b/examples/ijsem-quickscrape/ijsem-mounce-OLD-scraper/http_ijs.sgmjournals.org_content_63_Pt_11_4218.full/fulltext.pdf differ diff --git a/examples/ijsem-quickscrape/ijsem-mounce-OLD-scraper/http_ijs.sgmjournals.org_content_63_Pt_11_4218.full/results.json b/examples/ijsem-quickscrape/ijsem-mounce-OLD-scraper/http_ijs.sgmjournals.org_content_63_Pt_11_4218.full/results.json new file mode 100644 index 00000000..69f8f5c2 --- /dev/null +++ b/examples/ijsem-quickscrape/ijsem-mounce-OLD-scraper/http_ijs.sgmjournals.org_content_63_Pt_11_4218.full/results.json @@ -0,0 +1,98 @@ +{ + "publisher": { + "value": [ + "Society for General Microbiology" + ] + }, + "journal": { + "value": [ + "International Journal of Systematic and Evolutionary\n Microbiology" + ] + }, + "title": { + "value": [ + "Prevotella jejuni sp. nov., isolated from the small intestine of a child with coeliac disease" + ] + }, + "authors": { + "value": [ + "Maria E. Hedberg", + "Anne Israelsson", + "Edward R. B. Moore", + "Liselott Svensson-Stadler", + "Sun Nyunt Wai", + "Grzegorz Pietz", + "Olof Sandström", + "Olle Hernell", + "Marie-Louise Hammarström", + "Sten Hammarström" + ] + }, + "date": { + "value": [ + "11/01/2013" + ] + }, + "doi": { + "value": [ + "10.1099/ijs.0.052647-0" + ] + }, + "volume": { + "value": [ + "63" + ] + }, + "issue": { + "value": [ + "Pt 11" + ] + }, + "firstpage": { + "value": [ + "4218" + ] + }, + "abstract": { + "value": [ + "\n \n  Next Section\n Abstract\n \n Five obligately anaerobic, Gram-stain-negative, saccharolytic and proteolytic, non-spore-forming bacilli (strains CD3 : 27,\n CD3 : 28T, CD3 : 33, CD3 : 32 and CD3 : 34) are described. All five strains were isolated from the small intestine of a female child\n with coeliac disease. Cells of the five strains were short rods or coccoid cells with longer filamentous forms seen sporadically.\n The organisms produced acetic acid and succinic acid as major metabolic end products. Phylogenetic analysis based on comparative\n 16S rRNA gene sequence analysis revealed close relationships between CD3 : 27, CD3 : 28T and CD3 : 33, between CD3 : 32 and Prevotella histicola CCUG 55407T, and between CD3 : 34 and Prevotella melaninogenica CCUG 4944BT. Strains CD3 : 27, CD3 : 28T and CD3 : 33 were clearly different from all recognized species within the genus Prevotella and related most closely to but distinct from P. melaninogenica. Based on 16S rRNA, RNA polymerase β-subunit (rpoB) and 60 kDa chaperonin protein subunit (cpn60) gene sequencing, and phenotypic, chemical and biochemical properties, strains CD3 : 27, CD3 : 28T and CD3 : 33 are considered to represent a novel species within the genus Prevotella, for which the name Prevotella jejuni sp. nov. is proposed. Strain CD3 : 28T ( = CCUG 60371T = DSM 26989T) is the type strain of the proposed novel species. All five strains were able to form homologous aggregates, in which tube-like\n structures were connecting individual bacteria cells. The five strains were able to bind to human intestinal carcinoma cell\n lines at 37 °C.\n \n \n " + ] + }, + "fulltext_html": { + "value": [ + "http://ijs.sgmjournals.org/content/63/Pt_11/4218.full" + ] + }, + "fulltext_pdf": { + "value": [ + "http://ijs.sgmjournals.org/content/63/Pt_11/4218.full.pdf" + ] + }, + "supplementary_material": { + "value": [ + "http://ijs.sgmjournals.org/content/63/Pt_11/4218/suppl/DC1" + ] + }, + "figure": { + "value": [ + "http://ijs.sgmjournals.org/content/63/Pt_11/4218/F1.small.gif", + "http://ijs.sgmjournals.org/content/63/Pt_11/4218/F2.small.gif" + ] + }, + "figure_caption": { + "value": [ + "Fig. 1. \n \n Scanning electron micrographs showing surface structures of cells of P. jejuni, strains CD3 : 27 (a) and CD3 : 28T (b) and P. histicola strain CD3 : 32 (c). (d) Transmission electron micrograph of a cell of strain P. jejuni CD3 : 33; arrows indicate cross-section of the tube-like structures shown in (a)–(c) and arrowheads indicate outer membrane\n vesicles. Bars, 0.2 µm (a, b, d); 1 µm (c).\n \n \n \n ", + "Fig. 2. \n \n Phylogenetic tree based on 16S rRNA gene sequences showing the relationships between strains CD3 : 27, CD3 : 28T and CD3 : 33 and related species. The 16S rRNA gene sequence of Porphyromonas gingivalis ATCC 33277T served as an outgroup. Bar, 0.02 substitutions per nucleotide position.\n \n \n \n " + ] + }, + "license": { + "value": [ + "\n This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted\n use, distribution, and reproduction in any medium, provided the original work is properly cited.\n \n " + ] + }, + "copyright": { + "value": [ + "Copyright ©\n \t\t2015 International Union of Microbiological Societies\n \t\n " + ] + } +} \ No newline at end of file diff --git a/examples/ijsem-quickscrape/ijsem-mounce-OLD-scraper/http_ijs.sgmjournals.org_content_63_Pt_11_4340.full/DC1 b/examples/ijsem-quickscrape/ijsem-mounce-OLD-scraper/http_ijs.sgmjournals.org_content_63_Pt_11_4340.full/DC1 new file mode 100644 index 00000000..d45128cb --- /dev/null +++ b/examples/ijsem-quickscrape/ijsem-mounce-OLD-scraper/http_ijs.sgmjournals.org_content_63_Pt_11_4340.full/DC1 @@ -0,0 +1,351 @@ + + + + + Supplementary material + + + + + + + + + + + +
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Molecular and phenotypic analyses reveal the non-identity of the Phaeobacter gallaeciensis type strain deposits CIP 105210T and DSM 17395 +

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Molecular and phenotypic analyses reveal the non-identity of the Phaeobacter gallaeciensis type strain deposits CIP 105210T and DSM 17395 +

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  1. Thorsten Brinkhoff2
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  1. 1Leibniz Institute DSMZ – German Collection of Microorganisms and Cell Cultures, Braunschweig, Germany +
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  3. 2Institute for Chemistry and Biology of the Marine Environment, University of Oldenburg, Oldenburg, Germany +
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  1. Correspondence
    Jörn Petersen joern.petersen{at}dsmz.de
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Abstract

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The marine genus Phaeobacter currently comprises six species, some of which were intensively studied mainly due to their ability to produce secondary + metabolites. The type strain of the type species, Phaeobacter gallaeciensis BS107T, has been deposited at several public culture collections worldwide. Based on differences in plasmid profiles, we detected + that the alleged P. gallaeciensis type strains deposited at the Collection Institute Pasteur (CIP; Paris, France) as CIP 105210 and at the German Collection + of Microorganisms and Cell Cultures (DSMZ; Braunschweig, Germany) as DSM 17395 are not identical. To determine the identity + of these strains, we conducted DNA–DNA hybridization, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry + (MALDI-TOF), 16S rRNA gene and internal transcribed spacer (ITS) sequence analyses, as well as physiological experiments. + Based on the detailed 16S rRNA gene reanalysis we showed that strain CIP 105210 most likely corresponds to the original P. gallaeciensis type strain BS107T. In contrast, the Phaeobacter strain DSM 17395 exhibits a much closer affiliation to Phaeobacter inhibens DSM 16374T ( = T5T) and should thus be allocated to this species. The detection of the dissimilarity of strains CIP 105210T and DSM 17395 will influence future comparative studies within the genus Phaeobacter. +

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    These authors contributed equally to this work. +

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    The GenBank/EMBL/DDBJ accession numbers for the 16S rRNA gene sequences of the Phaeobacter strains CIP 105210T, DSM 16374T, DSM 17395 and DSM 24564T are KC176239, KC176240, KC176241 and KC176242, respectively. The GenBank/EMBL/DDBJ accession numbers for the 16S–23S rRNA + gene internal transcribed spacer of the Phaeobacter strains CIP 105210T, DSM 16374T, DSM 17395, DSM 23529T, DSM 23566T, DSM 24564T and DSM 25627T are KC176233, KC176234, KC176235, KC176236, KC176237, KC176238 and KC907729, respectively. +

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    Four supplementary figures and four supplementary tables are available with the online version of this paper.

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+ + +

Introduction

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The genus Phaeobacter, currently comprising the species Phaeobacter gallaeciensis, P. inhibens, P. daeponensis, P. caeruleus, P. arcticus and P. leonis (Gaboyer et al., 2013), belongs to the marine Roseobacter clade. It was established by Martens et al. (2006) after reclassification of Roseobacter gallaeciensis (Ruiz-Ponte et al., 1998) as P. gallaeciensis, which is the type species of the genus, and description of P. inhibens as a new species. During recent years, Phaeobacter strains have received a lot of interest due to the production of various secondary metabolites (e.g. Berger et al., 2011, 2012; Brinkhoff et al., 2004; Bruhn et al., 2007; Geng et al., 2008; Martens et al., 2007; Seyedsayamdost et al., 2011a, b). +

+ +

Recently the genomes of three Phaeobacter strains have been published, P. gallaeciensis DSM 17395, P. gallaeciensis 2.10 (Thole et al., 2012) and P. gallaeciensis ANG1 (Collins & Nyholm, 2011). However, evidence already indicated that strain ANG1 is more similar to P. daeponensis DSM 23529T ( = TF-218T) than to either DSM 17395 or DSM 24588 ( = 2.10) (unpublished results). Strain 2.10 was previously used in competition experiments + of bacterial biofilms on the thalloid green alga Ulva australis (Rao et al., 2005). Various physiological and genetic aspects of P. gallaeciensis DSM 17395 have also been studied, such as the pathway and substrate specificity of the algal metabolite dimethylsulfoniopropionate + (DMSP) catabolism (Dickschat et al., 2010), the compatibility of the plasmids (Petersen, 2011), and the primary metabolism by proteome analyses (Zech et al., 2009). +

+ +

With the description of the species P. gallaeciensis (basonym R. gallaeciensis) in 1998, the type strain BS107T was primarily deposited at the Collection Institute Pasteur (CIP; Paris, France) as CIP 105210 (Ruiz-Ponte et al., 1998). According to the strain history (http://www.straininfo.net/strains/620650), the CIP referred the strain to the Colección Española de Cultivos Tipo (CECT; Burjassot, Spain) and to the American Type + Culture Collection (ATCC; Manassas, USA), which in turn referred it to the Japan Collection of Micro-organisms at the RIKEN + Bioscience Center (Tsikiba, Japan) followed by a transfer to the NITE (National Institute of Technology and Evaluation) Biological + Resource Center (Kisarazu, Japan). At these culture collections the derivatives of strain CIP 105210 were designated CECT + 7277T, ATCC 700781T, JCM 21319T and NBRC 16654T, respectively. The Leibniz Institute DSMZ – German Collection of Microorganisms and Cell Cultures (DSMZ; Braunschweig, Germany) + independently requested P. gallaeciensis BS107T from the laboratory of the original depositor in 2005 and included it as DSM 17395 in the strain collection. Strain DSM 17395 + was subsequently collected by the Laboratorium voor Microbiologie (LMG; Gent, Belgium) and deposited as LMG 24391T. When investigating plasmid profiles of various Phaeobacter strains, we observed differences between the strains CIP 105210 and DSM 17395 even though both were considered identical + with the type strain BS107T. This is critical, as due to the broad scientific interest in the P. gallaeciensis type strain, it was either obtained from the public culture collections or retrieved from other sources several times. For + example, Seyedsayamdost et al. (2011b) allegedly used strain BS107T to investigate the mutualistic or pathogenic symbioses between P. gallaeciensis and the unicellular haptophycean alga Emiliania huxleyi. It was indicated that these authors received the strain BS107T from a collaborating laboratory; hence the biological identity of the strain used is ultimately unclear. +

+ +

In this study, we consequently reassessed the biological identity of these strains. We compared in detail the characteristics + of the strains CIP 105210 and DSM 17395 with those of the description of BS107T given by Ruiz-Ponte et al. (1998) and with those of other closely related Phaeobacter strains, i.e. P. gallaeciensis DSM 24588 ( = 2.10; Thole et al., 2012) and P. inhibens DSM 16374T ( = T5T; Martens et al., 2006). Based on our results, according reclassifications are proposed. +

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Methods

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+ +

Source of bacteria and culturing.

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The Phaeobacter strains DSM 16374T ( = T5T), DSM 17395, DSM 23529T ( = TF-218T), DSM 23566T ( = 20188T), DSM 24564T, DSM 24588 ( = 2.10) and DSM 25627T ( = 306T) as well as Roseobacter litoralis DSM 6996T, Marinovum algicola DSM 10251T and Roseobacter denitrificans DSM 7001T were obtained from the DSMZ. The Phaeobacter strain CIP 105210 was obtained from the CIP. Unless otherwise stated, cells were grown in marine broth 2216 (MB; Difco) or + on MB agar at 28 °C (and at 25 °C in case of P. leonis DSM 25627T). +

+ +
+
+ +

Profiles of the extrachromosomal elements.

+ +

To analyse the plasmid content of the Phaeobacter strains, their high-molecular-mass total genomic DNA was prepared within agarose plugs as previously described and subjected + to pulsed-field gel electrophoresis (PFGE; Pradella et al., 2010). PFGE was performed in a contour-clamped homogeneous electric field (CHEF) system on a CHEF-DR III device (Bio-Rad) with + 1 % or 1.2 % agarose gels and modified 0.5× TBE buffer (45 mM Tris, 45 mM boric acid, 0.1 mM EDTA) at 14 °C. PFGE parameters, + namely pulse time ramps and run times, were varied both to resolve chromosomal and extrachromosomal DNA and to identify different + plasmid conformations (Römling et al., 1996). Two PFGE parameter sets were applied to assess plasmid topology: (i) set A, 1 % (w/v) agarose gel with pulse times of 1 + to 48 s for 24 h at 200 V (6 V cm−1) and (ii) set B, 1 % (w/v) agarose gel with pulse times of 1 to 20 s for 22 h at 200 V (6 V cm−1). At least two PFGE gels were evaluated to determine plasmid sizes. The resulting plasmid profiles were interpreted as described + by Pradella et al. (2010). Conventional unidirectional gel electrophoresis of DNA was in 0.8 % agarose gels and 1× TBE (89 mM Tris, 89 mM boric acid, + 2 mM EDTA) at 10 °C and 70 mA for 8.5 h. The BAC Tracker supercoiled DNA ladder (from 38 to 120 kb; Epicentre) was used to + size plasmids with covalently closed circular (ccc) DNA topology. +

+ +
+
+ +

16S rRNA gene and 16S–23S rRNA gene internal transcribed spacer (ITS) analysis.

+ +

The PCR amplification of 16S rRNA genes from the genomic DNA of the Phaeobacter strains was done as described by Rainey et al. (1996). For the PCR amplification of the ITS region, the primer pair 16S_1401f 5′-GRGCCTTGYACACACCG-3′ (Lane, 1991) and 23S_130r 5′-GGTTBCCCCATTCRG-3′ (Gürtler & Stanisich, 1996) was used. Resulting PCR products were cycle sequenced with the primers mentioned above in ‘Extended Hot Shot’ reactions + as offered by the Seqlab company, Germany. The sequence analysis tool BioEdit 7.0.1 (http://www.mbio.ncsu.edu/BioEdit/bioedit.html) was utilized for 16S rRNA gene and ITS sequence editing. The accession numbers of retrieved 16S rRNA gene sequences from + P. gallaeciensis BS107T (Ruiz-Ponte et al., 1998), P. inhibens T5T (Martens et al., 2006), P. daeponensis TF-218T, P. arcticus 20188T, P. gallaeciensis LSS9 and P. leonis 306T were Y13244, AY177712, NR_044026, NR_043888, GQ906799 and HE661585, respectively. Further 16S rRNA gene or ITS sequences + used in this study were extracted from the genome sequences of Phaeobacter strains DSM 17395 (ABIF01000000), DSM 24588 ( = 2.10; CP002972–CP002975) and ANG1 (AFCF01000000) using the Integrated Microbial + Genomes (IMG) system (http://img.jgi.doe.gov/cgi-bin/w/main.cgi; Markowitz et al., 2012). +

+ +

Sequences were aligned with mafft version 6.850b, using the ‘--genafpair’ option but default settings otherwise (Katoh et al., 2005). Phylogenetic analysis under the maximum-likelihood (ML) criterion (Felsenstein, 1981) was conducted with RAxML version 7.2.8, using its novel rapid bootstrap option combined with the autoMRE bootstrapping criterion + (Pattengale et al., 2010) with subsequent search for the best tree under the GTRMIX approach (Stamatakis et al., 2008). Branch-and-bound search for the best trees under the maximum-parsimony (MP) criterion (Fitch, 1971) was done with paup* version 4.0b10 (Swofford, 2002), treating gaps as missing data and collapsing branches of zero minimum length; 1000 bootstrap replicates were conducted + in the same manner. The resulting best trees were rooted using the midpoint-rooting method (Farris, 1972; Hess & De Moraes Russo, 2007). +

+ +
+
+ +

MALDI-TOF MS protein analysis.

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Whole-cell protein extracts of the Phaeobacter strains CIP 105210, DSM 17395, DSM 24588, DSM 16374T, DSM 23529T, DSM 23566T, DSM 24564T and DSM 25627T were analysed by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) using a Microflex + L20 mass spectrometer (Bruker Daltonics) equipped with a N2 laser. Sample preparation for MALDI-TOF MS protein analysis was carried out according to the ethanol/formic acid extraction + protocol recommended by Bruker Daltonics as described in detail by Tóth et al. (2008). The MALDI-TOF mass spectra were analysed with the BioTyper software (version 3.0; Bruker Daltonics). +

+ +
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+ +

DNA–DNA hybridization (DDH).

+ +

Cells of the Phaeobacter strains CIP 105210, DSM 17395, DSM 16374T and DSM 24588 were disrupted by using a Constant Systems TS 0.75 kW (IUL Instruments) and the DNA in the crude lysate was + purified by chromatography on hydroxyapatite as described by Cashion et al. (1977). DNA–DNA hybridization was carried out as described by De Ley et al. (1970) and modified by Huß et al. (1983) using a model Cary 100 Bio UV/VIS-spectrophotometer equipped with a Peltier-thermostatted 6×6 multi-cell changer and a temperature + controller with in situ temperature probe (Varian). Each strain was measured in two technical replicates and the mean result was taken. +

+ +
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+ +

Growth and hydrolysis experiments.

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To determine the substrate spectrum of the Phaeobacter strains CIP 105210 and DSM 17395, cells were grown in artificial seawater (ASW; solution of Sigma sea salts: S9883) supplemented + with 10 mg caseine hydrolysate l−1 (CAS: 65072-00-6; Merck) to avoid auxotrophy and with different carbon sources at a concentration of 0.1 % each, including + 2-ketoglutarate, acetate, l-arabinose, butyrate, cellobiose, citrate, d-fucose, glucosamine, glycerol, l-leucine, maltose, l-rhamnose, l-serine, d-sorbitol, succinate, sucrose, trehalose, Tween 20, Tween 40 and Tween 80. The tests were performed in the 24-well microtitre-plate + format. In detail, cells were grown on MB agar for 2 days at 28 °C, then harvested with a sterile swab and inoculated in ASW + medium. The cell suspension was thereby adjusted to a turbidity of 80 % transmittance using a turbidimeter (AES Chemunex BLG + 3531). Afterwards, 2 ml of each suspension was pipetted into a 24-well microtitre plate (Greiner). A sample lacking any carbon + source was included as negative control. Cells were incubated in a microtitre plate reader (Infinite F200 pro; Tecan) at 23 + °C and with shaking at 88 r.p.m. for 7 days. Growth was automatically measured every 15 min with the Infinite F200 system + as increase of the OD600. Growth at temperatures of 4 °C and 37 °C was determined in 200 ml MB within Erlenmeyer flasks for one month and measured + photometrically as increase of the OD600 using an Ultrospec II spectrophotometer (LKB-Biochrom). +

+ +

Exoenzyme activities (hydrolysis of gelatin, starch and Tween 80) were analysed using MB solidified with 4 % (w/v) gelatin + or 1.5 % (w/v) agarose and supplemented with 0.2 % (w/v) starch and 1 % (v/v) Tween 80, respectively, as described by Smibert & Krieg (1981). As a positive control, R. litoralis DSM 6996T was used for gelatin and Tween 80 hydrolysis and M. algicola DSM 10251T for starch hydrolysis. Reduction of nitrate was tested according to Smibert & Krieg (1981) in MB supplemented with 0.1 % (w/v) potassium nitrate; R. denitrificans DSM 7001T served as a negative control. The assays were incubated for 7 days at 28 °C, except for the hydrolysis of starch, conducted + at 20 °C. The growth and hydrolysis tests described above were all performed in three technical replicates. +

+ +
+
+ +

Phenotype MicroArray (PM) experiments.

+ +

To determine the metabolic properties of the Phaeobacter strains CIP 105210, DSM 17395, DSM 24588 and DSM 16374T we used the PM technology (Biolog; Bochner, 2009). The Phaeobacter strains were grown on MB agar for 48 h and subsequently analysed using the Phenotype MicroArray MicroPlate PM01 and PM02-A + (AES Chemunex BLG 12111, BLG 12112) over 70 h; thus 190 different carbon sources were tested. Each strain was measured in + three biological replicates. The inoculation medium was modified according to the requirements of marine bacteria, i.e. 10 + ml of the inoculation fluid IF-0a (AES Chemunex BLG 72268) was supplemented with 1200 µl artificial seawater stock solution, + 120 µl vitamin stock solution, 12 µl trace element stock solution, 120 µl NaHCO3 buffer, 428 µl ultrapure H2O and 120 µl DyeD (AES Chemunex BLG 74224). The stock solutions had the following composition (l−1): (i) artificial seawater stock solution: 200 g NaCl, 40 g Na2SO4, 30 g MgCl2 . 6H2O, 5 g KCl, 2.5 g NH4Cl, 2 g KH2PO4, 1.5 g CaCl2 . 2H2O; (ii) trace element stock solution: 2.1 g FeSO4 . 7H2O, 13 ml 25 % HCl, 5.2 g Titriplex III (Na2EDTA; adjust pH to 6.0–6.5 to resolve), 190 mg CoCl2 . 6H2O, 144 mg ZnSO4 . 7H2O, 100 mg MnCl2 . 4H2O, 36 mg Na2MoO4 . 2H2O, 30 mg H3BO3, 24 mg NiCl2 . 6H2O, 2 mg CuCl2 . 2H2O; (iii) vitamin stock solution: 100 mg thiamine, 20 mg niacin, 8 mg 4-aminobenzoic acid, 2 mg biotin; and (iii) buffer stock + solution: 19 g NaHCO3. +

+ +

The cells were suspended in the modified inoculation medium using a sterile swab. The turbidity was adjusted to a cell density + of 85 % transmittance using a turbidimeter (AES Chemunex BLG 3531) and 100 µl of the cell suspension were pipetted in each + of the wells. The MicroPlates were sealed with Parafilm, incubated at 28 °C and measured in the Omnilog unit (Biolog). The + results were analysed using the R package ‘opm’ (Vaas et al., 2012). The curve parameter maximum height (A) was estimated for each substrate, differences were visualized using heat maps, and + the data were discretized into negative, ambiguous and positive reactions using the built-in functions of ‘opm’ under default settings. +

+ +
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+ + +

Results

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Profiles of the extrachromosomal elements

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The high-molecular-mass genomic DNA of different Phaeobacter strains was separated with PFGE. A representative PFGE gel resolving linear DNA molecules in the size range from 23 to 533 + kb is shown in Fig. 1(a). In addition to the chromosomes (Fig. 1a, Chr) a distinct number of extrachromosomal bands was revealed for each of the strains CIP 105210, DSM 17395, DSM 24588 and + DSM 16374T. To determine the conformation of the detected extrachromosomal DNA (ccc versus linear; Pradella et al., 2010; Römling et al., 1996), we varied the PFGE conditions (PFGE parameter set A and B) in different gel runs. Using PFGE parameter set A, the fuzzy, + faint bands within the lanes of strains CIP 105210 and DSM 17395 (Fig. 1a, marked a, b and c, respectively) ran at approximately 319 (a) and 380 (b, c) kb (Fig. 1a). With PFGE parameter set B (data not shown) band (a) ran at 184 kb and bands (b) and (c) ran at approximately 210 kb indicating + that the respective bands migrated independently of the PFGE parameters applied. From this anomalous migration behaviour we + concluded that the inherent DNA had a circular conformation. The sizes of the detected ccc DNA were estimated as 66 (a) and + 79 (b, c) kb by conventional electrophoresis using the BAC Tracker as ccc size marker (data not shown). As these sizes were + close to those estimated for the linearized plasmids of 64 and 77 kb in Phaeobacter strain CIP 105210 and 75 kb in strain DSM 17395 (see below), it is most likely that they represent the same plasmids in different + conformations. +

+ +
+
Fig. 1.
View larger version: + +
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+
Fig. 1. + +

(a) PFGE plasmid profiles of the Phaeobacter strains CIP 105210T, DSM 17395, DSM 24588 and DSM 16374T based on uncut high-molecular-mass genomic DNA. (b) Calculated plasmid sizes as mean values taken from at least two different + gel runs. The PFGE conditions were: 1 % (w/v) agarose gel with pulse times of 1 to 48 s for 24 h at 200 V (6 V cm−1). Chr, chromosomal DNA; λ, lambda phage concatemers as molecular-mass PFGE markers (New England Biolabs); li, linear. (*), The two largest plasmids (linearized forms) of Phaeobacter strains CIP 105210T and DSM 17395 migrated about the same distance in the gel and thus seemed to have an identical size. In contrast, both bands + could be clearly distinguished by their size in other PFGE runs (data not shown) using different DNA sample preparations. + DNA mobility is largely influenced by the DNA concentration of the sample. The observed discrepancy can thus be explained + by the relatively high DNA concentration in CIP 105210T (compared to DSM 17395T), which retards band migration (Römling et al., 1996). (†) (‡), The PFGE-based plasmid size estimations of 75 and 63 kb of DSM 17395 correspond to the plasmid sizes of 78 and 65 kb, respectively, + determined by genome sequencing (Thole et al., 2012; NC_018287.1, NC_018288.1). (§), The 36 kb plasmid of P. gallaeciensis CIP 105210T had a very low fluorescence intensity and is thus hardly visible on the gel image. ++, The 77 kb band of strain CIP 105210T showed increased fluorescence intensity and presumably represents a double band (plasmid duplet). +

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+
+ +

By contrast, the sharp bands between 23 kb and 262 kb were separated strictly in accordance with their size when PFGE parameter + sets A and B were used. They were thus assumed linear (li, Fig. 1a), most possibly originating from randomly linearized ccc plasmids (Pradella et al., 2010). +

+ +

Regarding the linearized plasmid fraction of the Phaeobacter strains, which was very well suited to determine the plasmid complement of the strains and their sizes (Pradella et al., 2010), seven extrachromosomal replicons were evident in P. gallaeciensis CIP 105210, four in P. inhibens DSM 16374T and three in the strains DSM 17395 and DSM 24588. The estimated sizes of the detected plasmids (17 altogether) ranged from + 36 to 262 kb (Fig. 1b). They were all different, but their size distribution in the individual strains showed some similarity, i.e. all Phaeobacter strains have one large plasmid (262, 253, 239 and 227 kb in strains DSM 17395, CIP 105210, DSM 24588 and DSM 16374T, respectively) and two or three smaller ones in the size range between 63 and 77 kb. Our PFGE analysis thus indicated that + the Phaeobacter strains CIP 105210 and DSM 17395 – both deposited as type strain of Phaeobacter gallaeciensis – are not identical. +

+ +
+
+ +

Classification of the Phaeobacter strains using 16S rRNA gene sequence, MALDI-TOF MS protein and 16S–23S rRNA gene ITS analyses +

+ +
+ +

16S rRNA gene sequence analysis.

+ +

We re-evaluated the phylogenetic relationships of the Phaeobacter strains and therefore resequenced the PCR-amplified 16S rRNA genes of strains DSM 17395, DSM 16374T and CIP 105210. In the phylogenetic tree inferred from 16S rRNA gene sequences of representative members of the genus Phaeobacter, as well as strains DSM 24588 ( = 2.10), ANG1 and LSS9, for which finished or draft genome sequences exist (Collins & Nyholm, 2011; Fernandes et al., 2011; Thole et al., 2012; Fig. 2), the Phaeobacter strains DSM 17395, DSM 24588 ( = 2.10), DSM 16374T and CIP 105210 clustered together (P. gallaeciensis/P. inhibens cluster) and were well separated from the P. arcticus/P. leonis lineage and the branch formed by P. caeruleus, Phaeobacter sp. ANG1 and P. daeponensis (16S rRNA gene identity ≥97.8 %). Within the P. gallaeciensis/P. inhibens cluster, the 16S rRNA gene of strain CIP 105210 (KC176239) grouped together with the originally deposited BS107T sequence (Y13244), exhibiting 72 % and 91 % support from MP and ML bootstrapping, respectively. The 16S rRNA gene sequences + of the Phaeobacter strains DSM 17395, DSM 24588 and DSM 16374T (KC176240) were identical and differed by four bases from the P. gallaeciensis CIP 105210 sequence KC176239 (16S rRNA gene identity of 99.7 %; see below). +

+ +
+
Fig. 2.
View larger version: + +
+
+
Fig. 2. + +

Midpoint-rooted MP phylogeny inferred from 16S rRNA gene sequences of Phaeobacter strains closely related to P. inhibens and P. gallaeciensis. Branches are scaled in terms of the minimum number of substitutions (using deltran optimization; Stamatakis et al., 2008). Numbers above branches are support values from MP (left) and ML (right) bootstrapping. Original designation of strains + that are deposited at culture collections is indicated in parentheses; square brackets give the respective accession number. +

+ +
+
+
+ +

Neither the 16S rRNA gene sequence of P. gallaeciensis CIP 105210 (KC176239) nor the sequence of P. inhibens DSM 16374T (KC176240) was exactly identical to that of the original deposit, P. gallaeciensis BS107T (Y13244) or P. inhibens T5T (AY177712), respectively (Fig. 2, Fig. S1 available in IJSEM Online). More precisely, the 16S rRNA gene sequences of the alleged P. gallaeciensis type strains differed at the base positions (Escherichia coli numbering; Gutell et al., 1994) 47, 260, 777, 928, 930, 1030, 1210 and 1387 (Fig. S1; Table S1); and those of the alleged P. inhibens type strains at the positions 29, 1210, 1387, 1436, 1459, 1466 and 1480 (Fig. S1; Table S2). We assessed in detail whether + these discrepancies could be caused by sequencing errors, as is already indicated by the long-terminal branches leading to + BS107T and T5T (Fig. 2). We thus compared the respective sequences with the bacterial 16S rRNA variability map (Baker et al., 2003) and/or the 16S rRNA secondary structure model (Gutell et al., 1994) and showed that the 16S rRNA gene sequences provided in this study were all in accordance with bases categorized as conserved + by Baker et al. (2003) or the proposed rRNA secondary structure (Tables S1 and S2), whereas the previously determined 16S rRNA gene sequences Y13244 + and AY177712 were flawed. +

+ +

Furthermore, we examined whether the four differences in the 16S rRNA gene sequences of P. gallaeciensis CIP 105210 (KC176239) and P. inhibens DSM 16374T (KC176240) were genuine. They were localized at the base positions 614 (P. gallaeciensis: G; P. inhibens: A) and 626 (P. gallaeciensis: C; P. inhibens: U) within the 16S rRNA variable region V4 (Baker et al., 2003) and at the positions 835 (P. gallaeciensis: G; P. inhibens: A) and 851 (P. gallaeciensis: C; P. inhibens: U) within the variable V5 region, respectively (E. coli numbering; Fig. S1; Table S3). Comparison with the secondary 16S rRNA structure model (Gutell et al., 1994) and a simulation of the rRNA folding using the Mfold web server (Zuker, 2003) indicated that bases 614 and 626 paired in the variable region V4 stem–loop (Fig. 3); similarly, bases 835 and 851 matched in the V5 stem–loop (Fig. S2). We thus assumed that the present transitions of G and + C in P. gallaeciensis to A and U in P. inhibens, respectively, reflect genuine and characteristic mutations in the 16S rRNA genes of these species. Considering these bases, + the 16S rRNA gene sequence of Phaeobacter strain CIP 105210 resembled the original one of BS107T (Y13244), which would indicate that strain CIP 105210 is the type strain of P. gallaeciensis. +

+ +
+
Fig. 3.
View larger version: + +
+
+
Fig. 3. + +

Secondary structure of the 16S rRNA variable region V4 of P. gallaeciensis CIP 105210T (a) and P. inhibens DSM 17395 (b) demonstrating transition of bases 614 and 626 (E. coli numbering; bases 529 and 541 according to the CIP 105210T numbering). RNA folding was simulated using the Mfold web server for nucleic acid folding and hybridization prediction (Zuker, 2003; http://mfold.rna.albany.edu/?q=mfold/RNA-Folding-Form). +

+ +
+
+
+
+
+ +

MALDI-TOF MS analysis.

+ +

In the MALDI-TOF MS dendrogram (Fig. 4), the Phaeobacter strains DSM 16374T, DSM 24588 and DSM 17395 not only formed a cluster but were virtually indistinguishable from each other. Strain CIP 105210 + appeared as the sister group of those three strains, whereas P. daeponensis and P. caeruleus as well as P. arcticus and P. leonis were well set apart. +

+ +
+
Fig. 4.
View larger version: + +
+
+
Fig. 4. + +

Score-oriented dendrogram showing the similarity of MALDI-TOF mass spectra from cell extracts of selected Phaeobacter strains. The dendrogram was generated by the BioTyper software (version 3.0; Bruker Daltonics). +

+ +
+
+
+
+
+ +

ITS analysis.

+ +

A comparable picture was observed in the ITS analysis (Fig. 5). Phaeobacter strain DSM 17395 appeared as sister strain of P. inhibens DSM 16374T with 93 % support under ML and 99 % support under MP. The sister-group relationship of these and strain DSM 24588 was supported + with 70 % and 88 % bootstrap values, respectively, to the exclusion of P. gallaeciensis CIP 105210. Phaeobacter sp. ANG1 was placed in a distinct cluster together with the type strains of P. daeponensis and P. caeruleus (100 % support). +

+ +
+
Fig. 5.
View larger version: + +
+
+
Fig. 5. + +

Midpoint-rooted ML phylogeny inferred from ITS sequences of Phaeobacter strains closely related to P. inhibens and P. gallaeciensis. Branches are scaled in terms of the expected number of substitutions per site. Numbers above branches are support values + from ML (left) and MP (right) bootstrapping. Original designation of strains that are deposited at culture collections is + indicated in parentheses; square brackets give the respective accession number. +

+ +
+
+
+
+
+
+ +

DNA–DNA hybridization.

+ +

In contrast to the highly similar genomic DNA between the strains DSM 17395 and DSM 16374T (82 %) as well as between the strains DSM 16374T and DSM 24588 (83 %), strain CIP 105210 shared only 62 % and 63 % DNA–DNA relatedness to the strains DSM 17395 and DSM 16374T, respectively (Table 1). This is below the threshold of 70 % recommended by Wayne et al. (1987) hence indicating the status of strain CIP 105210 in a separate species. Conversely, the values clearly above 70 % indicate + that strains DSM 17395, DSM 16374T and DSM 24588 belong to the same species. +

+ +
+
+
View this table: +
+
+
Table 1. + Mean DNA–DNA similarity values (n = 2) between the Phaeobacter strains CIP 105210T, DSM 17395, DSM 16374T and DSM 24588 + +
+
+
+
+
+ +

Growth, hydrolysis and PM experiments

+ +

The growth and hydrolysis experiments for Phaeobacter strains CIP 105210 and DSM 17395 could only partially reproduce those conducted by Ruiz-Ponte et al. (1998) (Table S4). The results for strain CIP 105210 differed from all other series of measurements by growth of this strain on + l-arabinose and hydrolysis of Tween 80. Strain DSM 17395 showed no specific characteristics, but it – as well as CIP 105210 + – differed from strain BS107T (Ruiz-Ponte et al., 1998) as they grew on serine (like T5T; Martens et al., 2006) and showed slow growth on l-rhamnose and 2-ketoglutarate (Table S4). The overall number of specific differences of all other strains to T5T (Martens et al., 2006) was four (growth on citrate, glucosamine and on MB at 4 °C or 37 °C). +

+ +

In contrast, the PM experiments, which are more sensitive than bacterial growth tests because they monitor substrate respiration + (Bochner et al., 2001), yielded significant physiological differences between all four tested Phaeobacter strains, DSM 24588, DSM 16374T, DSM 17395 and CIP 105210 (Figs S3 and S4). The physiological similarity between strains CIP 105210 and DSM 17395 was high, + but the differences between the two were clearly reproducible. According to the discretization approach implemented in ‘opm’ (Vaas et al., 2012), respiration on tyramine (PM01-H04; blue box Fig. S3) was positive in DSM 17395 and DSM 16374, weak in DSM 24588 but negative + in CIP 105210. Respiration on butyrate (PM02A-D12; Fig. S4) was positive in CIP 105210 and DSM 24588, weak in DSM 16374T, but negative in DSM 17395. +

+ +

Regarding the common subset of growth or hydrolysis experiments on the one hand and PM experiments on the other hand, the + results were identical with a few exceptions. Expectedly, no substrate was detected on which growth (or hydrolysis) was measurable + but respiration was not observed, whereas on some substrates respiration was detected by PM analysis even though these substrates + sustained no growth. Accordingly, a weak PM reaction on l-arabinose (PM01-A02) and a positive PM reaction on citrate (PM01-F02) were observed for all four tested strains. A positive + PM reaction to Tween 80 (PM01-E05) was observed for strains DSM 24588 and CIP 105210, whereas strains DSM 17395 and DSM 16374T showed a weak reaction (compare red boxes in Fig. S3 with Table S4). +

+ +
+
+
+ + +

Discussion

+ +

According to the PFGE profiles of the extrachromosomal elements – which are largely supported by the complete genome sequences + of the Phaeobacter strains DSM 17395, DSM 24588 (Thole et al., 2012), DSM 16374T (Dogs, M. and others, unpublished) and CIP 105210 (Frank, O. and others, unpublished) – DDH similarities, 16S rRNA gene sequence + analysis, 16S–23S rRNA gene ITS sequence analysis, MALDI-TOF MS protein analysis, and high-throughput phenotyping using the + PM technology, the Phaeobacter strains CIP 105210 and DSM 17395, both supposed to be deposits of the type strain of P. gallaeciensis BS107T, are biologically clearly distinct. ITS sequence and MALDI-TOF analysis additionally showed that DSM 17395 (and DSM 24588) + group together with P. inhibens DSM 16374T to the exclusion of CIP 105210. As confirmed by DDH (≥76 % similarity), DSM 16374T, DSM 17395 and DSM 24588 are conspecific, i.e. all belong to the species P. inhibens. Analysis of 16S rRNA gene sequences was in accordance with this finding, too, because the sequences of these strains were + identical (if the resequenced 16S rRNA gene sequence of DSM 16374T was considered). Our sequence analyses confirmed the finding of Thole et al. (2012) that the Phaeobacter sp. ANG1 does not belong to the species P. gallaeciensis. +

+ +

Because DSM 17395 must hence be excluded from the species P. gallaeciensis, the question arises whether the alternative type strain deposit, CIP 105210, represents P. gallaeciensis BS107T. DDH analysis (<70 % similarity) indicates that CIP 105210 is not conspecific with P. inhibens. Analysis of growth behaviours and enzymic activities could not fully reproduce the findings of Ruiz-Ponte et al. (1998), but given the overall low number of characters tested, the low number of known differences to the type strain of the sister + species, P. inhibens, and the well-known difficulties in reproducing physiological tests in distinct laboratories in general, the significance + of these discrepancies is unclear. Essentially, based on the newly generated CIP 105210 16S rRNA gene sequence that is identical + to the one from BS107T, except for deviations that were likely to be sequencing errors, we could clearly document the type strain status of P. gallaeciensis CIP 105210T. As the strains CIP 105210T and DSM 17395 have been independently deposited at the CIP and the DSMZ, respectively, it is the most probable explanation + that the later strain has been mixed-up prior to deposition. +

+ +

Research laboratories are usually not equipped with sufficient resources to verify the biological identity of their cultures. + Moreover, culture collections have to cope with the deposition of interchanged or contaminated strains and the quality of + incoming material will presumably even deteriorate due to the decline of basic microbiological methodology in the era of molecular + biology. Problems are expected particularly if confusion with closely related strains has occurred, as in the case of DSM + 17395, which apparently belongs to the sister species of the correct strain. Hence, it is advisable that researchers working + on a certain strain exactly denote the source from which it was received. Providing the accession numbers of culture-collection + deposits (such as ‘CIP 105210T’ or ‘DSM 17395’) should thus be preferred over just stating the original strain designator (such as ‘BS107T’) irrespective of the source from which the strain has been received. In any case, with respect to cultivatable microbes, + only strains with a demonstrable history should be considered in serious research. +

+ +

The three homologous plasmids of the completely sequenced P. inhibens strains DSM 17395 and DSM 24588 exhibit a long-range synteny (Thole et al., 2012), but several indels (insertions/deletions) are responsible for the deviating plasmid sizes [262 versus 238 kb (DnaA-like + replicon; Petersen, 2011), 75(78) versus 94 kb (RepB-I), 65(63) versus 70 kb (RepA-I); Fig. 1]. Homologues of these replicons may also be present in the sister species P. gallaeciensis CIP 105210T e.g. represented by the 253, 77 and 64 kb replicons. However, the conspicuously different plasmid profiles in P. gallaeciensis and P. inhibens (Fig. 1) may reflect horizontal recruitment of four additional replicons in P. gallaeciensis CIP 105210T. The same explanation is supported by the presence of a type IV secretion system on the fourth 86 kb plasmid of the P. inhibens type strain DSM 16374T (Dogs, M. and others, unpublished), which may be responsible for plasmid mobilization via conjugation (Petersen et al., 2013). In the near future, genome sequencing and comparative genomics of more distantly related strains, such as Phaeobacter arcticus, will help to reveal the extent of horizontal exchange and vertical evolution within the Roseobacter clade. +

+ +
+
+ +

Acknowledgements

+ +

This work, including a PhD stipend for N. B., was supported by the Transregional Collaborative Research Center ‘Roseobacter’ of the Deutsche Forschungsgemeinschaft (Transregio TRR 51) and the MICROME project, EU Framework Program 7 Collaborative + Project (222886-2). We thank Victoria Michael, Bettina Sträubler and Ulrike Steiner for excellent technical assistance, Brian + Tindall and Sabine Gronow for their helpful discussions, as well as the two anonymous reviewers for their constructive criticism. +

+ +
+
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    + + + + + doi: + 10.1099/ijs.0.053900-0 + + + + IJSEM + + vol. 63 + + no. Pt 11 + + 4340-4349 + + + + + + + +
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+ + \ No newline at end of file diff --git a/examples/ijsem-quickscrape/ijsem-mounce-OLD-scraper/http_ijs.sgmjournals.org_content_63_Pt_11_4340.full/fulltext.pdf b/examples/ijsem-quickscrape/ijsem-mounce-OLD-scraper/http_ijs.sgmjournals.org_content_63_Pt_11_4340.full/fulltext.pdf new file mode 100644 index 00000000..38beffcf Binary files /dev/null and b/examples/ijsem-quickscrape/ijsem-mounce-OLD-scraper/http_ijs.sgmjournals.org_content_63_Pt_11_4340.full/fulltext.pdf differ diff --git a/examples/ijsem-quickscrape/ijsem-mounce-OLD-scraper/http_ijs.sgmjournals.org_content_63_Pt_11_4340.full/results.json b/examples/ijsem-quickscrape/ijsem-mounce-OLD-scraper/http_ijs.sgmjournals.org_content_63_Pt_11_4340.full/results.json new file mode 100644 index 00000000..c0b05d37 --- /dev/null +++ b/examples/ijsem-quickscrape/ijsem-mounce-OLD-scraper/http_ijs.sgmjournals.org_content_63_Pt_11_4340.full/results.json @@ -0,0 +1,101 @@ +{ + "publisher": { + "value": [ + "Society for General Microbiology" + ] + }, + "journal": { + "value": [ + "International Journal of Systematic and Evolutionary\n Microbiology" + ] + }, + "title": { + "value": [ + "Molecular and phenotypic analyses reveal the non-identity of the Phaeobacter gallaeciensis type strain deposits CIP 105210T and DSM 17395" + ] + }, + "authors": { + "value": [ + "Nora Buddruhs", + "Silke Pradella", + "Markus Göker", + "Orsola Päuker", + "Rüdiger Pukall", + "Cathrin Spröer", + "Peter Schumann", + "Jörn Petersen", + "Thorsten Brinkhoff" + ] + }, + "date": { + "value": [ + "11/01/2013" + ] + }, + "doi": { + "value": [ + "10.1099/ijs.0.053900-0" + ] + }, + "volume": { + "value": [ + "63" + ] + }, + "issue": { + "value": [ + "Pt 11" + ] + }, + "firstpage": { + "value": [ + "4340" + ] + }, + "abstract": { + "value": [ + "\n \n  Next Section\n Abstract\n \n The marine genus Phaeobacter currently comprises six species, some of which were intensively studied mainly due to their ability to produce secondary\n metabolites. The type strain of the type species, Phaeobacter gallaeciensis BS107T, has been deposited at several public culture collections worldwide. Based on differences in plasmid profiles, we detected\n that the alleged P. gallaeciensis type strains deposited at the Collection Institute Pasteur (CIP; Paris, France) as CIP 105210 and at the German Collection\n of Microorganisms and Cell Cultures (DSMZ; Braunschweig, Germany) as DSM 17395 are not identical. To determine the identity\n of these strains, we conducted DNA–DNA hybridization, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry\n (MALDI-TOF), 16S rRNA gene and internal transcribed spacer (ITS) sequence analyses, as well as physiological experiments.\n Based on the detailed 16S rRNA gene reanalysis we showed that strain CIP 105210 most likely corresponds to the original P. gallaeciensis type strain BS107T. In contrast, the Phaeobacter strain DSM 17395 exhibits a much closer affiliation to Phaeobacter inhibens DSM 16374T ( = T5T) and should thus be allocated to this species. The detection of the dissimilarity of strains CIP 105210T and DSM 17395 will influence future comparative studies within the genus Phaeobacter.\n \n \n " + ] + }, + "fulltext_html": { + "value": [ + "http://ijs.sgmjournals.org/content/63/Pt_11/4340.full" + ] + }, + "fulltext_pdf": { + "value": [ + "http://ijs.sgmjournals.org/content/63/Pt_11/4340.full.pdf" + ] + }, + "supplementary_material": { + "value": [ + "http://ijs.sgmjournals.org/content/63/Pt_11/4340/suppl/DC1" + ] + }, + "figure": { + "value": [ + "http://ijs.sgmjournals.org/content/63/Pt_11/4340/F1.small.gif", + "http://ijs.sgmjournals.org/content/63/Pt_11/4340/F2.small.gif", + "http://ijs.sgmjournals.org/content/63/Pt_11/4340/F3.small.gif", + "http://ijs.sgmjournals.org/content/63/Pt_11/4340/F4.small.gif", + "http://ijs.sgmjournals.org/content/63/Pt_11/4340/F5.small.gif" + ] + }, + "figure_caption": { + "value": [ + "Fig. 1. \n \n (a) PFGE plasmid profiles of the Phaeobacter strains CIP 105210T, DSM 17395, DSM 24588 and DSM 16374T based on uncut high-molecular-mass genomic DNA. (b) Calculated plasmid sizes as mean values taken from at least two different\n gel runs. The PFGE conditions were: 1 % (w/v) agarose gel with pulse times of 1 to 48 s for 24 h at 200 V (6 V cm−1). Chr, chromosomal DNA; λ, lambda phage concatemers as molecular-mass PFGE markers (New England Biolabs); li, linear. (*), The two largest plasmids (linearized forms) of Phaeobacter strains CIP 105210T and DSM 17395 migrated about the same distance in the gel and thus seemed to have an identical size. In contrast, both bands\n could be clearly distinguished by their size in other PFGE runs (data not shown) using different DNA sample preparations.\n DNA mobility is largely influenced by the DNA concentration of the sample. The observed discrepancy can thus be explained\n by the relatively high DNA concentration in CIP 105210T (compared to DSM 17395T), which retards band migration (Römling et al., 1996). (†) (‡), The PFGE-based plasmid size estimations of 75 and 63 kb of DSM 17395 correspond to the plasmid sizes of 78 and 65 kb, respectively,\n determined by genome sequencing (Thole et al., 2012; NC_018287.1, NC_018288.1). (§), The 36 kb plasmid of P. gallaeciensis CIP 105210T had a very low fluorescence intensity and is thus hardly visible on the gel image. ++, The 77 kb band of strain CIP 105210T showed increased fluorescence intensity and presumably represents a double band (plasmid duplet).\n \n \n \n ", + "Fig. 2. \n \n Midpoint-rooted MP phylogeny inferred from 16S rRNA gene sequences of Phaeobacter strains closely related to P. inhibens and P. gallaeciensis. Branches are scaled in terms of the minimum number of substitutions (using deltran optimization; Stamatakis et al., 2008). Numbers above branches are support values from MP (left) and ML (right) bootstrapping. Original designation of strains\n that are deposited at culture collections is indicated in parentheses; square brackets give the respective accession number.\n \n \n \n ", + "Fig. 3. \n \n Secondary structure of the 16S rRNA variable region V4 of P. gallaeciensis CIP 105210T (a) and P. inhibens DSM 17395 (b) demonstrating transition of bases 614 and 626 (E. coli numbering; bases 529 and 541 according to the CIP 105210T numbering). RNA folding was simulated using the Mfold web server for nucleic acid folding and hybridization prediction (Zuker, 2003; http://mfold.rna.albany.edu/?q=mfold/RNA-Folding-Form).\n \n \n \n ", + "Fig. 4. \n \n Score-oriented dendrogram showing the similarity of MALDI-TOF mass spectra from cell extracts of selected Phaeobacter strains. The dendrogram was generated by the BioTyper software (version 3.0; Bruker Daltonics).\n \n \n \n ", + "Fig. 5. \n \n Midpoint-rooted ML phylogeny inferred from ITS sequences of Phaeobacter strains closely related to P. inhibens and P. gallaeciensis. Branches are scaled in terms of the expected number of substitutions per site. Numbers above branches are support values\n from ML (left) and MP (right) bootstrapping. Original designation of strains that are deposited at culture collections is\n indicated in parentheses; square brackets give the respective accession number.\n \n \n \n " + ] + }, + "license": { + "value": [] + }, + "copyright": { + "value": [ + "Copyright ©\n \t\t2015 International Union of Microbiological Societies\n \t\n " + ] + } +} \ No newline at end of file diff --git a/examples/ijsem-quickscrape/ijsem-mounce-OLD-scraper/http_ijs.sgmjournals.org_content_63_Pt_11_4350.full/DC1 b/examples/ijsem-quickscrape/ijsem-mounce-OLD-scraper/http_ijs.sgmjournals.org_content_63_Pt_11_4350.full/DC1 new file mode 100644 index 00000000..b1d0469d --- /dev/null +++ b/examples/ijsem-quickscrape/ijsem-mounce-OLD-scraper/http_ijs.sgmjournals.org_content_63_Pt_11_4350.full/DC1 @@ -0,0 +1,353 @@ + + + + + Supplementary material + + + + + + + + + + + +
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Reclassification of Bifidobacterium stercoris Kim et al. 2010 as a later heterotypic synonym of Bifidobacterium adolescentis

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  1. J. Kopečný1
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  1. 1Institute of Animal Physiology and Genetics v.v.i., Academy of Sciences of the Czech Republic, Vídeňská 1083, Prague 4 – Krč, + 142 20, Czech Republic +
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  3. 2Czech University of Life Sciences, Faculty of Agrobiology, Food and Natural Resources, Department of Microbiology, Nutrition + and Dietetics, Kamýcká 129, Prague 6 – Suchdol, 165 21, Czech Republic +
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  5. 3Czech Collection of Microorganisms, Department of Experimental Biology, Faculty of Science, Masaryk University, Tvrdého 14, + 60200 Brno, Czech Republic +
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  1. Correspondence
    J. Killer Killer.Jiri{at}seznam.cz or killer{at}iapg.cas.cz
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Abstract

+ +

The taxonomic position of Bifidobacterium stercoris Eg1T ( = JCM 15918T) based on comparative 16S rRNA gene and hsp60 sequence analyses was found to be controversial, as the strain showed high similarity to the type strain of Bifidobacterium adolescentis, CCUG 18363T. Therefore, the relationship between the two species was investigated by a taxonomic study that included, in addition to + re-evaluation of the 16S rRNA gene sequence, determination of DNA–DNA binding and multilocus sequence analysis (MLSA) of housekeeping + genes encoding the DNA-directed RNA polymerase B subunit (rpoC), putative xylulose-5-phosphate/fructose-6-phosphate phosphoketolase (xfp), elongation factor EF-G (fusA), 50S ribosomal protein L2 (rplB) and DNA gyrase B subunit (gyrB). Comparative 16S rRNA gene sequence analysis showed relatively high similarity (98.9 %) between B. stercoris KCTC 5756T and B. adolescentis ATCC 15703T. MLSA revealed close relatedness between B. stercoris KCTC 5756T and B. adolescentis CCUG 18363T, with 99.3–100 % similarity between the rpoC, xfp, fusA, rplB and gyrB gene sequences. In addition, relatively high dnaJ1 gene sequence similarity of 97.7 % was found between the strains. Similar phenotypes and a high DNA–DNA binding value (78.9 %) + confirmed that B. stercoris and B. adolescentis are synonymous. Based on these results, it is proposed that the species Bifidobacterium stercoris Kim et al. 2010 should be reclassified as a later heterotypic synonym of Bifidobacterium adolescentis Reuter 1963 (Approved Lists 1980). +

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    The GenBank/EMBL/DDBJ accession numbers for the partial rpoC, xfp, fusA, rplB, gyrB and dnaJ1 gene sequences of B. stercoris KCTC 5756T and B. adolescentis CCUG 18363T are respectively JQ363659 and JQ363660 (rpoC), JQ363666 and JQ363667 (xfp), JQ363628 and JQ363629 (fusA), JQ363655 and JQ363656 (rplB), JQ363638 and JQ363639 (gyrB) and JQ363622 and JQ363623 (dnaJ1). The GenBank/EMBL/DDBJ accession number for the revised partial 16S rRNA gene sequence of B. stercoris KCTC 5756T is KF147852. +

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    Two supplementary figures and a supplementary table are available with the online version of this paper.

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Bifidobacterium stercoris was described by Kim et al. (2010) for one strain isolated from faeces of a Korean adult mainly on the basis of phenotypic characteristics and DNA–DNA reassociation + results. All results confirmed that the new bacterial isolate belonged to the genus Bifidobacterium. However, the authors stated, based on phylogenetic analyses, that the new isolate was closely related to Bifidobacterium adolescentis. Moreover, the habitats from which these bacteria were isolated suggest the necessity of clarifying their taxonomic relationship + with additional genetic approaches. The affinity of B. stercoris KCTC 5756T and the type strain of B. adolescentis, CCUG 18363T, was therefore evaluated in this study by a polyphasic taxonomic approach. +

+

Both strains were grown at 37 °C in TPY anaerobic broth (Scardovi, 1986). Chromosomal DNA was extracted using the DNeasy Blood & Tissue kit (Qiagen) according to the manufacturer’s protocol. The + 16S rRNA gene sequence of B. stercoris KCTC 5756T was resequenced by the method of Killer et al. (2011). A comparative analysis based on the revised 16S rRNA gene sequence of B. stercoris KCTC 5756T (GenBank accession no. KF147852) and the 16S rRNA gene sequence of B. adolescentis ATCC 15703T (NR_074802) revealed relatively high similarity of 98.9 % (over a total of 1520 bp). This relatively high similarity is of + limited value for the resolution of bacterial species (Tindall et al., 2010). Protein-coding housekeeping gene sequences have recently been recommended for the determination of genomic relatedness + at the bacterial species level because of their ability to provide higher taxonomic resolution compared with 16S rRNA gene + sequence analysis (Ventura et al., 2006). Therefore, comparative sequence analyses were done between B. stercoris KCTC 5756T and B. adolescentis CCUG 18363T based on rpoC, xfp, fusA, rplB, gyrB and dnaJ1 gene sequences. Multilocus sequence analysis (MLSA) has been proposed as an alternative to DNA hybridization, enabling inter- + and intra-specific genomic relatedness to be established. In addition, the authors who described the species B. stercoris reported high hsp60 gene sequence similarity (99.4 %) between B. stercoris Eg1T and B. adolescentis JCM 1275T (Kim et al., 2010). Primers and PCR conditions for amplification of partial fusA, rplB and gyrB gene sequences were obtained from Delétoile et al. (2010). Partial sequences of rpoC and dnaJ1 genes were amplified under conditions described by Ventura et al. (2006). The gene encoding the xylulose-5-phosphate/fructose-6-phosphate phosphoketolase (xfp) was proposed as a suitable phylogenetic marker for bifidobacteria by Berthoud et al. (2005). Amplified DNA fragments were subsequently checked by electrophoresis on 1.5 % PCR agarose gel (Top-Bio), purified using + a PCR purification kit (Qiagen) and sequenced by using an automatic ABI PRISM 3130xl Genetic Analyzer (Applied Biosystems). + The values of sequence similarity based on rpoC, xfp, fusA, rplB, gyrB and dnaJ1 gene sequences using the jPHYDIT program (Jeon et al., 2005) were 99.3, 99.6, 99.6, 99.8, 100.0 and 97.7 %, respectively. Multilocus sequence typing based on partial fusA, rplB and gyrB gene sequences revealed ≥99 % similarity between different strains within bifidobacterial species (Delétoile et al., 2010). Ventura et al. (2006) determined means of 88.25 and 65.09 % sequence similarity for the rpoC and dnaJ1 genes between 31 bifidobacterial strains. +

+

The concatenation of protein-encoding housekeeping genes has been shown to be extremely useful in order to infer bacterial + phylogeny (Teichmann & Mitchison, 1999). Therefore, phylogenetic analysis to reveal the relationship between B. stercoris KCTC 5756T and B. adolescentis CCUG 18363T was based on concatenated sequences of the hsp60, xfp and dnaJ1 genes. These housekeeping genes were chosen because their sequences are available for a wider range of bifidobacterial species. + Phylogenetic trees were reconstructed by mega version 5.05 and the Gblocks program using the maximum-likelihood algorithm as described previously (Killer et al., 2013). The topology of the phylogenetic tree reconstructed on the basis of concatenated hsp60 and xfp gene sequences revealed a very close relationship between the two tested strains. The phylogenetic branch length between + the two strains was shorter than the length of the phylogenetic branches between distinctive subspecies of bifidobacteria + such as Bifidobacterium animalis subsp. animalis and B. animalis subsp. lactis and Bifidobacterium pseudolongum subsp. pseudolongum and B. pseudolongum subsp. globosum (Fig. 1). Very similar results were obtained using concatenated hsp60, xfp and dnaJ1 gene sequences (Fig. S1, available in IJSEM Online). The GenBank accession numbers for the partial hsp60, xfp and dnaJ1 gene sequences of type strains of bifidobacterial species used and generated in this study are listed in Table S1. A close + relationship of the two bacterial strains was also confirmed by the phylogenetic tree of the family Bifidobacteriaceae reconstructed on the basis of sequences of the 16S rRNA gene (Fig. S2). +

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Fig. 1.
View larger version: + +
+
+
Fig. 1. + +

Phylogenetic tree of the family Bifidobacteriaceae showing the very close relationship of B. adolescentis CCUG 18363T and B. stercoris KCTC 5756T, reconstructed by the maximum-likelihood method based on concatenated partial sequences of the hsp60 (539 nt) and xfp (418 nt) genes using mega version 5.05 software after removing hypervariable positions by using the program Gblocks. Sequence data were aligned using + the clustal w algorithm. The Tamura–Nei model was used for reconstruction of the phylogenetic tree. Bootstrap values, expressed as percentages + of 1000 datasets, are given at nodes. GenBank accession numbers of partial gene sequences derived from type strains are presented + in Table S1. The tree was rooted by Gardnerella vaginalis ATCC 14018T. Bar, 0.04 substitutions per nucleotide position. +

+ +
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The determination of DNA–DNA relatedness is the mandatory reference method for determining whether micro-organisms belong + to the same species (Tindall et al., 2010). DNA–DNA relatedness between B. stercoris KCTC 5756T and B. adolescentis CCUG 18363T was re-evaluated as follows. Wet biomass (3 g) from the tested strains suspended in isopropanol/water (1 : 1, v/v) was disrupted + using a Constant Systems TS 0.75 kW disruptor (IUL Instruments) and the DNA in the crude lysate was purified by chromatography + on hydroxyapatite as described by Cashion et al. (1977). DNA–DNA hybridization was carried out as described by De Ley et al. (1970) under consideration of the modifications described by Huss et al. (1983) using a model Cary 100 Bio UV/Vis spectrophotometer equipped with a Peltier-thermostatted 6×6 multicell changer and a temperature + controller with in-situ temperature probe (Varian). The results showed that the tested strains had a binding level of 78.9 % (mean of three experiments, + sd = 0.2 %), higher than the 70 % species boundary limit. +

+

The DNA G+C contents of B. stercoris KCTC 5756T and B. adolescentis CCUG 18363T were re-evaluated as follows. DNA was degraded enzymically into nucleosides as described by Mesbah et al. (1989). The nucleoside mixture was then separated by HPLC as described previously (Killer et al., 2011). The determined values were not significantly different between the studied strains (60.6 and 61.2 mol%, respectively). +

+

API 50 CHL and Rapid ID 32A commercial kits (bioMérieux) were used for comparison of biochemical characteristics of B. stercoris KCTC 5756T and B. adolescentis CCUG 18363T to determine intra- or interspecies divergence. For this purpose, the strains were cultivated in anaerobic TPY broth. Tests + were performed according to the manufacturer’s instructions, except that the API 50 CHL test strips were incubated under anaerobic + conditions (anaerobic jars; Oxoid) at 37 °C for 48 h. Minor differences in biochemical characteristics between B. adolescentis CCUG 18363T and B. stercoris KCTC 5756T are shown in Table 1. These results proved the close biochemical similarity of the tested strains. +

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Table 1. + Minor differences between B. stercoris KCTC 5756T and B. adolescentis CCUG 18363T + +

Both strains produced acids from d-ribose, d-galactose, d-glucose, amygdalin, arbutin, aesculin (hydrolysis), maltose, lactose, melibiose, sucrose, raffinose, gentiobiose and turanose. + Neither strain produced acids from glycerol, erythritol, d- or l-arabinose, d- or l-xylose, d-adonitol, methyl β-d-xylopyranoside, d-mannose, l-sorbose, l-rhamnose, dulcitol, inositol, d-mannitol, methyl α-d-mannopyranoside, methyl α-d-glucopyranoside, N-acetylglucosamine, cellobiose, trehalose, inulin, melezitose, starch, glycogen, xylitol, d-lyxose, d-tagatose, d- or l-fucose, d- or l-arabitol, gluconate or 2- or 5-ketogluconate. Both strains were positive for α-galactosidase, α-glucosidase, β-galactosidase, + β-glucosidase, α-arabinosidase, arginine arylamidase, proline arylamidase, leucyl glycine arylamidase, phenylalanine arylamidase, + leucine arylamidase, tyrosine arylamidase, alanine arylamidase, glycine arylamidase, histidine arylamidase and serine arylamidase. + Both strains were negative for urease, arginine dihydrolase, β-galactosidase-6-phosphate, β-glucuronidase, N-acetyl-β-glucosaminidase, glutamic acid decarboxylase, α-fucosidase, nitrate reduction, indole production, alkaline phosphatase, + pyroglutamic acid arylamidase, glutamyl glutamic acid arylamidase, esterase (C4), valine arylamidase, cystine arylamidase, + trypsin, α-chymotrypsin, α-mannosidase, gelatin hydrolysis, catalase and oxidase. +, Positive reaction; w, weakly positive reaction; −, negative reaction. +

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On the basis of the phenotypic and important genotypic results presented in this study, it is proposed that B. stercoris and B. adolescentis represent the same species and should be united under the same name. It is concluded that Bifidobacterium stercoris Kim et al. 2010 is a later heterotypic synonym of Bifidobacterium adolescentis Reuter 1963 (Approved Lists 1980), which has priority. +

+
+ +

Acknowledgements

+ +

This work was supported by the Czech Science Foundation (project no. GA CR 304/11/1252), the Operation Programme Education + for Competitiveness project CEB (CZ.1.07/2.3.00/20.0183) and the Institutional Research Project of the Institute of Animal + Physiology and Genetics, Acad. Sci. CR (RVO 67985904). +

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Killer", + "I. Sedláček", + "V. Rada", + "J. Havlík", + "J. Kopečný" + ] + }, + "date": { + "value": [ + "11/01/2013" + ] + }, + "doi": { + "value": [ + "10.1099/ijs.0.054957-0" + ] + }, + "volume": { + "value": [ + "63" + ] + }, + "issue": { + "value": [ + "Pt 11" + ] + }, + "firstpage": { + "value": [ + "4350" + ] + }, + "abstract": { + "value": [ + "\n \n  Next Section\n Abstract\n \n The taxonomic position of Bifidobacterium stercoris Eg1T ( = JCM 15918T) based on comparative 16S rRNA gene and hsp60 sequence analyses was found to be controversial, as the strain showed high similarity to the type strain of Bifidobacterium adolescentis, CCUG 18363T. Therefore, the relationship between the two species was investigated by a taxonomic study that included, in addition to\n re-evaluation of the 16S rRNA gene sequence, determination of DNA–DNA binding and multilocus sequence analysis (MLSA) of housekeeping\n genes encoding the DNA-directed RNA polymerase B subunit (rpoC), putative xylulose-5-phosphate/fructose-6-phosphate phosphoketolase (xfp), elongation factor EF-G (fusA), 50S ribosomal protein L2 (rplB) and DNA gyrase B subunit (gyrB). Comparative 16S rRNA gene sequence analysis showed relatively high similarity (98.9 %) between B. stercoris KCTC 5756T and B. adolescentis ATCC 15703T. MLSA revealed close relatedness between B. stercoris KCTC 5756T and B. adolescentis CCUG 18363T, with 99.3–100 % similarity between the rpoC, xfp, fusA, rplB and gyrB gene sequences. In addition, relatively high dnaJ1 gene sequence similarity of 97.7 % was found between the strains. Similar phenotypes and a high DNA–DNA binding value (78.9 %)\n confirmed that B. stercoris and B. adolescentis are synonymous. Based on these results, it is proposed that the species Bifidobacterium stercoris Kim et al. 2010 should be reclassified as a later heterotypic synonym of Bifidobacterium adolescentis Reuter 1963 (Approved Lists 1980).\n \n \n " + ] + }, + "fulltext_html": { + "value": [ + "http://ijs.sgmjournals.org/content/63/Pt_11/4350.full" + ] + }, + "fulltext_pdf": { + "value": [ + "http://ijs.sgmjournals.org/content/63/Pt_11/4350.full.pdf" + ] + }, + "supplementary_material": { + "value": [ + "http://ijs.sgmjournals.org/content/63/Pt_11/4350/suppl/DC1" + ] + }, + "figure": { + "value": [ + "http://ijs.sgmjournals.org/content/63/Pt_11/4350/F1.small.gif" + ] + }, + "figure_caption": { + "value": [ + "Fig. 1. \n \n Phylogenetic tree of the family Bifidobacteriaceae showing the very close relationship of B. adolescentis CCUG 18363T and B. stercoris KCTC 5756T, reconstructed by the maximum-likelihood method based on concatenated partial sequences of the hsp60 (539 nt) and xfp (418 nt) genes using mega version 5.05 software after removing hypervariable positions by using the program Gblocks. Sequence data were aligned using\n the clustal w algorithm. The Tamura–Nei model was used for reconstruction of the phylogenetic tree. Bootstrap values, expressed as percentages\n of 1000 datasets, are given at nodes. GenBank accession numbers of partial gene sequences derived from type strains are presented\n in Table S1. The tree was rooted by Gardnerella vaginalis ATCC 14018T. Bar, 0.04 substitutions per nucleotide position.\n \n \n \n " + ] + }, + "license": { + "value": [] + }, + "copyright": { + "value": [ + "Copyright ©\n \t\t2015 International Union of Microbiological Societies\n \t\n " + ] + } +} \ No newline at end of file diff --git a/examples/ijsem-quickscrape/ijsem-mounce-OLD-scraper/http_ijs.sgmjournals.org_content_63_Pt_11_4354.full/DC1 b/examples/ijsem-quickscrape/ijsem-mounce-OLD-scraper/http_ijs.sgmjournals.org_content_63_Pt_11_4354.full/DC1 new file mode 100644 index 00000000..7cdf1ee6 --- /dev/null +++ b/examples/ijsem-quickscrape/ijsem-mounce-OLD-scraper/http_ijs.sgmjournals.org_content_63_Pt_11_4354.full/DC1 @@ -0,0 +1,350 @@ + + + + + Supplementary material + + + + + + + + + + + +
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a/examples/ijsem-quickscrape/ijsem-mounce-OLD-scraper/http_ijs.sgmjournals.org_content_63_Pt_11_4354.full/fulltext.html b/examples/ijsem-quickscrape/ijsem-mounce-OLD-scraper/http_ijs.sgmjournals.org_content_63_Pt_11_4354.full/fulltext.html new file mode 100644 index 00000000..364023aa --- /dev/null +++ b/examples/ijsem-quickscrape/ijsem-mounce-OLD-scraper/http_ijs.sgmjournals.org_content_63_Pt_11_4354.full/fulltext.html @@ -0,0 +1,1307 @@ + + + + + Designation of type strains for seven species of the order Myxococcales and proposal for neotype strains of Cystobacter ferrugineus, + Cystobacter minus and Polyangium fumosum + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ +
+

Designation of type strains for seven species of the order Myxococcales and proposal for neotype strains of Cystobacter ferrugineus, Cystobacter minus and Polyangium fumosum

+
+
    + +
  1. Hans Reichenbach2,
  2. +
+
    +
  1. 1Leibniz-Institut DSMZ – Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH, Inhoffenstrasse 7B, 38124 Braunschweig, + Germany +
    +
  2. +
  3. 2Helmholtz-Zentrum für Infektionsforschung, Inhoffenstrasse 7, 38124 Braunschweig, Germany +
    +
  4. +
+
    +
  1. Corresponding
    Elke Lang ela{at}dsmz.de
  2. +
+
+
+ +

Abstract

+ +

Ten species of the order Myxococcales with validly published names are devoid of living type strains. Four species of the genus Chondromyces are represented by dead herbarium samples as the type material. For a species of the genus Melittangium and two species of the genus Polyangium, no physical type material was assigned at the time of validation of the names or later on. In accordance with rule 18f of + the International Code of Nomenclature of Bacteria the following type strains are designated for these species: strain Cm + a14T ( = DSM 14605T = JCM 12615T) as the type strain of Chondromyces apiculatus, strain Cm c5T ( = DSM 14714T = JCM 12616T) as the type strain of Chondromyces crocatus, strain Sy t2T ( = DSM 14631T = JCM 12617T) as the type strain of Chondromyces lanuginosus, strain Cm p51T ( = DSM 14607T = JCM 12618T) as the type strain of Chondromyces pediculatus, strain Me b8T ( = DSM 14713T = JCM 12633T) as the type strain of Melittangium boletus, strain Pl s12T ( = DSM 14670T = JCM 12637T) as the type strain of Polyangium sorediatum and strain Pl sm5T ( = DSM 14734T = JCM 12638T) as the type strain of Polyangium spumosum. Furthermore, the type strains given for three species of the genera Cystobacter and Polyangium had been kept at one university institute and have been lost according to our investigations. In accordance with Rule 18c + of the Bacteriological Code, we propose the following neotype strains: strain Cb fe18 ( = DSM 14716  = JCM 12624) as the neotype + strain of Cystobacter ferrugineus, strain Cb m2 ( = DSM 14751 = JCM 12627) as the neotype strain of Cystobacter minus and strain Pl fu5 ( = DSM 14668 = JCM 12636) as the neotype strain of Polyangium fumosum. The proposals of the strains are based on the descriptions and strain proposals given in the respective chapters of Bergey’s Manual of Systematic Bacteriology (2005). +

+ +
+
+ +
    +
  • +

    Retired. +

    +
  • +
  • +

    Two supplementary tables are available with the online version of this paper.

    +
  • +
+
+

An exceptionally high number of myxobacterial species descriptions is not supported by the availability of formally acknowledged + living type strain material. Because of this lack of material, the species could not be included, for example, in species-representing + 16S rRNA gene sequence databases. These are the most frequently used guides in taxonomy currently, and for that reason, great + efforts are taken to fill the sequencing gaps (Yarza et al., 2013). The International Code of Nomenclature of Bacteria (Lapage et al., 1992) allows for the designation of type strains in cases where descriptions or dead specimens represent the type given for species + with validly published species names. The code also allows for the proposal of neotype strains if a specimen of the strain + on which the original description was based cannot be found. These measures have been installed in order to clear the way + for inclusion of such species in future examinations, in particular in studies including ‘new’ methods which had not been + applied at the time of the species description. In this communication, we formally designate type strains for seven and formally + propose neotype strains for three species of the order Myxococcales. +

+

The present wording of Rule 18f of the International Code is: ‘If a description or illustration constitutes, or a dead preserved + specimen has been designated as the type of a species [Rule 18a(1)] and a later strain of this species is cultivated, then + the type strain may be designated by the person who isolated the strain or by a subsequent author. This type strain shall + then replace the description, illustration or preserved specimen as the nomenclatural type. The designation of a type strain + in this manner must be published in the IJSB/IJSEM, the authorship and date of priority of publication being determined by + the effective and valid publication of the name by the original authors (Rule 24b)’. +

+

The presently designated type strains of the species Chondromyces apiculatus (Thaxter, 1897), Chondromyces crocatus (Berkeley & Curtis, 1874), Chondromyces lanuginosus (Kofler, 1913) and Chondromyces pediculatus (Thaxter, 1904) are dead herbarium specimens in the Thaxter collection (TC), housed in the Farlow Herbarium, Harvard University, Cambridge, + USA (Table 1). Howard McCurdy studied myxobacteria at the University of Windsor, Ontario, Canada during the period around 1960–1970. He + assigned specific samples of the Thaxter collection as the types of these species (McCurdy, 1971). The species names were included in the Approved Lists (Skerman et al., 1980). According to a curator of the herbarium, the specimen for Chondromyces lanuginosus seems to be lost whereas the other three specimens are still there, dried on the original substrates, accompanied by some + slides. +

+
+
+
View this table: +
+
+
Table 1. + Myxobacterial species for which a cultivable type strain or neotype strain is formally proposed and the 16S rRNA sequences + of the proposed neotype strains. AL, type strain as given in Approved Lists (Skerman et al., 1980). VL, types as given in Validation List No 31 (Brockman, 1989b, c) + +
+
+
+

For the species Melittangium boletus (Jahn, 1924), Polyangium sorediatum (Brockman, 1989a) and Polyangium spumosum (Brockman, 1989a) no physical type strains were assigned in the Approved Lists (Skerman et al., 1980) or in Validation List No. 31 (Brockman, 1989b,c), respectively. Instead, the descriptions of Brockman (1989a) or simply the statement ‘not cultivated’ are given. +

+

Bergey’s Manual of Systematic Bacteriology, second edition, includes comprehensive chapters about the members of the order + Myxococcales. Reichenbach (2005a, b, c, d, e) are the chapters relevant to the taxa mentioned in this paper. These chapters are based on the experience and knowledge + accumulated during 40 years of intense investigations on myxobacteria and were written after more than 3000 myxobacterial + strains had been isolated. Based on the original species descriptions, appropriate strains were selected and described as + the type strains of the respective species (Table 1). However, it has not been formally proposed in the IJSEM until now to accept these strains as the type strains. +

+

For the reason that presently dead preserved material constitutes-, or a description has been designated-, the type strain + of the mentioned species, or no type strain has been assigned, it is formally proposed that the strains selected by Reichenbach + shall be designated the type strains of the respective species according to Rule 18f. The proposed type strains listed in + Table 1 shall replace the dead specimen or descriptions. These are Chondromyces apiculatus Cm a14T, Chondromyces crocatus Cm c5T, Chondromyces lanuginosus Sy t2T, Chondromyces pediculatus Cm p51T, M. boletus Me b8T, P. sorediatum Pl s12T and P. spumosum Pl sm5T. The prerequisite for the acceptance of type strains, their deposit and availability in two culture collections is achieved. + The designation of the type strains is based on the descriptions given in the respective chapters of Bergey’s Manual (Reichenbach 2005a, c, d). In order to facilitate the comparison of these recent descriptions with those of the authors who originally proposed, revived + or emended the species these original descriptions are assembled in Table S1 available in IJSEM Online. The fatty acid composition + of the proposed type strains are given in Table S2 (Garcia et al., 2011). The figures from the original descriptions and of the proposed type strains are shown face to face with figures showing + the proposed type strains in Figs 110. +

+
+
Fig. 1.
View larger version: + +
+
+
Fig. 1. + +

Chondromyces apiculatus. (a) Drawing from Thaxter (1897), plate XXX on pages 405–406. (b) Fruiting body (bar, 100 µm) and vegetative cells (insert; bar, 10 µm) of Cm a14T. +

+ +
+
+
+
+
Fig. 10.
View larger version: + +
+
+
Fig. 10. + +

Polyangium fumosum. (a) Drawing from Krzemieniewska & Krzemieniewski (1930), plate XVI, nos 6–9 depict P. fumosum. Courtesy of the Polish Botanical Society. (b) Swarm of PI fu5 (bar, 2000 µm) and single sporangium of PI fu5 (insert; bar, + 100 µm). (c) Fruiting bodies of PI fu5. Bar, 300 µm. +

+ +
+
+
+

The Bacteriological Code also allows for the proposal of neotype strains according to Rule 18c: ‘If a strain on which the + original description was based cannot be found, a neotype strain may be proposed. A neotype strain must be proposed (proposed + neotype) in the IJSB, together with citation of the author(s) of the name, a description or reference to an effectively published + description and a record of the permanently established culture collection(s) where the strain is deposited (see also Note + 1 to Rule 24a)’. +

+

The species Cystobacter ferrugineus, Cystobacter minus and Polyangium fumosum were first described by Krzemieniewska & Krzemieniewski (1926, 1927, 1930). McCurdy assigned three of his isolates as the type strains for the above-mentioned three species (McCurdy, 1970; Table 1). The species names and type strains were included in the Approved Lists (Skerman et al., 1980) but they have never been deposited in a culture collection to the best of our knowledge. In 2007, we wrote a letter to the + head of the microbiology laboratory of the University of Windsor with the request for subcultures of the strains Cystobacter ferrugineus M-203T, Cystobacter minus M-307T and P. fumosum M257T. Even though the importance for microbial taxonomy was stressed there was no response. In 2012, another attempt to contact + the department at Windsor University was more successful in the respect that we received answers from two colleagues at Windsor + and from H. D. McCurdy who retired several years ago. However, they informed us that they cannot find the samples. Since 1981, + there have been no scientific papers originating from the University of Windsor dealing with myxobacteria (PubMed), a fact + additionally suggesting that nobody at the university had a research interest to keep the cultures alive or, at least, under + surveillance. For that reasons we conclude that these cultures must have been lost. +

+

Since the presently assigned type strains of the mentioned species are no longer available as living cultures it is formally + proposed that the strains selected by Reichenbach shall be proposed as the neotype strains of the respective species in accordance + with Rule 18c, as given in Table 1. The deposit and availability of the neotype strains from two culture collections is achieved. The proposals of the neotype + strains are based on the suggestions in (Reichenbach (2005b, d). In these chapters, the strains Cystobacter ferrugineus Cb fe18, Cystobacter minus Cb m2 and P. fumosum Pl fu5 were proposed as the type strains according to the species descriptions given in the respective chapters which rely + on the original species descriptions by Krzemieniewska and Krzemieniewski and McCurdy (Reichenbach 2005b, d). However, since type strains have already been assigned these strains have to be proposed as the neotype strains of the + respective species according to rule 18c. +

+
+
Fig. 2.
View larger version: + +
+
+
Fig. 2. + +

Chondromyces crocatus. (a) Drawing from Berkeley (1857), page 313. (b) Fruiting bodies of Cm c5T. Bar, 500 µm. +

+ +
+
+
+
+
Fig. 3.
View larger version: + +
+
+
Fig. 3. + +

Chondromyces lanuginosus. (a) Figures from Kofler (1913), Figs 13 on page 877 depict Chondromyces lanuginosus. Courtesy Österreichische Akademie der Wissenschaften. (b) Fruiting body of Sy t2T. Bar, 100 µm. +

+ +
+
+
+
+
Fig. 4.
View larger version: + +
+
+
Fig. 4. + +

Chondromyces pediculatus. (a) Drawing from Thaxter (1904), plate XXVI on page 411; nos 7–13 depict Chondromyces pediculatus. (b) Fruiting body of Cm p51T. Bar 100 µm. +

+ +
+
+
+
+
Fig. 5.
View larger version: + +
+
+
Fig. 5. + +

Melittangium boletus. (a) Drawing from Jahn (1924), plate II, Fig. 17 on page 78. Courtesy Bornträger-Cramer, www.borntraeger-cramer.de. (b) and (c) Fruiting bodies of Me b8T. Bars, 120 and 80 µm, respectively. +

+ +
+
+
+
+
Fig. 6.
View larger version: + +
+
+
Fig. 6. + +

Polyangium sorediatum. (a) Drawing from Thaxter (1904), plate XXVII. Nos 22–30 depict P. sorediatum. (b and c) Fruiting bodies of PI s12T. Insert: crushed sporangium releasing the single sporangioles. Bars, 200 µm. +

+ +
+
+
+
+
Fig. 7.
View larger version: + +
+
+
Fig. 7. + +

Polyangium spumosum. (a) Figures from Krzemieniewska & Krzemieniewski (1926), plate V; no. 19 depicts P. spumosum and from Krzemieniewska & Krzemieniewski (1930), plate XVI; nos 10–12 depict P. spumosum. Courtesy of the Polish Botanical Society. (b–d) Degenerated fruiting bodies of PI sm5T. Bars, 500, 100 and 250 µm, respectively. +

+ +
+
+
+
+
Fig. 8.
View larger version: + +
+
+
Fig. 8. + +

Cystobacter ferrugineus. (a) Figures from McCurdy (1970). (b–d) Strain Cb fe18, (b) myxospores and (c) fruiting bodies on Escherichia coli as food bacteria and (d) on a cellulose plate. Bars, 10 µm, 1 mm and 10 mm, respectively. +

+ +
+
+
+
+
Fig. 9.
View larger version: + +
+
+
Fig. 9. + +

Cystobacter minus. (a), Figures from McCurdy (1970). (b and c), Fruiting bodies of Cb m2. Bars, 500 µm and 200 µm, respectively. +

+ +
+
+
+
+ +

Acknowledgements

+ +

We are thankful to K. Poling and I. Churchill at Windsor University, G. Lewis-Gentry at the Harvard University Herbaria and + H. D. McCurdy for taking the effort to investigate the disposition of the type materials. +

+ +
+
+ +

References

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+ + \ No newline at end of file diff --git a/examples/ijsem-quickscrape/ijsem-mounce-OLD-scraper/http_ijs.sgmjournals.org_content_63_Pt_11_4354.full/fulltext.pdf b/examples/ijsem-quickscrape/ijsem-mounce-OLD-scraper/http_ijs.sgmjournals.org_content_63_Pt_11_4354.full/fulltext.pdf new file mode 100644 index 00000000..2c9c5ebd Binary files /dev/null and b/examples/ijsem-quickscrape/ijsem-mounce-OLD-scraper/http_ijs.sgmjournals.org_content_63_Pt_11_4354.full/fulltext.pdf differ diff --git a/examples/ijsem-quickscrape/ijsem-mounce-OLD-scraper/http_ijs.sgmjournals.org_content_63_Pt_11_4354.full/results.json b/examples/ijsem-quickscrape/ijsem-mounce-OLD-scraper/http_ijs.sgmjournals.org_content_63_Pt_11_4354.full/results.json new file mode 100644 index 00000000..c64840e5 --- /dev/null +++ b/examples/ijsem-quickscrape/ijsem-mounce-OLD-scraper/http_ijs.sgmjournals.org_content_63_Pt_11_4354.full/results.json @@ -0,0 +1,104 @@ +{ + "publisher": { + "value": [ + "Society for General Microbiology" + ] + }, + "journal": { + "value": [ + "International Journal of Systematic and Evolutionary\n Microbiology" + ] + }, + "title": { + "value": [ + "Designation of type strains for seven species of the order Myxococcales and proposal for neotype strains of Cystobacter ferrugineus, Cystobacter minus and Polyangium fumosum" + ] + }, + "authors": { + "value": [ + "Elke Lang", + "Hans Reichenbach" + ] + }, + "date": { + "value": [ + "11/01/2013" + ] + }, + "doi": { + "value": [ + "10.1099/ijs.0.056440-0" + ] + }, + "volume": { + "value": [ + "63" + ] + }, + "issue": { + "value": [ + "Pt 11" + ] + }, + "firstpage": { + "value": [ + "4354" + ] + }, + "abstract": { + "value": [ + "\n \n  Next Section\n Abstract\n \n Ten species of the order Myxococcales with validly published names are devoid of living type strains. Four species of the genus Chondromyces are represented by dead herbarium samples as the type material. For a species of the genus Melittangium and two species of the genus Polyangium, no physical type material was assigned at the time of validation of the names or later on. In accordance with rule 18f of\n the International Code of Nomenclature of Bacteria the following type strains are designated for these species: strain Cm\n a14T ( = DSM 14605T = JCM 12615T) as the type strain of Chondromyces apiculatus, strain Cm c5T ( = DSM 14714T = JCM 12616T) as the type strain of Chondromyces crocatus, strain Sy t2T ( = DSM 14631T = JCM 12617T) as the type strain of Chondromyces lanuginosus, strain Cm p51T ( = DSM 14607T = JCM 12618T) as the type strain of Chondromyces pediculatus, strain Me b8T ( = DSM 14713T = JCM 12633T) as the type strain of Melittangium boletus, strain Pl s12T ( = DSM 14670T = JCM 12637T) as the type strain of Polyangium sorediatum and strain Pl sm5T ( = DSM 14734T = JCM 12638T) as the type strain of Polyangium spumosum. Furthermore, the type strains given for three species of the genera Cystobacter and Polyangium had been kept at one university institute and have been lost according to our investigations. In accordance with Rule 18c\n of the Bacteriological Code, we propose the following neotype strains: strain Cb fe18 ( = DSM 14716  = JCM 12624) as the neotype\n strain of Cystobacter ferrugineus, strain Cb m2 ( = DSM 14751 = JCM 12627) as the neotype strain of Cystobacter minus and strain Pl fu5 ( = DSM 14668 = JCM 12636) as the neotype strain of Polyangium fumosum. The proposals of the strains are based on the descriptions and strain proposals given in the respective chapters of Bergey’s Manual of Systematic Bacteriology (2005).\n \n \n " + ] + }, + "fulltext_html": { + "value": [ + "http://ijs.sgmjournals.org/content/63/Pt_11/4354.full" + ] + }, + "fulltext_pdf": { + "value": [ + "http://ijs.sgmjournals.org/content/63/Pt_11/4354.full.pdf" + ] + }, + "supplementary_material": { + "value": [ + "http://ijs.sgmjournals.org/content/63/Pt_11/4354/suppl/DC1" + ] + }, + "figure": { + "value": [ + "http://ijs.sgmjournals.org/content/63/Pt_11/4354/F1.small.gif", + "http://ijs.sgmjournals.org/content/63/Pt_11/4354/F2.small.gif", + "http://ijs.sgmjournals.org/content/63/Pt_11/4354/F3.small.gif", + "http://ijs.sgmjournals.org/content/63/Pt_11/4354/F4.small.gif", + "http://ijs.sgmjournals.org/content/63/Pt_11/4354/F5.small.gif", + "http://ijs.sgmjournals.org/content/63/Pt_11/4354/F6.small.gif", + "http://ijs.sgmjournals.org/content/63/Pt_11/4354/F7.small.gif", + "http://ijs.sgmjournals.org/content/63/Pt_11/4354/F8.small.gif", + "http://ijs.sgmjournals.org/content/63/Pt_11/4354/F9.small.gif", + "http://ijs.sgmjournals.org/content/63/Pt_11/4354/F10.small.gif" + ] + }, + "figure_caption": { + "value": [ + "Fig. 1. \n \n Chondromyces apiculatus. (a) Drawing from Thaxter (1897), plate XXX on pages 405–406. (b) Fruiting body (bar, 100 µm) and vegetative cells (insert; bar, 10 µm) of Cm a14T.\n \n \n \n ", + "Fig. 10. \n \n Polyangium fumosum. (a) Drawing from Krzemieniewska & Krzemieniewski (1930), plate XVI, nos 6–9 depict P. fumosum. Courtesy of the Polish Botanical Society. (b) Swarm of PI fu5 (bar, 2000 µm) and single sporangium of PI fu5 (insert; bar,\n 100 µm). (c) Fruiting bodies of PI fu5. Bar, 300 µm.\n \n \n \n ", + "Fig. 2. \n \n Chondromyces crocatus. (a) Drawing from Berkeley (1857), page 313. (b) Fruiting bodies of Cm c5T. Bar, 500 µm.\n \n \n \n ", + "Fig. 3. \n \n Chondromyces lanuginosus. (a) Figures from Kofler (1913), Figs 1–3 on page 877 depict Chondromyces lanuginosus. Courtesy Österreichische Akademie der Wissenschaften. (b) Fruiting body of Sy t2T. Bar, 100 µm.\n \n \n \n ", + "Fig. 4. \n \n Chondromyces pediculatus. (a) Drawing from Thaxter (1904), plate XXVI on page 411; nos 7–13 depict Chondromyces pediculatus. (b) Fruiting body of Cm p51T. Bar 100 µm.\n \n \n \n ", + "Fig. 5. \n \n Melittangium boletus. (a) Drawing from Jahn (1924), plate II, Fig. 17 on page 78. Courtesy Bornträger-Cramer, www.borntraeger-cramer.de. (b) and (c) Fruiting bodies of Me b8T. Bars, 120 and 80 µm, respectively.\n \n \n \n ", + "Fig. 6. \n \n Polyangium sorediatum. (a) Drawing from Thaxter (1904), plate XXVII. Nos 22–30 depict P. sorediatum. (b and c) Fruiting bodies of PI s12T. Insert: crushed sporangium releasing the single sporangioles. Bars, 200 µm.\n \n \n \n ", + "Fig. 7. \n \n Polyangium spumosum. (a) Figures from Krzemieniewska & Krzemieniewski (1926), plate V; no. 19 depicts P. spumosum and from Krzemieniewska & Krzemieniewski (1930), plate XVI; nos 10–12 depict P. spumosum. Courtesy of the Polish Botanical Society. (b–d) Degenerated fruiting bodies of PI sm5T. Bars, 500, 100 and 250 µm, respectively.\n \n \n \n ", + "Fig. 8. \n \n Cystobacter ferrugineus. (a) Figures from McCurdy (1970). (b–d) Strain Cb fe18, (b) myxospores and (c) fruiting bodies on Escherichia coli as food bacteria and (d) on a cellulose plate. Bars, 10 µm, 1 mm and 10 mm, respectively.\n \n \n \n ", + "Fig. 9. \n \n Cystobacter minus. (a), Figures from McCurdy (1970). (b and c), Fruiting bodies of Cb m2. Bars, 500 µm and 200 µm, respectively.\n \n \n \n " + ] + }, + "license": { + "value": [] + }, + "copyright": { + "value": [ + "Copyright ©\n \t\t2015 International Union of Microbiological Societies\n \t\n " + ] + } +} \ No newline at end of file diff --git a/examples/ijsem-quickscrape/ijsem-mounce-OLD-scraper/http_ijs.sgmjournals.org_content_63_Pt_12_4586.full/DC1 b/examples/ijsem-quickscrape/ijsem-mounce-OLD-scraper/http_ijs.sgmjournals.org_content_63_Pt_12_4586.full/DC1 new file mode 100644 index 00000000..beca2227 --- /dev/null +++ b/examples/ijsem-quickscrape/ijsem-mounce-OLD-scraper/http_ijs.sgmjournals.org_content_63_Pt_12_4586.full/DC1 @@ -0,0 +1,356 @@ + + + + + Supplementary material + + + + + + + + + + + +
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Spirosoma endophyticum sp. nov., isolated from Zn- and Cd-accumulating Salix caprea

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Spirosoma endophyticum sp. nov., isolated from Zn- and Cd-accumulating Salix caprea

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  1. Angela Sessitsch
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  1. AIT Austrian Institute of Technology GmbH, Bioresources Unit, Tulln, Austria
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  1. Correspondence
    Angela Sessitsch angela.sessitsch{at}ait.ac.at
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Abstract

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A Gram-reaction-negative, yellow-pigmented strain, designated EX36T, was characterized using a polyphasic approach comprising phylogenetic, morphological and genotypic analyses. The endophytic + strain was isolated from Zn/Cd-accumulating Salix caprea in Arnoldstein, Austria. Analysis of the 16S rRNA gene demonstrated that the novel strain is most closely related to members + of the genus Spirosoma (95 % sequence similarity with Spirosoma linguale). The genomic DNA G+C content was 47.2 mol%. The predominant quinone was and the major cellular fatty acids were summed feature + 3 (iso-C15 : 0 2-OH and/or C16 : 1ω7c), C16 : 1ω5c, iso-C17 : 0 3-OH and iso-C15 : 0. On the basis of its phenotypic and genotypic properties, strain EX36T should be classified as a novel species of the genus Spirosoma, for which the name Spirosoma endophyticum sp. nov. is proposed. The type strain is EX36T ( = DSM 26130T = LMG 27272T). +

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    The GenBank/EMBL/DDBJ accession number for the 16S rRNA gene sequence of strain EX36T is GQ342559. +

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    A supplementary figure is available with the online version of this paper.

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This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted + use, distribution, and reproduction in any medium, provided the original work is properly cited. +

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The genus Spirosoma was first proposed by Larkin & Borrall (1984) and belongs to the family Flexibacteraceae in the phylum Bacteroidetes. At the time of writing the genus Spirosoma includes five species, the type species Spirosoma linguale (Larkin & Borrall, 1984), Spirosoma rigui (Baik et al., 2007), Spirosoma panaciterrae (Ten et al., 2009), Spirosoma spitsbergense and Spirosoma luteum (Finster et al., 2009). So far, Spirosoma strains have been isolated from various habitats, such as fresh water, permafrost soil or soil from a ginseng field. Strain + EX36T, which is proposed in this study to represent a novel species, was isolated in course of the analysis of bacteria associated + with the heavy metal accumulating plant Salix caprea (Kuffner et al., 2010). +

+

For the isolation of strain EX36T, Salix caprea trees growing on a former Zn/Pb mining and processing site in Arnoldstein (Austria) were sampled (Kuffner et al., 2010). Xylem sap extract was directly plated on 10 % tryptic soy agar (TSA, Merck Darmstadt, Germany) and after 1 week of incubation + single colonies were picked and streaked on phosphate-poor MOPS medium (Neidhardt et al., 1974) containing 0.1 % glucose and 1 mM ZnSO4. The strain was routinely cultured on 10 % TSA. For maintenance, the cell material was suspended in 10 % tryptic soy broth + (TSB, Merck, Darmstadt, Germany) containing 15 % glycerol and stored at −80 °C. Endophytic colonization was confirmed by inoculating + two maize and two potato cultivars, growing the plants under in vitro conditions and reisolating the strain from root and stem tissues. +

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For the extraction of bacterial DNA the Gen Elute Bacterial Genomic DNA kit (Sigma–Aldrich) was used. The 16S rRNA gene was + amplified by PCR using the primers 8f (5′-AGAGTTTGATCCTGGCTCAG-3′) (Weisburg et al., 1991) and 1520r (5′-AAGGAGGTGATCCAGCCGCA-3′) (Edwards et al., 1989). Sequencing of the amplified PCR product was performed by LGC Genomics (Berlin, Germany). The obtained partial sequences + were assembled using the programs BioEdit (Hall, 1999) and seqman pro (DNAstar). The consensus sequence was subjected to nucleotide blast analysis (http://blast.ncbi.nlm.nih.gov/Blast.cgi) to search the database of the National Center for Biotechnology Information (NCBI) for the closest relatives of the bacterial + strains with validly published names. Sequence comparisons indicated that the isolate belonged to the family Flexibacteraceae. +

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Nearly complete 16S rRNA gene sequences of strain EX36T and of all species of the genus Spirosoma with validly published names and of selected species of the family Cytophagaceae, which were downloaded from the NCBI GenBank sequence database, were imported into the arb program package (Ludwig et al., 2004). Sequences were aligned into the silva SSURef 102 (Pruesse et al., 2007) database by using the option ‘autosearch by PT_server’ of the arb editor. Alignments were manually corrected using the arb editor. A maximum-likelihood phylogenetic tree was reconstructed using RAxML v. 7.4.2 (Stamatakis, 2006a) by execution of the following command line in raxmlGUI v. 1.3 (Silvestro & Michalak, 2012): raxmlHPC.exe -T 2 <number of processors >-f a -m GTRGAMMA -x 336 <seed1 >-p 115 <seed2 >-N 100 <bootstraps >-o CarHomin + <outgroup >-s <input file >-O <output order >. We used a combination of the Gamma model of rate heterogeneity (Yang, 1994) and the CAT model (Stamatakis, 2006b), which was implemented in the rapid bootstrapping algorithm, (Stamatakis et al., 2008) was performed with 100 replicates and using general time reversible (GTR) as the substitution matrix. In Fig. 1 the position of EX36T in the distinct cluster of the genus Spirosoma can be clearly recognized. The calculation of pairwise sequence similarity using a global alignment algorithm (Myers & Miller, 1988), which was implemented at the EzTaxon-e server (http://eztaxon-e.ezbiocloud.net/; Kim et al., 2012) showed highest sequence similarity values for strain EX36T to Spirosoma linguale DSM 74T (95.7 %), followed by S. luteum SPM-10T (93.9 %), S. spitsbergense SPM-9T (93.9 %), S. rigui KCTC 12531T (93.8 %) and S. panaciterrae Gsoil 1519T (92.5 %). +

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Fig. 1.
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Fig. 1. + +

Maximum-likelihood tree (bootstrap: 100 replicates) based on 16S rRNA gene sequence data (sequence length 1296 bp) showing + the phylogenetic position of strain EX36T among related species selected from the phylum Bacteroidetes. Cardiobacterium hominis ATCC 15826T (M35014) was used as an outgroup. +

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Growth of strain EX36T was tested at various temperatures (4, 20, 23, 28, 37 and 41 °C) on 10 % TSA plates for up to 1 week. The pH range for growth + (pH 4, 5, 6, 7, 8 and 9) was determined by measuring OD600 changes in cultures incubated at 28 °C with shaking at 190 r.p.m. compared with an uninoculated control. Salt tolerance was + determined by amending 10 % TSB with NaCl to final concentrations of 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.8, 1.0, 2.0, 3.0, 4.0, + 5.0 and 10.0 % NaCl (w/v). The Gram reaction of strain EX36T was determined by using the non-staining method described by Buck (1982). Pigment analysis of cells grown on 10 % TSA was performed in triplicates by extraction with acetone according to the method + described by Denner et al. (2001) using a U-2900 spectrophotometer (Hitachi). Minimal inhibition concentrations (MIC) for Zn and Cd were determined according + to the method of Kuffner et al. (2008). Additionally cells were tested for flexirubin pigments using the method described by Bernardet et al. (2002). Oxidase and catalase activity were tested as outlined by Smibert & Krieg (1994). Additional biochemical tests were performed by the Identification Service of the DSMZ (Leibniz-Institut DSMZ-Deutsche Sammlung + von Mikroorganismen und Zellkulturen GmbH, Braunschweig, Germany) using API 20NE (bioMérieux) and GENIII plates (Biolog). + Cell morphology after 4 days of growth at 28 °C was investigated using fluorescence and bright-field microscopy (IX81, Olympus; + Axiovert 200 M, Zeiss). Antibiotic susceptibility was determined by the disc diffusion method on 10 % TSA plates. +

+

Cells of strain EX36T were rod-shaped, Gram-reaction-negative and 1.2×2−17.5 µm in size (Fig S1, available in IJSEM Online). Most cells were arranged + in pairs, but filaments up to 55 µm were observed. EX36T showed yellowish, opaque, semi-translucent colonies with a smooth and shiny surface and a circular and convex shape. The + diameter of colonies grown on 10 % TSA at 28 °C for 1 week varied between 1.5 and 3.0 mm. The strain was positive for catalase + and oxidase activity; detailed results of biochemical and physiological analyses are listed in Table 1 and in the species description. In contrast to other species of the genus Spirosoma, cells of EX36T showed a length up to 17.5 µm, did not grow at 5 and 42 °C, did not tolerate NaCl concentrations higher than 0.6 % (w/v), + had the lowest genomic G+C content and showed differences in antibiotic susceptibility. Low tolerance of Cd and Zn was observed + (slow growth at 4 mM Zn and 1 mM Cd). The analysis of yellow pigments showed three absorption maxima at 428, 453 and 483 nm. + EX36T was negative for flexirubin-type pigments. +

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Table 1. + Differential characteristics of strain EX36T and recognized species of the genus Spirosoma + +

Strains: 1, EX36T (data from this study); 2, S. linguale DSM 74T (Larkin & Borrall, 1984; and this study); 3, S. luteum DSM 19990T (Finster et al., 2009); 4, S. spitsbergense DSM 19989T (Finster et al., 2009); 5, S. rigui KCTC 12531T (Baik et al., 2007); 6, S. panaciterrae DSM 21099T (Ten et al., 2009). All strains are catalase-positive, Gram-reaction-negative and negative for nitrate reduction, utilization of gluconate, + caprate, adipate and glycerol. +, Positive; −, negative; w, weakly positive; nd, not determined; r, resistant; s, susceptible. +

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Analyses of cellular fatty acid composition, respiratory quinones, polar lipids and chromosomal G+C content were performed + by the Identification Service of the DSMZ. The fatty acid profile was determined according to the protocol of the Microbial + Identification System (MIDI). The major fatty acids of strain EX36T were summed feature 3 (iso-C15 : 0 2-OH and/or C16 : 1ω7c; 49.3 %), C16 : 1ω5c (23.8 %), iso-C17 : 0 3-OH (6.2 %) and iso-C15 : 0 (5.4 %). A detailed overview of the cellular fatty acid profiles of all species of the genus Spirosoma can be found in Table 2. Differences between the fatty acid profile of EX36T and other species of the genus Spirosoma were found in the amounts of iso-C15 : 0, C16 : 1ω5c and summed feature 3. In contrast to S. linguale DSM 74T, the fatty acids C15 : 0 and anteiso-C15 : 0 were not detected. +

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View this table: +
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Table 2. + Fatty acid profiles (%) of strain EX36T and its closest phylogenetic neighbours from the genus Spirosoma + +

Strains: 1, EX36T (data from this study); 2, S. linguale DSM 74T (data from this study); 3, S. luteum DSM 19990T (Finster et al., 2009); 4, S. spitsbergense DSM 19989T (Finster et al., 2009); 5, S. rigui KCTC 12531T (Baik et al., 2007); 6, S. panaciterrae DSM 21099T (Ten et al., 2009). tr, Trace amount (<1 %); −, not detected. +

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The predominant menaquinone, in accordance with all other species of the genus Spirosoma, was MK-7. As polar lipids, phosphatidylethanolamine, two aminophospholipids, two aminolipids, a glycolipid and three unknown + lipids were detected on the TLC plate. The DNA G+C content of strain EX36T was 47.2 mol%, which is lower than reported values for all other species of the genus Spirosoma with validly published names. +

+

The analysis of DNA−DNA similarity of strain EX36T with its nearest phylogenetic neighbour S. linguale DSM 74T was also carried out by the Identification Service of the DSMZ. The experiment was performed in duplicates. DNA−DNA hybridization + showed a DNA−DNA similarity of 12.2 % (second measurement: 17.2 %), demonstrating that these two strains do not represent + the same species. +

+

The present data regarding 16S rRNA gene sequence analysis, physiological, chemotaxonomic and morphological properties indicates, + that strain EX36T represents a distinct species in the genus Spirosoma, for which the name Spirosoma endophyticum sp. nov. is proposed. +

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Description of Spirosomaendophytica sp. nov. +

+ +

Spirosom endophyticum (en.do.phy′ti.cum. Gr. Pref. endo within; Gr. n. phyton plant; L. neut. suff. ‐icum adjectival suffix used with the sense of belonging to; N.L. neut. adj. endophyticum within plant, referring to the endophytic nature of the strain and its isolation from plant tissue). +

+ +

Cells are rod-shaped, Gram-reaction-negative, non-spore-forming, with a size of 1.2×2–17.5 µm. A yellow pigment which is not + of the flexirubin type is produced. Filaments up to 55 µm may be formed. Colonies on 10 % TSA are opaque, semi-translucent + with a smooth and shiny surface and a circular, convex shape. Aerobic growth occurs at 20–28 °C (optimum at 28 °C), pH 5–8 + (optimum at pH 7); tolerates concentrations up to 0.6 % NaCl (w/v) in the medium, whereas best growth was achieved in absence + of NaCl. Positive for catalase and oxidase activity. Nitrate is not reduced and indole is not produced. Negative for glucose + fermentation, hydrolysis of arginine and gelatin, and urease activities and positive for aesculin hydrolysis. Does not utilize + the following substrates: arabinose, mannitol, N-acetylglucosamine, gluconate, caprate, adipate, malate, citrate, phenylacetate, β-methyl d-glucoside, d-salicin, n-acetyl-β-d-mannosamine, n-acetyl neuraminic acid, d-galactose, d-fucose, l-fucose, l-rhamnose, inosine, d-arabitol, myo-inositol, d-aspartic acid, d-serine, glycyl-l-proline, l-alanine, l-arginine, l-aspartic acid, l-glutamic acid, l-serine and pectin. The following substrates are weakly utilized: dextrin, maltose, trehalose, cellobiose, gentiobiose, sucrose, + turanose, stachyose, α-lactose, melibiose, α-d-glucose, d-mannose, d-fructose, d-mannitol and l-histidine. d-Raffinose and N-acetyl-d-glucosamine are utilized. Susceptible to the following antibiotics (µg per disc): streptomycin (10), kanamycin (30), chloramphenicol + (60) and rifampicin (15) and resistant to ampicillin (10), polymyxin B (20), tetracycline (15) and erythromycin (15). The + major fatty acids are summed feature 3 (iso-C15 : 0 2-OH and/or C16 : 1ω7c), C16 : 1ω5c, iso-C17 : 0 3-OH and iso-C15 : 0; the complete fatty acid profile can be found in Table 2. The predominant menaquinone is MK-7. The major polar lipid is phosphatidylethanolamine. +

+ +

The type strain, EX36T ( = DSM 26130T = LMG 27272T), was isolated from Zn/Cd-accumulating Salix caprea in Arnoldstein, Austria. The DNA G+C content of the type strain is 47.2 mol%. +

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Acknowledgements

+ +

We thank Marlies Polt for technical support and Katharina Fallmann, Friederike Trognitz and Muhammad Naveed for helpful discussions. + This study was supported by the Austrian Science Foundation [Förderung der wissenschaftlichen Forshung (FWF) grant no. L561-B17]. +

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References

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+ + \ No newline at end of file diff --git a/examples/ijsem-quickscrape/ijsem-mounce-OLD-scraper/http_ijs.sgmjournals.org_content_63_Pt_12_4586.full/fulltext.pdf b/examples/ijsem-quickscrape/ijsem-mounce-OLD-scraper/http_ijs.sgmjournals.org_content_63_Pt_12_4586.full/fulltext.pdf new file mode 100644 index 00000000..5c2ed86f Binary files /dev/null and b/examples/ijsem-quickscrape/ijsem-mounce-OLD-scraper/http_ijs.sgmjournals.org_content_63_Pt_12_4586.full/fulltext.pdf differ diff --git a/examples/ijsem-quickscrape/ijsem-mounce-OLD-scraper/http_ijs.sgmjournals.org_content_63_Pt_12_4586.full/results.json b/examples/ijsem-quickscrape/ijsem-mounce-OLD-scraper/http_ijs.sgmjournals.org_content_63_Pt_12_4586.full/results.json new file mode 100644 index 00000000..d3867c09 --- /dev/null +++ b/examples/ijsem-quickscrape/ijsem-mounce-OLD-scraper/http_ijs.sgmjournals.org_content_63_Pt_12_4586.full/results.json @@ -0,0 +1,90 @@ +{ + "publisher": { + "value": [ + "Society for General Microbiology" + ] + }, + "journal": { + "value": [ + "International Journal of Systematic and Evolutionary\n Microbiology" + ] + }, + "title": { + "value": [ + "Spirosoma endophyticum sp. nov., isolated from Zn- and Cd-accumulating Salix caprea" + ] + }, + "authors": { + "value": [ + "Julia Fries", + "Stefan Pfeiffer", + "Melanie Kuffner", + "Angela Sessitsch" + ] + }, + "date": { + "value": [ + "12/01/2013" + ] + }, + "doi": { + "value": [ + "10.1099/ijs.0.052654-0" + ] + }, + "volume": { + "value": [ + "63" + ] + }, + "issue": { + "value": [ + "Pt 12" + ] + }, + "firstpage": { + "value": [ + "4586" + ] + }, + "abstract": { + "value": [ + "\n \n  Next Section\n Abstract\n \n A Gram-reaction-negative, yellow-pigmented strain, designated EX36T, was characterized using a polyphasic approach comprising phylogenetic, morphological and genotypic analyses. The endophytic\n strain was isolated from Zn/Cd-accumulating Salix caprea in Arnoldstein, Austria. Analysis of the 16S rRNA gene demonstrated that the novel strain is most closely related to members\n of the genus Spirosoma (95 % sequence similarity with Spirosoma linguale). The genomic DNA G+C content was 47.2 mol%. The predominant quinone was and the major cellular fatty acids were summed feature\n 3 (iso-C15 : 0 2-OH and/or C16 : 1ω7c), C16 : 1ω5c, iso-C17 : 0 3-OH and iso-C15 : 0. On the basis of its phenotypic and genotypic properties, strain EX36T should be classified as a novel species of the genus Spirosoma, for which the name Spirosoma endophyticum sp. nov. is proposed. The type strain is EX36T ( = DSM 26130T = LMG 27272T).\n \n \n " + ] + }, + "fulltext_html": { + "value": [ + "http://ijs.sgmjournals.org/content/63/Pt_12/4586.full" + ] + }, + "fulltext_pdf": { + "value": [ + "http://ijs.sgmjournals.org/content/63/Pt_12/4586.full.pdf" + ] + }, + "supplementary_material": { + "value": [ + "http://ijs.sgmjournals.org/content/63/Pt_12/4586/suppl/DC1" + ] + }, + "figure": { + "value": [ + "http://ijs.sgmjournals.org/content/63/Pt_12/4586/F1.small.gif" + ] + }, + "figure_caption": { + "value": [ + "Fig. 1. \n \n Maximum-likelihood tree (bootstrap: 100 replicates) based on 16S rRNA gene sequence data (sequence length 1296 bp) showing\n the phylogenetic position of strain EX36T among related species selected from the phylum Bacteroidetes. Cardiobacterium hominis ATCC 15826T (M35014) was used as an outgroup.\n \n \n \n " + ] + }, + "license": { + "value": [ + "\n This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted\n use, distribution, and reproduction in any medium, provided the original work is properly cited.\n \n " + ] + }, + "copyright": { + "value": [ + "Copyright ©\n \t\t2015 International Union of Microbiological Societies\n \t\n " + ] + } +} \ No newline at end of file diff --git a/examples/ijsem-quickscrape/ijsemout-rsu-scraper/http_ijs.sgmjournals.org_content_53_1_1.full/fulltext.html b/examples/ijsem-quickscrape/ijsemout-rsu-scraper/http_ijs.sgmjournals.org_content_53_1_1.full/fulltext.html new file mode 100644 index 00000000..62ce95ee --- /dev/null +++ b/examples/ijsem-quickscrape/ijsemout-rsu-scraper/http_ijs.sgmjournals.org_content_53_1_1.full/fulltext.html @@ -0,0 +1,625 @@ + + + + + Validation of publication of new names and new combinations previously effectively published outside the IJSEM + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ +
+

Validation of publication of new names and new combinations previously effectively published outside the IJSEM

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+ +

Abstract

+

The purpose of this announcement is to effect the valid publication of the following new names and new combinations under + the procedure described previously [Int J Syst Bacteriol 27(3), iv (1977)]. Authors and other individuals wishing to have new names and/or combinations included in future lists should + send the pertinent reprint or a photocopy thereof to the IJSEM Editorial Office for confirmation that all of the other requirements for valid publication have been met. It should be noted that the date + of valid publication of these new names and combinations is the date of publication of this list, not the date of the original + publication of the names and combinations. The authors of the new names and combinations are as given below, and these authors' + names will be included in the author index of the present issue and in the volume author index. Inclusion of a name on these + lists validates the name and thereby makes it available in bacteriological nomenclature. The inclusion of a name on this list + is not to be construed as taxonomic acceptance of the taxon to which the name is applied. Indeed, some of these names may, + in time, be shown to be synonyms, or the organisms may be transferred to another genus, thus necessitating the creation of + a new combination.

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Sulfurimonas gotlandica sp. nov., a chemoautotrophic and psychrotolerant epsilonproteobacterium isolated from a pelagic redoxcline, and an emended + description of the genus Sulfurimonas

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  1. Klaus Jürgens1
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  1. 1IOW Leibniz Institute for Baltic Sea Research Warnemuende (IOW), Germany +
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  3. 2Royal Netherlands Institute of Sea Research (NIOZ), Yerseke, Netherlands +
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  5. 3Arbeitsbereich Medizinische Biologie und Elektronenmikroskopisches Zentrum (EMZ), Universität Rostock, Germany +
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  1. Correspondence
    Matthias Labrenz matthias.labrenz{at}io-warnemuende.de
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    Present address: Center for Microbial Oceanography: Research and Education, SOEST, University of Hawaii at Manoa, Honolulu, HI 96822, USA. +

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    § Present address: Robert Koch Institute, Berlin, Germany. +

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Abstract

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A psychro- and aerotolerant bacterium was isolated from the sulfidic water of a pelagic redox zone of the central Baltic Sea. + The slightly curved rod- or spiral-shaped cells were motile by one polar flagellum or two bipolar flagella. Growth was chemolithoautotrophic, + with nitrate or nitrite as electron acceptor and either a variety of sulfur species of different oxidation states or hydrogen + as electron donor. Although the bacterium was able to utilize organic substances such as acetate, pyruvate, peptone and yeast + extract for growth, these compounds yielded considerably lower cell numbers than obtained with reduced sulfur or hydrogen; + in addition, bicarbonate supplementation was necessary. The cells also had an absolute requirement for NaCl. Optimal growth + occurred at 15 °C and at pH 6.6–8.0. The predominant fatty acid of this organism was 16 : 1ω7c, with 3-OH 14 : 0, 16 : 0, 16 : 1ω5c+t and 18 : 1ω7c present in smaller amounts. The DNA G+C content was 33.6 mol%. As determined in 16S rRNA gene sequence phylogeny analysis, + the isolate belongs to the genus Sulfurimonas, within the class Epsilonproteobacteria, with 93.7 to 94.2 % similarity to the other species of the genus Sulfurimonas, Sulfurimonas autotrophica, Sulfurimonas paralvinellae and Sulfurimonas denitrificans. However, the distinct physiological and genotypic differences from these previously described taxa support the description + of a novel species, Sulfurimonas gotlandica sp. nov. The type strain is GD1T ( = DSM 19862T = JCM 16533T). Our results also justify an emended description of the genus Sulfurimonas. +

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    These authors contributed equally to this study. +

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    The GenBank/EMBL/DDBJ accession number for the 16S rRNA gene sequence of strain GD1T is AFRZ01000001 (804671..806178), locus_tag SMGD1_rRNA3. +

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This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted + use, distribution, and reproduction in any medium, provided the original work is properly cited. +

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+

Deep-sea vents are among the most productive marine systems on Earth. The discovery of these primarily chemoautotrophic environments, + in 1977, has been followed by an appreciation of the remarkable physiological and phylogenetic diversity of their endosymbiotic + and often thermophilic inhabitants, most commonly species of the class Epsilonproteobacteria. Moreover, deep-sea vent chemolithoautotrophs are thought to be representatives of the earliest biological communities on + Earth (see the review by Nakagawa & Takai, 2008). Indeed, many epsilonproteobacteria are globally ubiquitous in oxygen-deficient and sulfide-rich marine and terrestrial + ecosystems, which accommodate their predominantly auto- to mixotrophic lifestyles (Campbell et al., 2006). A number of studies have verified the significant role of epsilonproteobacteria in biogeochemical cycles, particularly + those which are sulfur-dependent, as is the case in deep-sea hydrothermal fields (Nakagawa et al., 2005; Campbell et al., 2006), sulfidic cave springs (Engel et al., 2004) and autotrophic episymbiotic associations (Suzuki et al., 2006). In the suboxic to sulfidic transition zones of aquatic pelagic redox zones, high dark CO2 fixation rates, mainly due to the activities of epsilonproteobacterial chemolithoautotrophs, have been determined, for instance, + in the Black Sea and the Baltic Sea (Grote et al., 2008; Glaubitz et al., 2010; Jost et al., 2008). +

+

The Baltic Sea is among the largest brackish basins of the world, with periodically anoxic conditions in its bottom waters. + In the region known as the Baltic Proper there are a number of such areas, including the Gotland Deep, where at depths below + 50–60 m a stable halocline separates the water column into an upper oxygenated layer and underlying oxygen-deficient and anoxic/sulfidic + layers (Lepland & Stevens, 1998; Neretin et al., 2003), in which high dark CO2 fixation rates have been reported (Jost et al., 2010). +

+

In stimulation experiments (Labrenz et al., 2005; Brettar et al., 2006), quantitative 16S rRNA PCR (Labrenz et al., 2004), catalysed reporter deposition–fluorescence in situ hybridization (CARD-FISH; Grote et al., 2007) and microautoradiography (MICRO)-CARD-FISH (Grote et al., 2008) analyses, as well as 16S rRNA stable isotope probing (RNA-SIP; Glaubitz et al., 2009), the epsilonproteobacterial ‘Uncultured Helicobacteraceae G138eps1/GD17’ subgroup was shown to account for up to 30 % of the total cell numbers in pelagic redox zones of the central + Baltic Sea. The abundance of these bacteria highlights the importance of chemolithoautotrophic denitrification, which was + convincingly demonstrated to be the major N-loss process in water columns with a sulfide–nitrate interface (Brettar & Rheinheimer, 1991; Hannig et al., 2007; Jensen et al., 2009), catalysed by the GD17 group as potential key organisms for this process. According to its 16S rRNA phylogeny, the ‘Uncultured + Helicobacteraceae G138eps1/GD17’ subgroup belongs to the genus Sulfurimonas, which comprises mesophilic, facultatively anaerobic, chemolithoautotrophic species originating from deep-sea hydrothermal + and marine sulfidic environments (Takai et al., 2006). In previous work (Grote et al., 2012) we described the isolation of strain Gotland Deep 1 (GD1T), a close phylogenetic relative (16S rRNA similarity of 95.7 %) and thus representative of the Baltic Sulfurimonas ‘Uncultured Helicobacteraceae G138eps1/GD17’ subgroup. Selected genomic and physiological data suggested an ecological role for GD1T, especially with respect to its sulfide detoxification ability (Grote et al., 2012). Here, we expand on previous work by presenting the taxonomic characteristics of GD1T. Our results form the basis of an emended description of the genus Sulfurimonas. +

+

Strain GD1T was isolated from a pelagic redox zone of the Gotland Deep in the central Baltic Sea during a research cruise on board the + RV Alkor in May 2005 (57° 19.2′ N 20° 03′ E). Water was collected in a free-flow bottle attached to a CTD-rosette from a depth of + 215 m. The in situ temperature was 6 °C, the salinity 13 practical salinity units (PSU), and the sulfide concentration 11 µM. Directly on board, + 100 µM KNO3 and 100 µM Na2S2O3 were added to the water samples, which were then incubated in the dark at 10 °C under anoxic conditions. For further isolation + and cultivation in the laboratory, a modified version of artificial brackish water medium (ABW) (Bruns et al., 2002) was used, consisting of 95 mM NaCl, 11.2 mM MgCl2 . 6H2O, 2.3 mM CaCl2 . 2H2O, 2.0 mM KCl, 6.4 mM Na2SO4, 192 µM KBr, 92 µM H3BO3, 34 µM SrCl2, 92 µM NH4Cl, 9 µM KH2PO4 and 16 µM NaF, buffered with 10 mM HEPES (pH 7.3). For anaerobic cultivation, the medium was boiled, bubbled with N2 for 30 min, and then autoclaved under anoxic conditions. Subsequently, anoxic and sterile-filtered 0.1 % (v/v) of the trace + element solution SL10 (Widdel et al., 1983), 0.2 % (v/v) of a 10-vitamin solution (Balch et al., 1979), 0.02 % (v/v) of a selenite–tungstate solution (Widdel & Bak, 1992), and 2–5 mM NaHCO3 were added. The standard medium ABW+nitrate+thiosulfate (ABW+NS) was prepared by the variable addition of 10 mM KNO3 and 10 mM Na2S2O3, with the final concentration depending on the experiment. A pure culture was acquired by the dilution to extinction method + and was cryopreserved at −80 °C in glycerol for long-term storage. +

+

Morphological, physiological, and metabolic characteristics were, for the most part, analysed as described earlier (Grote et al., 2012). For these analyses, strain GD1T was cultivated in triplicate for 7–10 days at 15 °C in the dark. Growth was usually measured by counting 4′,6′-diamidino-2-phenylindol + (DAPI) stained cells, observed using epifluorescence microscopy, or by flow cytometric determinations of SYBR-Green I (Molecular + Probes) stained cells (Labrenz et al., 2007) at the end of the experiment. Sulfurimonas denitrificans DSM 1251T was used as the reference strain in the cultivation experiments. +

+

Isolate GD1T is a motile, Gram-reaction-negative, slightly curved or spirilla-shaped bacterium typically with one polar flagellum (Fig. 1a, b), but in some cases two flagella at opposite poles (Fig. 1c). Cell width was rather constant (mean = 0.66 µm, sd = 0.083 µm, n = 112) whereas cell length, i.e. from pole to pole, was variable (mean = 2.1 µm, sd = 0.54 µm, n = 112). The cells had a positive chemotactic response to nitrate (Grote et al., 2012). Under optimal conditions in ABW+NS medium the cell doubling time of strain GD1T was 13 h. Cells in older cultures tended to form aggregates. Growth at temperatures in the range of 4–40 °C was investigated, + with highest cell numbers obtained between 4 and 20 °C and optimal growth at 15 °C (Grote et al., 2012). Thus, isolate GD1T is the first psychrotolerant species within the genus Sulfurimonas, in which all member species at the time of writing are mesophilic (Table 1). +

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+
Fig. 1.
View larger version: + +
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+
Fig. 1. + +

Cell morphology of spirilla-shaped cells of strain GD1T cultivated on ABW+NS medium. (a) Fluorescence microscopy of 4′,6′-diamidino-2-phenylindol (DAPI) stained cells. (b) Transmission + electron microscopy of a bacterium with one flagellum and (c) of a bacterium with two flagella (indicated by arrows), both + negatively stained with phosphotungstic acid. +

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Table 1. + Differential characteristics between strain GD1T and species of the genus Sulfurimonas + +

Taxa: 1, Sulfurimonas gotlandica sp. nov. GD1T; 2, Sulfurimonas denitrificans DSM 1251T (data from this study; Timmer-ten Hoor, 1975; Brinkhoff et al., 2005); 3, Sulfurimonas paralvinellae GO25T (Takai et al., 2006); 4, Sulfurimonas autotrophica OK10T (Inagaki et al., 2003). nd, Not determined; +, positive; −, negative. +

+ +
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+

To obtain media with different pH values, the pH of a 20 ml subsample from the anoxic ABW+NS was adjusted to pH 6.0, 6.5, + 6.7, 6.9, 7.1, 7.5, 8.0, 8.4 and 9.0 by the addition of the appropriate amount of 0.1M HCl. For the experimental setup, the + corresponding amount of 1 M HCl was added to the media preparations, which were then inoculated. After 14 days of incubation, + the pH was measured. At an initial pH of 6.5–8.4, it remained constant (±0.02) throughout the experiment whereas below and + above this range it decreased by about 0.18–0.25 pH units. Optimal growth occurred over a wide pH range (6.7–8.0) but no growth + occured at pH 6.0 and 8.4. The NaCl requirement was determined by cultivation in ABW+NS containing the following salt concentrations + [NaCl (g l−1)/MgCl2 . 6H2O (g l−1)]: 0/0, 0/0.50, 2.50/0.38, 5.00/0.75, 7.50/1.13, 10.00/1.50, 12.50/1.88, 15.00/2.25, 17.50/2.63 and 20.00/3.00. The isolate + had an absolute requirement for NaCl and grew best with between 10 and 20 g NaCl l−1; the upper limit for growth was not further determined. No growth was observed in media without added NaCl, in contrast to + Sulfurimonas denitrificans DSM 1251T, which grew equally well without NaCl and at all NaCl concentrations tested (Table 1). +

+

To identify the electron donors sustaining chemoautotrophic growth of isolate GD1T, ABW medium containing 5 mM nitrate was supplemented with sulfite (1 mM), sulfide (10 µM, 20 µM, 100 µM) or elemental sulfur + (1 mM). Hydrogen utilization was assessed by bubbling ABW+NS with forming gas (N2/H2, 95 : 5) for several hours prior to inoculation and cultivation. Strain GD1T was able to use all of the tested electron donors as an energy source for growth although growth was inhibited by sulfide + concentrations >20 µM (Grote et al., 2012). This observation is in accordance with in situ activities of chemoautotrophic micro-organisms in pelagic Gotland Deep redox zones, where dark CO2 fixation rates are significantly reduced at environmental sulfide concentrations >20 µM (Jost et al., 2010). As electron acceptors, nitrate (100 µM, 2 mM, 5 mM, 10 mM), nitrite (600 µM, 2 mM) (Grote et al., 2012), manganese(IV) oxide (200 µM), manganese(III) acetate dihydrate (2.4 mM), iron(III) chloride hexahydrate (5 mM), fumarate + (100 µM) and oxygen (4 % saturation, approx. 12 µmol O2 l−1) were tested in ABW containing 5 mM thiosulfate. For the oxygen experiment, the oxygen content in fully oxygenated ABW+thiosulfate + was measured with an optode (POF-PSt3; PreSens) and the appropriate amount of oxygen was then mixed with anoxic ABW+thiosulfate + to achieve the desired amount of saturation. However, only nitrate and nitrite served as electron acceptors during growth + of the bacterium. +

+

Although the manganese and iron concentrations tested may have been too high and thereby suppressed cell growth, previous + thiosulfate/manganese stimulation experiments with Baltic Sea water samples containing lower metal concentrations similarly + failed to reveal active manganese-reducing species of the genus Sulfurimonas (Labrenz et al., 2005). Sulfurimonas autotrophica is likewise unable to reduce ferrihydrite (Inagaki et al., 2003), which further supports the lack of direct participation of strain GD1T in the Mn/Fe-shuttle (Neretin et al., 2003) of Baltic pelagic redox zones. It also cannot be excluded that strain GD1T is able to grow in medium with an oxygen concentration below 4 %, given that the genome of this bacterium includes a gene + encoding a putative cbb3-type cytochrome c oxidase with the potential to mediate aerobic respiration (Grote et al., 2012). If aerobic respiration could occur at very low oxygen concentrations, it was beyond the scope of our experimental design. + The oxygen sensitivity of strain GD1T was examined in detail, using ABW+NS with oxygen saturations of 0.5, 3, 5, 10, 20, 30, 40 and 50 %. Compared to oxygen-free + conditions, oxygen concentrations ≥20 % reduced or inhibited the growth of this strain whereas oxygen concentration ≤10 % + had no such effect (Grote et al., 2012). Thus, the oxygen tolerance of strain GD1T is similar to that of aerobic Sulfurimonas autotrophica OK10T (Table 1). Based on our current knowledge, we consider strain GD1T to be an aerotolerant representative of the genus Sulfurimonas. +

+

Chemolithoautotrophic growth was directly confirmed in ABW+NS containing 14C-bicarbonate followed by a combination of fluorescence in situ hybridization and microautoradiography (MICRO-CARD-FISH) (Grote et al., 2012). As electron donor (in ABW+5 mM KNO3) alone or as electron donor and sole carbon source (in NaHCO3-free ABW+5 mM KNO3) the following compounds were tested: (a) glucose (0.1 mM), (b) a mixture of lactate, malate, fumarate, succinate, glycerine + and glucose (abbreviated as mix 4) (100 µM), (c) yeast extract (0.01 mg l−1), (d) pyruvate (100 µM), (e) acetate (100 µM), (f) fumarate (100 µM), (g) alcohol mix (butanol, ethanol, methanol, propanol; + 100 µM) (Grote et al., 2012) and (h) an amino acid mix (0.1 mM) consisting of (g l−1): β-alanine 0.466, l-arginine 0.872, l-asparagine 0.750, l-cysteine 0.606, l-glutamine 0.730, l-glutamic acid 0.736, glycine 0.376, isoleucine 0.656, l-leucine 0.656, l-methionine 0.746, l-phenylalanine 0.826, l-serine 0.526, l-threonine 0.596, l-valine 0.586, l-proline 0.576, l-tryptophan 1.022, l-histidine 0.776, l-lysine 0.822, l-tyrosine 0.906 and l-asparagine 0.666. +

+

In the presence of 2 mM NaHCO3, the growth of isolate GD1T was promoted with formate, acetate, yeast extract, pyruvate and the amino acid mix as electron donors. However, maximal cell + numbers were usually more than a magnitude less than those reached with thiosulfate/nitrate-containing medium, as shown in + Fig. 2(a) for pyruvate, which was also used in radiotracer experiments aimed at confirming the capability of strain GD1T to use organics as electron donor. In those experiments, CO2 production was measured following the addition of 16 kBq [2-14C]pyruvate (specific activity 0.6 GBq mmol−1) to cultures grown solely on pyruvate or on thiosulfate/pyruvate. After 24 h or 72 h of incubation, CO2 was degassed by the acidification of cell-free medium and trapped in ethanolamine. In nitrate/pyruvate medium, the growth + of strain GD1T was accompanied by elevated CO2 production (Fig. 2b). The simultaneous incorporation of [2-14C]pyruvate into GD1T cells was much less pronounced, but its uptake and contribution to biomass production were clearly determined + in thiosulfate/nitrate/pyruvate medium, where total cell numbers were also higher than those reached in thiosulfate/nitrate + medium (Fig. 2a), but the difference was not statistically significant (unpublished data). By contrast, in NaHCO3-free medium strain GD1T was unable to use any of the organics offered simultaneously as electron donor and carbon source (Fig. 2a). It has long been recognized that even heterotrophic bacteria may require CO2 for growth (Dehority, 1971), e.g. in anaplerotic reactions (Alonso-Sáez et al., 2010). Similar findings were reported for Nitrobacter hamburgensis, which requires atmospheric CO2 or the addition of sodium carbonate for mixotrophic growth (in the presence of NO2) on d-lactate (Starkenburg et al., 2008). The authors of that study suggested that CO2 fixation served as a reductant sink necessary to maintain cellular redox balance. The physiological background for the growth + of isolate GD1T on organics is thus far unclear. In other species of the genus Sulfurimonas, organic substance utilization is variable. For example, in a similar experiment Sulfurimonas denitrificans was able to use formate, fumarate, yeast extract and the alcohol mix as electron donors (Table 1). The ability of this bacterium to oxidize formate was proposed in a genome analysis, which identified a formate dehydrogenase + complex (Sievert et al., 2008). Homologues of genes involved in glycolysis and proteolysis are also present in the genome of strain GD1T (Grote et al., 2012), whereas Sulfurimonas autotrophica (Inagaki et al., 2003; but tested without bicarbonate supplementation to the organic medium) and Sulfurimonas paralvinellae (Takai et al., 2006) are unable to grow on organic compounds. In conclusion, although under specific circumstances organic compounds enhance + the growth of some species of the genus Sulfurimonas, members of this genus characteristically grow chemolithoautotrophically. +

+
+
Fig. 2.
View larger version: + +
+
+
Fig. 2. + +

Impact of pyruvate on the growth of isolate GD1T. Error bars indicate the standard deviation of three independent replicates for each assay. (a) Growth on media with different + substrate combinations: 1, NaHCO3, S2O32-, NO3; 2, NaHCO3, S2O32-, NO3, pyruvate; 3, NaHCO3, pyruvate; 4, pyruvate; 5, ABW without further supplements. The relative enrichment factor describes the increase of cell + numbers after 7 days of incubation compared to the initial cell numbers after inoculation at day 0 (6.1×105 ml−1). (b) 14CO2 production and [14C]pyruvate incorporation after 24 h and 72 h of incubation. Media: 1, NaHCO3, S2O32-, NO3, [14C]pyruvate; 2, NaHCO3, NO3, [14C]pyruvate. P, pyruvate incorporation; CO2, CO2 production. +

+ +
+
+
+

Total fatty acids and phospholipid-derived fatty acids were extracted as described by Sasser (1990) and Boschker (2004), respectively, and analysed by gas chromatography with a flame-ionization detector on a non-polar HP-5ms column (Agilent). + The dominant cellular fatty acid of strain GD1T was 16 : 1ω7c, with 3-OH 14 : 0, 16 : 0, 16 : 1ω5c+t, and 18 : 1ω7c detected in lower amounts. This fatty acid profile is comparable to those of other species of the genus Sulfurimonas but most similar to that of Sulfurimonas denitrificans (Table 1). This may reflect the fact that strain GD1T and Sulfurimonas denitrificans were cultivated on ABW+NS under identical conditions. However, a high percentage of C16 : 0 and one or both of the monounsaturated + C16 and C18 fatty acids has also been described in other members of the class Epsilonproteobacteria, such as Nitratifractor salsuginis and Sulfurovum lithotrophicum (Suzuki et al., 2005). Accordingly, this combination may be a general characteristic of these epsilonproteobacteria. +

+

The DNA guanine-plus-cytosine (G+C) content of strain GD1T was determined to be 33.6 mol%, as calculated by analysis of the whole genome (Grote et al., 2012). +

+

To establish the closest relatives of strain GD1T based on 16S rRNA sequencing, preliminary searches in the EMBL Data Library were performed with the program fasta (Pearson & Lipman, 1988). Closely related sequences were retrieved from GenBank and aligned and analysed with the newly determined sequence, within + the program arb (Ludwig et al., 2004). Sequences for analysis were reduced to unambiguously alignable positions using group-specific filters. For phylogenetic + analyses, three different trees were calculated using the neighbour-joining, parsimony and maximum-likelihood (Phyml) algorithms + based on nearly full-length 16S rRNA sequences (approx. 1400 bp). For neighbour-joining, the Jukes–Cantor-correction was applied. + Shorter sequences were gradually inserted into the reconstructed tree without changing the topology. Sequence searches of + the EMBL database (latest: 2013-05-14) revealed that our isolate is related to the epsilon class of the phylum Proteobacteria (data not shown). In a pairwise analysis, it displayed highest (93.7–94.2 %) 16S rRNA gene sequence similarity to species + of the genus Sulfurimonas and to the Baltic ‘Uncultured Helicobacteraceae G138eps1/GD17’ subgroup (95.7 %). Lower levels of relatedness (≤91 % sequence similarity) were determined for the other examined + species belonging to the epsilon class of the phylum Proteobacteria. +

+

An unrooted tree reconstructed using the neighbour-joining method showed the phylogenetic position of the novel bacterium, + strain GD1T, amongst the members of the class Epsilonproteobacteria (Fig. 3). Treeing analyses confirmed it to be a member of the genus Sulfurimonas, forming a stable cluster with the ‘Uncultured Helicobacteraceae G138eps1/GD17’ subgroup. This cluster is specifically detected by the SUL90 16S rRNA gene probe, originally developed to + be 100 % complementary to the G138eps1/GD17 target site (Grote et al., 2007). +

+
+
Fig. 3.
View larger version: + +
+
+
Fig. 3. + +

Unrooted tree showing phylogenetic relationships of isolate GD1T and closely related members of the class Epsilonproteobacteria. The tree was reconstructed using the neighbour-joining method and was based on a comparison of approximately 1400 nt. Solid + squares indicate that the corresponding nodes (or groups) were recovered in neighbour-joining, maximum-parsimony and maximum-likelihood + methods. Branching points supported by two algorithms are marked by an open square. The following strains were used as an + outgroup (not shown): Antarctobacter heliothermus EL-219T, Sagittula stellata E-37T, Roseovarius tolerans EL-172T, Roseovarius nubinhibens ISMT and Roseovarius mucosus DFL-24T. Bar, 1 substitution per 10 nt. +

+ +
+
+
+

There is no precise correlation between percentage 16S rRNA sequence divergence and species delineation, but it is generally + recognized that divergence values ≥3 % are significant (Stackebrandt & Goebel, 1994). However, it is pertinent to note that the phylogenetic separateness of strain GD1T is strongly supported by phenotypic considerations. For instance, this novel bacterium is distinguishable from other species + of the genus Sulfurimonas by its psychrotolerance and energy metabolism (Table 1). Additional characteristics useful in differentiating Baltic isolate GD1T from related organisms are shown in Table 1. Based on phenotypic and genetic evidence, we propose the classification of strain GD1T as a representative of a novel species of the genus Sulfurimonas: Sulfurimonas gotlandica sp. nov. +

+
+ + + +
+ +

Emended description of the genus Sulfurimonas

+ +

The description is based on that by Takai et al. (2006). Cells are Gram-negative and morphologically variable. Straight to slightly short rods, elongated rods and spiral in different + growth phases and under different growth conditions. Psychrotolerant to mesophilic and aerotolerant to facultatively anaerobic. + Do not always require NaCl for growth. Optimal growth occurs chemolithoautotrophically with sulfide, S0, thiosulfate and H2 as electron donors, and with nitrate, nitrite and O2 as electron acceptors, using CO2 as a carbon source. Supplementation of bicarbonate can enable growth on organic substances, but yields much lower cell numbers + compared to growth on reduced sulfur or hydrogen. Potential ecological niches are deep-sea hydrothermal environments and benthic + or pelagic marine to brackish transition zones from oxic to anoxic/sulfidic environments. The type species is Sulfurimonas autotrophica (Inagaki et al. 2003). +

+ +
+
+ +

Description of Sulfurimonas gotlandica sp. nov. +

+ +

Sulfurimonas gotlandica (got.lan′di.ca. N.L. fem. adj. gotlandica pertaining to the Gotland Deep, the basin in the central Baltic Sea from which the organism was first isolated). +

+ +

Gram-negative, slightly curved or spirilla-shaped cells. Motile by one polar flagellum or two flagella at opposite poles. + Cells exhibit a positive chemotactic response to nitrate. Cell sizes are 0.66±0.083×2.1±0.54 µm. Cells have a tendency to + aggregate at older stages. Psychro- and aerotolerant. The temperature range for growth is 4–20 °C. Optimal growth occurs at + 15 °C and pH 6.7–8.0. The cells have an absolute requirement for NaCl. Chemolithoautotrophic growth occurs with H2, HS, S0 and thiosulfate. Supplementation of bicarbonate can enable growth on formate, acetate, yeast extract, pyruvate or amino acid + mix, but yields much lower cell numbers compared with growth on reduced sulfur or hydrogen. Sulfide concentrations of more + than 20 µM inhibit, but up to 10 % of oxygen in the medium does not influence growth. Dominant cellular fatty acid is 16 : 1ω7c, with 14 : 0, 16 : 0, 16 : 1ω5c+t, and 18 : 1ω7c present in smaller amounts. +

+ +

The type strain is GD1T ( = DSM 19862T = JCM 16533T), isolated from water of a pelagic redox zone of the central Baltic Sea. The G+C content of the type strain is 33.6 mol%. +

+ +
+
+
+ +

Acknowledgements

+ +

We thank the captain and the crew of the RV Alkor. We gratefully acknowledge the skilful technical assistance of Bärbel Buuk. Michael Hannig helped during the isolation procedure. + We thank the Deutsche Forschungsgemeinschaft (DFG) for grants LA 1466/4-1 and LA 1466/4-2. +

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References

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+ +
+

Prevotella jejuni sp. nov., isolated from the small intestine of a child with coeliac disease +

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  1. Sten Hammarström1
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  1. 1Department of Clinical Microbiology, Immunology, Umeå University, SE-90187 Umeå, Sweden +
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  3. 2CCUG – Culture Collection University of Gothenburg, Department of Clinical Bacteriology, Sahlgrenska University Hospital, + SE-41345 Göteborg, Sweden +
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  5. 3Department of Infectious Diseases, Sahlgrenska Academy of the University of Gothenburg, SE-40530 Göteborg, Sweden +
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  7. 4Department of Molecular Biology, Umeå University, SE-90187 Umeå, Sweden +
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  9. 5Department of Clinical Sciences, Pediatrics, Umeå University, SE-90187 Umeå, Sweden +
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  1. Correspondence
    Maria E. Hedberg maria.hedberg{at}climi.umu.se Sten Hammarström sten.hammarstrom{at}climi.umu.se
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+ +

Abstract

+ +

Five obligately anaerobic, Gram-stain-negative, saccharolytic and proteolytic, non-spore-forming bacilli (strains CD3 : 27, + CD3 : 28T, CD3 : 33, CD3 : 32 and CD3 : 34) are described. All five strains were isolated from the small intestine of a female child + with coeliac disease. Cells of the five strains were short rods or coccoid cells with longer filamentous forms seen sporadically. + The organisms produced acetic acid and succinic acid as major metabolic end products. Phylogenetic analysis based on comparative + 16S rRNA gene sequence analysis revealed close relationships between CD3 : 27, CD3 : 28T and CD3 : 33, between CD3 : 32 and Prevotella histicola CCUG 55407T, and between CD3 : 34 and Prevotella melaninogenica CCUG 4944BT. Strains CD3 : 27, CD3 : 28T and CD3 : 33 were clearly different from all recognized species within the genus Prevotella and related most closely to but distinct from P. melaninogenica. Based on 16S rRNA, RNA polymerase β-subunit (rpoB) and 60 kDa chaperonin protein subunit (cpn60) gene sequencing, and phenotypic, chemical and biochemical properties, strains CD3 : 27, CD3 : 28T and CD3 : 33 are considered to represent a novel species within the genus Prevotella, for which the name Prevotella jejuni sp. nov. is proposed. Strain CD3 : 28T ( = CCUG 60371T = DSM 26989T) is the type strain of the proposed novel species. All five strains were able to form homologous aggregates, in which tube-like + structures were connecting individual bacteria cells. The five strains were able to bind to human intestinal carcinoma cell + lines at 37 °C. +

+ +
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+ +
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  • +

    The GenBank/EMBL/DDBJ accession number for the 16S rRNA gene sequence of strain CD3 : 28T is JQ778983. +

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    One supplementary figure and three supplementary tables are available with the online version of this paper.

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This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted + use, distribution, and reproduction in any medium, provided the original work is properly cited. +

+
+

Coeliac disease (CD) is an immune-mediated enteropathy with a multifactorial aetiology. Early childhood infections have been + shown to be a risk factor for CD (Myléus et al., 2012). Also, the jejunal microbiota is considered to play a role in the pathogenesis of CD (Olivares et al., 2013). This is supported by epidemiological data from Sweden showing that childhood CD has features of an infectious disease with + a peak incidence between 1985 and 1996 in children younger than 2 years of age, a period referred to as ‘the Swedish CD epidemic’ + (Ivarsson et al., 2000). A similar increase in incidence was seen later, during 2001–2004 (Olsson et al., 2008; Namatovu, F. et al., unpublished data). After both peaks, incidence returned to normal. We have shown that CD patients born during ‘the Swedish + CD epidemic’ had a significant enrichment of mucosa-associated rod-shaped bacteria of the order Clostridiales, and genera Prevotella and Actinomyces in the jejunum (Forsberg et al., 2004; Ou et al., 2009). Recently, we characterized a novel species of a new genus, Lachnoanaerobaculum umeaense, that had been isolated from the jejunal mucosa of a child born during ‘the Swedish CD epidemic’ (Hedberg et al., 2012). We assumed that this bacterium corresponded to the prevalent bacteria of the order Clostridiales we had previously reported (Ou et al., 2009). To further characterize the microbiota of the small intestine of children with CD born during the first epidemic we have + now studied isolates of the genus Prevotella. +

+

At the time of writing, 48 species of the genus Prevotella have been described (Euzéby, 2013). The vast majority were isolated from humans, with the oral cavity being the main source (Dewhirst et al., 2010). However, Prevotella species have also been isolated from faeces (Hayashi et al., 2007), the female genital tract, skin and respiratory tract, and from the rumen and hindgut of non-human mammals (Alauzet et al., 2010). Until now, no species of the genus Prevotella from the human small intestine had been characterized. Species of the genus Prevotella are generally considered to be non-pathogenic or opportunistic pathogens. However, they have been shown to be involved in + serious infections, and virulence factors such as haemolysins, haemagglutinins, fimbrial adhesins, proteases and phospholipases + have been demonstrated in strains of several species (Alauzet et al., 2010). +

+

This study describes the phenotypic and genotypic characterization of strains CD3 : 27, CD3 : 28T and CD3 : 33, representing isolates of a novel species, CD3 : 32, probably a strain of Prevotella histicola (Downes et al., 2008), and CD3 : 34, probably a strain of Prevotella melaninogenica (Shah & Collins, 1990). Additionally, we describe the phylogenetic relationships between the five isolates and other members of the genus Prevotella, based upon comparative 16S rRNA gene sequence analyses. Moreover, the five isolates have been subjected to whole genome + sequencing (WGS) using 454 pyro-sequencing technology (GS Junior; Roche Diagnostics), and the sequences of the genes encoding + chaperonin 60 (cpn60) and DNA-directed RNA polymerase subunit-β (rpoB) have also been compared. +

+

The five strains were isolated from a biopsy of the proximal small intestine of a girl with CD, born in 1995, i.e. during + the 1985–1996 Swedish CD epidemic. She was on a gluten-free diet when the biopsy was taken at the Department of Paediatrics, + Umeå University Hospital, Umeå, in 2007. Informed consent was obtained from her parents. The study was approved by the local + Research Ethics Committee of the Faculty of Medicine (Um dnr: 96-304 and 04-156). The biopsy was weighed, homogenized and + serially diluted ten-fold in Fastidious Anaerobe Broth medium (Lab M) and immediately plated onto selective and non-selective + agar media. All Prevotella strains were primarily isolated on blood agar plates [Columbia Blood Agar Base (Acumedia), supplemented with 5 % defibrinated + horse blood]. P. histicola CCUG 55407T, P. melaninogenica CCUG 4944BT and Prevotella stercorea CCUG 55595T were obtained from the Culture Collection University of Gothenburg (CCUG; http://www.ccug.se). +

+

Pure cultures of the five strains grew well on blood agar plates and in Brucella broth (BBL) supplemented with vitamin K (1 + µg ml−1) and haemin (5 µg ml−1) under an anaerobic atmosphere (10 % H2, 5 % CO2 in N2) at 37 °C. +

+

Colony morphologies and the results of presumptive identification tests by diagnostic discs (Jousimies-Somer et al., 2002) were examined on blood agar plates after incubation for 3–5 days. None of the five strains grew in the presence of oxygen + and they should be considered strictly anaerobic. Growth was improved and pigmentation and haemolytic activity increased if + the atmosphere contained 10 % CO2 and 5 % H2 as compared with standard conditions. The appearance of the colonies of the five strains differed: isolate CD3 : 27 had circular, + raised, convex, weakly to moderately pigmented and strongly haemolytic colonies; CD3 : 28T and CD3 : 33 had circular, convex, weakly pigmented, weakly haemolytic colonies; CD3 : 32 had circular, slightly raised and + brown-reddish pigmented colonies with a shiny ‘wet’ appearance. Moreover, the centres of the colonies of CD3 : 32 were darker + than the outer part. Colonies of CD3 : 34 were similar to those of CD3 : 28T and CD3 : 33, but with a surface appearing ‘drier’ (Fig. S1 available in IJSEM Online). +

+

Light microscopy after Gram staining, dark field microscopy, scanning electron microscopy (SEM) and transmission electron + microscopy (TEM) were used to investigate cell morphologies. Cells of the five strains were rod-shaped, 0.7×0.8–2 µm in size, + occurring most often as short rods or as coccoid cells, with longer filamentous forms (>10 µm) seen sporadically. All five + strains were Gram-stain-negative and lacked spores. SEM revealed that all five strains, particularly if grown on agar medium, + as opposed to in liquid culture, formed large aggregates of bacterial cells connected to each other by multiple, thin, strait, + rod-shaped structures (Fig. 1a–c). Cells of strains CD3 : 27, CD3 : 28T and CD3 : 33 showed a similar degree of interconnectivity. Outer membrane vesicles were frequently observed. Analysis of + thin sections of the aggregates by TEM suggested that the rod-shaped structures were hollow, characterized as tubes connecting + cells to each other (Fig. 1d). +

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+
Fig. 1.
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+
+
Fig. 1. + +

Scanning electron micrographs showing surface structures of cells of P. jejuni, strains CD3 : 27 (a) and CD3 : 28T (b) and P. histicola strain CD3 : 32 (c). (d) Transmission electron micrograph of a cell of strain P. jejuni CD3 : 33; arrows indicate cross-section of the tube-like structures shown in (a)–(c) and arrowheads indicate outer membrane + vesicles. Bars, 0.2 µm (a, b, d); 1 µm (c). +

+ +
+
+
+

All five strains exhibited a temperature optimum for growth at 37 °C. The optimal pH for growth was 6–7 with reduced growth + at pH 5.5 and 7.5. Motility was not observed. All five strains were haemolytic and produced NH3. Growth on glucose as the sole carbon source yielded acetic acid, succinic acid and small amounts of isovaleric acid for + strains CD3 : 27, CD3 : 32 and CD3 : 34, and acetic acid and succinic acid for strains CD3 : 28T and CD3 : 33. +

+

The nucleotide sequences of the 16S rRNA genes of strains CD3 : 27, CD3 : 28T, CD3 : 33, CD3 : 32 and CD3 : 34 were determined by primer walking, covering the gene, and by cloning and sequencing of PCR + amplification fragments also covering the gene (Hedberg et al., 2012). These sequences were subsequently confirmed by genomic sequencing, allowing us to establish that there was only one copy + of the 16S rRNA gene per genome. Other 16S rRNA gene sequences for comparative analyses were retrieved from the NCBI database + (Sayers et al., 2010). Strains CD3 : 27, CD3 : 28T and CD3 : 33 shared >99.8 % 16S rRNA gene sequence similarity with each other and 98.1–98.3 % similarity with P. melaninogenica CCUG 4944BT (AY323525), P. histicola CCUG 55407T (AB547685), N 12-20 (EU126662), CD3 : 34 and CD3 : 32, and 97.3–97.7 % similarity with Prevotella veroralis CCUG 15422T (AY836507). Strain CD3 : 32 was related most closely to P. histicola (AB547685 and EU126662) showing >99.6 % sequence similarity. Strain CD3 : 34 showed 99.8 % sequence similarity to P. melaninogenica (AY323525 and NC-014370). Fig. 2 shows the phylogenetic tree reconstructed using the maximum composite likelihood model based on 16S rRNA gene sequences. + Strains CD3 : 27, CD3 : 28T and CD3 : 33 formed a separate group distinct from recognized species of the genus Prevotella while strain CD3 : 32 clustered with P. histicola and strain CD3 : 34 with P. melaninogenica. +

+
+
Fig. 2.
View larger version: + +
+
+
Fig. 2. + +

Phylogenetic tree based on 16S rRNA gene sequences showing the relationships between strains CD3 : 27, CD3 : 28T and CD3 : 33 and related species. The 16S rRNA gene sequence of Porphyromonas gingivalis ATCC 33277T served as an outgroup. Bar, 0.02 substitutions per nucleotide position. +

+ +
+
+
+

Genomic DNA–DNA reassociation analysis was carried out using the hybridization protocols described by Urdiain et al. (2008). Strain CD3 : 28T hybridized to a high level (95–112 %) with strains CD3 : 27 and CD3 : 33, confirming that these three strains belong to the + same species. The level of hybridization between strain CD3 : 28T and P. histicola CCUG 55407T, P. melaninogenica CCUG 4944BT, Prevotella scopos CCUG 57945T and P. veroralis CCUG 15422T was below 43 %. Levels of hybridization between strain CD3 : 28T and strains CD3 : 32 and CD3 : 34 were 49 and 59 % respectively. The level of hybridization between P. melaninogenica CCUG 4944BT and strain CD3 : 34 was high (104 %), while that between strain CD3 : 34 and strain CD3 : 28T was 51 %. P. melaninogenica hybridized to a low level (30 %) with P. histicola CCUG 55407T. The coefficient of variation was less than 5.5 %. As the genomic DNA hybridization values were well below 70 % for strains + CD3 : 27, CD3 : 28T and CD3 : 33 on the one hand and strains CD3 : 32 or CD3 : 34 on the other, the strains can be considered to represent different + species (Stackebrandt & Goebel, 1994). +

+

To shed further light on whether CD3 : 27, CD3 : 28T and CD3 : 33 should be considered as strains of the same novel species we compared the nucleotide sequences of the rpoB and cpn60 genes (Alauzet et al., 2010; Sakamoto & Ohkuma, 2010). Similarly, we compared strain CD3 : 32 with P. histicola and strain CD3 : 34 with P. melaninogenica. The rpoB and cpn60 (3810 and 1626 nt respectively) gene sequences were 100.0 % identical between strains CD3 : 27, CD3 : 28T and CD3 : 33. Sequence similarity between CD3 : 32 and P. histicola F0411 was 99.3 % for rpoB and 98.7 % for cpn60. Strain CD3 : 34 and P. melaninogenica CCUG 4944BT shared 98.3 % rpoB gene sequence similarity and 97.7 % cpn60 gene sequence similarity. +

+

The sizes of the genomes and the DNA G+C contents of the five strains were determined from WGS data (Table 1). Strains CD3 : 28T and CD3 : 33 had almost the same genome size, 3.81×106 and 3.80×106 bp, respectively, while CD3 : 27 had a size of 3.68×106 bp. The genome of strain CD3 : 32 had a size of 3.20×106 bp, larger than that of the closely related P. histicola F0411 (2.99×106 bp). The genome size of strain CD3 : 34 was 3.27×106 bp, about 102×103 bp larger than that of P. melaninogenica CCUG 4944BT. The DNA G+C contents of the strains grouped together, in that strains CD3 : 27, CD3 : 28T and CD3 : 33 had values of 41.7–41.8 mol%, CD3 : 32 and P. histicola F0411 had values of 41.1 and 41.2 mol%, respectively, and CD3 : 34 and P. melaninogenica CCUG 4944BT values of 40.7 and 41.0 mol%, respectively. +

+
+
+
View this table: +
+
+
Table 1. + Genome size and DNA G+C content of Prevotella jejuni sp. nov., and the other two Prevotella isolates from human small intestine compared with P. histicola and P. melaninogenica + +
+
+
+

Cellular fatty acid (CFA) methyl ester analyses were performed using a standardized protocol (http://www.ccug.se/pages/CFA_method_2008 and as detailed by Hedberg et al., 2012). Strains were grown anaerobically (10 % H2, 5 % CO2 in N2), using chocolate agar as culture medium at 37 °C, and harvested after 48 h. CFAs were extracted and saponified by mild alkaline + methanolysis and released fatty acids were methylated. CFAs were identified and quantified by GC (Hewlett Packard HP 5890). + Retention times of CFA peaks were converted to equivalent chain-length values and the relative amount (w/w) of each fatty + acid was expressed as a percentage of the total fatty acids in the profile of the respective strain (Table S1). The major + CFAs detected in strains CD3 : 27, CD3 : 28T, CD3 : 33, CD3 : 32 and CD3 : 34 were iso-C15 : 0, anteiso-C15 : 0, C16 : 0, C18 : 2ω6,9c/anteiso-C18 : 0 and iso-C17 : 0 3-OH. These five CFAs occurred in approximately the same relative amounts in the five strains with anteiso-C15 : 0 accounting for 38.5–42.5 % of the total CFAs. Interestingly, strains CD3 : 27, CD3 : 28T, CD3 : 33, CD3 : 32 and CD3 : 34 were more similar to each other than were CD3 : 32 to P. histicola CCUG 55407T or CD3 : 34 to P. melaninogenica CCUG 4944BT (Table S1). The similarities between the five jejunal isolates, although representing three different species, are perhaps + a reflection of the fact that they were isolated from the same organ of one individual. +

+

Analysis of metabolic and biochemical characteristics (rapid ID 32A, API 20A and APIZYM; bioMérieux) showed that the five + strains are saccharolytic and proteolytic (Table S2). Strains CD3 : 27, CD3 : 28T and CD3 : 33 demonstrated an almost identical pattern of biochemical characteristics. The only difference observed was that + strain CD3 : 33 had α-galactosidase activity, while the other two strains did not. CD3 : 32 and P. histicola CCUG 55407T showed an identical pattern of biochemical characteristics and the same was true for the comparison between CD3 : 34 and + P. melaninogenica CCUG 4944BT. Sialidase activity was detected using 2′-(4-methylumbelliferyl)α-d-N-acetylneuraminic acid as substrate (Moncla & Braham, 1989). All strains produced sialidase except CD3 : 32 and P. histicola CCUG 55407T. +

+

By disc diffusion it was shown that all five isolates and P. histicola CCUG 55407T were resistant to vancomycin (5 µg) but susceptible to kanamycin (1 mg), colistin (10 µg) (Oxoid) and bile (1000 µg) (Oxgall + tablets; Rosco Diagnostica), whereas P. melaninogenica CCUG 4944BT was resistant to vancomycin and kanamycin but susceptible to colistin and bile. P. stercorea CCUG 55595T was resistant to kanamycin and colistin but susceptible to bile and unexpectedly also susceptible to vancomycin (Jousimies-Somer et al., 2002). Because the bacteria were isolated from the small intestine adjacent to the bile duct, susceptibility to bile was investigated + further using an agar dilution technique. A stock solution containing 320 mM synthetic bile acids (taurocholate, 134.4 mM; + taurochenodeoxycholate, 83.2 mM; glycocholate, 70.4 mM; glycochenodeoxycholate, 32 mM) yielded final concentrations of 0.125–16 + mM bile acids in the assay. Interestingly, growth and haemolytic activity of all five jejunum isolates were stimulated at + low concentrations of bile (0.5–1.5 mM) compared with medium without bile, while growth was inhibited at higher bile concentrations + (2–8 mM). +

+

Susceptibility to penicillin G was tested using MIC Evaluator Strips (Oxoid). Strains CD3 : 32, CD3 : 34 and P. histicola CCUG 55407T were resistant (MIC >32 µg ml−1). The other strains were susceptible to penicillin G, with MICs ranging from 0.003 to 0.015 µg ml−1. According to the nitrocefin disc test (Remel), strains CD3 : 32, CD3 : 34 and P. histicola CCUG 55407T produce β-lactamase. WGS revealed the presence of the cfxA β-lactamase gene in strains CD3 : 32 and CD3 : 34, but not in P. histicola F0411, the only other P. histicola isolate that has been sequenced so far, or P. melaninogenica CCUG 4944BT. Strains CD3 : 32 and CD3 : 34 shared 100 and 99 % cfxA gene sequence similarity with Prevotella marshii CCUG 50419T, respectively. +

+

The abilities of strains CD3 : 27, CD3 : 28T, CD3 : 33, CD3 : 32, CD3 : 34, P. histicola CCUG 55407T and P. melaninogenica CCUG 4944BT to agglutinate human erythrocytes was investigated. Strains CD3 : 27, CD3 : 28T and CD3 : 33 strongly agglutinated human O and AB erythrocytes; there was no difference in the strength of the agglutination + reaction between the three strains, nor was there a difference in their ability to agglutinate AB versus O red blood cells. + Strain CD3 : 34 showed a weak agglutination reaction while strains CD3 : 32, P. histicola CCUG 55407T and P. melaninogenica CCUG 4944BT were negative. The finding that some strains of P. melaninogenica are able to weakly agglutinate red blood cells (Haraldsson et al., 2005) is in agreement with our results. +

+

To confirm that the five jejunal isolates were able to bind to intestinal epithelial cells, binding of PKH-2 fluorescence + dye-labelled bacteria to PKH-26 fluorescence dye-labelled intestinal epithelial cells was studied by flow cytometry (Hara-Kaonga & Pistole, 2007). Binding was evaluated after incubation at 37 °C and at 4 °C for 1 h. The cell lines were T84 (colon carcinoma), LS174T + (colon carcinoma), HT29 (small intestine-like carcinoma) and Int407 (fetal small intestine epithelial cells), all obtained + from the American Type Culture Collection (Rockville, MD). At 37 °C, all five isolates were able to bind to the four cell + lines with two exceptions: strains CD3 : 27 and CD3 : 28T did not bind to LS174T cells (Table S3). +

+

We conclude that strains CD3 : 27, CD3 : 28T and CD3 : 33 represent a novel species of the genus Prevotella, for which the name Prevotella jejuni sp. nov. is proposed, that CD3 : 32 is a strain of P. histicola and that CD3 : 34 is a strain of P. melaninogenica. The latter two jejunal isolates have larger genome sizes than the corresponding previously characterized strains. All five + jejunal isolates are able to bind to human intestinal epithelial cells. +

+
+ + + +
+ +

Description of Prevotella jejuni sp. nov. +

+ +

Prevotella jejuni (je.ju′ni. L. gen. n. jejuni of or from the jejunum, referring to the isolation of the type strain from the jejunum). +

+ +

The description is based on three strains isolated from the human jejunum. Cells are obligately anaerobic, non-motile, Gram-stain-negative + bacilli (0.7×0.8–2 µm). After 3–5 days of incubation on blood agar plates, colonies are 1–2 mm in diameter, circular, convex, + weakly to moderately pigmented and weakly to strongly haemolytic. The optimum conditions for growth are 37 °C and pH 6–7. + Acetic acid, succinic acid and small amounts of isovaleric acid are produced from glucose. NH3 is produced. Cells are saccharolytic and proteolytic and are able to ferment glucose, lactose, maltose, mannose, raffinose + and sucrose, but not arabinose, cellobiose, mannitol, melezitose, rhamnose, salicin, sorbitol, trehalose or xylose. Positive + for activity of β-galactosidase, β-galactosidase-6-phosphate, α-glucosidase, N-acetyl-β-glucosaminidase, α-fucosidase, sialidase, acid phosphatase, alkaline phosphatase, naphthol-AS-BI-phosphate, arginine + arylamidase, alanine arylamidase, leucine arylamidase and leucyl glycine arylamidase (Table S2). Gelatin is hydrolysed but + aesculin is not. Cells agglutinate human AB and O erythrocytes and bind to several human intestinal cell lines. The predominant + CFA is anteiso-C15 : 0, accounting for 42.5 % of the total CFA profile. +

+ +

The type strain is CD3 : 28T ( = CCUG 60371T = DSM 26989T), which was isolated from a biopsy of the small intestine of a child with CD. Strains CD3 : 27 ( = CCUG 60308) and CD3 : 33 + ( = CCUG 60311) are additional strains of this species. The DNA G+C content of the type strain is 41.7 mol%. +

+ +
+
+
+ +

Acknowledgements

+ +

Funding was provided by: the Swedish Research Council, Natural Sciences and Engineering Sciences (no. 2010-5669); the TORNADO-project + within the 7th framework program theme (grant agreement no. 222720-2); the Fund for Biotechnology-oriented Basic Science at + Umeå University; the County of Västerbotten; and the Medical Faculty of Umeå University. The funders had no role in study + design, data collection and analysis, decision to publish, or preparation of the manuscript. +

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References

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Molecular and phenotypic analyses reveal the non-identity of the Phaeobacter gallaeciensis type strain deposits CIP 105210T and DSM 17395 +

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  1. Thorsten Brinkhoff2
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  1. 1Leibniz Institute DSMZ – German Collection of Microorganisms and Cell Cultures, Braunschweig, Germany +
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  3. 2Institute for Chemistry and Biology of the Marine Environment, University of Oldenburg, Oldenburg, Germany +
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  1. Correspondence
    Jörn Petersen joern.petersen{at}dsmz.de
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Abstract

+ +

The marine genus Phaeobacter currently comprises six species, some of which were intensively studied mainly due to their ability to produce secondary + metabolites. The type strain of the type species, Phaeobacter gallaeciensis BS107T, has been deposited at several public culture collections worldwide. Based on differences in plasmid profiles, we detected + that the alleged P. gallaeciensis type strains deposited at the Collection Institute Pasteur (CIP; Paris, France) as CIP 105210 and at the German Collection + of Microorganisms and Cell Cultures (DSMZ; Braunschweig, Germany) as DSM 17395 are not identical. To determine the identity + of these strains, we conducted DNA–DNA hybridization, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry + (MALDI-TOF), 16S rRNA gene and internal transcribed spacer (ITS) sequence analyses, as well as physiological experiments. + Based on the detailed 16S rRNA gene reanalysis we showed that strain CIP 105210 most likely corresponds to the original P. gallaeciensis type strain BS107T. In contrast, the Phaeobacter strain DSM 17395 exhibits a much closer affiliation to Phaeobacter inhibens DSM 16374T ( = T5T) and should thus be allocated to this species. The detection of the dissimilarity of strains CIP 105210T and DSM 17395 will influence future comparative studies within the genus Phaeobacter. +

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  • +

    These authors contributed equally to this work. +

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    The GenBank/EMBL/DDBJ accession numbers for the 16S rRNA gene sequences of the Phaeobacter strains CIP 105210T, DSM 16374T, DSM 17395 and DSM 24564T are KC176239, KC176240, KC176241 and KC176242, respectively. The GenBank/EMBL/DDBJ accession numbers for the 16S–23S rRNA + gene internal transcribed spacer of the Phaeobacter strains CIP 105210T, DSM 16374T, DSM 17395, DSM 23529T, DSM 23566T, DSM 24564T and DSM 25627T are KC176233, KC176234, KC176235, KC176236, KC176237, KC176238 and KC907729, respectively. +

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    Four supplementary figures and four supplementary tables are available with the online version of this paper.

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+ + +

Introduction

+ +

The genus Phaeobacter, currently comprising the species Phaeobacter gallaeciensis, P. inhibens, P. daeponensis, P. caeruleus, P. arcticus and P. leonis (Gaboyer et al., 2013), belongs to the marine Roseobacter clade. It was established by Martens et al. (2006) after reclassification of Roseobacter gallaeciensis (Ruiz-Ponte et al., 1998) as P. gallaeciensis, which is the type species of the genus, and description of P. inhibens as a new species. During recent years, Phaeobacter strains have received a lot of interest due to the production of various secondary metabolites (e.g. Berger et al., 2011, 2012; Brinkhoff et al., 2004; Bruhn et al., 2007; Geng et al., 2008; Martens et al., 2007; Seyedsayamdost et al., 2011a, b). +

+ +

Recently the genomes of three Phaeobacter strains have been published, P. gallaeciensis DSM 17395, P. gallaeciensis 2.10 (Thole et al., 2012) and P. gallaeciensis ANG1 (Collins & Nyholm, 2011). However, evidence already indicated that strain ANG1 is more similar to P. daeponensis DSM 23529T ( = TF-218T) than to either DSM 17395 or DSM 24588 ( = 2.10) (unpublished results). Strain 2.10 was previously used in competition experiments + of bacterial biofilms on the thalloid green alga Ulva australis (Rao et al., 2005). Various physiological and genetic aspects of P. gallaeciensis DSM 17395 have also been studied, such as the pathway and substrate specificity of the algal metabolite dimethylsulfoniopropionate + (DMSP) catabolism (Dickschat et al., 2010), the compatibility of the plasmids (Petersen, 2011), and the primary metabolism by proteome analyses (Zech et al., 2009). +

+ +

With the description of the species P. gallaeciensis (basonym R. gallaeciensis) in 1998, the type strain BS107T was primarily deposited at the Collection Institute Pasteur (CIP; Paris, France) as CIP 105210 (Ruiz-Ponte et al., 1998). According to the strain history (http://www.straininfo.net/strains/620650), the CIP referred the strain to the Colección Española de Cultivos Tipo (CECT; Burjassot, Spain) and to the American Type + Culture Collection (ATCC; Manassas, USA), which in turn referred it to the Japan Collection of Micro-organisms at the RIKEN + Bioscience Center (Tsikiba, Japan) followed by a transfer to the NITE (National Institute of Technology and Evaluation) Biological + Resource Center (Kisarazu, Japan). At these culture collections the derivatives of strain CIP 105210 were designated CECT + 7277T, ATCC 700781T, JCM 21319T and NBRC 16654T, respectively. The Leibniz Institute DSMZ – German Collection of Microorganisms and Cell Cultures (DSMZ; Braunschweig, Germany) + independently requested P. gallaeciensis BS107T from the laboratory of the original depositor in 2005 and included it as DSM 17395 in the strain collection. Strain DSM 17395 + was subsequently collected by the Laboratorium voor Microbiologie (LMG; Gent, Belgium) and deposited as LMG 24391T. When investigating plasmid profiles of various Phaeobacter strains, we observed differences between the strains CIP 105210 and DSM 17395 even though both were considered identical + with the type strain BS107T. This is critical, as due to the broad scientific interest in the P. gallaeciensis type strain, it was either obtained from the public culture collections or retrieved from other sources several times. For + example, Seyedsayamdost et al. (2011b) allegedly used strain BS107T to investigate the mutualistic or pathogenic symbioses between P. gallaeciensis and the unicellular haptophycean alga Emiliania huxleyi. It was indicated that these authors received the strain BS107T from a collaborating laboratory; hence the biological identity of the strain used is ultimately unclear. +

+ +

In this study, we consequently reassessed the biological identity of these strains. We compared in detail the characteristics + of the strains CIP 105210 and DSM 17395 with those of the description of BS107T given by Ruiz-Ponte et al. (1998) and with those of other closely related Phaeobacter strains, i.e. P. gallaeciensis DSM 24588 ( = 2.10; Thole et al., 2012) and P. inhibens DSM 16374T ( = T5T; Martens et al., 2006). Based on our results, according reclassifications are proposed. +

+ +
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+ + +

Methods

+ +
+ + +
+ +

Source of bacteria and culturing.

+ +

The Phaeobacter strains DSM 16374T ( = T5T), DSM 17395, DSM 23529T ( = TF-218T), DSM 23566T ( = 20188T), DSM 24564T, DSM 24588 ( = 2.10) and DSM 25627T ( = 306T) as well as Roseobacter litoralis DSM 6996T, Marinovum algicola DSM 10251T and Roseobacter denitrificans DSM 7001T were obtained from the DSMZ. The Phaeobacter strain CIP 105210 was obtained from the CIP. Unless otherwise stated, cells were grown in marine broth 2216 (MB; Difco) or + on MB agar at 28 °C (and at 25 °C in case of P. leonis DSM 25627T). +

+ +
+
+ +

Profiles of the extrachromosomal elements.

+ +

To analyse the plasmid content of the Phaeobacter strains, their high-molecular-mass total genomic DNA was prepared within agarose plugs as previously described and subjected + to pulsed-field gel electrophoresis (PFGE; Pradella et al., 2010). PFGE was performed in a contour-clamped homogeneous electric field (CHEF) system on a CHEF-DR III device (Bio-Rad) with + 1 % or 1.2 % agarose gels and modified 0.5× TBE buffer (45 mM Tris, 45 mM boric acid, 0.1 mM EDTA) at 14 °C. PFGE parameters, + namely pulse time ramps and run times, were varied both to resolve chromosomal and extrachromosomal DNA and to identify different + plasmid conformations (Römling et al., 1996). Two PFGE parameter sets were applied to assess plasmid topology: (i) set A, 1 % (w/v) agarose gel with pulse times of 1 + to 48 s for 24 h at 200 V (6 V cm−1) and (ii) set B, 1 % (w/v) agarose gel with pulse times of 1 to 20 s for 22 h at 200 V (6 V cm−1). At least two PFGE gels were evaluated to determine plasmid sizes. The resulting plasmid profiles were interpreted as described + by Pradella et al. (2010). Conventional unidirectional gel electrophoresis of DNA was in 0.8 % agarose gels and 1× TBE (89 mM Tris, 89 mM boric acid, + 2 mM EDTA) at 10 °C and 70 mA for 8.5 h. The BAC Tracker supercoiled DNA ladder (from 38 to 120 kb; Epicentre) was used to + size plasmids with covalently closed circular (ccc) DNA topology. +

+ +
+
+ +

16S rRNA gene and 16S–23S rRNA gene internal transcribed spacer (ITS) analysis.

+ +

The PCR amplification of 16S rRNA genes from the genomic DNA of the Phaeobacter strains was done as described by Rainey et al. (1996). For the PCR amplification of the ITS region, the primer pair 16S_1401f 5′-GRGCCTTGYACACACCG-3′ (Lane, 1991) and 23S_130r 5′-GGTTBCCCCATTCRG-3′ (Gürtler & Stanisich, 1996) was used. Resulting PCR products were cycle sequenced with the primers mentioned above in ‘Extended Hot Shot’ reactions + as offered by the Seqlab company, Germany. The sequence analysis tool BioEdit 7.0.1 (http://www.mbio.ncsu.edu/BioEdit/bioedit.html) was utilized for 16S rRNA gene and ITS sequence editing. The accession numbers of retrieved 16S rRNA gene sequences from + P. gallaeciensis BS107T (Ruiz-Ponte et al., 1998), P. inhibens T5T (Martens et al., 2006), P. daeponensis TF-218T, P. arcticus 20188T, P. gallaeciensis LSS9 and P. leonis 306T were Y13244, AY177712, NR_044026, NR_043888, GQ906799 and HE661585, respectively. Further 16S rRNA gene or ITS sequences + used in this study were extracted from the genome sequences of Phaeobacter strains DSM 17395 (ABIF01000000), DSM 24588 ( = 2.10; CP002972–CP002975) and ANG1 (AFCF01000000) using the Integrated Microbial + Genomes (IMG) system (http://img.jgi.doe.gov/cgi-bin/w/main.cgi; Markowitz et al., 2012). +

+ +

Sequences were aligned with mafft version 6.850b, using the ‘--genafpair’ option but default settings otherwise (Katoh et al., 2005). Phylogenetic analysis under the maximum-likelihood (ML) criterion (Felsenstein, 1981) was conducted with RAxML version 7.2.8, using its novel rapid bootstrap option combined with the autoMRE bootstrapping criterion + (Pattengale et al., 2010) with subsequent search for the best tree under the GTRMIX approach (Stamatakis et al., 2008). Branch-and-bound search for the best trees under the maximum-parsimony (MP) criterion (Fitch, 1971) was done with paup* version 4.0b10 (Swofford, 2002), treating gaps as missing data and collapsing branches of zero minimum length; 1000 bootstrap replicates were conducted + in the same manner. The resulting best trees were rooted using the midpoint-rooting method (Farris, 1972; Hess & De Moraes Russo, 2007). +

+ +
+
+ +

MALDI-TOF MS protein analysis.

+ +

Whole-cell protein extracts of the Phaeobacter strains CIP 105210, DSM 17395, DSM 24588, DSM 16374T, DSM 23529T, DSM 23566T, DSM 24564T and DSM 25627T were analysed by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) using a Microflex + L20 mass spectrometer (Bruker Daltonics) equipped with a N2 laser. Sample preparation for MALDI-TOF MS protein analysis was carried out according to the ethanol/formic acid extraction + protocol recommended by Bruker Daltonics as described in detail by Tóth et al. (2008). The MALDI-TOF mass spectra were analysed with the BioTyper software (version 3.0; Bruker Daltonics). +

+ +
+
+ +

DNA–DNA hybridization (DDH).

+ +

Cells of the Phaeobacter strains CIP 105210, DSM 17395, DSM 16374T and DSM 24588 were disrupted by using a Constant Systems TS 0.75 kW (IUL Instruments) and the DNA in the crude lysate was + purified by chromatography on hydroxyapatite as described by Cashion et al. (1977). DNA–DNA hybridization was carried out as described by De Ley et al. (1970) and modified by Huß et al. (1983) using a model Cary 100 Bio UV/VIS-spectrophotometer equipped with a Peltier-thermostatted 6×6 multi-cell changer and a temperature + controller with in situ temperature probe (Varian). Each strain was measured in two technical replicates and the mean result was taken. +

+ +
+
+ +

Growth and hydrolysis experiments.

+ +

To determine the substrate spectrum of the Phaeobacter strains CIP 105210 and DSM 17395, cells were grown in artificial seawater (ASW; solution of Sigma sea salts: S9883) supplemented + with 10 mg caseine hydrolysate l−1 (CAS: 65072-00-6; Merck) to avoid auxotrophy and with different carbon sources at a concentration of 0.1 % each, including + 2-ketoglutarate, acetate, l-arabinose, butyrate, cellobiose, citrate, d-fucose, glucosamine, glycerol, l-leucine, maltose, l-rhamnose, l-serine, d-sorbitol, succinate, sucrose, trehalose, Tween 20, Tween 40 and Tween 80. The tests were performed in the 24-well microtitre-plate + format. In detail, cells were grown on MB agar for 2 days at 28 °C, then harvested with a sterile swab and inoculated in ASW + medium. The cell suspension was thereby adjusted to a turbidity of 80 % transmittance using a turbidimeter (AES Chemunex BLG + 3531). Afterwards, 2 ml of each suspension was pipetted into a 24-well microtitre plate (Greiner). A sample lacking any carbon + source was included as negative control. Cells were incubated in a microtitre plate reader (Infinite F200 pro; Tecan) at 23 + °C and with shaking at 88 r.p.m. for 7 days. Growth was automatically measured every 15 min with the Infinite F200 system + as increase of the OD600. Growth at temperatures of 4 °C and 37 °C was determined in 200 ml MB within Erlenmeyer flasks for one month and measured + photometrically as increase of the OD600 using an Ultrospec II spectrophotometer (LKB-Biochrom). +

+ +

Exoenzyme activities (hydrolysis of gelatin, starch and Tween 80) were analysed using MB solidified with 4 % (w/v) gelatin + or 1.5 % (w/v) agarose and supplemented with 0.2 % (w/v) starch and 1 % (v/v) Tween 80, respectively, as described by Smibert & Krieg (1981). As a positive control, R. litoralis DSM 6996T was used for gelatin and Tween 80 hydrolysis and M. algicola DSM 10251T for starch hydrolysis. Reduction of nitrate was tested according to Smibert & Krieg (1981) in MB supplemented with 0.1 % (w/v) potassium nitrate; R. denitrificans DSM 7001T served as a negative control. The assays were incubated for 7 days at 28 °C, except for the hydrolysis of starch, conducted + at 20 °C. The growth and hydrolysis tests described above were all performed in three technical replicates. +

+ +
+
+ +

Phenotype MicroArray (PM) experiments.

+ +

To determine the metabolic properties of the Phaeobacter strains CIP 105210, DSM 17395, DSM 24588 and DSM 16374T we used the PM technology (Biolog; Bochner, 2009). The Phaeobacter strains were grown on MB agar for 48 h and subsequently analysed using the Phenotype MicroArray MicroPlate PM01 and PM02-A + (AES Chemunex BLG 12111, BLG 12112) over 70 h; thus 190 different carbon sources were tested. Each strain was measured in + three biological replicates. The inoculation medium was modified according to the requirements of marine bacteria, i.e. 10 + ml of the inoculation fluid IF-0a (AES Chemunex BLG 72268) was supplemented with 1200 µl artificial seawater stock solution, + 120 µl vitamin stock solution, 12 µl trace element stock solution, 120 µl NaHCO3 buffer, 428 µl ultrapure H2O and 120 µl DyeD (AES Chemunex BLG 74224). The stock solutions had the following composition (l−1): (i) artificial seawater stock solution: 200 g NaCl, 40 g Na2SO4, 30 g MgCl2 . 6H2O, 5 g KCl, 2.5 g NH4Cl, 2 g KH2PO4, 1.5 g CaCl2 . 2H2O; (ii) trace element stock solution: 2.1 g FeSO4 . 7H2O, 13 ml 25 % HCl, 5.2 g Titriplex III (Na2EDTA; adjust pH to 6.0–6.5 to resolve), 190 mg CoCl2 . 6H2O, 144 mg ZnSO4 . 7H2O, 100 mg MnCl2 . 4H2O, 36 mg Na2MoO4 . 2H2O, 30 mg H3BO3, 24 mg NiCl2 . 6H2O, 2 mg CuCl2 . 2H2O; (iii) vitamin stock solution: 100 mg thiamine, 20 mg niacin, 8 mg 4-aminobenzoic acid, 2 mg biotin; and (iii) buffer stock + solution: 19 g NaHCO3. +

+ +

The cells were suspended in the modified inoculation medium using a sterile swab. The turbidity was adjusted to a cell density + of 85 % transmittance using a turbidimeter (AES Chemunex BLG 3531) and 100 µl of the cell suspension were pipetted in each + of the wells. The MicroPlates were sealed with Parafilm, incubated at 28 °C and measured in the Omnilog unit (Biolog). The + results were analysed using the R package ‘opm’ (Vaas et al., 2012). The curve parameter maximum height (A) was estimated for each substrate, differences were visualized using heat maps, and + the data were discretized into negative, ambiguous and positive reactions using the built-in functions of ‘opm’ under default settings. +

+ +
+
+
+
+ + +

Results

+ +
+ +

Profiles of the extrachromosomal elements

+ +

The high-molecular-mass genomic DNA of different Phaeobacter strains was separated with PFGE. A representative PFGE gel resolving linear DNA molecules in the size range from 23 to 533 + kb is shown in Fig. 1(a). In addition to the chromosomes (Fig. 1a, Chr) a distinct number of extrachromosomal bands was revealed for each of the strains CIP 105210, DSM 17395, DSM 24588 and + DSM 16374T. To determine the conformation of the detected extrachromosomal DNA (ccc versus linear; Pradella et al., 2010; Römling et al., 1996), we varied the PFGE conditions (PFGE parameter set A and B) in different gel runs. Using PFGE parameter set A, the fuzzy, + faint bands within the lanes of strains CIP 105210 and DSM 17395 (Fig. 1a, marked a, b and c, respectively) ran at approximately 319 (a) and 380 (b, c) kb (Fig. 1a). With PFGE parameter set B (data not shown) band (a) ran at 184 kb and bands (b) and (c) ran at approximately 210 kb indicating + that the respective bands migrated independently of the PFGE parameters applied. From this anomalous migration behaviour we + concluded that the inherent DNA had a circular conformation. The sizes of the detected ccc DNA were estimated as 66 (a) and + 79 (b, c) kb by conventional electrophoresis using the BAC Tracker as ccc size marker (data not shown). As these sizes were + close to those estimated for the linearized plasmids of 64 and 77 kb in Phaeobacter strain CIP 105210 and 75 kb in strain DSM 17395 (see below), it is most likely that they represent the same plasmids in different + conformations. +

+ +
+
Fig. 1.
View larger version: + +
+
+
Fig. 1. + +

(a) PFGE plasmid profiles of the Phaeobacter strains CIP 105210T, DSM 17395, DSM 24588 and DSM 16374T based on uncut high-molecular-mass genomic DNA. (b) Calculated plasmid sizes as mean values taken from at least two different + gel runs. The PFGE conditions were: 1 % (w/v) agarose gel with pulse times of 1 to 48 s for 24 h at 200 V (6 V cm−1). Chr, chromosomal DNA; λ, lambda phage concatemers as molecular-mass PFGE markers (New England Biolabs); li, linear. (*), The two largest plasmids (linearized forms) of Phaeobacter strains CIP 105210T and DSM 17395 migrated about the same distance in the gel and thus seemed to have an identical size. In contrast, both bands + could be clearly distinguished by their size in other PFGE runs (data not shown) using different DNA sample preparations. + DNA mobility is largely influenced by the DNA concentration of the sample. The observed discrepancy can thus be explained + by the relatively high DNA concentration in CIP 105210T (compared to DSM 17395T), which retards band migration (Römling et al., 1996). (†) (‡), The PFGE-based plasmid size estimations of 75 and 63 kb of DSM 17395 correspond to the plasmid sizes of 78 and 65 kb, respectively, + determined by genome sequencing (Thole et al., 2012; NC_018287.1, NC_018288.1). (§), The 36 kb plasmid of P. gallaeciensis CIP 105210T had a very low fluorescence intensity and is thus hardly visible on the gel image. ++, The 77 kb band of strain CIP 105210T showed increased fluorescence intensity and presumably represents a double band (plasmid duplet). +

+ +
+
+
+ +

By contrast, the sharp bands between 23 kb and 262 kb were separated strictly in accordance with their size when PFGE parameter + sets A and B were used. They were thus assumed linear (li, Fig. 1a), most possibly originating from randomly linearized ccc plasmids (Pradella et al., 2010). +

+ +

Regarding the linearized plasmid fraction of the Phaeobacter strains, which was very well suited to determine the plasmid complement of the strains and their sizes (Pradella et al., 2010), seven extrachromosomal replicons were evident in P. gallaeciensis CIP 105210, four in P. inhibens DSM 16374T and three in the strains DSM 17395 and DSM 24588. The estimated sizes of the detected plasmids (17 altogether) ranged from + 36 to 262 kb (Fig. 1b). They were all different, but their size distribution in the individual strains showed some similarity, i.e. all Phaeobacter strains have one large plasmid (262, 253, 239 and 227 kb in strains DSM 17395, CIP 105210, DSM 24588 and DSM 16374T, respectively) and two or three smaller ones in the size range between 63 and 77 kb. Our PFGE analysis thus indicated that + the Phaeobacter strains CIP 105210 and DSM 17395 – both deposited as type strain of Phaeobacter gallaeciensis – are not identical. +

+ +
+
+ +

Classification of the Phaeobacter strains using 16S rRNA gene sequence, MALDI-TOF MS protein and 16S–23S rRNA gene ITS analyses +

+ +
+ +

16S rRNA gene sequence analysis.

+ +

We re-evaluated the phylogenetic relationships of the Phaeobacter strains and therefore resequenced the PCR-amplified 16S rRNA genes of strains DSM 17395, DSM 16374T and CIP 105210. In the phylogenetic tree inferred from 16S rRNA gene sequences of representative members of the genus Phaeobacter, as well as strains DSM 24588 ( = 2.10), ANG1 and LSS9, for which finished or draft genome sequences exist (Collins & Nyholm, 2011; Fernandes et al., 2011; Thole et al., 2012; Fig. 2), the Phaeobacter strains DSM 17395, DSM 24588 ( = 2.10), DSM 16374T and CIP 105210 clustered together (P. gallaeciensis/P. inhibens cluster) and were well separated from the P. arcticus/P. leonis lineage and the branch formed by P. caeruleus, Phaeobacter sp. ANG1 and P. daeponensis (16S rRNA gene identity ≥97.8 %). Within the P. gallaeciensis/P. inhibens cluster, the 16S rRNA gene of strain CIP 105210 (KC176239) grouped together with the originally deposited BS107T sequence (Y13244), exhibiting 72 % and 91 % support from MP and ML bootstrapping, respectively. The 16S rRNA gene sequences + of the Phaeobacter strains DSM 17395, DSM 24588 and DSM 16374T (KC176240) were identical and differed by four bases from the P. gallaeciensis CIP 105210 sequence KC176239 (16S rRNA gene identity of 99.7 %; see below). +

+ +
+
Fig. 2.
View larger version: + +
+
+
Fig. 2. + +

Midpoint-rooted MP phylogeny inferred from 16S rRNA gene sequences of Phaeobacter strains closely related to P. inhibens and P. gallaeciensis. Branches are scaled in terms of the minimum number of substitutions (using deltran optimization; Stamatakis et al., 2008). Numbers above branches are support values from MP (left) and ML (right) bootstrapping. Original designation of strains + that are deposited at culture collections is indicated in parentheses; square brackets give the respective accession number. +

+ +
+
+
+ +

Neither the 16S rRNA gene sequence of P. gallaeciensis CIP 105210 (KC176239) nor the sequence of P. inhibens DSM 16374T (KC176240) was exactly identical to that of the original deposit, P. gallaeciensis BS107T (Y13244) or P. inhibens T5T (AY177712), respectively (Fig. 2, Fig. S1 available in IJSEM Online). More precisely, the 16S rRNA gene sequences of the alleged P. gallaeciensis type strains differed at the base positions (Escherichia coli numbering; Gutell et al., 1994) 47, 260, 777, 928, 930, 1030, 1210 and 1387 (Fig. S1; Table S1); and those of the alleged P. inhibens type strains at the positions 29, 1210, 1387, 1436, 1459, 1466 and 1480 (Fig. S1; Table S2). We assessed in detail whether + these discrepancies could be caused by sequencing errors, as is already indicated by the long-terminal branches leading to + BS107T and T5T (Fig. 2). We thus compared the respective sequences with the bacterial 16S rRNA variability map (Baker et al., 2003) and/or the 16S rRNA secondary structure model (Gutell et al., 1994) and showed that the 16S rRNA gene sequences provided in this study were all in accordance with bases categorized as conserved + by Baker et al. (2003) or the proposed rRNA secondary structure (Tables S1 and S2), whereas the previously determined 16S rRNA gene sequences Y13244 + and AY177712 were flawed. +

+ +

Furthermore, we examined whether the four differences in the 16S rRNA gene sequences of P. gallaeciensis CIP 105210 (KC176239) and P. inhibens DSM 16374T (KC176240) were genuine. They were localized at the base positions 614 (P. gallaeciensis: G; P. inhibens: A) and 626 (P. gallaeciensis: C; P. inhibens: U) within the 16S rRNA variable region V4 (Baker et al., 2003) and at the positions 835 (P. gallaeciensis: G; P. inhibens: A) and 851 (P. gallaeciensis: C; P. inhibens: U) within the variable V5 region, respectively (E. coli numbering; Fig. S1; Table S3). Comparison with the secondary 16S rRNA structure model (Gutell et al., 1994) and a simulation of the rRNA folding using the Mfold web server (Zuker, 2003) indicated that bases 614 and 626 paired in the variable region V4 stem–loop (Fig. 3); similarly, bases 835 and 851 matched in the V5 stem–loop (Fig. S2). We thus assumed that the present transitions of G and + C in P. gallaeciensis to A and U in P. inhibens, respectively, reflect genuine and characteristic mutations in the 16S rRNA genes of these species. Considering these bases, + the 16S rRNA gene sequence of Phaeobacter strain CIP 105210 resembled the original one of BS107T (Y13244), which would indicate that strain CIP 105210 is the type strain of P. gallaeciensis. +

+ +
+
Fig. 3.
View larger version: + +
+
+
Fig. 3. + +

Secondary structure of the 16S rRNA variable region V4 of P. gallaeciensis CIP 105210T (a) and P. inhibens DSM 17395 (b) demonstrating transition of bases 614 and 626 (E. coli numbering; bases 529 and 541 according to the CIP 105210T numbering). RNA folding was simulated using the Mfold web server for nucleic acid folding and hybridization prediction (Zuker, 2003; http://mfold.rna.albany.edu/?q=mfold/RNA-Folding-Form). +

+ +
+
+
+
+
+ +

MALDI-TOF MS analysis.

+ +

In the MALDI-TOF MS dendrogram (Fig. 4), the Phaeobacter strains DSM 16374T, DSM 24588 and DSM 17395 not only formed a cluster but were virtually indistinguishable from each other. Strain CIP 105210 + appeared as the sister group of those three strains, whereas P. daeponensis and P. caeruleus as well as P. arcticus and P. leonis were well set apart. +

+ +
+
Fig. 4.
View larger version: + +
+
+
Fig. 4. + +

Score-oriented dendrogram showing the similarity of MALDI-TOF mass spectra from cell extracts of selected Phaeobacter strains. The dendrogram was generated by the BioTyper software (version 3.0; Bruker Daltonics). +

+ +
+
+
+
+
+ +

ITS analysis.

+ +

A comparable picture was observed in the ITS analysis (Fig. 5). Phaeobacter strain DSM 17395 appeared as sister strain of P. inhibens DSM 16374T with 93 % support under ML and 99 % support under MP. The sister-group relationship of these and strain DSM 24588 was supported + with 70 % and 88 % bootstrap values, respectively, to the exclusion of P. gallaeciensis CIP 105210. Phaeobacter sp. ANG1 was placed in a distinct cluster together with the type strains of P. daeponensis and P. caeruleus (100 % support). +

+ +
+
Fig. 5.
View larger version: + +
+
+
Fig. 5. + +

Midpoint-rooted ML phylogeny inferred from ITS sequences of Phaeobacter strains closely related to P. inhibens and P. gallaeciensis. Branches are scaled in terms of the expected number of substitutions per site. Numbers above branches are support values + from ML (left) and MP (right) bootstrapping. Original designation of strains that are deposited at culture collections is + indicated in parentheses; square brackets give the respective accession number. +

+ +
+
+
+
+
+
+ +

DNA–DNA hybridization.

+ +

In contrast to the highly similar genomic DNA between the strains DSM 17395 and DSM 16374T (82 %) as well as between the strains DSM 16374T and DSM 24588 (83 %), strain CIP 105210 shared only 62 % and 63 % DNA–DNA relatedness to the strains DSM 17395 and DSM 16374T, respectively (Table 1). This is below the threshold of 70 % recommended by Wayne et al. (1987) hence indicating the status of strain CIP 105210 in a separate species. Conversely, the values clearly above 70 % indicate + that strains DSM 17395, DSM 16374T and DSM 24588 belong to the same species. +

+ +
+
+
View this table: +
+
+
Table 1. + Mean DNA–DNA similarity values (n = 2) between the Phaeobacter strains CIP 105210T, DSM 17395, DSM 16374T and DSM 24588 + +
+
+
+
+
+ +

Growth, hydrolysis and PM experiments

+ +

The growth and hydrolysis experiments for Phaeobacter strains CIP 105210 and DSM 17395 could only partially reproduce those conducted by Ruiz-Ponte et al. (1998) (Table S4). The results for strain CIP 105210 differed from all other series of measurements by growth of this strain on + l-arabinose and hydrolysis of Tween 80. Strain DSM 17395 showed no specific characteristics, but it – as well as CIP 105210 + – differed from strain BS107T (Ruiz-Ponte et al., 1998) as they grew on serine (like T5T; Martens et al., 2006) and showed slow growth on l-rhamnose and 2-ketoglutarate (Table S4). The overall number of specific differences of all other strains to T5T (Martens et al., 2006) was four (growth on citrate, glucosamine and on MB at 4 °C or 37 °C). +

+ +

In contrast, the PM experiments, which are more sensitive than bacterial growth tests because they monitor substrate respiration + (Bochner et al., 2001), yielded significant physiological differences between all four tested Phaeobacter strains, DSM 24588, DSM 16374T, DSM 17395 and CIP 105210 (Figs S3 and S4). The physiological similarity between strains CIP 105210 and DSM 17395 was high, + but the differences between the two were clearly reproducible. According to the discretization approach implemented in ‘opm’ (Vaas et al., 2012), respiration on tyramine (PM01-H04; blue box Fig. S3) was positive in DSM 17395 and DSM 16374, weak in DSM 24588 but negative + in CIP 105210. Respiration on butyrate (PM02A-D12; Fig. S4) was positive in CIP 105210 and DSM 24588, weak in DSM 16374T, but negative in DSM 17395. +

+ +

Regarding the common subset of growth or hydrolysis experiments on the one hand and PM experiments on the other hand, the + results were identical with a few exceptions. Expectedly, no substrate was detected on which growth (or hydrolysis) was measurable + but respiration was not observed, whereas on some substrates respiration was detected by PM analysis even though these substrates + sustained no growth. Accordingly, a weak PM reaction on l-arabinose (PM01-A02) and a positive PM reaction on citrate (PM01-F02) were observed for all four tested strains. A positive + PM reaction to Tween 80 (PM01-E05) was observed for strains DSM 24588 and CIP 105210, whereas strains DSM 17395 and DSM 16374T showed a weak reaction (compare red boxes in Fig. S3 with Table S4). +

+ +
+
+
+ + +

Discussion

+ +

According to the PFGE profiles of the extrachromosomal elements – which are largely supported by the complete genome sequences + of the Phaeobacter strains DSM 17395, DSM 24588 (Thole et al., 2012), DSM 16374T (Dogs, M. and others, unpublished) and CIP 105210 (Frank, O. and others, unpublished) – DDH similarities, 16S rRNA gene sequence + analysis, 16S–23S rRNA gene ITS sequence analysis, MALDI-TOF MS protein analysis, and high-throughput phenotyping using the + PM technology, the Phaeobacter strains CIP 105210 and DSM 17395, both supposed to be deposits of the type strain of P. gallaeciensis BS107T, are biologically clearly distinct. ITS sequence and MALDI-TOF analysis additionally showed that DSM 17395 (and DSM 24588) + group together with P. inhibens DSM 16374T to the exclusion of CIP 105210. As confirmed by DDH (≥76 % similarity), DSM 16374T, DSM 17395 and DSM 24588 are conspecific, i.e. all belong to the species P. inhibens. Analysis of 16S rRNA gene sequences was in accordance with this finding, too, because the sequences of these strains were + identical (if the resequenced 16S rRNA gene sequence of DSM 16374T was considered). Our sequence analyses confirmed the finding of Thole et al. (2012) that the Phaeobacter sp. ANG1 does not belong to the species P. gallaeciensis. +

+ +

Because DSM 17395 must hence be excluded from the species P. gallaeciensis, the question arises whether the alternative type strain deposit, CIP 105210, represents P. gallaeciensis BS107T. DDH analysis (<70 % similarity) indicates that CIP 105210 is not conspecific with P. inhibens. Analysis of growth behaviours and enzymic activities could not fully reproduce the findings of Ruiz-Ponte et al. (1998), but given the overall low number of characters tested, the low number of known differences to the type strain of the sister + species, P. inhibens, and the well-known difficulties in reproducing physiological tests in distinct laboratories in general, the significance + of these discrepancies is unclear. Essentially, based on the newly generated CIP 105210 16S rRNA gene sequence that is identical + to the one from BS107T, except for deviations that were likely to be sequencing errors, we could clearly document the type strain status of P. gallaeciensis CIP 105210T. As the strains CIP 105210T and DSM 17395 have been independently deposited at the CIP and the DSMZ, respectively, it is the most probable explanation + that the later strain has been mixed-up prior to deposition. +

+ +

Research laboratories are usually not equipped with sufficient resources to verify the biological identity of their cultures. + Moreover, culture collections have to cope with the deposition of interchanged or contaminated strains and the quality of + incoming material will presumably even deteriorate due to the decline of basic microbiological methodology in the era of molecular + biology. Problems are expected particularly if confusion with closely related strains has occurred, as in the case of DSM + 17395, which apparently belongs to the sister species of the correct strain. Hence, it is advisable that researchers working + on a certain strain exactly denote the source from which it was received. Providing the accession numbers of culture-collection + deposits (such as ‘CIP 105210T’ or ‘DSM 17395’) should thus be preferred over just stating the original strain designator (such as ‘BS107T’) irrespective of the source from which the strain has been received. In any case, with respect to cultivatable microbes, + only strains with a demonstrable history should be considered in serious research. +

+ +

The three homologous plasmids of the completely sequenced P. inhibens strains DSM 17395 and DSM 24588 exhibit a long-range synteny (Thole et al., 2012), but several indels (insertions/deletions) are responsible for the deviating plasmid sizes [262 versus 238 kb (DnaA-like + replicon; Petersen, 2011), 75(78) versus 94 kb (RepB-I), 65(63) versus 70 kb (RepA-I); Fig. 1]. Homologues of these replicons may also be present in the sister species P. gallaeciensis CIP 105210T e.g. represented by the 253, 77 and 64 kb replicons. However, the conspicuously different plasmid profiles in P. gallaeciensis and P. inhibens (Fig. 1) may reflect horizontal recruitment of four additional replicons in P. gallaeciensis CIP 105210T. The same explanation is supported by the presence of a type IV secretion system on the fourth 86 kb plasmid of the P. inhibens type strain DSM 16374T (Dogs, M. and others, unpublished), which may be responsible for plasmid mobilization via conjugation (Petersen et al., 2013). In the near future, genome sequencing and comparative genomics of more distantly related strains, such as Phaeobacter arcticus, will help to reveal the extent of horizontal exchange and vertical evolution within the Roseobacter clade. +

+ +
+
+ +

Acknowledgements

+ +

This work, including a PhD stipend for N. B., was supported by the Transregional Collaborative Research Center ‘Roseobacter’ of the Deutsche Forschungsgemeinschaft (Transregio TRR 51) and the MICROME project, EU Framework Program 7 Collaborative + Project (222886-2). We thank Victoria Michael, Bettina Sträubler and Ulrike Steiner for excellent technical assistance, Brian + Tindall and Sabine Gronow for their helpful discussions, as well as the two anonymous reviewers for their constructive criticism. +

+ +
+
+ +

References

+
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+ +
+

Designation of type strains for seven species of the order Myxococcales and proposal for neotype strains of Cystobacter ferrugineus, Cystobacter minus and Polyangium fumosum

+
+
    + +
  1. Hans Reichenbach2,
  2. +
+
    +
  1. 1Leibniz-Institut DSMZ – Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH, Inhoffenstrasse 7B, 38124 Braunschweig, + Germany +
    +
  2. +
  3. 2Helmholtz-Zentrum für Infektionsforschung, Inhoffenstrasse 7, 38124 Braunschweig, Germany +
    +
  4. +
+
    +
  1. Corresponding
    Elke Lang ela{at}dsmz.de
  2. +
+
+
+ +

Abstract

+ +

Ten species of the order Myxococcales with validly published names are devoid of living type strains. Four species of the genus Chondromyces are represented by dead herbarium samples as the type material. For a species of the genus Melittangium and two species of the genus Polyangium, no physical type material was assigned at the time of validation of the names or later on. In accordance with rule 18f of + the International Code of Nomenclature of Bacteria the following type strains are designated for these species: strain Cm + a14T ( = DSM 14605T = JCM 12615T) as the type strain of Chondromyces apiculatus, strain Cm c5T ( = DSM 14714T = JCM 12616T) as the type strain of Chondromyces crocatus, strain Sy t2T ( = DSM 14631T = JCM 12617T) as the type strain of Chondromyces lanuginosus, strain Cm p51T ( = DSM 14607T = JCM 12618T) as the type strain of Chondromyces pediculatus, strain Me b8T ( = DSM 14713T = JCM 12633T) as the type strain of Melittangium boletus, strain Pl s12T ( = DSM 14670T = JCM 12637T) as the type strain of Polyangium sorediatum and strain Pl sm5T ( = DSM 14734T = JCM 12638T) as the type strain of Polyangium spumosum. Furthermore, the type strains given for three species of the genera Cystobacter and Polyangium had been kept at one university institute and have been lost according to our investigations. In accordance with Rule 18c + of the Bacteriological Code, we propose the following neotype strains: strain Cb fe18 ( = DSM 14716  = JCM 12624) as the neotype + strain of Cystobacter ferrugineus, strain Cb m2 ( = DSM 14751 = JCM 12627) as the neotype strain of Cystobacter minus and strain Pl fu5 ( = DSM 14668 = JCM 12636) as the neotype strain of Polyangium fumosum. The proposals of the strains are based on the descriptions and strain proposals given in the respective chapters of Bergey’s Manual of Systematic Bacteriology (2005). +

+ +
+
+ +
    +
  • +

    Retired. +

    +
  • +
  • +

    Two supplementary tables are available with the online version of this paper.

    +
  • +
+
+

An exceptionally high number of myxobacterial species descriptions is not supported by the availability of formally acknowledged + living type strain material. Because of this lack of material, the species could not be included, for example, in species-representing + 16S rRNA gene sequence databases. These are the most frequently used guides in taxonomy currently, and for that reason, great + efforts are taken to fill the sequencing gaps (Yarza et al., 2013). The International Code of Nomenclature of Bacteria (Lapage et al., 1992) allows for the designation of type strains in cases where descriptions or dead specimens represent the type given for species + with validly published species names. The code also allows for the proposal of neotype strains if a specimen of the strain + on which the original description was based cannot be found. These measures have been installed in order to clear the way + for inclusion of such species in future examinations, in particular in studies including ‘new’ methods which had not been + applied at the time of the species description. In this communication, we formally designate type strains for seven and formally + propose neotype strains for three species of the order Myxococcales. +

+

The present wording of Rule 18f of the International Code is: ‘If a description or illustration constitutes, or a dead preserved + specimen has been designated as the type of a species [Rule 18a(1)] and a later strain of this species is cultivated, then + the type strain may be designated by the person who isolated the strain or by a subsequent author. This type strain shall + then replace the description, illustration or preserved specimen as the nomenclatural type. The designation of a type strain + in this manner must be published in the IJSB/IJSEM, the authorship and date of priority of publication being determined by + the effective and valid publication of the name by the original authors (Rule 24b)’. +

+

The presently designated type strains of the species Chondromyces apiculatus (Thaxter, 1897), Chondromyces crocatus (Berkeley & Curtis, 1874), Chondromyces lanuginosus (Kofler, 1913) and Chondromyces pediculatus (Thaxter, 1904) are dead herbarium specimens in the Thaxter collection (TC), housed in the Farlow Herbarium, Harvard University, Cambridge, + USA (Table 1). Howard McCurdy studied myxobacteria at the University of Windsor, Ontario, Canada during the period around 1960–1970. He + assigned specific samples of the Thaxter collection as the types of these species (McCurdy, 1971). The species names were included in the Approved Lists (Skerman et al., 1980). According to a curator of the herbarium, the specimen for Chondromyces lanuginosus seems to be lost whereas the other three specimens are still there, dried on the original substrates, accompanied by some + slides. +

+
+
+
View this table: +
+
+
Table 1. + Myxobacterial species for which a cultivable type strain or neotype strain is formally proposed and the 16S rRNA sequences + of the proposed neotype strains. AL, type strain as given in Approved Lists (Skerman et al., 1980). VL, types as given in Validation List No 31 (Brockman, 1989b, c) + +
+
+
+

For the species Melittangium boletus (Jahn, 1924), Polyangium sorediatum (Brockman, 1989a) and Polyangium spumosum (Brockman, 1989a) no physical type strains were assigned in the Approved Lists (Skerman et al., 1980) or in Validation List No. 31 (Brockman, 1989b,c), respectively. Instead, the descriptions of Brockman (1989a) or simply the statement ‘not cultivated’ are given. +

+

Bergey’s Manual of Systematic Bacteriology, second edition, includes comprehensive chapters about the members of the order + Myxococcales. Reichenbach (2005a, b, c, d, e) are the chapters relevant to the taxa mentioned in this paper. These chapters are based on the experience and knowledge + accumulated during 40 years of intense investigations on myxobacteria and were written after more than 3000 myxobacterial + strains had been isolated. Based on the original species descriptions, appropriate strains were selected and described as + the type strains of the respective species (Table 1). However, it has not been formally proposed in the IJSEM until now to accept these strains as the type strains. +

+

For the reason that presently dead preserved material constitutes-, or a description has been designated-, the type strain + of the mentioned species, or no type strain has been assigned, it is formally proposed that the strains selected by Reichenbach + shall be designated the type strains of the respective species according to Rule 18f. The proposed type strains listed in + Table 1 shall replace the dead specimen or descriptions. These are Chondromyces apiculatus Cm a14T, Chondromyces crocatus Cm c5T, Chondromyces lanuginosus Sy t2T, Chondromyces pediculatus Cm p51T, M. boletus Me b8T, P. sorediatum Pl s12T and P. spumosum Pl sm5T. The prerequisite for the acceptance of type strains, their deposit and availability in two culture collections is achieved. + The designation of the type strains is based on the descriptions given in the respective chapters of Bergey’s Manual (Reichenbach 2005a, c, d). In order to facilitate the comparison of these recent descriptions with those of the authors who originally proposed, revived + or emended the species these original descriptions are assembled in Table S1 available in IJSEM Online. The fatty acid composition + of the proposed type strains are given in Table S2 (Garcia et al., 2011). The figures from the original descriptions and of the proposed type strains are shown face to face with figures showing + the proposed type strains in Figs 110. +

+
+
Fig. 1.
View larger version: + +
+
+
Fig. 1. + +

Chondromyces apiculatus. (a) Drawing from Thaxter (1897), plate XXX on pages 405–406. (b) Fruiting body (bar, 100 µm) and vegetative cells (insert; bar, 10 µm) of Cm a14T. +

+ +
+
+
+
+
Fig. 10.
View larger version: + +
+
+
Fig. 10. + +

Polyangium fumosum. (a) Drawing from Krzemieniewska & Krzemieniewski (1930), plate XVI, nos 6–9 depict P. fumosum. Courtesy of the Polish Botanical Society. (b) Swarm of PI fu5 (bar, 2000 µm) and single sporangium of PI fu5 (insert; bar, + 100 µm). (c) Fruiting bodies of PI fu5. Bar, 300 µm. +

+ +
+
+
+

The Bacteriological Code also allows for the proposal of neotype strains according to Rule 18c: ‘If a strain on which the + original description was based cannot be found, a neotype strain may be proposed. A neotype strain must be proposed (proposed + neotype) in the IJSB, together with citation of the author(s) of the name, a description or reference to an effectively published + description and a record of the permanently established culture collection(s) where the strain is deposited (see also Note + 1 to Rule 24a)’. +

+

The species Cystobacter ferrugineus, Cystobacter minus and Polyangium fumosum were first described by Krzemieniewska & Krzemieniewski (1926, 1927, 1930). McCurdy assigned three of his isolates as the type strains for the above-mentioned three species (McCurdy, 1970; Table 1). The species names and type strains were included in the Approved Lists (Skerman et al., 1980) but they have never been deposited in a culture collection to the best of our knowledge. In 2007, we wrote a letter to the + head of the microbiology laboratory of the University of Windsor with the request for subcultures of the strains Cystobacter ferrugineus M-203T, Cystobacter minus M-307T and P. fumosum M257T. Even though the importance for microbial taxonomy was stressed there was no response. In 2012, another attempt to contact + the department at Windsor University was more successful in the respect that we received answers from two colleagues at Windsor + and from H. D. McCurdy who retired several years ago. However, they informed us that they cannot find the samples. Since 1981, + there have been no scientific papers originating from the University of Windsor dealing with myxobacteria (PubMed), a fact + additionally suggesting that nobody at the university had a research interest to keep the cultures alive or, at least, under + surveillance. For that reasons we conclude that these cultures must have been lost. +

+

Since the presently assigned type strains of the mentioned species are no longer available as living cultures it is formally + proposed that the strains selected by Reichenbach shall be proposed as the neotype strains of the respective species in accordance + with Rule 18c, as given in Table 1. The deposit and availability of the neotype strains from two culture collections is achieved. The proposals of the neotype + strains are based on the suggestions in (Reichenbach (2005b, d). In these chapters, the strains Cystobacter ferrugineus Cb fe18, Cystobacter minus Cb m2 and P. fumosum Pl fu5 were proposed as the type strains according to the species descriptions given in the respective chapters which rely + on the original species descriptions by Krzemieniewska and Krzemieniewski and McCurdy (Reichenbach 2005b, d). However, since type strains have already been assigned these strains have to be proposed as the neotype strains of the + respective species according to rule 18c. +

+
+
Fig. 2.
View larger version: + +
+
+
Fig. 2. + +

Chondromyces crocatus. (a) Drawing from Berkeley (1857), page 313. (b) Fruiting bodies of Cm c5T. Bar, 500 µm. +

+ +
+
+
+
+
Fig. 3.
View larger version: + +
+
+
Fig. 3. + +

Chondromyces lanuginosus. (a) Figures from Kofler (1913), Figs 13 on page 877 depict Chondromyces lanuginosus. Courtesy Österreichische Akademie der Wissenschaften. (b) Fruiting body of Sy t2T. Bar, 100 µm. +

+ +
+
+
+
+
Fig. 4.
View larger version: + +
+
+
Fig. 4. + +

Chondromyces pediculatus. (a) Drawing from Thaxter (1904), plate XXVI on page 411; nos 7–13 depict Chondromyces pediculatus. (b) Fruiting body of Cm p51T. Bar 100 µm. +

+ +
+
+
+
+
Fig. 5.
View larger version: + +
+
+
Fig. 5. + +

Melittangium boletus. (a) Drawing from Jahn (1924), plate II, Fig. 17 on page 78. Courtesy Bornträger-Cramer, www.borntraeger-cramer.de. (b) and (c) Fruiting bodies of Me b8T. Bars, 120 and 80 µm, respectively. +

+ +
+
+
+
+
Fig. 6.
View larger version: + +
+
+
Fig. 6. + +

Polyangium sorediatum. (a) Drawing from Thaxter (1904), plate XXVII. Nos 22–30 depict P. sorediatum. (b and c) Fruiting bodies of PI s12T. Insert: crushed sporangium releasing the single sporangioles. Bars, 200 µm. +

+ +
+
+
+
+
Fig. 7.
View larger version: + +
+
+
Fig. 7. + +

Polyangium spumosum. (a) Figures from Krzemieniewska & Krzemieniewski (1926), plate V; no. 19 depicts P. spumosum and from Krzemieniewska & Krzemieniewski (1930), plate XVI; nos 10–12 depict P. spumosum. Courtesy of the Polish Botanical Society. (b–d) Degenerated fruiting bodies of PI sm5T. Bars, 500, 100 and 250 µm, respectively. +

+ +
+
+
+
+
Fig. 8.
View larger version: + +
+
+
Fig. 8. + +

Cystobacter ferrugineus. (a) Figures from McCurdy (1970). (b–d) Strain Cb fe18, (b) myxospores and (c) fruiting bodies on Escherichia coli as food bacteria and (d) on a cellulose plate. Bars, 10 µm, 1 mm and 10 mm, respectively. +

+ +
+
+
+
+
Fig. 9.
View larger version: + +
+
+
Fig. 9. + +

Cystobacter minus. (a), Figures from McCurdy (1970). (b and c), Fruiting bodies of Cb m2. Bars, 500 µm and 200 µm, respectively. +

+ +
+
+
+
+ +

Acknowledgements

+ +

We are thankful to K. Poling and I. Churchill at Windsor University, G. Lewis-Gentry at the Harvard University Herbaria and + H. D. McCurdy for taking the effort to investigate the disposition of the type materials. +

+ +
+
+ +

References

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    +
  46. +
+
+
+
+ +
+ | + + + Table of Contents + + + +
+
+ + FREE ARTICLE + + +
+
+
+

This Article

+
+
    +
  1. +
    + + + + + doi: + 10.1099/ijs.0.056440-0 + + + + IJSEM + + vol. 63 + + no. Pt 11 + + 4354-4360 + + + + + + + +
    +
  2. +
+
+ +
+

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+
    +
  1. + +
  2. +
+
+ + + + +
+

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+
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+ +
+

Spirosoma endophyticum sp. nov., isolated from Zn- and Cd-accumulating Salix caprea

+
+
    + + + +
  1. Angela Sessitsch
  2. +
+
    +
  1. AIT Austrian Institute of Technology GmbH, Bioresources Unit, Tulln, Austria
    +
  2. +
+
    +
  1. Correspondence
    Angela Sessitsch angela.sessitsch{at}ait.ac.at
  2. +
+
+
+ +

Abstract

+ +

A Gram-reaction-negative, yellow-pigmented strain, designated EX36T, was characterized using a polyphasic approach comprising phylogenetic, morphological and genotypic analyses. The endophytic + strain was isolated from Zn/Cd-accumulating Salix caprea in Arnoldstein, Austria. Analysis of the 16S rRNA gene demonstrated that the novel strain is most closely related to members + of the genus Spirosoma (95 % sequence similarity with Spirosoma linguale). The genomic DNA G+C content was 47.2 mol%. The predominant quinone was and the major cellular fatty acids were summed feature + 3 (iso-C15 : 0 2-OH and/or C16 : 1ω7c), C16 : 1ω5c, iso-C17 : 0 3-OH and iso-C15 : 0. On the basis of its phenotypic and genotypic properties, strain EX36T should be classified as a novel species of the genus Spirosoma, for which the name Spirosoma endophyticum sp. nov. is proposed. The type strain is EX36T ( = DSM 26130T = LMG 27272T). +

+ +
+
+ +
    +
  • +

    The GenBank/EMBL/DDBJ accession number for the 16S rRNA gene sequence of strain EX36T is GQ342559. +

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    A supplementary figure is available with the online version of this paper.

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This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted + use, distribution, and reproduction in any medium, provided the original work is properly cited. +

+
+

The genus Spirosoma was first proposed by Larkin & Borrall (1984) and belongs to the family Flexibacteraceae in the phylum Bacteroidetes. At the time of writing the genus Spirosoma includes five species, the type species Spirosoma linguale (Larkin & Borrall, 1984), Spirosoma rigui (Baik et al., 2007), Spirosoma panaciterrae (Ten et al., 2009), Spirosoma spitsbergense and Spirosoma luteum (Finster et al., 2009). So far, Spirosoma strains have been isolated from various habitats, such as fresh water, permafrost soil or soil from a ginseng field. Strain + EX36T, which is proposed in this study to represent a novel species, was isolated in course of the analysis of bacteria associated + with the heavy metal accumulating plant Salix caprea (Kuffner et al., 2010). +

+

For the isolation of strain EX36T, Salix caprea trees growing on a former Zn/Pb mining and processing site in Arnoldstein (Austria) were sampled (Kuffner et al., 2010). Xylem sap extract was directly plated on 10 % tryptic soy agar (TSA, Merck Darmstadt, Germany) and after 1 week of incubation + single colonies were picked and streaked on phosphate-poor MOPS medium (Neidhardt et al., 1974) containing 0.1 % glucose and 1 mM ZnSO4. The strain was routinely cultured on 10 % TSA. For maintenance, the cell material was suspended in 10 % tryptic soy broth + (TSB, Merck, Darmstadt, Germany) containing 15 % glycerol and stored at −80 °C. Endophytic colonization was confirmed by inoculating + two maize and two potato cultivars, growing the plants under in vitro conditions and reisolating the strain from root and stem tissues. +

+

For the extraction of bacterial DNA the Gen Elute Bacterial Genomic DNA kit (Sigma–Aldrich) was used. The 16S rRNA gene was + amplified by PCR using the primers 8f (5′-AGAGTTTGATCCTGGCTCAG-3′) (Weisburg et al., 1991) and 1520r (5′-AAGGAGGTGATCCAGCCGCA-3′) (Edwards et al., 1989). Sequencing of the amplified PCR product was performed by LGC Genomics (Berlin, Germany). The obtained partial sequences + were assembled using the programs BioEdit (Hall, 1999) and seqman pro (DNAstar). The consensus sequence was subjected to nucleotide blast analysis (http://blast.ncbi.nlm.nih.gov/Blast.cgi) to search the database of the National Center for Biotechnology Information (NCBI) for the closest relatives of the bacterial + strains with validly published names. Sequence comparisons indicated that the isolate belonged to the family Flexibacteraceae. +

+

Nearly complete 16S rRNA gene sequences of strain EX36T and of all species of the genus Spirosoma with validly published names and of selected species of the family Cytophagaceae, which were downloaded from the NCBI GenBank sequence database, were imported into the arb program package (Ludwig et al., 2004). Sequences were aligned into the silva SSURef 102 (Pruesse et al., 2007) database by using the option ‘autosearch by PT_server’ of the arb editor. Alignments were manually corrected using the arb editor. A maximum-likelihood phylogenetic tree was reconstructed using RAxML v. 7.4.2 (Stamatakis, 2006a) by execution of the following command line in raxmlGUI v. 1.3 (Silvestro & Michalak, 2012): raxmlHPC.exe -T 2 <number of processors >-f a -m GTRGAMMA -x 336 <seed1 >-p 115 <seed2 >-N 100 <bootstraps >-o CarHomin + <outgroup >-s <input file >-O <output order >. We used a combination of the Gamma model of rate heterogeneity (Yang, 1994) and the CAT model (Stamatakis, 2006b), which was implemented in the rapid bootstrapping algorithm, (Stamatakis et al., 2008) was performed with 100 replicates and using general time reversible (GTR) as the substitution matrix. In Fig. 1 the position of EX36T in the distinct cluster of the genus Spirosoma can be clearly recognized. The calculation of pairwise sequence similarity using a global alignment algorithm (Myers & Miller, 1988), which was implemented at the EzTaxon-e server (http://eztaxon-e.ezbiocloud.net/; Kim et al., 2012) showed highest sequence similarity values for strain EX36T to Spirosoma linguale DSM 74T (95.7 %), followed by S. luteum SPM-10T (93.9 %), S. spitsbergense SPM-9T (93.9 %), S. rigui KCTC 12531T (93.8 %) and S. panaciterrae Gsoil 1519T (92.5 %). +

+
+
Fig. 1.
View larger version: + +
+
+
Fig. 1. + +

Maximum-likelihood tree (bootstrap: 100 replicates) based on 16S rRNA gene sequence data (sequence length 1296 bp) showing + the phylogenetic position of strain EX36T among related species selected from the phylum Bacteroidetes. Cardiobacterium hominis ATCC 15826T (M35014) was used as an outgroup. +

+ +
+
+
+

Growth of strain EX36T was tested at various temperatures (4, 20, 23, 28, 37 and 41 °C) on 10 % TSA plates for up to 1 week. The pH range for growth + (pH 4, 5, 6, 7, 8 and 9) was determined by measuring OD600 changes in cultures incubated at 28 °C with shaking at 190 r.p.m. compared with an uninoculated control. Salt tolerance was + determined by amending 10 % TSB with NaCl to final concentrations of 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.8, 1.0, 2.0, 3.0, 4.0, + 5.0 and 10.0 % NaCl (w/v). The Gram reaction of strain EX36T was determined by using the non-staining method described by Buck (1982). Pigment analysis of cells grown on 10 % TSA was performed in triplicates by extraction with acetone according to the method + described by Denner et al. (2001) using a U-2900 spectrophotometer (Hitachi). Minimal inhibition concentrations (MIC) for Zn and Cd were determined according + to the method of Kuffner et al. (2008). Additionally cells were tested for flexirubin pigments using the method described by Bernardet et al. (2002). Oxidase and catalase activity were tested as outlined by Smibert & Krieg (1994). Additional biochemical tests were performed by the Identification Service of the DSMZ (Leibniz-Institut DSMZ-Deutsche Sammlung + von Mikroorganismen und Zellkulturen GmbH, Braunschweig, Germany) using API 20NE (bioMérieux) and GENIII plates (Biolog). + Cell morphology after 4 days of growth at 28 °C was investigated using fluorescence and bright-field microscopy (IX81, Olympus; + Axiovert 200 M, Zeiss). Antibiotic susceptibility was determined by the disc diffusion method on 10 % TSA plates. +

+

Cells of strain EX36T were rod-shaped, Gram-reaction-negative and 1.2×2−17.5 µm in size (Fig S1, available in IJSEM Online). Most cells were arranged + in pairs, but filaments up to 55 µm were observed. EX36T showed yellowish, opaque, semi-translucent colonies with a smooth and shiny surface and a circular and convex shape. The + diameter of colonies grown on 10 % TSA at 28 °C for 1 week varied between 1.5 and 3.0 mm. The strain was positive for catalase + and oxidase activity; detailed results of biochemical and physiological analyses are listed in Table 1 and in the species description. In contrast to other species of the genus Spirosoma, cells of EX36T showed a length up to 17.5 µm, did not grow at 5 and 42 °C, did not tolerate NaCl concentrations higher than 0.6 % (w/v), + had the lowest genomic G+C content and showed differences in antibiotic susceptibility. Low tolerance of Cd and Zn was observed + (slow growth at 4 mM Zn and 1 mM Cd). The analysis of yellow pigments showed three absorption maxima at 428, 453 and 483 nm. + EX36T was negative for flexirubin-type pigments. +

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View this table: +
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+
Table 1. + Differential characteristics of strain EX36T and recognized species of the genus Spirosoma + +

Strains: 1, EX36T (data from this study); 2, S. linguale DSM 74T (Larkin & Borrall, 1984; and this study); 3, S. luteum DSM 19990T (Finster et al., 2009); 4, S. spitsbergense DSM 19989T (Finster et al., 2009); 5, S. rigui KCTC 12531T (Baik et al., 2007); 6, S. panaciterrae DSM 21099T (Ten et al., 2009). All strains are catalase-positive, Gram-reaction-negative and negative for nitrate reduction, utilization of gluconate, + caprate, adipate and glycerol. +, Positive; −, negative; w, weakly positive; nd, not determined; r, resistant; s, susceptible. +

+ +
+
+
+

Analyses of cellular fatty acid composition, respiratory quinones, polar lipids and chromosomal G+C content were performed + by the Identification Service of the DSMZ. The fatty acid profile was determined according to the protocol of the Microbial + Identification System (MIDI). The major fatty acids of strain EX36T were summed feature 3 (iso-C15 : 0 2-OH and/or C16 : 1ω7c; 49.3 %), C16 : 1ω5c (23.8 %), iso-C17 : 0 3-OH (6.2 %) and iso-C15 : 0 (5.4 %). A detailed overview of the cellular fatty acid profiles of all species of the genus Spirosoma can be found in Table 2. Differences between the fatty acid profile of EX36T and other species of the genus Spirosoma were found in the amounts of iso-C15 : 0, C16 : 1ω5c and summed feature 3. In contrast to S. linguale DSM 74T, the fatty acids C15 : 0 and anteiso-C15 : 0 were not detected. +

+
+
+
View this table: +
+
+
Table 2. + Fatty acid profiles (%) of strain EX36T and its closest phylogenetic neighbours from the genus Spirosoma + +

Strains: 1, EX36T (data from this study); 2, S. linguale DSM 74T (data from this study); 3, S. luteum DSM 19990T (Finster et al., 2009); 4, S. spitsbergense DSM 19989T (Finster et al., 2009); 5, S. rigui KCTC 12531T (Baik et al., 2007); 6, S. panaciterrae DSM 21099T (Ten et al., 2009). tr, Trace amount (<1 %); −, not detected. +

+ +
+
+
+

The predominant menaquinone, in accordance with all other species of the genus Spirosoma, was MK-7. As polar lipids, phosphatidylethanolamine, two aminophospholipids, two aminolipids, a glycolipid and three unknown + lipids were detected on the TLC plate. The DNA G+C content of strain EX36T was 47.2 mol%, which is lower than reported values for all other species of the genus Spirosoma with validly published names. +

+

The analysis of DNA−DNA similarity of strain EX36T with its nearest phylogenetic neighbour S. linguale DSM 74T was also carried out by the Identification Service of the DSMZ. The experiment was performed in duplicates. DNA−DNA hybridization + showed a DNA−DNA similarity of 12.2 % (second measurement: 17.2 %), demonstrating that these two strains do not represent + the same species. +

+

The present data regarding 16S rRNA gene sequence analysis, physiological, chemotaxonomic and morphological properties indicates, + that strain EX36T represents a distinct species in the genus Spirosoma, for which the name Spirosoma endophyticum sp. nov. is proposed. +

+
+ + + +
+ +

Description of Spirosomaendophytica sp. nov. +

+ +

Spirosom endophyticum (en.do.phy′ti.cum. Gr. Pref. endo within; Gr. n. phyton plant; L. neut. suff. ‐icum adjectival suffix used with the sense of belonging to; N.L. neut. adj. endophyticum within plant, referring to the endophytic nature of the strain and its isolation from plant tissue). +

+ +

Cells are rod-shaped, Gram-reaction-negative, non-spore-forming, with a size of 1.2×2–17.5 µm. A yellow pigment which is not + of the flexirubin type is produced. Filaments up to 55 µm may be formed. Colonies on 10 % TSA are opaque, semi-translucent + with a smooth and shiny surface and a circular, convex shape. Aerobic growth occurs at 20–28 °C (optimum at 28 °C), pH 5–8 + (optimum at pH 7); tolerates concentrations up to 0.6 % NaCl (w/v) in the medium, whereas best growth was achieved in absence + of NaCl. Positive for catalase and oxidase activity. Nitrate is not reduced and indole is not produced. Negative for glucose + fermentation, hydrolysis of arginine and gelatin, and urease activities and positive for aesculin hydrolysis. Does not utilize + the following substrates: arabinose, mannitol, N-acetylglucosamine, gluconate, caprate, adipate, malate, citrate, phenylacetate, β-methyl d-glucoside, d-salicin, n-acetyl-β-d-mannosamine, n-acetyl neuraminic acid, d-galactose, d-fucose, l-fucose, l-rhamnose, inosine, d-arabitol, myo-inositol, d-aspartic acid, d-serine, glycyl-l-proline, l-alanine, l-arginine, l-aspartic acid, l-glutamic acid, l-serine and pectin. The following substrates are weakly utilized: dextrin, maltose, trehalose, cellobiose, gentiobiose, sucrose, + turanose, stachyose, α-lactose, melibiose, α-d-glucose, d-mannose, d-fructose, d-mannitol and l-histidine. d-Raffinose and N-acetyl-d-glucosamine are utilized. Susceptible to the following antibiotics (µg per disc): streptomycin (10), kanamycin (30), chloramphenicol + (60) and rifampicin (15) and resistant to ampicillin (10), polymyxin B (20), tetracycline (15) and erythromycin (15). The + major fatty acids are summed feature 3 (iso-C15 : 0 2-OH and/or C16 : 1ω7c), C16 : 1ω5c, iso-C17 : 0 3-OH and iso-C15 : 0; the complete fatty acid profile can be found in Table 2. The predominant menaquinone is MK-7. The major polar lipid is phosphatidylethanolamine. +

+ +

The type strain, EX36T ( = DSM 26130T = LMG 27272T), was isolated from Zn/Cd-accumulating Salix caprea in Arnoldstein, Austria. The DNA G+C content of the type strain is 47.2 mol%. +

+ +
+
+
+ +

Acknowledgements

+ +

We thank Marlies Polt for technical support and Katharina Fallmann, Friederike Trognitz and Muhammad Naveed for helpful discussions. + This study was supported by the Austrian Science Foundation [Förderung der wissenschaftlichen Forshung (FWF) grant no. L561-B17]. +

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References

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00000000..3083fc2d Binary files /dev/null and b/examples/theses/20130912_Fei_YAO/fulltext.pdf differ diff --git a/examples/theses/20130912_Fei_YAO/fulltext.pdf.txt b/examples/theses/20130912_Fei_YAO/fulltext.pdf.txt new file mode 100644 index 00000000..d27d2820 --- /dev/null +++ b/examples/theses/20130912_Fei_YAO/fulltext.pdf.txt @@ -0,0 +1,4116 @@ +Carbon-Based Nanomaterials as an Anode for Lithium +Ion Battery +Fei Yao, Costel Sorin Cojocaru +To cite this version: +Fei Yao, Costel Sorin Cojocaru. Carbon-Based Nanomaterials as an Anode for Lithium Ion +Battery. Micro and nanotechnologies/Microelectronics. Ecole Polytechnique X, 2013. English. + +HAL Id: pastel-00967913 +https://pastel.archives-ouvertes.fr/pastel-00967913 +Submitted on 31 Mar 2014 +HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est +archive for the deposit and dissemination of sci- destine´e au de´poˆt et a` la diffusion de documents +entific research documents, whether they are pub- scientifiques de niveau recherche, publie´s ou non, +lished or not. The documents may come from e´manant des e´tablissements d’enseignement et de +teaching and research institutions in France or recherche franc¸ais ou e´trangers, des laboratoires +abroad, or from public or private research centers. publics ou prive´s. + + + + + + + +Carbon-Based Nanomaterials as an Anode +for Lithium Ion Battery + + + + + + +Fei YAO + + + + + + + + +LPICM-École Polytechnique, CNRS (UMR 7647) +Laboratoire de Physique des Interfaces et Couches Minces +Route de Saclay; 91128 PALAISEAU Cedex , France + + + + +The Graduate School +Sungkyunkwan University +Department of Energy Science (DOES) +IBS Center for Integrated Nanostructure Physics +300 Cheoncheon-dong, Jangan-gu, Suwon 440-746, R. O. Korea + + + + +THÈSE + +Présentée pour obtenir le grade de +DOCTEUR DE L’ ÉCOLE POLYTECHNIQUE +Spécialité: Physique +Par +Fei YAO + + + +Carbon-Based Nanomaterials as an Anode +for Lithium Ion Battery + + + + + + +Soutenue le 27 / 06 / 2013 devant le jury constitué de : + + +M. Jean-Pierre Pereira-Ramos Directeur de Recherche CNRS Rapporteur +M. Kee Seok Nahm Professor à Chonbuk National University Rapporteur +M. Won Sub Yoon Professor à Sungkyunkwan University Examinateur +M. Marc Chatelet Directeur de Recherche CNRS Examinateur +M. Costel-Sorin Cojocaru Chargé de recherche au CNRS Directeur de Thèse +Enseignant à l’École polytechnique +M. Young Hee Lee Professor à Sungkyunkwan University Directeur de Thèse + + + + + + + + + +LABORATOIRE DE PHYSIQUE DES INTERFACES ET COUCHES MINCES (LPICM) +CNRS, UMR7647, ÉCOLE POLYTECHNIQUE + + + + + +The Graduate School +Sungkyunkwan University +June 2013 + + +ACKNOWLEDGMENTS +First and foremost, I would like to express my greatest gratitude to Prof. +Young Hee Lee and Dr. Costel Sorin Cojocaru, my advisors of graduate research, for +their patient guidance and continuous support throughout the last three years. They +taught me strict sense of research, humble attitude of study, and correct path in life. I +feel so lucky and honored for being their student in the most important days of my +growth. Their great fairness, concern and understanding will be appreciated through +all my life. +My sincerely thanks are extended to all my coworks, Dr. Fethullah Güneş, Mr. +Bing Li, Dr. Kangpyo So, Mr. Huy Quang Ta, Mr. Jian Chang, Mr. An Quoc Vu, Mr. +Seung Jin Chae, Dr. Hongyan Yue, Prof. Didier Pribat and Prof. Sishen Xie, in +Sungkyunkwan University. And also Dr. Seung Mi Lee from Center for +Nanocharacterization, Korea Research Institute of Standards, Dr. Kyeu Yoon Sheem +from Science and Samsung SDI Corporate R&D Center. +I would like to dedicate this thesis to my parents and sister for their continuous +understanding, support, and love. My deepest appreciation to my beloved husband, +Humin Li, for his love, encouragement and accompanying all the time! + + +TO MY PARENTS… + + + ABSTRACT + + + +In this thesis work, carbon-based nanomaterials using as an anode for +lithium ion battery have been generally investigated. Compared to typical +micron-sized carbon materials, nanosized carbon materials exhibited great +potentials not only in practical anode application but also in the fundamental +science exploration of Li ion diffusion. In the case of practical application, one +dimensional carbon nanofibers (CNFs) fabricated by electrospinning was +prepared for anode material. The structure involves neither a metal substrate nor +binders and therefore eventually benefited the capacity and long term stability. +Yet, the energy density is still limited to 370 mAh/g of conventional carbon. In +order to improve the capacity of raw carbon nanofibers, silicon, a high Li storage +material, was incorporated by electrochemical deposition. The resulted Si/CNF +mat improved clearly the capacity of carbon materials more than twice for most +of cases. + +In the case of fundamental study, chemical vapor deposition (CVD)- +synthesized two dimensional graphene was chosen to be a media to reveal the +diffusion pathways of Li ion. Compared to typical graphite which contains both +basal and edge planes, a well defined basal plane with large area can be realized +in graphene to provide a comprehensive picture of lithium diffusion mechanism. +We have discovered that electrochemical reaction of electrode +(substrate/graphene) not only is related to the number of graphene layers but also +relies on the defect sites on the basal plane of graphene. Combing the +experimental results and density functional theory calculations, we proved that +basal plane hindered lithium ion diffusion with a high diffusion barrier height, +whereas divacancies and higher order defects can be shortcuts for lithium ion +diffusion. + + +Keyworks: nanocarbon materials, lithium ion battery, carbon nanofiber, silicon, +graphene, lithium ion diffusion + + + + +I + +RESUME + + + +Dans ce travail de thèse, nous avons exploré l’utilisation des nanomatériaux +à base de carbone comme anode pour les batteries lithium-ion. Par rapport aux +matériaux d’anode classiques qui sont de type carbone graphitique a des tailles de +grains de l’ordre du micromètre, les matériaux de carbone de taille nanométrique +présentent un grand potentiel non seulement pour l'application pratique en tant +que matériau d'anode, mais aussi du point de vue de la science fondamentale car +permettent l'exploration fine des phénomènes de diffusion des ions lithium. Dans +le cadre de l'application pratique, nous avons exploré les nanofibres +unidimensionnelles de carbone (CNF) en tant que matériau d'anode. Cette +structure d’anode comporte un substrat métallique comme collecteur de courant +mais n’avons pas utilisé des liants ce qui bénéficie a la stabilité à long terme. +Pourtant, la densité d'énergie que nous avons obtenu était encore limitée à 370 +mAh /g similaire à celle du carbone conventionnel. Afin d'améliorer la capacité +des nanofibres de carbone bruts, nous les avons recouverts de silicium (par dépôt +électrochimique), un matériau d’insertion de lithium avec une bien plus +importante capacité de stockage. Le tapis hybrides Si / CNF ont permis +d'améliorer nettement la capacité des matériaux de carbone jusqu'à deux fois de +plus pour la plupart des cas. + + Du point de vue des études fondamentales, le graphène matériau +bidimensionnel, a été synthétisé par dépôt chimique en phase vapeur (CVD) et +utilisé comme un support pour mettre en évidence les chemins de diffusion des +ions lithium. Par rapport à du graphite classique qui contient à la fois les deux +plans de type basal et prismatique, seulement un plan basal bien défini et d’une +grande surface spécifique peut être réalisé dans le cas du graphène. Nous avons +découvert que la réaction électrochimique a l'électrode (substrat / graphène) est +non seulement liée au nombre de couches de graphène mais s'appuie également +sur la présence de défauts dans le plan de graphène. Combinant les résultats +expérimentaux et les calculs de théoriques, nous avons pu prouver que le plan +basal empêche la diffusion des ions de lithium avec une hauteur de barrière de +diffusion élevé, alors que les divacancies et les défauts d'ordre supérieur peuvent +constituer des raccourcis pour la diffusion des ions de lithium. + + +Keyworks: Matériaux des nanocarbonés, batterie lithium-ion, nanofibre de +carbone, Silicium, graphène, diffusion des ions lithium +II + +Table of Contents +1 +Introduction +Bibliography of Introduction 4 +Chapter 1. Overview of Rechargeable Lithium Ion Battery +1.1 Electrochemical Energy Storage Systems 6 +1.2 Rechargeable Lithium Based Battery 8 +1.3 Rechargeable Lithium Ion Battery 11 +Bibliography of Chapter 1 13 +Chapter 2. Carbonaceous Materials as An Anode of Li-Ion Battery +2.1 Operation Mechanism of Li-Ion Battery 16 +2.2 Classification of Carbonaceous Materials 21 +2.2.1 Graphitic Carbon 21 +2.2.2 Non-graphitic Carbon 22 +2.3 Lithium Intercalation into Carbonaceous Materials 24 +2.3.1 Lithium Intercalation into Graphitic Carbon Materials 24 +2.3.1-1 Description 24 +2.3.1-2 Charge/Discharge Profile of Graphitic Carbon Materials 26 +2.3.2 Lithium Intercalation into Non-graphitic Carbon Materials 29 +III + +2.3.2-1 Low Specific Charge Carbon 29 +2.3.2-2 High Specific Charge Carbon 31 +2.4 Summary of Chapter Two 36 +Bibliography of Chapter 2 38 +Chapter 3. Silicon-Coated Carbon Nanofiber Mat for Anode of Lithium +Ion Battery +One Dimensional Carbon Materials as an Anode Material for +3.1 51 +LIB +3.1.1 General Introduction of CNFs and CNTs 51 +3.1.2 CNFs and CNTs Using as an Anode Material for LIB 56 +3.1.3 Fabrication Methods of CNFs and CNTs 58 +3.1.3-1 Chemical Vapor Deposition for Both CNFs and CNTs 58 +3.1.3-2 Electrospinning Method for CNFs Mat 63 +Electrospinning Fabricated CNFs Mat as an Anode Material +3.2 66 +for LIB +SEM and Raman Characterization of CNFs Synthesized +3.2.1 67 +Through Electrospinning +Anode Performance of CNFs Synthesized Through +3.2.2 69 +Electrospinning +3.3.3 Anode Performance of CNF-Si Mat 83 +IV + +3.4 Summary of Chapter Three 95 +Bibliography of Chapter 3 97 +Chapter 4. Diffusion Mechanism of Lithium Ions through Basal Plane of +Layered Graphene +4.1 Brief Introduction of Two Dimensional Graphene 105 +4.1.1 General Physical Properties of Graphene 105 +4.1.2 Synthesis Methods of Graphene 110 +Diffusion Mechanism of Lithium Ions through Basal Plane of +4.2 113 +Layered Graphene +4.2.1 Material Preparation 116 +4.2.2 Transfer Process of Graphene 116 +4.2.3 Characterization of Graphene 117 +4.2.4 Anode Performance of Graphene 121 +4.3 Summary of Chapter Four 140 +Bibliography of Chapter 4 141 + + + + +V + +List of Tables +Table 3.1 Anode performance comparison of silicon/CNF composites 89 +fabricated by different methods. CNF film is usually fabricated +by mixing CNF powder with a binder. CNF mat is binder-free +freestanding film fabricated by electrospinning method. +Table 4.1 Defects related Li adsorption energy, and Li atomic charges 137 +calculated by Mulliken, Hirshfeld, and electrostatic potential +(ESP) at the minimum energy configurations (M) and the barrier +states (B). Positive charge indicates charge depletion from +lithium atom. + + + + + + + + + + + + + + +VI + +List of Figures +Fig. 1.1 Ragone plot showing energy density vs. power density for 7 +various energy storage devices. +Fig. 1.2 Comparison of the different battery technologies in terms of 8 +volumetric and gravimetric energy density. +Fig. 1.3 Schematic representation of lithium batteries. a, Rechargeable 10 +lithium-metal battery, dendrite formation was shown in the +negative electrode. b, Rechargeable lithium-ion battery. +Fig. 1.4 Current issues remaining in different types of anode materials. 12 +Fig. 2.1 Schematic illustration of detailed charge/discharge process in Li- 15 +ion battery. +Fig. 2.2 Potential profile of anode and cathode during charge/discharge. 17 +Fig. 2.3 Charge curves of different metals (M) with respect to highly 18 +oriented turbostratic pitch carbon fibers. +Fig. 2.4 Left: Schematics of the crystal structure of hexagonal graphite 20 +with an AB stacking order. Right: view perpendicular to the +basal plane of graphite. Edges can be subdivided into arm-chair +and zigzag faces. +Fig. 2.5 Schematic indications of (a) graphite and (b) non-graphitic 23 +(disordered) carbonaceous material. +Fig. 2.6 Structure indications of LiC6. (a) Left: schematic drawing 25 +showing the AA layer stacking sequence with Li intercalation. +Right: simplified representation. (b) Perpendicular view to the +basal plane of LiC6. (c) Enlarged schematic of AA stacking +order. +VII + +Fig. 2.7 Schematic indication of stage formation during Li ion 26 +intercalation into graphite layers. +Fig. 2.8 Constant current charge/discharge curves of the graphite 27 +(Timrex KS 44, Cirr is the irreversible specific charge, and Crev is +the reversible specific charge). +Fig. 2.9 Constant current charge/discharge curves of a coke (Conoco). 31 +(Cirr is the irreversible specific charge, Crev the reversible +specific charge). +Fig. 2.10 a) Storage mechanisms of Li ions in graphite. b) Li storage in a 33 +form of Li2 covalent molecules. c) Schematic model of Li +storage in cavities and nanopores. d) Li adsorption on the two +sides of an isolated graphene sheet. +Fig. 2.11 Constant current charge/discharge curves (1st and 2nd cycle) of 34 +a high specific charge carbon material after heat treatment at 700 +°C. (Cirr is the irreversible specific charge, Crev the reversible +specific charge). +Fig. 3.1 Schematic comparison of the diameter dimensions on a log scale 52 +for various types of fibrous carbons. +Fig. 3.2 Wrapping of graphene sheet to form SWNT. 53 +Fig. 3.3 Schematic indications of (a) SWCNT, (b) MWCNT, and the 54 +corresponding TEM images in (c) and (d). +Fig. 3.4 Chiral vector and chiral angle θ definition for a (2, 4) 55 +nanotube on graphene sheet. and .are the unit cell vectors +of the two-dimensional hexagonal graphene sheet. The +circumference of nanotube is given by the length of chiral +vector. The chiral angle θ is defined as the angle between +VIII + +chiral vector and the zigzag axis. +Fig. 3.5 CVD process-fabricated (a) CNT power, (b) vertically aligned 59 +CNTs, and (c) CNF planar network. +Fig. 3.6 Typical anode assembling based on CVD process fabricated 62 +carbon powder. +Fig. 3.7 Schematic of CNF mat fabrication processes: (a) schematic of 65 +electrospinning apparatus and (b) the fabricated nanofiber +network. +Fig. 3.8 SEM images of as-synthesized CNFs with (a) top view and (b) 68 +cross-sectional images. +Fig. 3.9 Micro Raman spectra of CNFs mat fabricated by electrospinning 68 +method. +Fig. 3.10 (a) Voltage profiles electrospinning fabricated CNF mat between 70 +0.01 and 2 V at a charging rate of 0.1 C. The cycle numbers are +indicated in the figure. (b) Rate performance and columbic +efficiency of the above sample. +Fig. 3.11 (a) Structure deformation indication of Si based film/particles 73 +before and after charge/discharge cycling. (b) SEI images of +st th +CVD deposited Si thin film on Cu stustrate after 1 and 30 +cycles of charge/discharge. +Fig. 3.12 Schematic of the apparatus for electrodeposition of Si. The cell 74 +consists of three electrodes: woking electrode (as-fabricated +CNF mat), counter electrode (Pt wire) and reference electrode ++ +(Ag/Ag ). During the deposition, a Si-containing electrolyte +(SiCl4 in PC) was add into the cell and a cyclic voltage scan (20 +-1 +mV s ) was applied to the electrodes. +IX + +Fig. 3.13 (a) Cyclic voltammograms of silicon electrodeposition in PC 76 +-1 +solution with/without SiCl4 at a scan rate of 20 mV s . (b) Mass +and thickness of Si/CNF mat with respect to different silicon +deposition cycles. The error bar is added in the figure. +Fig. 3.14 (a) Micro-Raman spectra of bare CNF mat and Si/CNF mat with 78 +200 cycles of Si deposition before/after annealing, indicated as +Si-200-p and as Si-200-a in the figure. (b) XPS spectra of the +electrode surface with active materials consisting of Si-200-p +and Si-200-a, respectively. +Fig. 3.15 SEM images of (a) Si-200-p and (b) Si-200-a samples. Dark 79 +color portion indicates electrolyte residues on the surface of +CNF mat. After 1000 °C annealing, the uniform mat surface was +observed by the removal of electrolyte, as shown in (b). +Fig. 3.16 (a) SEM images of as-synthesized bare CNFs and (b) Si-200-a. 80 +The cross-sectional images are shown in the insets. (c) AFM +image of Si-200-a. The high resolution image of dashed square +in (c) is shown in (d). +Fig. 3.17 (a) TEM image of Si-200-a. The EDS line profile along the 81 +dashed line is shown in (b). +Fig. 3.18 High-resolution XPS spectra of Si/CNF with 200 cycles of Si 83 +deposition before and after annealing. Figure (a) and (c) are C 1s +and Si 2p fitted peaks before annealing. (b) and (d ) are C 1s and +Si 2p fitted peaks after 1000 °C annealing. Peak positions and +relative ratios are shown in the figure. +Fig. 3.19 (a) CV profile comparison between bare CNF mat and CNF mat 84 +° stafter 1000 C annealing. The curves were recorded after 1 CV +-1 +scan between 0.01 to 2 V at a scan rate of 0.1 mV s . (b) AC +X + +impedance spectra of the above two electrodes. The spectra were +recorded right after the cell assembling before cycling. +nd th +Fig. 3.20 (a) The 2 and 10 cyclic voltammograms of CNF-a (square), 86 +Si-200-p (dashed line) and Si-200-a (solid line) mats between +-1 +0.01 and 2 V at a scan rate of 0.1 mV s . (b) and (c) are voltage +profiles of Si-200-p/Si-200-a and CNF-a/Si-200-a between 0.01 +and 2 V at a charging rate of 0.1 C. The cycle numbers are +indicated in the figure. (d) Charge/discharge capacity and +Coulombic efficiency of Si-200-a for the first 80 cycles. +Fig. 3.21 (a) Charge (filled symbols)/discharge (open symbols) capacity in 90 +terms of different numbers of silicon deposition cycles after high +temperature annealing. Capacity was calculated based on silicon +mass only. Sample indications are shown in the right dashed +square. (b) AC impedance spectra of the above five electrodes. +The spectra were recorded right after the cell assembling before +cycling. The equivalent circuit is shown in the inset. The related +resistance value in Figure (b) was plotted in Figure (c) with +respect to different silicon deposition cycles. +Fig. 3.22 SEM images of (a-b) Si-1500-p and (c-d) Si-1500-a samples. 92 +Fig. 3.23 Charaterizations of Si-200-a electrode after 80 cycles 94 +charge/discharge. (a) Top-view SEM image, (b) Cross-sectional +SEM image, (c) High resolution TEM image, and (d) AFM +image. The SEI layer was selectively removed by washing the +sample with acetonitrile and diluted HCl. +Fig. 4.1 Graphene is a basic 2D building block for other carbon 106 +allotropes with different dimensionalities. +Fig. 4.2 a) Honeycomb lattice of graphene with two carbon atoms per 107 +XI + +unit cell. b) Tight-binding band structure of graphene π-bands, +considering only nearest neighbor hopping. c) Band structure +near K point showing the linear dispersion relation. +Fig. 4.3 Electronic Structure of: a) Metal: Finite Density of States (DOS) 109 +at Fermi energy. b) Semiconductor: Gap at Fermi energy. c) +Graphene: Zero gap Semiconductor. Zero DOS metal. +Fig. 4.4 Production techniques of graphene: a) Micro-cleavage method, 112 +isolating graphitic layers from graphite into monolayer graphene +flakes with the help of a cohesive tape, b) epitaxial growth of +graphene by decomposition of SiC into graphene, c) chemical +vapor deposition method by decomposition of hydrocarbon +gases on metal substrates, and d) chemical exfoliation of +graphite oxide by weakening van der Waals cohesive force via +insertion of reactants into interlayer space. +Fig. 4.5 Schematic of fabrication process with Cu-grown SLG or Ni- 117 +grown MLG (left panel). Bilayer and trilayer graphene can be +fabricated by transferring monolayer graphene repeatedly. +Photograph of as-prepared monolayer graphene (PMMA on top) +floating in water and CR 2032 coin cell case (right panel). +Fig. 4.6 Schematic of a coin cell structure with Cu-grown SLG or Ni- 118 +grown MLG. Bilayer and trilayer graphene coin cells were +fabricated by transferring monolayer graphene repeatedly. +Fig. 4.7 Optical micrographs of (a) Cu-grown SLG and (b) Ni-grown 120 +MLG on SiO2/Si substrate. White dashed lines indicate wrinkles. +Some portion of thicker graphene is indicated by arrows. (c) +Schematic of (i) SLG with a well defined basal plane and (ii) +edge plane enriched MLG. (d) Micro-Raman spectra of SLG and +MLG. Confocal Raman mapping of D/G intensity ratio of (e) +XII + +SLG and (f) MLG from squared positions of (a) and (b). The +contrast is normalized to 0.4 to visualize the defect distribution +for both images. (g) Wavelength-dependent transmittance +(values are provided at a wavelength of 550 nm) and (h) optical +photographs of different number of graphene layers on PET +substrate. +Fig. 4.8 (a) Cyclic voltammograms of different number of graphene 123 +layers samples at a scan rate of 0.1 mV/s. SUS-related redox +reaction peaks (SO, SR) and lithium intercalation/deintercalation +st +related peaks (LiIn/LiDe) are marked in the figure. (b) 1 and (c) +nd +2 galvanostatic charge/discharge profiles of different number +2 +of graphene layers at a current density of 5 µA/cm . (d) The +related layer-dependent capacities. Two regimes of corrosion- +dominant and lithiation-dominant are indicated. +nd +Fig. 4.9 Cyclic voltammograms at a scan rate of 0.1 mV/s (a) and 2 125 +galvanostatic charge/discharge profiles at a current density of 5 +2 +µA/cm (b) of bare CR2032 coin cell case and foil SUS 316. +Fig. 4.10 AC impedance spectra obtained by applying a sine wave with an 128 +amplitude of 10 mV over a frequency range from 100 kHz to 10 +mHz. The inset shows impedance at higher frequency region to +demonstrate charge transfer resistance. +Fig. 4.11 Theoretically estimated capacity based on LiC6 intercalation. No 130 +absorption of Li ions occurs at monolayer graphene. +Fig. 4.12 (a) Raman spectra, (b) cyclic voltammograms at a scan rate of 134 +0.1 mV/s, and (c) 2nd galvanostatic charge/discharge profiles at +2 +a current density of 5 A/cm for monolayer graphene treated by +Ar plasma with different plasma powers (15 W and 100 W). (d) +nd +Capacity of 2 charge as a functional of number of graphene +XIII + +layers under different Ar plasma powers. Absolute slopes +according to different plasma powers and critical layer thickness +(lc) are indicated in the figure. (e) Schematics of proposed Li +diffusion mechanism through defects on the basal plane with +different defect population. Broad down arrows indicate Li ion +diffusion through defect sites of basal plane. Red glows +represent steric hindrance for Li ion diffusion formed by the +accumulated Li ions or functional groups. The inset in the right +indicates the relative magnitude of diffusion coefficient. (f) +Relationship of D/G ratio with the extracted slope from (d). +Fig. 4.13 Side and top views of atomic configurations (top panel), 137 +isosurface images of electrostatic potential (second panel), bond + + lengths and local charge distributions at the barrier states (third + +panel), and the diffusion barrier profiles of Li (bottom panel) + + through (a) graphene hexagonal site (H site), (b) Stone-Wales + +(SW) defect (c) monovacancy (V1), and (d) divacancy (V2). + + 3Isovalue for rendering isosurfaces is 0.25 e/Å . The insets in the + +third panel show isosurface image of electrostatic potential for + + each corresponding structure without Li ion. Bond lengths + +(yellow color) and electrostatic potential charges (white color) + + are in units of Å and electrons, respectively. + + + + + + + +XIV + +INTRODUCTION + +The issue of the sustainability of energy supply has attracted worldwide +concern due to the crisis in rapid depletion of fossil energy resources along with +serious environmental pollution issues. Over the past several decades, +tremendous efforts have been made in developing alternative technologies to +harvest and store sustainable clean energy. Thanks to the development of +nanoscience and nanotechnology, clean energy technologies are progressing +impressively which makes them more practical and price competitive with fossil +fuels. Clean energy technology covers production, storage, and conversion. +Researches on energy production from renewable natural resources include solar +energy conversion, wind, geothermal and hydraulic energy and involve often +heavy engineering works. Our main concern using nanoscience from basic +science point of view is energy storage. Among all different kinds of energy +storage systems, rechargeable lithium-ion battery (LIB) is one of the greatest +successes of modern material electrochemistry. It has drawn the most attention +not only because of its higher energy density and longer cycle life compared to +any existing battery systems but also its lightweight and compact which benefit +the application in hybrid vehicles and portable electronics [1]. + +LIB consists of an anode (negative electrode) and a cathode (positive +electrode). These two electrodes are capable of reversibly hosting lithium in ionic +1 + +form. Common candidates for the cathode are lithiated metal oxides and +carbonaceous materials for the anode. Prior to the discovery of graphite anode +materials, lithium metal had been used. However, possibility of thermal runaway +caused by the internal shorts triggered by the formation of lithium dendrites has +been a long standing issue [2]. The use of graphite as an anode material for +intercalating lithium ions in rechargeable LIB was then proposed [3]. It is still the +main stream of anode material for commercial LIB up to now due to its well +defined layered structure for lithium intercalation, low operating potential, and +remarkable interfacial stability [4]. Unfortunately, the intercalation capacity of +lithium ions in graphite is limited to 372 mAh/g with LiC6 stoichiometry. +Numerous efforts have been made to increase this value by modifying the +crystallinity, the microstructure, and the micromorphology of the carbonaceous +material [5-8]. These structural parameters play a crucial part in determining and +optimizing the electrochemical performance of carbon anodes. + +The exploration of nanomaterials and nanocomposites provides us new +opportunities to improve the anode performance of LIB. Compared to +micrometer-scaled carbon material, nanostructured carbon exhibits differences +not only in dimensionality and morphology, but also in the distribution of +chemical bonding which allows the mixtures of local electronic structures +2 3 +between sp and sp [9] Therefore, carrier transport properties are different from +classic carbon material when nanometer-scaled carbon is in contact with +2 + +reactants. Nanostructured carbon materials with high accessible surface areas and +short diffusion time for lithium ions open new perspectives for high energy +density and high power density LIB. + +In order to fully develop the potential of nanoscaled carbon as an anode for +LIB, a systematical study is needed. In this thesis work, after a brief overview of +LIB (chapter one), fundamentals that provide the basic idea of operation +mechanism in LIB, types of conventional carbon anode materials, and their +anode performance will be reviewed in chapter two. Chapter three will mainly +focus on studying the one dimensional carbon nanofiber anode material. An easy +fabrication process, electrospinning, which is a good for mass production is +introduced for raw carbon nanofiber synthesis. In order to improve the +performance of raw carbon nanofiber, Si, a high Li storage material, is +incorporated through electrochemical deposition method. Using nanoscaled +carbon material for fundamental research of lithium ion diffusion pathway is +given in chapter four. Here, two dimensional graphene synthesized by chemical +vapor deposition is chosen to study the nature of Li ion diffusion since it is the +basic building block of graphite which is the most common material for anode. + +Finally, a general conclusion and perspectives are given. + + +3 + +Bibliography of Introduction +[1] J. M. Tarascon, M. Armand, Nature 2001, 414, 359. +[2] F. Orsini, et al., J. Power Source 1999, 81, 918. +[3] M. Armand, P. Touzain, Materials Science and Engineering 1977, 31, +319. +[4] M. Winter, O. J. Besenhard, E. M. Spahr, P. Novák, Adv. Mater. 1998, +10, 725. +[5] M. Winter, J. O. Besenhard, Lithium Ion Battery: Fundamentals and +Performance 1998 (Eds.: M. Wahihara, O. Yamamoto), Wiley-VCH, +Weinheim. +[6] A. Mabuchi, K. Tokumitsu, H. Fujimoto, T. Kasuh, J. Electrochem. Soc. +1995, 142, 1041. +[7] W. Ruland, J. Appl. Phys. 1967, 38, 3585. +[8] M. Endo, C. Kim, K. Nishimura, T. Fujino, K. Miyashita, Carbon 2000, +38, 183. +[9] D. S. Su, R. Schlögl, ChemSusChem, 2010, 3, 136. + + + +4 + + Outline of Chapter One + +Overview of Rechargeable Lithium Ion Battery + + +1.1 Electrochemical Energy Storage Systems 6 +1.2 Rechargeable Lithium Based Battery 8 +1.3 Rechargeable Lithium Ion Battery 11 +Bibliography of Chapter 1 13 + + + + + + + +5 + +CHAPTER ONE +Overview of Rechargeable Lithium Ion Battery +1.1 Electrochemical Energy Storage Systems +Systems for electrochemical energy storage convert chemical energy into +electrical energy. Electrochemical energy storage devices basically include +batteries, fuel cells, and electrochemical capacitors (ECs). Although the +mechanisms for energy storage and conversion are different, similarities do exist +among these three systems. Common features are that batteries, fuel cells, and +ECs consist of two electrodes which in contact with electrolyte. Requirements +upon electron and ion conduction in electrodes and electrolyte are valid for all +three systems. Furthermore, electron and ion transport are separated during the +charge/discharge processes which take place at the phase boundary of the +electrode/electrolyte interface [1]. The main difference between battery, fuel cell +and ECs is the way of elec trical energy generation. In batteries and fuel cells, +electrical energy is produced by conversion of chemical energy via redox +reactions (Faradic process) at the anode and cathode. On the other hand, in ECs, +energy may not be delivered via redox reactions but rather via the formation of +electrical double layers (non-Faradic process) by orientation of electrolyte ions at +the electrode/electrolyte interface, and thus the use of the terms anode and +cathode may not be appropriate [2]. + +6 + +In order to value the energy contents of a system, terms of “energy density” +(or “specific energy”) and “power density” (or “specific power”) are used. +“Energy density” is expressed in watt-hours per liter (Wh/L) [or in watt-hours per +kilogram (Wh/kg)] and “power density” is expressed in watt per liter (W/L) [or +in watt per kilogram (W/kg)] [2]. To compare the performance of various energy +storage devices, a reprehensive chart known as the Ragone plot was developed. +In such a plot, the values of specific energy (in Wh/kg) are plotted versus specific +power [3], as shown in Figure 1.1. It is clear to see that fuel cell can be +considered as high energy density system and supercapacitor as high power +density system. However, battery has intermediate energy and power +characteristics. Compared to fuel cells and supercapacitors, batteries have +realized the biggest application markets so far. Whereas supercapacitors have +found its own position as memory protection in several electronic devices and +instantaneous power backup systems, fuel cells are basically still in the +development stage [1]. + + + + + + + +7 + +Figure 1.1. Ragone plot showing energy density vs. power density +for various energy storage devices. Cited and modified from Ref. [3]. + +1.2 Rechargeable Lithium Based Battery +There are two types of batteries: primary batteries that are designed to be +used once and discarded, and secondary batteries that are designed to be +recharged and used multiple times. Therefore, they are also named as disposable +batteries and rechargeable batteries. Common types of disposable batteries such +as zinc–carbon battery cannot be reliably recharged, since the chemical reactions +are not easily reversible and active materials cannot recover to the original forms +[4]. On the other hand, electrochemical reactions in rechargeable batteries such as +nickel-cobalt battery and lithium-based batteries are electrically reversible. + +Figure 1.2. Comparison of the different battery technologies in terms +8 + +of volumetric and gravimetric energy density. Cited from Ref. [5]. + +Considering the requirements of modern society with popular portable +electronics, rechargeable batteries are more favorable nowadays. The +development of rechargeable batteries is a long story. To this date, among various +existing technologies, such as lead-acid, Ni-Cd, nickel-metal hydride (Ni-MeH), +Li-based batteries draw the most attention because of their high energy density +and possibility of compact-flexible design, as indicated in Figure 1.2. Combining +the profound mechanism study and the involvement of advanced materials, they +have become the most dominant power source for cell phones, digital cameras, +laptops etc. According to the recent market investigation, the share of worldwide +sales for Ni–Cd and Ni–MeH batteries are 23 and 14%. However, Li-ion portable +batteries take up to 63% of the battery market [5]. + +The starting point of incorporating lithium metal in battery technology is the +fact that lithium is the most electropositive (–3.04 V Vs standard hydrogen +electrode) as well as the lightest (specific gravity ρ= –30.53 g cm ) metal which +benefits the design of high energy density system [5]. Lithium metal as an anode +was firstly reported in 1970 where TiS2 was used as a cathode [6-8]. However, +Li-metal cell encountered many problems. One of shortcomings is redeposition +of lithium as a form of metal and uneven dendrite formation during subsequent +charge/discharge cycle, as shown in Figure. 1.3a. This could lead to a short +9 + +circuit problem and thus explosion issues [9]. Therefore, even though Li-metal +based cells exhibit the highest energy density as shown in Figure 1.2, their +practical application is limited. Upon the inspiration of the development on the +positive electrode which used LixMO2 (where M is Co, Ni or Mn) as a host +material for Li ions [10-11], the Li metal is not necessarily required, therefore a +concept so-called Li-ion or rocking-chair battery which introduced a second +host material to replace Li metal was emerged to solve the safety issues in +rechargeable Li-metal battery, as shown in Figure 1.3b [12-15]. + +Figure 1.3. Schematic representation of lithium batteries. a, +10 + +Rechargeable lithium-metal battery, dendrite formation was shown +in the negative electrode. b, Rechargeable lithium-ion battery. +Cited from Ref. [5]. + +1.3 Rechargeable Lithium Ion Battery +The configuration of Li-ion battery electrodes is two types of lithium host +materials (Figure 1.3b). The storage capacity of the battery is given by the +amount of Li that can be stored reversibly in these two electrodes. To be clear, for +rechargeable Li-metal batteries, the positive host electrode does not need to be +lithiated before cell assembly since the use of metallic Li as the negative +electrode. In contrast, for Li-ion batteries, the positive host electrode usually acts +as a source of Li since the common negative electrode such as carbon, Si, +transition metal oxide contains no Li. Thus, air-stable Li-based intercalation +compounds in positive electrode are required to complete the cell assembly. + +The structural stability of the host material during insertion and de-insertion +of Li ions is a critical factor since it determines the long term stability of Li-ion +battery. Generally, anode materials can be classified into three categories +according to the Li storage mechanisms besides graphite: alloying, insertion, +conversion. Most of these materials show different disadvantages compared to +graphite, as indicated in Figure 1.4. In the case of Li alloy (Si, Sn, Ge, Al, Pb +etc) and conversion-based electrodes (CoO, Fe2O3 etc), the volume change +11 + +between the Li-containing states and the corresponding lithium-free states is very +large due to the mechanical stresses generated during charge/discharge cycles. +Therefore, the cracks are easily produced and thus the electrodes collapse. So the +cycle life is very much limited. In the case of insertion based materials (TiO2, +MoO2 etc), rather low capacity is the key factor needed to be improved. In +contrast, materials with two dimensional layered structure such as carbonaceous ++ +materials, show good cycling behavior since this kind of Li insertion materials +exhibits low mechanical strain with small volume changes [2, 5, 12-15]. At the +present time, research and development activities are mainly focused on such +highly reversible carbonaceous materials. + + + + + + + + + + + +Figure 1.4. Current issues remaining in different types of anode +materials. + + +12 + +Bibliography of Chapter 1 + +[1] M. Winter, R. J. Brodd, Chem. Rev 2004, 104, 4245. +[2] B. E. Conway, Electrochemical Supercapacitors: Scientific Fundamentals +and Technological Applications 1999. +[3] The plot shown here is based on the data provided by Maxwell +Technologies: http://www.maxwell.com. +[4] Alkaline Manganese Dioxide Handbook and Application Manual, 2008. +[5] J. M. Tarascon, M. Armand, Nature 2001, 414, 359. +[6] T. Ikeda, H. Tamura, Proc. Manganese Dioxide Symp. 1975, Vol. 1, (IC +sample Office, Cleveland, OH). +[7] M. S. Whittingham, Science 1976, 192, 1226. +[8] M. S. Whittingham, US Patent 4009052. +[9] F. Orsini, et al., J. Power Sources 1999, 81, 918. +[10] K. Mizushima, P. C. Jones, P. J. Wiseman, J. B. Goodenough, Mat. Res. +Bull.1980, 15, 783. +[11] M. M. Thackeray, W. I. F. David, P. G. Bruce, J. B. Goodenough, Mat. +Res. Bull. 1983, 18, 461. +[12] D. W. Murphy, F. J. DiSalvo, J. N. Carides, J. V. Waszczak, Mat. Res. +Bull. 1978, 13, 1395. +[13] M. Lazzari, B. Scrosati, J. Electrochem. Soc.1980, 127, 773. +[14] M. Mohri, et al., J. Power Sources 1989, 26, 545. +[15] J. R. Dahn, U. V. Sacken, M. W. Juzkow, H. Al-Janaby, J. Electrochem. +13 + +Soc. 1991, 138, 2207. + + + + + + + + + + + + + + + + + + + + + +14 + + Outline of Chapter Two + +Carbonaceous Materials as an Anode of Li-Ion Battery + +2.1 Operation Mechanism of Li-Ion Battery 16 +2.2 Classification of Carbonaceous Materials 21 +2.2.1 Graphitic Carbon 21 +2.2.2 Non-graphitic Carbon 22 +2.3 Lithium Intercalation into Carbonaceous Materials 24 +2.3.1 Lithium Intercalation into Graphitic Carbon Materials 24 +2.3.1-1 Description 24 +2.3.1-2 Charge/Discharge Profile of Graphitic Carbon Materials 26 +2.3.2 Lithium Intercalation into Non-graphitic Carbon Materials 29 +2.3.2-1 Low Specific Charge Carbon 29 +2.3.2-2 High Specific Charge Carbon 31 +2.4 Summary of Chapter Two 36 +Bibliography of Chapter 2 38 + +15 + +CHAPTER TWO +Carbonaceous Materials as an Anode of Li-Ion Battery +2.1 Operation Mechanism of Li-Ion Battery +Carbon as one of the most abundant elements on earth plays a critical role in +the development of human society. For thousands of years, human history is +closely associated with the struggle to extract and utilize the power from carbon +materials. Carbonaceous materials have been adopted in various electrochemical +energy storage systems previously. This was motivated by the good electrical +2 +conductance of sp -hybridized solid carbon, its high chemical stability, and its +enormous adaptability to different interface processes [1]. Li-ion battery is one +typical example to utilize the carbonaceous materials in energy storage devices. +Commercialized LIB usually consists of layered LiCoO2 as a cathode and +carbonaceous materials as an anode. These two electrodes are usually separated +by a porous polymer membrane and the ionic transport within the cell is ensured +by an aprotic organic electrolyte which is a good ionic conductor and electronic +insulator [2]. Nowadays, the most common electrolyte is a solution of LiPF6 in a +mixture of alkyl carbonates such as ethylene carbonate, diethyl carbonate, and +dimethyl carbonate which provides high-permittivity and low-viscosity. + +In common Li-ion battery cells, during the charging process, Li ions are +extracted from the LiCoO2 electrode (cathode) and simultaneously +16 + +inserted/intercalated into the carbon electrode (anode) by forming a +lithium/carbon intercalation compound indicated as LixCn, coupled with +negatively charged electrons to keep overall charge neutrality, as shown on the +left side of Figure 2.1. During the discharging process, Li ions are reversibly +extracted/deintercalated from the negative electrode and simultaneously inserted +into the positive electrode, as shown on the right side of Figure 2.1. This +charge/discharge process can be summarized by the typical chemical equations as +shown below [3]: + +Figure. 2.1. Schematic illustration of detailed charge/discharge +process in Li-ion battery. + +Positive Electrode: LiCoO2 ++ - + Li1-x CoO2 + xLi + xe ++ - +Negative Electrode: Cn + xLi + xe LixCn + Overall: LiCoO2+ Cn Li1-xCoO2 + LixCn +17 + +Compared to ECs whose electrodes are composed of same materials which +therefore exhibit the same potential, an inherent potential difference exists +between LiCoO2 and carbonaceous material in LIB, as simply indicated in +Figure 2.2. The original potentials of LiCoO2 and carbon materials are usually ~ ++ +4 V and ~ 0.2-0.5 V (depending on types of carbon) vs. Li/Li , respectively [2,4]. ++ +During the charge process, the cathode will release Li under the influence of +external power and the potential of cathode will increase to 4.2 V, whereas the ++ +anode potential will decrease to approximately 0.01 V vs. Li/Li upon Li ion +insertion, thus delivering an output voltage of nearly 4 V to the external load. +Here, the cut off voltage of LiCoO2 and graphite is usually limited to 4.2 +(corresponding to a removal of 0.5 mol Li) and 0.01 V in order to maintain the +structural stability [5]. On the other hand, during the spontaneous discharge +process, Li0.5CoO2 needs to go back to its original potential state which is more +energetically stable therefore Li ions go back to Li0.5CoO2 and the electrode +potential goes back to the original state, and the system is thus ready for the next +charge process. + + + + + + +18 + +Figure 2.2. Potential profile of anode and cathode during +charge/discharge. + +The discovery of different carbon allotropes associated with nanoscience +and nanotechnology provided us a room to further improve the performance of +anode material. Therefore, carbonaceous material used as an anode in LIB is +chosen to be the main focus in this work. Before moving to the details, we +summarize one more time the advantages of carbon-based anode material. +Compared to transition-metal oxides and chalcogenides, carbonaceous materials +such as graphite and hard carbons are more preferable not only because of (1) the +unstable inherent nature of the transition-metal oxides and chalcogenides +materials as mentioned at the end of Chapter 1 and (2) the dimensional stability +and good conductivity of carbonaceous materials, but also (3) the lowest ++ +potential versus Li/Li which gives higher output cell voltage compared to other +composite alloys, three dimensional metal oxides and so on. For instance, the ++ +potential of many Li alloys is ~0.3 to ~1.0 V vs. Li/Li whereas it is only ~0.1 V ++ +vs. Li/Li for graphite, as indicated in Figure 2.3 [6]. + + + + + +19 + + + + + + + +Figure 2.3. Charge curves of different metals (M) with respect to +highly oriented turbostratic pitch carbon fibers. Cited from Ref. [6]. + +One good carbonaceous anode material needs to fulfill high capacity, long +cycle life, fast charge etc. in addition to high energy/power density, good +conductivity and stability, as mentioned above. A charge/discharge curve can be +used as one of the most straightforward tools to demonstrate the storage +capability, cyclic ability, rate of charge/discharge. The charge/discharge curve +(capacity-voltage curve) is converted from a voltage-time profile with one or +several constant current densities that are fixed in advance. The capacity (mAh) +therefore equals to the current (mA) multiply the time (h). The charge/discharge +curve usually exhibits very different features according to the structure of carbon +materials. Thus, in order to further improve the performance of carbonaceous +anode and to assist in explaining the phenomenon of nanocarbon-based anode +later, the classification of carbon materials upon the structure and also their +20 + +associated charge/discharge profiles need to be elaborated first. The related topics +are explained in detail in the following section. + +2.2 Classification of Carbonaceous Materials +Carbonaceous materials that are capable of reversible lithium reaction can +be roughly classified into two categories according to their structures: graphitic +and non-graphitic (disordered) carbon. The non-graphitic carbon can be further +categorized into soft carbon/hard carbon upon annealing and high specific charge +carbon/low specific charge carbon according to the capability of reversible +lithium storage. Charge/discharge behaviors of each type of carbon are presented +and analyzed in detail in the following context. + +2.2.1 Graphitic Carbon +Graphitic carbon is a well-defined layered structure. Normally, a number of +structural defects could appear in graphitic carbon. The term of “graphite” was +derived from crystallographic point of view which should be only applied to +carbons whose layered lattice structure follows a perfect stacking order of +graphene layers. That is to say it contains the layer stacking order of either the +common AB (hexagonal graphite, Figure 2.4 and Figure 2.5a) or the rather rare +ABC (rhombohedral graphite). However, since the transformation energy from +AB stacking to ABC stacking (and vice versa) is rather small, perfectly stacked +graphite crystals are not readily available. Therefore the term of “graphite” is +21 + +often used regardless of well-defined stacking order [7]. The terms of natural +graphite, artificial graphite, and pyrolytic graphite are commonly used, although +the materials are polycrystalline [8]. The actual structure of carbonaceous +materials typically deviates more or less from the ideal graphite structure. +Materials consisting of aggregates of graphite crystallites are called graphites as +well. +Figure 2.4. Left: Schematics of the crystal structure of hexagonal +graphite with an AB stacking order. Right: view perpendicular to the +basal plane of graphite. Edges can be subdivided into arm-chair and +zigzag faces. Cited from Ref. [7]. + +2.2.2 Non-Graphitic Carbon +Non-graphitic (disordered) carbonaceous materials consist of carbon atoms +that are mainly arranged in a planar hexagonal network but no crystallographic +order in the c-direction compared to graphite, as shown in Figure 2.5c [7,9]. The +22 + +structure of those carbons is characterized by amorphous areas embedded and +cross-linked in the network. Non-graphitic carbons are mostly prepared by +pyrolysis of organic polymer or hydrocarbon precursors at temperature below +~1500°C [10-12]. + (a) graphite (b) graphitizable carbon (c) non-graphitizable carbon +Figure 2.5. Schematic indications of (a) graphite and (b) non- +graphitic (disordered) carbonaceous material. + +Heat treatment of most non-graphitic carbons (from ~1500 to ~3000°C) +allows us to further classify non-graphitic carbon into two sub-categories: soft +carbon and hard carbon. In the case of soft carbons, crosslinking between the +carbon layers is weak and therefore the layers are mobile enough to form +graphite-like crystallites and develop the graphite structure continuously during +the heating process, as shown in Figure 2.5b [9]. In the case of hard carbons, +since the carbon layers are immobilized by crosslinking, they show no real +development of the graphite structure even at temperatures of 2500 ~ 3000 °C +[10]. The representative figure is shown in Figure 2.5c. +23 + +2.3 Lithium Intercalation into Carbonaceous Materials +2.3.1 Lithium Intercalation into Graphitic Carbon Materials +2.3.1-1 Description +Lithium-intercalated graphitic carbon compounds (GICs) are known with +the configuration LixCn. It is well known that Li intercalation reaction occurs +only at the edge plane of graphite. Through the basal plane, intercalation is +possible only at defect sites [13-16]. The maximum lithium content for highly +crystalline graphitic carbons is one Li guest atom per six carbon host atoms (i.e. +n 6 in LiCn or x 1 in LixC6) at ambient pressure [17]. That is to say it follo +ws the equation as below: + ++ - +6 C + x Li +x e  LixC6, where, x = 1 in LixC6 (the maximum Li conte +nt). + +In LiC6, lithium avoids to occupy the nearest neighbor sites due to the +Columbic repulsive force of Li, as shown in Figure 2.6. Two major changes in +graphite structure point of view occur when Li intercalats into graphite layers: (1) +the stacking order of the carbon layers (i.e. graphene layers) shifts to AA stacking, +see Figure 2.6a and Figure 2.6c. (2) The interlayer distance between the +graphene layers increases moderately (10.3% has been calculated for LiC6) due +to the lithium intercalation, as indicated in the right panel in Figure 2.6a [18-21]. +24 + + + + + + + + + +Figure 2.6. Structure indications of LiC6. (a) Left: schematic +drawing showing the AA layer stacking sequence with Li +intercalation. Right: simplified representation. (b) Perpendicular +view to the basal plane of LiC6. (c) Enlarged schematic of AA +stacking order. Cited and modified from Ref. [20-21]. + +An important feature of Li intercalation into graphite is the “stage +formation”. Stage formation means a stepwise formation of a periodic pattern of +unoccupied graphitic layer gaps at low concentrations of Li [23-31]. This +stepwise process can be described by the stage index, s (s = I, II, III, IV) which is +equal to the number of graphene layers between two nearest guest layers as +shown in Figure 2.7. Note that stage IV is not indicated in the figure because Li +concentration is too low in graphene layers. It is also known as a dilute stage +25 + +when s > IV [32]. Two factors determine the formation of stages during Li +intercalation into graphite i) the energy required to expand van der Waals gap +between two graphene layers [31,33] and ii) the repulsive interactions between +guest species. Therefore, compared to a random distribution of Li in the graphitic +layers during charge process, Li ions prefer to occupy van der Waals gaps with +high density first to reach an energetically stable state [7]. + + + + + + + + + Figure 2.7. Schematic indication of stage formation during Li ion + intercalation into graphite layers. + +2.3.1-2 Charge/Discharge Profile of Graphitic Carbon Materials +Stage formation as mentioned above is one of the most important +characteristic of charge profile for graphitic carbon. It can be easily observed in +the form of plateaus by constant current measurement (i.e. in charge/discharge +curve), as indicated in Figure 2.8. The associated stages are marked in bottom +26 + +panel of the figure. The plateaus indicate the coexistence of two phases [24,34]. +The formation of stages II, IIL (a transition stage of stage II and stage III), III, +and IV have been identified from experimental electrochemical curves [18,35,37- +40] and confirmed by X-ray diffraction and Raman spectroscopy [17,25,27- +28,35-38]. A schematic potential / composition curve for galvanostatic reduction +of graphite to LiC6 is shown in the bottom panel in Figure 2.8. + + + + + + + + + + + + + +Figure 2.8. Constant current charge/discharge curves of the graphite +(Timrex KS 44, Cirr is the irreversible specific charge, and Crev is the +reversible specific charge). Modified and replotted from Ref. [7]. +27 + ++ +Ideally, Li intercalation into carbons should be fully reversible and the +maximum Li storage capacity should not exceed 372 mAh/g according to LiC6 +configuration. However, the charge accumulated in the first cycle usually larger +than the maximum theoretical specific capacity, as shown in Figure 2.8. +Compared to the first charge, the first discharge capacity is much smaller. The +excess charge generated in the first cycle which cannot be recovered can be +ascribed to a film formation of the solid electrolyte interface (SEI) which is ++ +caused by the decomposition of the Li containing electrolyte, such as propylene +carbonate and ethylene carbonate [41-46]. The decomposition of electrolyte ++ +usually takes place at less than 1 V vs. Li/Li and appears as the first plateau in +the charge curve, as indicated in Figure 2.8 [47]. The advantage of the SEI +formation is that it can prevent further electrolyte decomposition and create a +rather stable state for the surface of GIC [48-53]. On the other hand, the ++ +formation of SEI is a charge-consuming side reaction in the first few Li +st +intercalation/deintercalation cycles, especially in the 1 charge cycle. +Considering that the positive electrode is responsible to provide the Li ion in LIB, +the charge and lithium losses are detrimental to the specific energy of the whole +cell and have to be minimized. Because of the irreversible consumption of +lithium and electrolyte, a corresponding charge loss exists, so called “irreversible +specific charge” as indicated in Figure 2.8. The reversible lithium intercalation is +called “reversible specific charge”. + +28 + +2.3.2 Lithium Intercalation into Non-Graphitic Carbon Materials +According to the capability of reversible lithium storage, non-graphitic +carbons can be further classified into two categories: high specific charge carbon +and low specific charge carbon. + +2.3.2-1 Low Specific Charge Carbon +(i) Definition +Low specific charge carbons are carbonaceous materials which incorporate +only a considerably lower amount of lithium than graphite. That is to say it follo +ws the equation as below: + ++ - +6C + xLi +xe  LixC6, where x = 0.5~0.8 in LixC6 at the maximum +stoichiometry. + +(ii) Examples of Low Specific Charge Carbon +Cokes [68,77-83] and carbon blacks [81,84-85] are typical disordered +carbons with low specific charges. During the charge process, Li intercalation- +induced formation of AA stacking is hindered due to the existence of crosslinking +of carbon sheets as mentioned in chapter 2.1.2. This will eventually affect the +accommodation of a higher Li amount into graphitic sites and deliver a lower +specific charge [86-88]. + +29 + +Turbostratic carbon [43,86-90] which can also be classified into the category +of graphitizing/soft carbon is one type of low specific charge carbon. The lower +amount of Li intercalation than graphite is due to not only the effect of +crosslinking as mentioned in cokes and carbon blacks, but also larger amount of +wrinkled and buckled structural segments existing in the structure, and thus +available lithium intercalation sites is rather low therefore the specific charge is +lower than graphite [91-92]. + +(iii) Charge/Discharge Profile of Low Specific Charge Carbon ++ +Figure 2.9 shows the first Li intercalation/deintercalation cycle of a coke- +containing electrode. The potential profile of low specific carbon differs ++ +considerably from that of graphite, as the reversible intercalation of Li begins at ++ +around 1.2 V vs. Li/Li , and the curve slopes without distinguishable plateaus. +This behavior is a consequence of the disordered structure providing +electronically and geometrically nonequivalent sites, whereas for a particular +intercalation stage in highly crystalline graphite, the sites are equivalent [93-94]. +30 + + + + + + + + + + + + + + +Figure 2.9. Constant current charge/discharge curves of a coke (Conoco). +(Cirr is the irreversible specific charge, Crev the reversible specific charge). +Cited and redrawn from Ref. [7]. + +2.3.2-2 High Specific Charge Carbon +(i) Definition +High specific charge carbons can store more lithium than graphite. That is to +say it follows the equation as below: +31 + ++ - +6 C + x Li +x e  LixC6, where x > 1 in LixC6. + +Li storage capacity of high specific charge carbons could vary from 400 +Ah/kg to ~2000 Ah/kg which corresponding to x = ~1.2 to ~5 in LixC6. The +difference in the capacity depends on the heat treatment temperature, organic +precursor, and electrolyte. Even though the higher specific capacity (in terms of +Ah/kg) is desired in LIB, a larger volume of the carbonaceous matrix is usually +needed to accommodate the excess intercalated Li which indicates lower charge +density in terms of Ah/L [7]. + +(ii) Origin of the Excess Charges +Several different scenarios have been proposed in order to explain +origin of excess charges. These different models provide the intuitive +understanding even though some of them are still debatable [54-58]. A few +well known examples are listed below. Extra capacity can be realized +through: (1) The formation of Li2 molecules between layers which indicates +that lithium molecules occupy the nearest neighbor sites in intercalated ++ +carbons [59]. (2) The presence of charged Li clusters in the cavities [60]. +(3) The “adsorption” of lithium on both sides of single-layer sheets that are +arranged like a “falling cards” [61]. All of mechanisms are indicated in +Figure 2.10. +32 + + + + + + + + + + +Figure 2.10. a) Storage mechanisms of Li ions in graphite. b) Li +storage in a form of Li2 covalent molecules. c) Schematic model of Li +storage in cavities and nanopores. d) Li adsorption on the two sides of +an isolated graphene sheet. Cited from Ref. [3]. + +(iii) Charge/discharge Profile of High Specific Charge Carbon +For both graphitizing (soft) and non-graphitizing (hard) carbons prepared < +o +1000 C, the typical charge/discharge profile is shown in Figure 2.11. +33 + + + + + + + + + + + + + + + +st nd +Figure 2.11. Constant current charge/discharge curves (1 and 2 cycle) of +a high specific charge carbon material after heat treatment at 700 °C. (Cirr +is the irreversible specific charge, Crev the reversible specific charge). Cited +and redrawn from Ref. [7]. + +It is clear to see a SEI-related plateau appears at around 0.6V and a high +specific charge of around 3720 Ah/kg was achieved during the first charge, as +34 + +shown in the top panel in Figure 2.11. The special feature of this kind of carbon +material is that it exhibits a larger voltage hysteresis between charge and +discharge processes compared to that of graphite (Figure 2.8). To be more +specific, the second charge/discharge is shown at the bottom of Figure 2.11 +which does not show the effect of SEI. The potential for Li insertion is close to 0 ++ +V vs. Li/Li whereas the one for Li de-insertion is much more positive [54-55,62- +65] in the second charge/discharge process. According to the previous study, it +has been shown that the extent of hysteresis is proportional to the hydrogen +content in the carbon since Li is somehow bound near the hydrogen [66-67]. + +Since hydrogen can be removed with increasing temperature, the specific +charges achieved after the removal of hydrogen need to be evaluated. It was +found that the value of specific charge after high temperature annealing strongly +depend on the structure of the non-graphitic material [55,65,68-75]. (i) In the +case of soft carbon, it will deliver a lower value of specific charge (x < ~0.5 in +LixC6) which is similar to the low specific charge carbon [54,75-76], when heat +treated at ~1000 °C. And the specific charge again increases when the +temperature is > 1000 °C [73,74]. (ii) In the case of hard carbon, it can still +display a specific charge of several hundred Ah/kg when heat-treated at ~1000 ° ++ +C. But Li inserts at a very low potential of a few millivolts versus Li/Li and a +smaller hysteresis is shown in charge/discharge profile. In contrast to soft carbon, +a drastically reduction of specific charge is observed when the temperature is > +35 + +1000 °C [72,76]. + +Although the high specific charge carbons show much higher specific +capacity than graphite, they have some serious drawbacks such as higher +irreversible specific charges, larger hysteresis and poorer cycling performance +than graphite [54-55,62,95-96,98,100-101,103-104]. Although the cycling +performance of non-graphitizing (hard) carbons heat-treated at ~1000 °C is +reasonable and almost no hysteresis occurs, the end of the charge potential of the +carbons is very close to metallic lithium [62,75,102]. Under such a charging +regime, lithium deposition occurs, which will induce safety issue like Li-metal +battery [7]. + +2.4 Summary of Chapter Two +The operation mechanism of Li-ion battery and the charge/discharge +behavior based on different types of carbonaceous materials were generally +reviewed in this chapter. This kind of information provides fundamental +knowledge to characterize and understand the anodic behavior of nanoscaled +carbon materials which will be covered in Chapter 3. + +Based on this chapter, it is clear to see that there are so many unsolved +issues related to carbonaceous materials. In the case of graphite, it exhibits good +cyclic performance and structure stability but the capacity is limited. On the +36 + +contrary, in the case of high specific carbon, the capacity is higher than that of +graphite but the long time stability and safety issues remain unsolved. + +Although the current understanding of the origins of excess charge is limited, +it is clear that numerous factors such as surface area, crystallinity, defect +population, basal/edge plane effects and so on could affect the storage capacity. +Compared to graphite, the analysis of non-graphitic carbon is more complicated +since so many unpredictable factors exist. Ahead of understanding of Li storage +mechanisms and the realization of high capacity anode materials, one preliminary +issue still remains unclear, that is the Li diffusion pathway in carbonaceous +materials. Therefore, further understanding of Li diffusion pathway through +graphene plane and the role of defects in Li diffusion is highly required to +provide more information to reveal the mystery of Li-C system. 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Met. 1995, 73, 9. + +46 + + Outline of Chapter Three + +Silicon-Coated Carbon Nanofiber Mat for Anode of Lithium +Ion Battery + +One Dimensional Carbon Materials as an Anode Material for 51 +3.1 +LIB +3.1.1 General Introduction of CNFs and CNTs 51 +3.1.2 CNFs and CNTs Using as an Anode Material for LIB 56 +3.1.3 Fabrication Methods of CNFs and CNTs 58 +3.1.3-1 Chemical Vapor Deposition for Both CNFs and CNTs 58 +3.1.3-2 Electrospinning Method for CNFs Mat 63 +3.2 Electrospinning Fabricated CNFs Mat as an Anode Material 66 +for LIB +3.2.1 SEM and Raman Characterization of CNFs Synthesized 67 + Through Electrospinning +3.2.2 Anode Performance of CNFs Synthesized Through 69 + Electrospinning +3.3 Silicon-Coated Carbon Nanofiber Mat for Anode of Lithium 71 +47 + +Ion Battery +3.3.1 Introduction 72 +3.3.2 Characterizations of CNF-Si Mat 76 +3.3.3 Anode Performance of CNF-Si Mat 83 +3.4 Summary of Chapter Three 95 +Bibliography of Chapter 3 97 +48 + +CHAPTER THREE +Silicon-Coated Carbon Nanofiber Mat for Anode of Lithium +Ion Battery +Owing to the current performance deficiencies of micron-sized carbon +anode materials such as graphites and hard carbons, researchers have been +struggling a long time to develop new materials and new structures to meet the +ever-growing market demands. Just as indicated by Richard Feynman in 1959 +that “there is plenty of room at the bottom” [1], the emergency of nanoscience +and nanotechnology which leads to revolution in basic material science and +engineering provided us new opportunities to improve carbonaceous anode +performance. The discovery of nanoscaled carbon materials covers carbon +nanotubes (CNTs), carbon nanofibers (CNFs), and graphene (Gr) which had +profound impact on the development of clean energy storage and conversion +systems. Compared to bulk carbon materials, low dimensional carbons exhibit +novel properties which are often superior to their bulk counterparts associated +with decreased size, unique shape, and defects. Therefore, Li storage mechanism +and anodic behavior could be very different from bulk graphite. + +Nanocarbon materials enable electrode reactions to occur that cannot take +place for materials composed of micrometer-sized particles. The diffusion time +2 +constant for Li ions is given by t=L /D, where L is the diffusion length and D the +49 + +diffusion constant [2]. The reduced dimensions increase significantly the rate of +lithium insertion/removal and also the electron transport because of the short +distances for Li ion transport within the particles [3]. High surface area permits +high contact area with electrolyte and hence high Li ions flux across the interface. +The strain associated with intercalation is expected to be better accommodated +[4] in nanosized carbons. Due to the advantages as mentioned above, nanocarbon +materials have been extensively investigated as an anode of LIB. + +However, it was found that nanocarbon materials can only provide certain +degree of capacity improvement which is still far lower than that people expected. +Thus, incorporation of another cheap and high capacity material such as silicon +-1 +whose specific capacity can reach 3572 mA h g at room temperature provides a +new way to overcome the above issue [5]. Nevertheless, severe structural +pulverization induced by the large volume expansion during charge/discharge +makes this material impractical [5]. Therefore, anode capacity improvement by +Si while maintaining the structural stability is another big challenge. Thus, the Si- +coated CNF mat was synthesized by combining electrospinning and +electrochemical deposition in this work. The original idea is to improve the Si +structure stability by taking advantage of the entangled three dimensional CNF +network which consists of good conductivity and porosity. The structure-related +characterization and anode performance of CNF/Si mat will be given in detail. +Before that, the relatively popular one dimensional carbon materials such as +50 + +CNFs and CNTs will be discussed and compared based on their general +properties and the potential to be applied as an anode in LIB. Then the detailed +fabrication process of CNF mat through electrospinning method and the anodic +performance of as-fabricated CNF mats will be provided in this chaper. + +3.1 One Dimensional Carbon Materials as an Anode Material for LIB +One dimensional carbon materials, carbon nanofibers (CNFs) and carbon +nanotubes (CNTs) are of great practical and scientific importance. Owing to their +similar cylinder shapes, the definitions of CNTs and CNFs are often misleading. +Due to the material and structural similarity, common features do exist in their +basic properties and Li storage mechanisms. Nevertheless, they are similar in +form but distinct in (1) general physical properties, (2) Li storage mechanisms +and (3) means of production which will eventually affect the practical application +in anode. Therefore, before the detailed discussion of electrospinning fabricated +CNF mat, the main anode material applied in this chapter, the general +comparison between CNFs and CNTs based on these three different factors is +provided here for comprehensive understanding of one dimensional anode +materials. + +3.1.1 General Physical Property of CNFs and CNTs +If one takes a close look at the basic structure of CNTs and CNFs, the +51 + +geometry differences can be easily observed between them. CNFs can be +visualized as regularly stacked truncated conical or planar layers along the +filament length without hollow core [5–8] whereas, CNTs are formed by rolling +up graphene sheets to form concentric tubes containing an entire hollow core. In +fact, some of the carbon nanotubes being investigated actually qualify as carbon +nanofibers because the lack of long-range order as in graphitic materials and/or +they have imperfectly rolled graphene sheets. Generally, diameters of CNFs and +CNTs can be used as a criterion to distinguish these two kinds of materials, as +shown in Figure 3.1[9].The diameter of CNTs is around few tens of nanometers +whereas the diameter of CNFs is usually larger than hundred nanometers. Both +nanomaterials are available in various lengths and could be up to several hundred +micrometers depending on the feedstock and the production method. + + + + + +Figure 3.1 Schematic comparison of the diameter dimensions on a log +52 + +scale for various types of fibrous carbons. Cited form Ref. [9]. +In the case of CNFs, the most important feature is that it exposes large +portion of graphene edge planes on its surfaces. In the case of CNTs, since it was +formed by rolling up graphene sheets, the basal plane of graphene is exposed, as +shown in Figure 3.2 [10]. This general difference in structure will eventually +affect the Li storage mechanism which will be discussed later. Compared to the +rather simple configuration of CNFs, CNTs display several different structures +based on the number of graphene layers and the rolling direction. + + + + + +Figure 3.2 Wrapping of graphene sheet to form SWNT. Cited and +modified form Ref. [10]. + +According to the number of graphene layers, CNTs can be further +distinguished into SWNTs and MWNTs. SWNT is a single graphene sheet rolled +into a form of a tube, whereas MWNTs are composed of several concentric tubes +53 + +of graphenes. The diameter of CNTs varies from a few nanometers in the case of +SWNTs to several tens of nanometers in the case of MWNTs. The representative +TEM figures of SWNT and MWNT are shown in Figure 3.3 [11]. + +Figure 3.3 Schematic indications of (a) SWCNT, (b) MWCNT, and +the corresponding TEM images in (c) and (d). Cited and replotted +from Ref. [11]. + +According to the rolling directions, SWNTs can be completely described by +a single vector (called chiral vector), as shown in Figure 3.4. Two atoms in +a planar graphene sheet are chosen and one set to be origin. The chiral vector +is pointed from the first atom toward the second one and is defined by the +relation = n + m , where n and m are integers, and are the unit +cell vectors of the two-dimensional lattice formed by the graphene sheets. The +54 + +direction of the nanotube axis is perpendicular to this chiral vector. The angle +between the chiral vector and zigzag nanotube axis is the chiral angle θ +(Figure 3.4). With the integers of n and m already introduced before, this angle +can be defined by θ −1 = tan ( ). SWNTs can be described by +the pair of integers (n,m) which is related to the chiral vector. Three types of +SWNTs are revealed with these values: when n = m, the nanotube is called +“armchair” type (θ = 0◦); when m = 0, then it is of the “zigzag” type (θ = 30◦). +Otherwise, when n ≠ m, it is a “chiral” tube and θ takes a value between 0◦ +and 30◦. The value of (n,m) determines the chirality of the nanotube and affects +the electronic property. SWNTs with |n-m| = 3q are metallic and those with |n- +m| = 3q±1 are semiconducting (q is an integer) [12]. + +Figure 3.4. Chiral vector and chiral angle θ definition for a (2, +4) nanotube on graphene sheet. and .are the unit cell vectors +55 + +of the two-dimensional hexagonal graphene sheet. The circumference +of nanotube is given by the length of chiral vector. The chiral angle +θ is defined as the angle between chiral vector and the zigzag axis. +Cited and modified from Ref. [12]. + +Compared to SWNTs which display complex structure-determined +electronic properties, MWNTs are multi-surface graphene with various chiral +angles and would lose special electronic properties, and thus they reveal an +average effect of all chiral tubes and thus usually exhibit a metallic property +since their diameters are large. [11]. In comparison with CNTs, CNFs show +relatively low conductivity. As a result, in the aspect of material conductivity, +CNTs could be better choice for LIB anode. + +3.1.2 CNFs and CNTs Using as an Anode Material for LIB +The limited capacity of graphite as introduced in chapter two has hindered +the further development of battery technology. The interesting properties of one +dimensional carbon materials therefore have been widely studied to substitute +graphite as an anode material of LIB. Generally, CNTs and CNFs show similar +advanced properties with graphite. On the one hand, they preserve even exceed +the common graphite in the sense of high chemical stability and low resistance; +On the other hand, they show other favorable characteristics which could further +56 + +benefit the performance of anode. For example, CNTs and CNFs exhibit high +specific area which increases the contact area of electrode and electrolyte leading +to higher charge/discharge rates. The high mechanical strength and flexibility is +again superb for a long cycle life [13-16] and potential application in flexible +electronics, respectively. + +The storage mechanisms of Li in CNFs and CNTs are similar to each other +and resemble that of bulk carbon materials combing the characteristics of +graphite and non-graphitic carbon. Li ions could be stored through: (1) +intercalation (LiC6 stoichiometry); (2) adsorption and accumulation on the outer +surface, (3) void space between bundles, (4) defect sites, cavities and nanopores. +These kind of storage mechanisms have been well illustrated in chapter two, see +Figure 2.10 [17-18]. + +However, one main difference does exist between CNFs and CNTs. In the +case of CNTs, lithium insertion through the walls (basal plane of graphene sheet) +or the capped ends is energetically not favorable as suggested by Kar et al. who +investigated lithium insertion into CNTs by ab initio and DFT methods [19]. On +the other hand, lithium ions can be inserted through CNF walls since it is mainly +composed of edge plane of graphene sheets [5-9]. More comprehensive +information related to Li insertion through these two kinds of graphene planes +will be provided in chapter 4. Thus, in the aspect of feasibility of Li penetration +57 + +which is closely related to the storage capacity and charge/discharge rate, CNFs +using as anode material could be more advanced compared to CNTs. + +In addition to the differences in basic material property and Li storage +mechanism as mention above, one more important factor that needs to be +considered is the means of fabrication for one dimensional carbon materials. As a +matter of fact, styles of the produced carbon materials, feasibility for further +processing into LIB anode, and also cost all have huge influences for the real +application of CNFs and CNTs. Thus, the following section will mainly focus on +discussion of two popular fabrication methods of CNFs and CNTs. + +3.1.3 Fabrication Methods of CNFs and CNTs +3.1.3-1 Chemical Vapor Deposition for CNFs and CNTs +Owing to material and structure similarity, both CNFs and CNTs can be +synthesized through chemical vapor deposition (CVD). CVD is a well known +production method for carbon based materials. One dimensional CNF/CNT and +two dimensional graphene can be fabricated using this method. Three basic +elements for CVD growth are catalyst, carbon precursor, and sufficient thermal +energy for gas decomposition and reaction to occur. Briefly, the CVD method +involves the decomposition of a gaseous or volatile compound of carbon, +catalyzed by metallic nanoparticles with external energy supply, which will also +58 + +serve as nucleation sites for the initiation of low dimensional carbon growth. The +most frequently used catalysts are transition metals, primarily Fe, Co, or Ni. The +energy source is heat from a furnace of CVD [11]. By varying the conditions, +powder-like samples or film-like samples consist of vertically aligned CNTs or +network of CNFs/CNTs which are supposed to benefit the fabrication process of +LIB electrodes, can be easily obtained, as shown in Figure 3.5. The length, +diameter, and morphology of CNFs and CNTs also can be controlled during the +synthesis process. +Figure 3.5 CVD process-fabricated (a) CNT power, (b) vertically +aligned CNTs, and (c) CNF planar network. Cited from Ref. [11]. + +One dimensional carbon anode usually consists of a thin layer of +CNFs/CNTs which is mounted onto a metal current collector. Compared to +vertically aligned CNFs/CNTs electrode, planar network-like (film or mat) +morphology is preferred not only because it is suitable to the conventional coin +cell battery fabrication but also the short circuit problem triggered by material +59 + +piercing through the separator can be avoided. In the case of as-grown CNFs or +CNTs network, the remaining impurities such as catalyst for growth and also an +appropriate substrate for growth need to be considered before anode preparation. +Combining all of the factors, power-like CNFs/CNTs samples are widely used +nowadays. In order to form a network style CNFs or CNTs film from the as- +synthesized powder, material functionalization and dispersion in liquid are +usually required before the electrode fabrication. + +Since CNFs expose graphene edge planes on its surfaces, the surface state +can be easily modified through chemical functionalization or thermal treatments +whenever necessary. Functionalizing and dispersing the CNFs are possible to be +performed using traditional, scalable, and fast processing methods. On the other +hand, the CNT functionalization was usually performed before dispersion by first +creating defect sites along the side walls of tubes, which can then be utilized for +attaching functional groups. This kind of method usually reduces the +conductivity and mechanical strength of CNTs and requires several processing +steps. Thus CNTs are more difficult and more costly to scale-up with respect to +CNFs. + +Furthermore, in the case of CNTs, due to their smaller sizes than CNFs, van +der Waals forces are stronger which induce the formation of ropes or reassemble +after being dispersed. Therefore, chemical dispersants or functionalization +60 + +techniques are usually required to aid and maintain dispersion. Unlike CNTs, +CNFs with a stacked-cup style are less affected by van der Waals forces and tend +to stay dispersed for a longer period of time. This difference enables CNFs to be +dispersed through purely mechanical processing techniques without the need for +additional, and costly, processing steps, making CNFs easier and cheaper to +process. + +Finally, the prices of CNTs and CNFs are very different depending on the +producer but in general, the cost of CNFs is typically an order-of-magnitude +lower than that of CNTs. CNFs are available in large volumes (up to 70,000 +pounds per year) and range in price from as low as $ 100 per pound to as high as +$ 500 per pound. As to CNTs, the price varies widely and is strongly dependent +on the quality and purity of the products. One can find commercialized CNT +powder with the price as low as $100 per pound to as high as $ 750 per gram or +more. Therefore, the costs for just the raw material plus the one for the extra cost +of additional processing steps (such as purification and functionalization) are +much higher than that of CNFs. The series of post-treatment procedures also +significantly increase the complexity of the application of CNTs. + +To conclude all of the factors as mentioned above, it is clear that CNFs +could be simpler and more cost effective material to be adopted in LIB compared +to CNTs. However, CVD method for the production of CNFs still remains +61 + +unsolved in many aspects. The complex experimental setup such as certain +vacuum level, toxic gases protection, and even plasma or microwave +involvement makes it less cost effective. Also, metals that are introduced as +catalysts during the synthesis usually exist in the sample which interferes with +the desired properties of CNFs and cause a serious impediment in detailed +characterization and applications [10-12,20]. + + + + + + + + + +Figure 3.6 Typical anode assembling based on CVD process +fabricated carbon powder. Cited and modified from Ref. [20] + +Furthermore, it is worth noting that a metal current collector and binders are +required to complete the final assembly of CVD-grown CNFs powder electrode, +as shown in Figure 3.6 [20]. The use of metal substrate not only increases the +mass of electrode which decreases the specific capacity but also causes a +62 + +corrosion-related issue in a long run. As for the use of binder, the conductivity +and effective mass of the electrode also will be affected. Therefore, a mature +CNF network fabrication method which is catalyst-free, easy, cost-effective +combining a mat/film style sample as a final product to avoid the multiple steps +of post treatments is highly demanded in the industrial field of anode fabrication. + +3.1.3-2 Electrospinning Method for CNF Mat +Fortunately, free-standing CNFs mat can be fabricated by electrospinning as +an alternative method of CVD. Electrospinning uses an electrical charge to draw +very fine (typically on the micro or nano scale) fibres from liquid. This +traditional method usually combines electrospinning of organic polymers and +thermal treatment in an inert atmosphere. The electrospinning technique has been +considered to be one of the advanced fiber formation techniques from polymer +solution by using electrostatic forces [21-24]. Electrospun-based nanofibers +exhibited noticeable properties, such as nanosized diameter, high surface area, +and thin web morphology, which make them applicable to the fabrication of +high-performance nanocomposites and energy storage devices [25-31]. The +simple experimental setup and rather easy process compared to CVD are +particularly suitable for the production of CNFs in large scale. Since this method +was adopted in the research part in this work, the fundamental mechanism and +detailed experimental procedures will be further explained as following. + +63 + +In the electrospinning process, a polymer solution held by its surface tension +at the end of a capillary tube is subjected to an electric field. Charge is induced +on the liquid surface by an electric field. Mutual charge repulsion causes a force +directly opposite to the surface tension. As the intensity of the electric field is +increased, the hemispherical surface of the solution at the tip of the capillary tube +elongates to form a conical shape known as the Taylor cone [32]. When the +electric field reaches a critical value in which the repulsive electric force +overcomes the surface tension force, a charged jet of the solution is ejected from +the tip of the Taylor cone. Since this jet is charged, its track can be controlled by +an electric field. As the jet travels in air, the solvent evaporates, leaving behind a +charged polymer fiber which lays itself randomly on a collecting metal screen. +Thus, continuous fibers are laid to form a fabric film [32]. + +The above description of the process suggests that the following parameters +affect the process: solution properties including viscosity, conductivity, and +surface tension; controlled variables including hydrostatic pressure in the +capillary, electric potential at the tip, and the distance between the tip and the +collection screen; and ambient parameters including temperature, humidity, and +air velocity in the electrospinning chamber. By appropriately varying one or +more of the above parameters, fibers with desired properties can be successfully +produced [32]. + +64 + + + + +Figure 3.7. Schematic of CNF mat fabrication processes: (a) +schematic of electrospinning apparatus and (b) the fabricated +nanofiber network. + +To be more specific, here, fabrication process of polyimide (PI)-based CNFs +which were also characterized as an anode in LIB in the following section are +taken as an example. The apparatus used in the electrospinning process is shown +in Figure 3.7. It consists of a glass syringe with a maximum volume of 20 ml. +The glass syringe was filled with a Poly(amic acid) (PAA) solution, inside where +a metal needle (figure not shown) was embedded at the tip of the solution. A +syringe pump (figure not shown) was used to keep the solution at the tip of the +tube and also control the flow rate (injection rate) of solution. The solution was +65 + +charged by connecting the metal electrode to a high voltage power supply. A +cylindrical collector wrapped with aluminum foil was used as collecting devices +for the charged fibers. + +The Poly(amic acid) (PAA) was synthesized by pyromellitic dianhydride +(PMDA, Sigma Aldrich) and oxydianiline (ODA). PMDA of 4.4 g was added +into ODA (4.0 g) pre-dissolved DMF solution (21 g). The mixture was stirred for +30 min with a magnetic bar. 413 μL triethyl amine (TEA) was then added to +control the molecular weight. The as-prepared solution was then electrospun into +PAA nanofibers. The separation distance between the needle and collector, DC +bias voltage, and solution flow rate were 15 cm, 20 kV, and 0.2 mL h-1, +respectively. The PAA nanofiber mat with aluminum foil was then put into +stabilization oven and converted into polyimide (PI) mat after seven different +-1 +oxidation steps at a rate of 1°C min .[52] The PI mat was then peeled off from +the aluminum foil and transferred into high temperature furnace. CNF mat was +formed by annealing the PI mat according to three steps annealing procedures +(firstly from room temperature to 600 °C in 1 h, then 600 °C to 1000 °C in 1.3 +h, and finally maintaining in 1000 °C for 1 h) under argon gas environment by +following the previous publication [33]. + +3.2 Electrospinning Fabricated CNFs Mat as an Anode Material for +LIB +66 + +3.2.1 SEM and Raman Characterization of CNFs Synthesized Through +Electrospinning +The as-fabricated CNFs mat was free-standing film with a large area up to +2 +15 x 15 cm . CNF mat were carefully weighted by using the A&D BM-22 +microbalance located inside the dry room after cut into a 1.5 cm diameter round +shape. The average mass of the film was around 1mg with a thickness of 25 ± 3 +m. Typical SEM images of CNFs mat were shown in Figure 3.8. The average +diameter of the fiber was around 180 nm and the surface of CNFs was smooth +and clean. The micro-Raman spectra was shown in Figure 3.9. It clearly showed +-1 +a G-band near 1592 cm , which is related to the optical E2g phonon at the +2 +Brillouin zone center indicating sp hybridization of carbon network and a D- +−1 +band near 1352 cm , which corresponds to transverse optical phonon near the K +3 +point and indicates sp hybridization of carbon network [34]. The intensity ratio +of D band to G band (ID/IG) was around 0.83. This fairly high value of ID/IG +indicates the existence of large amount of disorder carbon phase and rather poor +conductivity of CNFs. This could lead to a poor electrochemical cycle +performance. Further extensive high temperature (> 1000 °C) and high vacuum +treatment could improve the crystallinity of the as-synthesized CNFs mat, but the +degree of the flexibility and the extra cost need to be considered. + + + +67 + + + + + + +Figure 3.8. SEM images of as-synthesized CNFs with (a) top view and (b) +cross-sectional images. + + + + + + + + +Figure 3.9. Micro-Raman spectra of CNFs mat fabricated by +electrospinning method. + +This kind of free-standing CNF mat fabricated through a simple +electrospinning method is of great interest to be studied as an anode material in +LIB because not only the sample exhibits a film-like nature right after the +68 + +fabrication, which avoids the use of binder and metal substrate, but also the well- +interconnected three-dimensional network structure provides a good porosity and +reasonable conductivity compared to common graphite. Therefore, the as- +fabricated CNF mat was applied and tested as an anode in the following section. + +3.2.2 Anode Performance of CNFs Synthesized Through +Electrospinning +The electrospinning fabricated CNF mat were directly used as an anode for +LIB test in the section. Electrochemical measurements were carried out with a +CR 2032 coin cell using VMP3 instrument (BioLogic Science Instruments). The +cell was assembled in a dry room using CR 2032 cell case with bare CNF mat as +a working electrode, lithium metal foil as a counter/reference electrode, and 1 M +of LiPF6 in a 1:1 (v/v) mixture of ethylene carbonate (EC) and diethyl carbonate +(DEC) as electrolyte. No extra metal current collector, binder or conducting agent +were used. A glassy carbon microfiber was used as a separator. The cells were ++ +charged and discharged galvanostatically between 2.0 and 0.01 V vs. Li/Li . Here, +-1 +we defined 1 C to be 372 mA h g . The general charge/discharge profile is shown +in Figure 3.10a. + +The charge/discharge (CD) profiles of CNF mat show a gradual change in a +broad voltage window during charge/discharge, revealing a V-shape feature. This +is in good contrast with a U-shaped graphite CD curve due to the existence of +69 + +st +disordered carbon phase in our CNF mat [35-36]. In the 1 charge of CNF, a +plateau near 0.7 V vs. Li/Li+ can be attributed to the formation of solid- +electrolyte interface (SEI) via electrolyte decomposition [35]. In the discharge ++ +process, the slope of the curve started approximately at 0.3 V vs. Li/Li and has +-1 + +delivered a specific capacity around 100 mA h g below 0.1 V vs. Li/Li . The +capacity from the potential region above 0.1 V may be ascribed to the faradic +capacitance on the surface of CNFs and the capacity from the region lower than +0.1 V can be related to the lithium intercalation into CNFs [36-38]. This is in +good agreements with combining effect of graphite and non-graphitic carbon as +analyzed in chapter two. The CNF mat delivered a charge and discharge capacity +-1 st +of 776 and 458 mA h g in the 1 cycle and nearly saturated to 280 and 281 mA +-1 +h g after 50 cycles. The related capacity of each cycle, the rate performance + +Figure 3.10. (a) Voltage profiles electrospinning fabricated CNF mat +between 0.01 and 2 V at a charging rate of 0.1 C. The cycle numbers +70 + +are indicated in the figure. (b) Rate performance and columbic +efficiency of the above sample. + +with higher current and columbic efficiency were summarized in Figure 3.10b. It +is clear to see the columbic efficiency which is defined as discharge capacity +divide by the charge capacity in the first cycle was only 60% and increased to +almost 100% in the following cycle. The small columbic efficiency is induced by +the large irreversible capacity which is related to the SEI formation as mentioned +in chapter two. +In summary, although both lithium intercalation and other storage +mechanisms are possible in CNF mat, the slightly higher lithium storage capacity +compared to graphite in the beginning of the cycling is far lower than we +expected. Furthermore, similar problems of surface-electrolyte interface (SEI) +formation and rather large Li insertion potential window as mentioned in non- +graphitic carbon in chapter two still exist. As a result, CNFs do not seem to offer +a major route to improve the anode performance. Thus, searching for +nanomaterial-based alternatives for graphite that combine inherent protection +against lithium deposition, low cost, low toxicity, fast lithium insertion/removal +speed and also higher capacity still remains challenging. + +3.3 Silicon-Coated Carbon Nanofiber Mat for Anode of Lithium Ion +71 + +Battery +3.3.1 Introduction +In order to improve the capacity of conventional carbon based materials, +researchers have been focusing on the discovery of high capacity materials. +Recently, silicon, a high lithium storage capacity material (specific capacity of +-1 +3572 mA h g at room temperature, corresponding to Li15Si4) has been proposed +[39]. Yet, large volume expansion up to 400 % during charge/discharge causes a +severe structural pulverization, making this material impractical. For instance, a +simple deposition of Si thin film on metal substrate leaves crack formation during +cycling and therefore a contact loss between active material and current collector +occurs, leading to a poor cyclability, as shown in Figure 3.11 [40]. Si +nanowires/nanotubes (NWs/NTs) fabricated by various methods on metal +substrate could be an ideal approach to accommodate the volume change due to +existence of sufficient empty space between adjacent NWs/NTs [41-42]. +However, poor root adhesion with substrate and its brittle nature usually create +troubles in traditional coin cell fabrication process. On the other hand, the major +issue for Si nanoparticles, compared to Si NWs/NTs, is the formation and +preservation of electrical contact between each nanoparticle and substrate [43]. +This means that additional binder and conductive additives are usually needed, +which is similar to carbon based powder materials as mentioned in section 3.1.3- +1 and will in turn increase the dead mass and thus reduce the capacity of the +72 + +electrode. + + + + + + + +Figure 3.11. (a) Structure deformation indication of Si based +film/particles before and after charge/discharge cycling. (b) SEI +st +images of CVD deposited Si thin film on Cu stustrate after 1 and +th +30 cycles of charge/discharge. Cited and modified from Ref. [20]. +Owing to these difficulties, several Si/nanocarbon composites have been +proposed. Silicon has been successfully deposited onto carbon fibers or CNFs +through chemical vapor deposition or sputtering [44-53]. Although Li storage +capacity was improved due to the contribution of deposited Si layers, +inhomogeneous deposition of Si atoms on fibers along the depth of the film +diminishes the effect of Si layers. Si nanoparticles have been deposited on CNFs +73 + +by dispersing them in organic solution and then co-spinning onto metal substrate +followed by heat treatment [50-53]. This causes again undefined nature of +adhesion between Si nanoparticles and CNFs, which is closely related to the +efficiency of charge transport across the interface. Electrochemical deposition of +silicon onto CNF substrate is rather promising, since the liquid reaction is easy to +handle with low cost and also the shape of silicon can be controlled by the +deposition conditions. Apart from the fabrication benefits, the CNF mat is a free- +standing three dimensional skeleton and is conductive and porous so that the use +of binders and conductive additives can be avoided. + + + + + + + +Figure 3.12.Schematic of the apparatus for electrodeposition of Si. +The cell consists of three electrodes: woking electrode (as-fabricated +CNF mat), counter electrode (Pt wire) and reference electrode +74 + ++ +(Ag/Ag ). During the deposition, a Si-containing electrolyte (SiCl4 in +-1 +PC) was add into the cell and a cyclic voltage scan (20 mV s ) was +applied to the electrodes. + +In this study, the free-standing CNF mat was fabricated by using +electrospinning of polymer solution followed by stabilization and carbonization, +as introduced in section 3.1.3-2. Si was deposited on the surface of CNFs by +electrodeposition method through a home-made three-electrode cell. The cell +configuration was shown in Figure 3.12. By varying the deposition conditions, a +spaghetti-like Si layer with high surface area and porosity was formed. Si layer +was uniformly coated over nanofibers independent of the depth of the film. More +importantly, volume expansion was easily accommodated on the cylindrical +fibers and highly porous network of CNF mat. High temperature annealing of +1000 °C was performed to improve material purity and construct stable Si and +CNF interface by forming Si-C bond. This free-standing Si-coated CNF mat was +directly used as an anode material for LIB without using any additional metal +substrate or extra binder materials. The capacity of Si/CNF mat anode was +clearly improved by almost twice compared to that of graphite material. The +detailed electrochemical analysis was provided in conjunction with structural +properties. + +75 + +3.3.2 Characterizations of CNF-Si Mat +Figure 3.13a shows typical cyclic voltammograms (CVs) at a scan rate of +-1 +20 mV s for CNF in PC electrolyte with/without adding SiCl4. It is clear to see a +reduction peak centered at around -2.0 V only in the case of electrolyte +containing SiCl4. This suggests that Si ion is reduced into Si and deposited onto +- +CNF mat during CV test following the electrochemical reaction SiCl4 + 4 eSi ++ ++ 4Cl . Si loading amount on CNF mat was controlled by varying number of CV +deposition cycles, as shown in Figure 3.13b. Mass (thickness) of Si/CNF mat +keeps increasing from ~ 1 mg to ~ 4 mg (from ~ 25 m to 130 m), as the +number of Si deposition cycles increased to 1000 cycles. + + +Figure 3.13. (a) Cyclic voltammograms of silicon electrodeposition +-1 +in PC solution with/without SiCl4 at a scan rate of 20 mV s . (b) +Mass and thickness of Si/CNF mat with respect to different silicon +76 + +deposition cycles. The error bar is added in the figure. + + A series of structure characterizations of Si/CNF mat of with 200 cycles +CV deposition are shown in Figure 3.14. Micro-Raman spectra of bare CNF mat +(also shown in Figure 3.9) and pristine Si/CNF mat (without annealing, indicated +as Si-200-p) in Figure 3.14a shows intensity ratio of D band to G band (ID/IG) +remained unchanged (∼ 0.83) between bare CNF and Si-200-p after +electrodeposition of Si, indicating that carbon material is remarkably stable +compared to traditional metal substrate in severe electrochemical environment +[37]. However, in the case of Si/CNF mat after 1000 °C annealing (indicated as +Si-200-a), the value of ID/IG slightly decreased to ~ 0.79, suggesting an improved +graphitization in the CNF network. It is of note that no Si related peak can be +found in Si-200-p. This could be ascribed to the highly disordered nature of the +deposited Si which is caused by electrostatic clustering with alkyl terminators +and also the presence of deposited electrolyte residues on the surface, as shown +in Figure 3.15a [54]. On the other hand, three additional Si related peaks were +shown in the spectrum of Si-200-a. It is known that first order transverse-optical +−1 +(TO) phonon mode of crystalline Si (c-Si) will display a sharp peak at 520 cm +which usually becomes broaden and is downshifted when the long-range order in +-1 +Si is lost [55]. In our case, the peak located at around 500 cm was assigned to +microcrystalline or nanocrystalline (c/nc) Si and a broad band at the low energy +-1 +side originated from the presence of amorphous Si (a-Si). The peak near 300 cm +77 + +resembles transverse acoustic (TA) phonon mode of c-Si and could be softened in +-1 +a-Si [55-57]. In addition, c-Si usually exhibits a small peak at 950 cm which is +related to the chemisorption of atomic/molecular oxygen species [58]. Here, we +-1 -1 +also found a softened peak at 920 cm in Si-200-a. A red shift of 30 cm is + +possibly caused by the existence of a-Si [57]. All of these factors demonstrate +that as-deposited Si is completely disordered and evolves into more distinct a-Si +and c/nc-Si with additional oxygen species after high temperature annealing. + + + +Figure 3.14. (a) Micro-Raman spectra of bare CNF mat and Si/CNF +mat with 200 cycles of Si deposition before/after annealing, indicated +as Si-200-p and as Si-200-a in the figure. (b) XPS spectra of the +electrode surface with active materials consisting of Si-200-p and Si- +200-a, respectively. + +Figure 3.14b plots the XPS spectra of Si/CNF mat with 200 cycles +78 + +deposition before and after1000 °C annealing. It is obvious to see that the +intensities of Si 2s and Si 2p peaks increased clearly while the C 1s peak +relatively decreased. In addition, Cl 2p peak which appeared in Si-200-p +disappeared after annealing. After Si electrodeposition, certain amount of +electrolyte could be decomposed and remained on the Si surface. After annealing, +the residual film which mainly contained C, O, and Cl was removed, as seen in +Figure 3.15. This is also in good corroboration with Figure 3.14a. + + + + + + + + +Figure 3.15. SEM images of (a) Si-200-p and (b) Si-200-a samples. +Dark color portion indicates electrolyte residues on the surface of +CNF mat. After 1000 °C annealing, the uniform mat surface was +observed by the removal of electrolyte, as shown in (b). + +Figure 3.16a is the SEM image of the bare CNF mat which already +explained in Figuer 3.8. On the other hand, the Si-200-a sample displayed a +79 + +rough spaghetti-like surface, as shown in Figure 3.16b. The cross sectional view +of Si-CNF core-shell structure was shown in the inset of Figure 3.16b. It is of +note that the core-shell structure was formed uniformly independent of the depth +over hundred micrometers, which is in good contrast with other methods such as +sputtering and CVD, in which Si is not uniformly deposited along the depth of +the sample. AFM morphology of the same sample was provided in Figure 3.16c +with an amplified phase image in Figure 3.16d, again demonstrating rough Si +surface on the surface of CNFs. This unique spaghetti-like Si structure provided +large surface area compared to the flat Si thin film which can facilitate the charge +transfer at the electrolyte/Si interface. Moreover, the volume expansion can be +accommodated to certain degree by the high porosity of Si under the condition of +200 cycles deposition which is certainly better than the thick Si layers. + + + + + + + + + + +80 + +Figure 3.16. (a) SEM images of as-synthesized bare CNFs and (b) +Si-200-a. The cross-sectional images are shown in the insets. (c) +AFM image of Si-200-a. The high resolution image of dashed square +in (c) is shown in (d). + +Figure 3.17a is the TEM image of the Si-200-a sample. The layer thickness +of deposited Si was ~ 20 nm in this case. The existence of Si on the surface of +CNF was again confirmed by EDS line profile along the dashed line in the TEM +figure, as shown in Figure 3.17b. The spaghetti shape of Si was not visible here +probably due to the sample damage during TEM sample preparation process with +sonication. Since the thin film of electrodeposited silicon is highly active and +therefore can be oxidized immediately upon exposure to air during transfer from +the glove box to TEM, or X-ray diffraction (XRD) measurements, the crystalline +nature of the electrodeposited Si film is unlikely to be directly observed [59]. + + + + + + + + +81 + +Figure 3.17. (a) TEM image of Si-200-a. The EDS line profile +along the dashed line is shown in (b). + +To obtain information of interface between CNF and Si, C 1s and Si 2p +peaks in XPS were deconvoluted, as shown in Figure 3.18. C 1s peaks before +and after annealing were clearly distinct with each other. Clear Si-C peak near +2 3 +283 eV was visible in addition to small sp and sp peaks after annealing, while +2 3 +only intense sp and sp peaks were shown before annealing [60-61]. It is of note +3 2 +that the ratio of sp to sp peak was slightly reduced after annealing (from 62 % +reduced to 48 %), revealing similar trend to the change of D/G ratio in Raman +spectra, shown in Figure 3.14a. In addition, COx peak near 288 eV slightly +increased after annealing [62]. Similar phenomenon was observed in Si 2p peak +(Figure 3.18c, d). Before annealing, the main peak near 102.2 eV was SiOx peak +with additional Si-Si peak near 99.3 eV [62]. After annealing, SiOx content was +slightly increased due to ambient oxidation, in good agreement with C 1s peak +analysis. More importantly, Si-C peak near 100.8 eV appeared after annealing +[60]. The Si-C peak shown in C 1s and Si 2p after annealing comes from +chemical bonding between CNF and Si at the interface. This peak is small due to +narrow interface region, which is hardly observable by Raman spectroscopy, as +shown in Figure 3a. The presence of such Si-C bonds at the interface may not +contribute to Li storage but plays an important role in strengthening adhesion of +Si layer to CNFs and furthermore efficient charge transfer at the interface during +82 + +lithiation/delithiation process [63-64]. + +Figure 3.18. High-resolution XPS spectra of Si/CNF with 200 +cycles of Si deposition before and after annealing. Figure (a) and (c) +are C 1s and Si 2p fitted peaks before annealing. (b) and (d) are C +1s and Si 2p fitted peaks after 1000 °C annealing. Peak positions +and relative ratios are shown in the figure. +3.3.3 Anode Performance of CNF-Si Mat +The electrochemical performance of bare CNF and Si/CNF mat was +investigated in LiPF6/EC+ DEC solution. For better comparison, the bare CNF +83 + +mat was annealed (indicated as CNF-a) at the same condition as the composite +mat. The electrochemical performance comparison between CNF-a and non- +annealed CNF was shown in Figure 3.19. In Figure 3.19a, lithiation/delithiation +occurred below ~ 0.3 V in the cathodic/anodic scan which resembled the +characteristic of hard carbon in the case CNF [35,38]. However, the cathodic +peak below 0.1 V and the anodic peak at ~ 0.1 V belong to the characteristic of Li +intercalation/deintercalation into graphitic layers in CNF-a [65-66].This +manifests that our as-fabricated CNF mat contains a certain degree of +graphitization and disordered phase which is consistent with Figure 3.14a and +Figure 3.18 and also the improved graphitization degree of CNFs after 1000 °C +annealing. In Figure 3.19b, the impedance profiles show decrease of both series +resistance (the starting point) and charge transfer resistance (the radius of +semicircle ) after 1000 °C annealing. This again can be attributed to the higher +graphitization degree of CNF after annealing. + +84 + +Figure 3.19. (a) CV profile comparison between bare CNF mat and +CNF mat after 1000 °C annealing. The curves were recorded after +st -1 +1 CV scan between 0.01 to 2 V at a scan rate of 0.1 mV s . (b) AC +impedance spectra of the above two electrodes. The spectra were +recorded right after the cell assembling before cycling. + +The CV curves of CNF-a and Si/CNF mat with 200 cycles of Si deposition +were shown in Figure 3.20a. In the case of Si/CNF mat, no appreciable peaks +related to LixSi alloy formation were observed in Si-200-p (dashed line). On the +contrary, two pairs of redox reaction peaks were observed in Si-200-a (solid line). +The sharp cathodic peak at ~ 0.01 V can be attributed to a combination effect of +CNF mat and c-Si/a-Si. The cathodic peak (Li alloy) at 0.2 V and anodic peaks +(Li dealloy) at 0.37 V and 0.52 V are due to the formation of amorphous LixSi +phase and delithiation back to a-Si, respectively [67-68]. The increase of the peak +intensities of a-Si with increasing the scan cycle numbers can be ascribed to the +conversion of the c/nc-Si into amorphous phase during the repeated CV scans. +The electrochemical analysis in Figure 3.20a provides us further understanding +of the Si crystallinity which is again in good agreement with Figure 3.14a. +85 + + nd th +Figure 3.20. (a) The 2 and 10 cyclic voltammograms of CNF-a +(square), Si-200-p (dashed line) and Si-200-a (solid line) mats +-1 +between 0.01 and 2 V at a scan rate of 0.1 mV s . (b) and (c) are +voltage profiles of Si-200-p/Si-200-a and CNF-a/Si-200-a between +0.01 and 2 V at a charging rate of 0.1 C. The cycle numbers are +indicated in the figure. (d) Charge/discharge capacity and Coulombic +efficiency of Si-200-a for the first 80 cycles. + +th +The 1, 2, 10, 30, 50 galvanostatic charge/discharge (CD) profiles between +86 + +0.01 and 2 V of Si/CNF mat with 200 cycles deposition before/after 1000 °C +annealing are plotted in Figure 3.20b. The CD rate was 0.1 C, where 1 C is +-1 +defined to be 372 mA h g . Compared to Si-200-p which delivers a capacity +-1 +around 300 mA h g , Si-200-a exhibited much higher capacity of almost 900 mA +-1 st -1 th +h g at 1 discharge and 730 mA h g at 50 discharge according to the total +mass of Si and CNF with an average fading rate of 0.34 % per cycle. This can be +attributed to the presence of a mixed phase of Si (c-Si and a-Si) and also the +improved material purity after annealing by removing the electrolyte residues as +discussed. Figure 3.20c is the galvanostatic CD profiles of CNF-a mat and Si- +200-a. The CD profiles of CNF-a mat has already explained in Figure 3.10. +Compared to CNF-a mat, the Si-200-a sample showed a large capacity of 1650 +-1 st +mA h g in the 1 charge and a higher capacity by almost three times (730 mA h +-1 th +g ) after 50 cycles, since Si contains a higher Li storage capacity than carbon. +However, the large capacitance loss of the first cycle related to the formation of +the SEI layer was observed. Figure 3.20d shows capacity retention of the Si-200- +nd +a sample at the specific charging rates. The discharge capacity at the 2 cycle +-1 -1 -1 +was 710 mA h g at 0.2 C, 637 mA h g at 1 C and 565 mA h g at 2 C. The +Coulombic efficiency is defined as the ratio of the discharge to charge capacity +and plotted in the same figure. The Coulombic efficiency of Si-200-a sample +st +approached to 54 % at the 1 cycle due to the SEI formation and increased to +99 % after 20 cycles at 0.1 C rate. The value was smaller than the ideal efficiency +because of the reformation of SEI layer on newly exposed Si during cycling with +87 + + +a cost of Li consumption [69]. Compared to the Si thin film on the two +dimensional Cu substrate, the improved cyclic life was attributed to the highly +porous three dimensional CNF substrate and also the unique Si spaghetti +structure, which can both accommodate Si volume expansion. The comparison +between our work and previous publications with respect to the different +fabrication methods of Si/CNF composite structure was shown in Table 3.1. It is +clear to see that our result showed reasonable capacity and also capacity retention. +More importantly, our structure involved no metal substrate compared to others. + +Table 1. Anode performance comparison of silicon/CNF composites +fabricated by different methods. CNF film is usually fabricated by +mixing CNF powder with a binder. CNF mat is binder-free +freestanding film fabricated by electrospinning method. + + + + +88 + +Current +Si deposition Mass Si mass Capacity@cycles Capacity Structural +Structure -2 density -1 Remarks +Method [mg cm ] ratio -1 [mA h g ][a] retention features +[mA g ] +[44] +Si@CNF CVD 2 75 % 500 1600@55 80 % film Metal substrate +[45] CF mesh as a +Si@CNF CVD 4 37 % 50 766@20 80.3 % film +substrate +[46] +Si@Hollow CNF CVD — 25 % 0.5C[b] 750@100 68.2 % film Metal substrate +[47] +Si@CNFs Sputtering 0.4 16 % 50 1200@105 90 % film Metal substrate +VACNFs grown +[48] 2752@ +Si@VACNFs Sputtering 0.2 49 % 323 89 % — on metal +100[c] +substrate +[49] +SiNWs@CNF VLS 3.6 80 % 342 1400@40 77 % film — +[50] Si NPs in DMF & +Si/CNF — 16 % 100 773@20 90.4 % mat Metal substrate +electrospinning +[51] +Si/CNF As above 1.6 26 % 50 726@40 46.8 % mat Metal substrate +Si-CNF +[52] As above — 50 % 240 1300@100 1 film Metal substrate +core-shell +[53] Si NPs in DI & +Si/CNF — 41 % 35 892@50 — mat Metal substrate +electrospinning +No substrate +Si/CNF (Ours) Electro-deposition 1 43 % 37 730@50 85 % mat +No binder +[a] Capacity is calculated based on silicon & carbon mass. [b] C rate is not mentioned in the reference. [c] Capacity is +calculated based on silicon mass. + +89 + + + + + + + + + +Figure 3.21. (a) Charge (filled symbols)/discharge (open symbols) +capacity in terms of different numbers of silicon deposition cycles +after high temperature annealing. Capacity was calculated based on +silicon mass only. Sample indications are shown in the right dashed +square. (b) AC impedance spectra of the above five electrodes. The +spectra were recorded right after the cell assembling before cycling. +The equivalent circuit is shown in the inset. The related resistance +value in Figure (b) was plotted in Figure (c) with respect to different +silicon deposition cycles. +90 + +For better understanding of the structure-related Li storage capacity, +different Si amount was deposited on the CNF mat by varying the number of +electrodeposition cycles. The capacity retention of Si/CNF mats (all after +1000 °C annealing) upon the different Si deposition cycle numbers are +summarized in Figure 3.21a. Here, the specific capacity was expressed in terms +of net Si mass excluding carbon mass. The specific capacity with respect to net +Si mass from the composite was calculated from the following equation: +QSi = mCNF/mSi {Qcomposite (1+ mSi/mCNF) – QCNF} + +where “Qcomposite” is the total capacity of CNF-Si composite according to the total +mass of Si+CNF electrode. QSi (QCNF) is the specific capacity based on the net +mass of Si (CNF). Here mSi (mCNF) is the mass of deposited Si (CNF) in the +-1 +composite. The values of specific capacity was ~ 1545 mA h g at the beginning +of charge/discharge and were similar to each other regardless of the Si deposition +cycle numbers. However, capacity retention became poorer as the Si loading +amount increased, for example, the capacity of 200 and 1500 Si electrodeposition +-1 -1 +cycles was 1354 mA h g and 873 mA h g , respectively. As the Si thickness +increases, deformation energy of Si increases as well, inducing more crack +initiation and propagation. In other words, in the case of thicker Si layers, crack +generation caused by volume variation is more significant [43]. Therefore, +thicker Si layer peels off easily and eventually the capacity degradation occurs +more severely than that of thinner Si layer. The cohesive energy of Si-C bonds at +91 + +the interface between Si and CNF is helpful for structure stabilization against the +increased deformation energy. Deformation energy is proportional to the +thickness, while interfacial energy is constant. When deformation energy exceeds +interfacial cohesive energy at critical layer thickness of Si, the structure of Si +breaks down. On the other hand, Si shape transformation was observed from +spaghetti-like to granule-like when CV deposition cycles keep increasing from +200 to 1500, as shown in Figure 3.22. The thin Si layer fabricated with 200 +cycles CV deposition revealed a highly porous structure (See Figure 3.16), and +therefore the volume expansion can be minimized compared to the thick granular +shape Si layers. + + + + + + + + + + + + +92 + +Figure 3.22. SEM images of (a-b) Si-1500-p and (c-d) Si-1500-a +samples. + +Nyquist plots of Si/CNF mat with different Si loading masses are plotted in +Figure 3.21b. The curves were collected right before electrochemical +charge/discharge cycling. All of the curves showed a depressed semicircle and a +tail, which indicates the mixed kinetics and diffusion process. The semicircle in +the high frequency range indicates the charge transfer resistance (Rct) at the +interface between electrode and electrolyte. The tail at low frequency region +implies a diffusion-controlled process. An equivalent circuit is shown in the inset +where Rs, Cdl, and Zw represent respective series resistance of +electrolyte/electrolyte contact, double layer capacitance, and Warburg impedance +related to the diffusion of ions in the bulk electrode [70-71]. The value of Rs (first +point) and Rct (diameter of semicircle) were extracted from Figure 3.21b and +replotted in Figure 3.21c. As the Si loading amount increased, Rs slightly +increased due to lower conductivity of Si. The Rct decreased sharply with Si +deposition and then increased gradually as the Si coating amount increased. The +origin of large value of Rct observed in bare CNF-a sample compared to the Si- +coated CNF sample could be the morphology difference between CNF-a and Si. +The Si shell exhibited much rougher surface than that of bare CNF-a (See Figure +3.16), which benefited the charge transfer process through large surface area. The +different lithiation mechanisms between silicon and carbon may also play a role +93 + +here. The increase of Rct in Si/CNF mat with increasing Si deposition cycles is +attributed to the larger granular size and less porosity of the deposited Si layers +(See Figure 3.22a). The straight line can be interpreted as the resistance for the +diffusion process of lithium ions into the electrode. The smaller angle between +real axis and the straight line as the Si loading amount increases simply indicates +again the limited diffusion of Li ions with increasing Si loading amount. + + + + + + + + + + + + +Figure 3.23. Charaterizations of Si-200-a electrode after 80 cycles +charge/discharge. (a) Top-view SEM image, (b) Cross-sectional SEM +image, (c) High resolution TEM image, and (d) AFM image. The SEI +layer was selectively removed by washing the sample with acetonitrile +94 + +and diluted HCl. + + Figure 3.23a and b show SEM images for the structural changes of Si- +200-a after cycling test. The SEI layer was selectively removed by using +acetonitrile and then HCl prior to imaging [72]. Si layer became rough hairy and +highly porous, compared to the one before cycling test in Figure 3.16. The lower +density of Si suggested that some spaghetti type Si at the outermost surface was +removed, as can be seen in the TEM image of Figure 3.23c. This is why capacity +was degraded during cycling. Nevertheless, compared to the sample with hgiher +Si loading amount (Figure 3.22c,d), the major portion of Si remained after +cycling test (See AFM image of Figure 3.23d), retaining relatively high capacity +and reasonable capacity retention. This is in fact corroborated to the robust Si-C +bonds formed at the interface between Si and CNF which was achieved by +1000 °C annealing. Free-standing CNF mat assembled through electospinning +process without a binder or a metal substrate is a good platform to provide such +3 +robust Si-C bonds due to abundant existence of sp bonds at the surface of CNF, +as discussed in Figure 3.14 and Figure 3.18. + +3.4 Summary of Chapter Three +In this chapter, general introduction of common one dimensional carbon +materials like CNFs and CNTs has been given. Compared to higher conductivity +of CNTs, CNFs exhibit an easier Li insertion pathway and a cost effective +95 + +property which make them a good candidate for anode of LIB. Especially, the +electrospinning method synthesized free-standing CNF mat has been intensively +studied in this work since it prevents the use of metal substrate, binder and +conducting polymers which usually increase the mass of electrode, degrade the +long term stability and reduce the anode capacity. Due to the unsatisfied capacity +of as-fabricated CNF mat, Si, a high capacity media was introduced into the three +dimensional CNF network through electrochemical deposition. Once again, the +structure involves neither a metal substrate nor binders. This could help us in +designing anode structures with high capacity and long cycle life in an economic +way. Thermal annealing of the combined mat at 1000 °C was necessary to +remove undesired residues formed during electrodeposition process and to form +strong Si-C bonds at the interface between Si layer and CNFs, which eventually +improved adhesion of Si to CNF and furthermore facilitated efficient charge +transfer between Si and CNF during lithiation/delithiation. This resulted in clear +improvement of the capacity of carbon materials more than twice for most of +cases. 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Cui, Nano Lett. +2012, 12, 904. + + + + + + + + + + +102 + +Outline of Chapter Four + +Diffusion Mechanism of Lithium Ions through Basal Plane of +Layered Graphene + +4.1 Brief Introduction of Two Dimensional Graphene 105 +4.1.1 General Physical Properties of Graphene 105 +4.1.2 Synthesis Methods of Graphene 110 +4.2 Diffusion Mechanism of Lithium Ions through Basal Plane of 113 +Layered Graphene +4.2.1 Material Preparation 116 +4.2.2 Transfer Process of Graphene 116 +4.2.3 Characterization of Graphene 117 +4.2.4 Anode Performance of Graphene 121 +4.3 Summary of Chapter Four 140 +Bibliography of Chapter 4 141 + + + + + +103 + +CHAPTER FOUR +Diffusion Mechanism of Lithium Ions through Basal Plane of +Layered Graphene +Recently, graphene, composed of monolayer of carbon atoms arranged in a +honeycomb network, has emerged explosively and attracted much attention in the +fields of materials science and condensed-matter physics. High mobility of +graphene is probably the most fascinating properties for physicists and engineers, +which is attributed to the linear band dispersion, leading to massless Dirac +quasiparticle feasture. On the other hand, as the thinnest carbon material, +graphene and graphene-based materials have promising applications in numerous +energy sciences, for instance, Li-ion batteries (LIBs), fuel cells, and solar cells. +In particular, these materials have superior electrical conductivities to graphitic +2 +carbons and higher surface area of over 2600 m /g than CNTs, and a broad +electrochemical window that would be more advantageous in energy storage. +Thus, a series of research works on LIB based on graphene were performed +intensively with the similar routes to the CNTs-based electrode materials for LIB +[1-6]. Some scientists used graphene sheets directly as an anode material for LIB +and found that they had improved electrochemical properties. For example, the +first reversible specific capacity of the prepared graphene sheets with a specific +2 -1 +surface area of 492.5 m /g was as high as 1264 mAh g at a current density of +-1 +100 mA/g. After 40 cycles, the reversible capacity was still kept at 848 mAh g +at a current density of 100 mA/g, higher than that of CNTs or CNF electrodes [7]. +104 + +The interesting single atomic layer structure of Gr can also be used for +fundamental science and a good candidate for the fundamental study of Li ion +diffusion pathway in addition to its real applications as an anode in LIB. Large +area single layer graphene (SLG) which consists of a clean basal plane for the +study of Li insertion prevents the coexistence of both edge plane and basal plane +in graphite that often hinders the understanding of lithium ion diffusion +mechanism. Therefore, in this chapter, after a brief introduction which includes +the general properties and production methods of Gr, the diffusion mechanism of +lithium ion through basal plane of layered graphene has been intensively studied. +In this case, two types of graphene samples were prepared by chemical vapor +deposition (CVD): i) well-defined basal plane single layer graphene grown on Cu +foil, ii) edge plane-enriched graphene layers grown on Ni film. Electrochemical +performance of graphene electrodes has been examed based on different number +of graphene layers and also different defect population on graphene basal plane. +Density functional theory calculations were also provided to clarify the diffusion +barrier heights for various types of defects. + +4.1 Brief Introduction of Two Dimensional Graphene +4.1.1 General Physical Properties of Graphene +Graphene, as a two-dimensional (2D) honeycomb lattice structure consists of +2 +sp -hybridized carbon atoms in the form of one-atom thick planar sheet. This +105 + +unique material is a basic building block for many other carbon-based graphitic +materials such as zero-dimensional (0D) fullerenes, one-dimensional (1D) carbon +nanotubes, and three-dimensional (3D) graphite and is an excellent basic model +for many other 2D materials (Figure 4.1) With its unique structure, graphene +exhibits extraordinary thermal, mechanical, and electrical properties, which +makes it a popular material in many different research areas, theoretically and +experimentally. + +Figure 4.1. Graphene is a basic 2D building block for other carbon +allotropes with different dimensionalities. Cited from Ref.[8]. + +The unusual electronic properties of graphene are originated from its unique +106 + +band structure. In the lattice of graphene, carbon atoms are located at each corner +of hexagons binding with three neighboring carbon atoms. Carbon atom has four +valance electrons, of which three of them were used for covalent σ-bonding with +adjacent carbon atoms in graphene lattice. The remaining π-orbital determines +the electronic structure of graphene which is "coupled" with the other π-electrons +on adjacent carbon atoms. Each π-electron is delocalized, i.e., has a "field of +influence" of 360 degrees around its own carbon atom within an individual +graphene layer. The unit cell of graphene contains two π-orbitals (π and π*), +which disperse to form two π-bands that can be considered as bonding (the lower +energy valence band) and anti-bonding (the higher energy conduction band) in +nature. + +Figure 4.2. a) Honeycomb lattice of graphene with two carbon atoms +per unit cell. b) Tight-binding band structure of graphene π-bands, +considering only nearest neighbor hopping. c) Band structure near K +point showing the linear dispersion relation. Cited from Ref. [9]. +107 + + The bonding-antibonding gap closes at the corners of the Brillouin zone, or +the K points. (See Figure 4.2) As a result, the π-band dispersion is approximately +linear around the K points: E = ħvF |k| where k is the wave vector measured from +K, ħ is Planck’s constant, h divided by 2π, and vF is the Fermi velocity in +6 +graphene, approximately 10 m/s. Since the electrons in graphene have kinetic +energies exceeding their mass energy, electrons behave like photons or ultra- +relativistic particles with an energy-independent velocity vF that is approximately +300 times smaller than the speed of light in vacuum, allowing relativistic effects +to be observed in graphene without using particle accelerators [9]. These +quasiparticles, called massless Dirac fermions, can be seen as electrons that have +lost their rest mass m0 or as neutrinos that acquired the electron charge e [10]. +This linear (or “conical") dispersion relation at low energies, electrons and holes +near these six points, two of which are inequivalent, behave +like relativistic particles described by the Dirac equation for spin 1/2 particles +[11]. Dirac fermions behave in unusual ways when compared to ordinary +electrons if subjected to magnetic fields, leading to new physical phenomena [12- +14] such as the anomalous integer quantum Hall effect (IQHE) measured +experimentally [14-15]. The IQHE in graphene can be observed at room +temperature because of the large cyclotron energies for “relativistic” electrons +[16]. In fact, the anomalous IQHE is the signature of Dirac fermion behavior. +With these properties, graphene is a perfect mixture of semiconductor (zero +density of states) and a gapless metal which is quite different from other metals +108 + +and semiconductors with its very long mean free paths (Figure 4.3). +Figure 4.3. Electronic Structure of: a) Metal: Finite Density of States +(DOS) at Fermi energy. b) Semiconductor: Gap at Fermi energy. c) +Graphene: Zero gap Semiconductor. Zero DOS metal. Cited from Ref. +[18].The interesting 2D structure of graphene makes it a good +candidate for electronic device applications [17]. Unlike an ordinary +metal, in which any impurities in the crystal scatter electrons and so +lead to energy loss, the electrical resistance in graphene is independent +of the number of impurities. This means that electrons can travel for +several microns without colliding with impurities, making graphene a +promising material for a potential high-speed electronic switching +devices called a “ballistic transistor”. Experimental transport +measurements show that graphene has a unusual high electron +2 -1 -1 +mobility even at room temperature in excess of 15,000 cm v s , of +which mobilities for holes and electrons are nearly same [9,14,18-19]. +Graphene has a number of other extraordinary properties such as strong +109 + +mechanical properties and high flexibility allowing strain based graphene +electronics [20-21]. Another important aspect of graphene is its high thermal +conductivity up to 5000 W/mK at room temperature, 20 times higher than that of +copper, which could be exploited to applications in microelectronics and thermal +management structures [22]. Its optical properties are strongly related to its +electronic properties such as its low energy electronic structure where conical +bands of electron and hole meet at the Dirac point resulting in unexpected high +opacity. An atomic monolayer of graphene absorbs πα ≈ 2.3% of white light, +where α is the fine-structure constant [23]. It has been shown that graphene +system exhibits electrochromic behavior, allowing tuning of both linear and +ultrafast optical properties [24-25]. + +4.1.2 Synthesis Methods of Graphene +First attempts to understand graphene basic properties was made by micro- +cleavage method, which is a simple method to isolate graphitic layers from +graphite into monolayer graphene flakes with the help of a cohesive tape [26]. +Although many basic electronic properties of graphene such as the bipolar +transistor effect, ballistic transport of charges, large quantum oscillations, etc., +was explored by this method, for the large area graphene applications it was +necessary to find other synthesis methods (Figure 4.4). For this purpose, +epitaxial synthesis of graphene on different substrates was realized. Many +110 + +important graphene properties have been identified in graphene produced by SiC +substrate. In this method, the face of SiC, silicon or carbon-terminated, is used +for graphene formation in ultra high vacuum furnaces at very high temperatures +o +(>1100 C) to decompose SiC into graphene [27]. Another approach for epitaxial +growth of graphene is studied on metal substrates, such as ruthenium, iridium, +and nickel [28-30]. Although these substrates have been employed to obtain +graphene, the interaction of graphene with underlying substrate and conducting +behavior of these substrates necessitated the transfer of graphene layers onto +other substrates for the application. Synthesis of large area few-layered graphene +together with transferring onto another substrate has been realized by chemical +vapor deposition (CVD) method on polycrystalline metallic substrates such as Ni +and Cu [31-33]. Unlike the epitaxial growth techniques, CVD method has been +realized by decomposition of carbon gases such as ethylene and methane +followed by either carburization-precipitation, or surface adsorption of carbon +gases. To fabricate devices, graphene, then, can be transferred by +polymethylmethacrylate (PMMA) as a supporting layer after dissolving the +underlying metallic substrate in a metal etchant and “fishing” the single-layer +graphene up onto a desired substrate (e.g., SiO2/Si). This method will be +explained in detail later. Graphene has been also derived from graphite oxide by +thermal annealing or chemical reduction by hydrazine [34-35]. This method +combining with the typical powder process (involves metal current collector and +binders) as mentioned in chapter three has been considered as one of the most +111 + +popular one used in battery electrode fabrication. However, graphene produced +by graphite oxide reduction is lower in quality compared to graphene obtained by +aforementioned production methods due to incomplete removal of various +functional groups by existing reduction methods. + + + + + + + +Figure 4.4 Production techniques of graphene: a) Micro-cleavage +method, isolating graphitic layers from graphite into monolayer +graphene flakes with the help of a cohesive tape, b) epitaxial growth +of graphene by decomposition of SiC into graphene, c) chemical +vapor deposition method by decomposition of hydrocarbon gases on +metal substrates, and d) chemical exfoliation of graphite oxide by +weakening van der Waals cohesive force via insertion of reactants +into interlayer space. +112 + +4.2 Diffusion Mechanism of Lithium Ions through Basal Plane +of Layered Graphene +Graphite has been widely used for anode material in lithium ion battery due +to its well defined layered structure for lithium intercalation, low operating +potential, and remarkable interfacial stability [36]. Graphite has two +characteristic planes: basal plane and edge plane which are parallel and +perpendicular to the c-axis, respectively. It is known in general that the basal +plane and edge plane exhibit different physical and chemical activities in many +aspects, leading to different lithiation capabilities in graphite [37-38]. The +diffusion time constant for Li ion insertion within the active graphitic flakes is +governed by the formula τ = L2/2D, where L is the diffusion length (or radius of +spherical flake) and D is diffusion coefficient [39]. Although lithium diffusion +through basal plane is rather limited, lithium diffusion may still occur through +several defect sites such as vacancies and grain boundaries [40-41]. Lithium +diffusion through edge plane of graphitic flakes can be easily facilitated but +further complicated by the presence of different functional groups such as +hydroxyl and carboxyl groups. In other words, lithiation through these two +different planes is highly anisotropic [42-46]. +One ambiguity in understanding diffusion pathway of lithium ions in +graphite is the coexistence of both edge plane and basal plane in the sample. The +presence of these two different interfaces is unavoidable in conventional graphite +[32,47]. Currently available highly oriented pyrolytic graphite (HOPG), which is +113 + +well known as highly ordered crystallographic structure, has a finite size of +flakes whose edge planes are still abundant in addition to basal planes. Therefore, +lithium ion diffusion through basal plane cannot be observed exclusively [40- +43].Thus, a well defined basal plane of graphite with large area is required to +have a comprehensive picture of lithium diffusion mechanism in lithium ion +battery. + +Recently large area monolayer and multi-layer graphene have been +synthesized by chemical vapor deposition (CVD) [32,47]. This paves a new route +for exploring numerous new fundamental sciences and moreover developing +numerous technological breakthroughs in electronics and energy storage [48-50]. +Large area graphene can be transferred onto any substrate by a simple transfer +process and therefore an anode electrode with layered graphene without leaving +edge plane (or negligible portion of edge plane) is easily attainable. This provides +an opportunity to study diffusion of lithium ions exclusively through the basal +plane of graphene. + +On the other hand, in lithium ion battery, corrosion of conventional current +collectors such as Al, Cu, and stainless steel (SUS) can adversely affect life time +and safety through increased internal resistance, passivation of active materials, +and consumption of electrolyte/ active electrode materials [51-57]. Anode +performance of thin graphene layers can be misguided by the strong substrate +114 + +reaction since the most reactive lithium ions exist in electrolyte [58-59]. It has +been proposed that monolayer graphene can be used as a protective layer for + +substrate against air oxidation and mild electrochemical reaction [60-61]. +Therefore, information on the critical layer thickness of graphene (lc) to minimize +the substrate effect and the influence of defects to lc are key ingredients to +understand electrochemical reaction and protective nature of graphene layers +under severe electrochemical condition. + +The main purpose of this work is twofold: i) To clarify lithium diffusion +pathway through basal plane of graphene layers and ii) to investigate the +influence of defect population to lithium ion diffusion and the protective ability +of graphene layers. In this article, we prepared Cu-grown monolayer graphene +(SLG) samples and Ni-grown multi-layered graphene (MLG) samples that are +dominated with graphene basal plane and edge plane, respectively. We found that +the electrochemical performance of few-layer graphenes (FLGs) which are +overlapped up to three layers of SLG is strongly affected by the substrate +reaction. Experiments with Ar plasma treatment indicated that 6 layers of basal +plane-enriched large area graphene were needed to provide sufficient substrate +protection. Combing the experimental results and density functional theory +calculations, we proved that basal plane hindered lithium ion diffusion with a +high diffusion barrier height, whereas divacancies and higher order defects can +be shortcuts for lithium ion diffusion. +115 + +4.2.1 Material Preparation +Large area SLG was synthesized on copper foil by atmospheric pressure +(AP) CVD. Cu foil purchased from Nilaco (Lot No. 113321, 99.96 %, 100 μm in +thickness) was preannealed to 1060 °C for two hours with 100 sccm of Ar gas +and 200 sccm of H2 gas to enlarge Cu grain size and then chemico-mechanically +polished with FeCl3 solution for flattening. The prepared Cu foil was then +brought into the growth chamber. The temperature of the chamber was heated up +to 1060 °C with 1000 sccm of Ar gas and 200 sccm of H2 gas for 20 min. +Methane (5sccm) was then introduced with 10 sccm H2 gas for 5 min. After +growth, the sample was cooled down to room temperature naturally in the same +atmosphere. In the case of MLG synthesis, Ni thin film (300 nm) was deposited +on SiO2 (300 nm)/Si by a thermal evaporator. This was placed in rapid thermal +CVD chamber. Temperature was increased to 1000 °C in 5 min in vacuum. Ni +surface was reduced by flowing 45 sccm H2 gas at 1000 °C. The gas mixing ratio +of C2H2:H2 was optimized to 2:45 sccm and flown for a minute. After completion +of growth, the gas supply was terminated and the chamber was cooled down to + +room temperature. The detail has been described elsewhere [62-63]. + +4.2.2 Transfer Process of a Graphene + PMMA (e-beam resist, 950 k C4, Microchem) was spin-coated on the +graphene/Cu foil (Ni film) at 1000 rpm for 60 s. To etch away Cu foil (Ni film), +the sample was submerged in a copper etchant (CE-100, Transene) for ∼30 min +116 + +(4 hours for Ni film). After rinsing by deionized water for a few times, +PMMA/graphene layer was fished onto the CR 2032 cell case coated with +lithium-reaction resistive polymer, as shown in Figure 4.5. PMMA was removed +by acetone later after graphene was completely dried and attached onto the cell +case. The transferred sample was then annealed up to 650 °C for 5 h in high +-6 +vacuum (1 x 10 Torr) for further removal of PMMA [63-64]. + +Figure 4.5. Schematic of fabrication process with Cu-grown SLG +or Ni-grown MLG (left panel). Bilayer and trilayer graphene can be +fabricated by transferring monolayer graphene repeatedly. +Photograph of as-prepared monolayer graphene (PMMA on top) +floating in water and CR 2032 coin cell case (right panel). + +4.2.3 Characterization of a Graphene +117 + +Figure 4.6 shows a schematic of the CR 2032 coin cell type battery. The +half cell was then fabricated with a counter/reference electrode of Li foil for the +test of Li diffusion through well defined basal graphene plane (Figure 1f). +Bilayer and trilayer graphene coin cells were also fabricated by transferring +monolayer graphene repeatedly. MLG was synthesized on Ni film to represent +graphene where the edge plane was enriched and the half cell was fabricated +similarly. + + + + + + + +Figure 4.6. Schematic of a coin cell structure with Cu-grown SLG +or Ni-grown MLG. Bilayer and trilayer graphene coin cells were +fabricated by transferring monolayer graphene repeatedly. + +In order to clarify the quality and layer number of graphene, a series of +characterization was done, as shown in Figure 4.7. Figure 4.7a and b are optical +118 + +micrographs of the transferred SLG and MLG on SiO2/Si substrate, respectively. +The SLG grown on Cu foil was rather flat except small portion (~ 4%) of bilayer +and trilayer graphene domains represented by the dark spots (arrows) in the +image (Figure 4.7a). Some wrinkles indicated by the white dashed lines +introduced during transfer process were also visible. Contrary to this, Ni-grown +MLG showed multi-layered flakes represented by the white spots (arrows) in +Figure 4.7b, creating numerous edge planes, as can be visualized in Figure 4.7c. +−1 +Micro-Raman spectra in Figure 4.7d clearly show G-band near 1590 cm , +2 +which is related to optical E2g phonon at the Brillouin zone center indicating sp +hybridization of carbon network, and G’ −1-band around 2694 cm , which is also + +known as 2D-band, an overtone of D-band, in both samples [66]. Large G’/G +−1 +intensity ratio (~ 2) with a small D-band near 1350 cm , which corresponds to +3 +transverse optical phonon near the K point and indicates sp hybridization of +carbon network, was observed in SLG, indicating high quality monolayer +graphene. On the other hand, the intensity ratio of G’/G which is less than one +reveals multi-layered properties of Ni-grown graphene. Defect distribution was +shown in the images of confocal Raman mapping of D/G intensity ratio in +Figure 4.7e and Figure 4.7f. Defects indicated by bright spots were scattered +uniformly over the surface, while grain boundary lines were faintly visible in +SLG. Small flakes were visible in MLG (Figure 4.7f). Although D-band +intensity was barely visible in Figure 4.7d, we clearly observed from D/G band +mapping that some defects were distributed in both samples. Transmittance of +119 + +each graphene layer transferred onto PET substrate was provided in Figure 4.7g. +The transmittance of SLG was 96.5%, slightly smaller than HOPG value of +97.7%, which may be attributed to some portion of multi-layered domains +formation as described in Figure 4.7a [67]. Correspondingly, bilayer and trilayer +graphene samples revealed a systematic reduction in the transmittance. The Ni- +grown MLG showed 63.6% of transmittance, corresponding to 15 layers in +average by assuming 2.3 % absorption per each layer [68]. Optical photographs +were provided to visualize different transmittances with different number of +graphene layers in Figure 4.7h. + +Figure 4.7. Optical micrographs of (a) Cu-grown SLG and (b) Ni- +grown MLG on SiO2/Si substrate. White dashed lines indicate +wrinkles. Some portion of thicker graphene is indicated by arrows. +(c) Schematic of (i) SLG with a well defined basal plane and (ii) +edge plane enriched MLG. (d) Micro-Raman spectra of SLG and +120 + +MLG. Confocal Raman mapping of D/G intensity ratio of (e) SLG +and (f) MLG from squared positions of (a) and (b). The contrast is +normalized to 0.4 to visualize the defect distribution for both +images. (g) Wavelength-dependent transmittance (values are +provided at a wavelength of 550 nm) and (h) optical photographs of +different number of graphene layers on PET substrate. + +4.2.4 Anode Performance of a Graphene +Electrochemical measurements of different layers of Gr samples were +performed with a CR2032 coin cell using VMP3 instrument (BioLogic Science +Instruments). The cell was assembled in a dry room using CR 2032 cell case with +different number of graphene layers and bare foil (SUS 316) as a working +electrode, lithium metal foil as a counter/reference electrode, and a 1 M of LiPF6 +in a 1:1 (v/v) mixture of ethylene carbonate (EC) and diethyl carbonate (DEC) as +an electrolyte. A glassy carbon microfiber was used as a separator. The cells +were charged and discharged galvanostatically between 3.0 and 0.01 V at a + 2constant current of 5 A/cm . The AC impedance spectra were obtained by +applying a sine wave with an amplitude of 10 mV over a frequency range of 100 +kHz to 10 mHz [69]. Figure 4.8a shows cyclic voltammograms (CV) of different +number of graphene layers at a scan rate of 0.1 mV/s from 0.01 V to 3 V. The +bare SUS electrode showed an anodic peak near 1.03 V (SO) and a cathodic peak +around 0.78 V (SR). These redox peaks involve chemical reactions with Li ions +121 + +and possibly electrolytes. Both anodic and cathodic peaks were reduced in the +monolayer graphene electrode. These peaks were reduced consecutively in +bilayer and trilayer graphene electrodes. It is obvious to see that the redox +reaction of the bare SUS electrode was suppressed by the coated graphene layers. +An additional cathodic peak appeared near 0.28 V in bilayer and trilayer samples. +Origin of these peaks could be ascribed to defect-associated lithium adsorption +[41]. At MLG (15 layer graphenes) sample, a sharp cathodic peak near 0.01 V +(LiIn) is identified as lithium intercalation and a rather broad peak near 0.12 V +(LiDe) is related to decomposition of graphitic intercalation compound (GIC) +stages [58]. It is of note that the bare SUS-related peak was nearly compressed in +this case. Both LiDe and LiIn peaks appeared in this case, in good contrast with +FLG samples in which only a clear LiIn peak was observed, suggesting that no +GIC stages were formed in FLGs. The distinct CV behavior of FLGs and MLG +demonstrates that lithium ion intercalation becomes more effective in MLG +induced by the considerable amount of edge planes, as shown in Figure 4.7b. +122 + + Figure 4.8. (a) Cyclic voltammograms of different number of +graphene layers samples at a scan rate of 0.1 mV/s. SUS-related +redox reaction peaks (SO, SR) and lithium +intercalation/deintercalation related peaks (LiIn/LiDe) are marked in +st nd +the figure. (b) 1 and (c) 2 galvanostatic charge/discharge profiles +of different number of graphene layers at a current density of 5 +123 + + 2A/cm . (d) The related layer-dependent capacities. Two regimes of +corrosion-dominant and lithiation-dominant are indicated. + +st +Figure 4.8b shows the 1 galvanostatic charge/discharge profile with a +2 +voltage sweeping range of 0.01 ~ 3 V at a constant current of 5 A/cm . As the +number of graphene layers increased, long tail appeared in the charge curve at +low voltage region. At MLG sample, a plateau appeared in the range of 1.25 - 0.6 +V. In graphitic material, the solid-electrolyte interface (SEI) formation via +electrolyte decomposition takes place in the range of less than 1.0 V [43, 68, 70- +71]. The SEI formation potential varies with types of graphite planes. In general, +SEI forms at higher potential in edge plane than in basal plane [72-74]. +Therefore, we ascribed this plateau in MLG to edge plane-related SEI formation. +nd +In the 2 cycle, the voltage profile shows a gradual change in a wide range of +voltages during charge/discharge, revealing a V-shape curve, i.e., no plateau +region, as shown in Figure 4.8c. This is in good contrast with a U-shape curve in +graphite electrode, where the edge plane intercalation is dominant in the plateau +region of low voltage within 0.1 V [68,75] Capacities of graphene coated +electrodes in Figure 4.8c were consistently smaller than that of the bare electrode, +and furthermore much smaller by about 30 times than the recently reported +graphene battery result [51]. The huge capacity difference comes from the use of +different substrates, as shown in Figure 4.9. +124 + + Figure 4.9. Cyclic voltammograms at a scan rate of 0.1 mV/s (a) +nd +and 2 galvanostatic charge/discharge profiles (b) at a current +2 +density of 5 µA/cm of bare CR2032 coin cell case and foil SUS +316. + +Abundant reaction peaks and larger area of CV curve indicate that more +severe corrosion reaction occurs in the case of foil SUS 316 in Figure 4.9a. The +capacity indicating substrate corrosion intensity obtained from the cell case in +Figure 4.9b shows almost 8 times smaller than that of the SUS 316. This huge +capacity difference can be attributed to the corrosion resistive polymer coated on +2 +the cell case. The capacity of bare foil SUS (~14 µAh/cm ) is still smaller than +2 +the reported value for graphene on Cu substrate (~ 40 µAh/cm ) in Ref. 53, i.e., +Cu reaction is much stronger than SUS 316 reaction. Therefore, the relative +higher capacity can be understood by the effect of Cu substrate.This also implies +125 + +that in spite of graphene layers coated on the electrode with well defined basal +plane, the reaction with electrode did occur inevitably. + +The related layer-dependent capacities are summarized in Figure 4.8d. As +st +the number of graphene layers increased, the 1 charge capacity increased rapidly +up to trilayer graphene electrode and saturated at the MLG electrode. As +described in the schematic of Figure 4.7c, the basal plane is exposed during +lithiation up to three layers, whereas both edge plane and basal plane are present +in 15 layers. Two different types of SEI are formed: i) basal-plane associated SEI +(b-SEI) which is formed up to 3 graphene layers and ii) edge-plane associated +SEI (e-SEI) which is formed in MLG sample. It has been known that b-SEI +formed at lower potential is associated with solvent reduction, while e-SEI + +formed at higher potential is associated with salt ions [72-74, 43]. Since our basal +plane contains abundant defect sites, as observed from Figure 4.7d and e, some +decomposed solvent molecules may further diffuse into the subjacent layers +along with Li ions or in a form of lithium salvation and form additional b-SEI +layer. This is why b-SEI increases as the number of graphene layers increases at +FLG samples. At MLG electrode, both b-SEI and e-SEI are formed. Although e- +SEI increases in this case, b-SEI is reduced compared to FLG electrodes due to +the decrease of effective basal plane area of 15 layers (See Figure 4.7c) and +st +therefore the capacity from SEI formation is saturated in the 1 charge. + +126 + +st + On the other hand, the 1 discharge capacity decreased gradually up to +three layer graphene electrode and increased at 15 layer electrode. Similar trend +nd +was also observed in the 2 charge/discharge profile. The discharge capacities of +nd st +the 2 cycle were not much different from those of the 1 cycle. Large capacity +of the bare SUS electrode was reduced by coating graphene layers up to three +layers. This gradual reduction was also expected from the reduced areas of CV +curves in FLGs (Figure 4.8a). This implies several facts: i) SUS substrate +reaction is systematically suppressed with increasing number of graphene layers +ii) Because lithium ions can diffuse through basal plane of graphene, monolayer +graphene is not sufficient to prohibit substrate reaction. Since the pure basal +plane presumably does not allow Li diffusion, the diffusion may be provoked +through some defect sites that exist on the graphene plane, as observed from the +D/G intensity ratio of confocal Raman mapping in Figure 4.7e. This will be +described later in detail. In FLG samples, If we presume capacity only to be +0.028 μAhcm-2 contributed from intercalation ( / interlayer in the case of LiC6), +the intercalation capacity reaches 0.056 μAh/cm2 at trilayer graphene sample. +μAh/cm2This value is negligible to the capacity (0.73 ) observed in our +experiment. This tells us that even if intercalation of lithium ions was invoked, +the observation was still obscured by the dominant SUS redox reaction. By +noting a linear decrease of the capacity and hence extrapolating to a minimum +capacity, lc to sufficiently prohibit the SUS redox reaction is predicted to be ~ 6 +127 + +layers. As the number of graphene layers increases, the capacity from the SUS +redox reaction decreases, while the capacity reduction will be compensated by +the intercalation capacity between graphene layers. After 6 layers, the capacity +starts increasing by the pure intercalation. We can define substrate corrosion- +dominant region up to 6 layers and lithiation-dominant region after 6 layers, as +visualized in Figure 4.8d. + + + + + + + +Figure 4.10. AC impedance spectra obtained by applying a sine +wave with an amplitude of 10 mV over a frequency range from 100 +kHz to 10 mHz. The inset shows impedance at higher frequency +region to demonstrate charge transfer resistance. +128 + +In order to get the complete image of substrate-related corrosion behavior, +we performed AC impedance measurement to 6 layers of graphene in the full +frequency range of 100 kHz to 10 mHz by applying a sine wave with an +amplitude of 10 mV, as shown in Figure 4.10. All of the impedance spectra +consisted of a depressed semicircle in higher frequency (Figure 4.10 inset) and a +straight line with different angles to the real axis in the lower frequency range. +The depressed semicircle usually can be deconvoluted into two semicircles, +resulting from SEI formation and charge transportation. Since this measurement +was carried out without any charge/discharge test, the formation of the SEI +would be minimized. Therefore, the main contribution of this semicircle could be +attributed to the charge transport. The charge transport resistances of graphene- +coated samples were obviously larger than that of bare SUS coin cell case which +can be indicated by the increased diameters of semicircles. Smaller angles of +graphene electrodes than SUS electrode in the straight line region again +demonstrated difficulty of lithium ion diffusion into graphene electrodes. All of +these proved that graphene can be a good protective layer by limiting the ion +diffusion process at the SUS/graphene interface. Especially, at six layers of +graphene electrode, the charge transport resistance is largest and the angle of +straight line is smallest compared to the electrodes coated with one, two, and +three layers of graphene. This is because further overlapping of larger area +129 + +graphene can further minimize lithium ion diffusion which will provide much +better protective ability compared to less number of graphene layers. + +Figure 4.11. Theoretically estimated capacity based on LiC6 +intercalation. No absorption of Li ions occurs at monolayer +graphene. +The theoretically estimated capacity at 15 layers (or effectively 9 layers, see +Figure 4.11), is 0.2 μAh/cm2. However, this value is still far smaller than the +observed value of 1.30 μAh/cm2. This extra capacity could be ascribed to the +lithium adsorption on defects of the graphene surface, which can be supported by +the widely distributed defects observed from confocal Raman mapping in our +nd +experiments (Figure 4.7f). In the 2 cycle, the discharge capacity was smaller +130 + +than the charge capacity consistently, nearly independent of the thickness of +graphene layers. This difference of 0.35 μAh/cm2 in the charge/discharge +capacity is irreversible capacity and can be ascribed to strongly adsorbed lithium +ions on defects such as vacancies or grain boundaries formed on the graphene +layers. This will be discussed in the theory section later. + +Since defects on graphene basal plane seem to play an important role in +lithium diffusion, a systematic study is required for comprehensive analysis. ++ +Thus, structural defects of graphene were created by Ar bombardment with +different plasma powers (15W, 100W) for one minute. The transferred graphene +-6 +was brought into vacuum chamber with a base pressure of 1 x 10 Torr and then +filled with Ar gas of 100 sccm for a minute, followed by the plasma ignition. ++ +This was repeated layer by layer to obtain Ar plasma-treated FLG samples. +Figure 4.12a shows Raman spectra of Ar plasma-treated monolayer graphene. At +15 W plasma power, D/G intensity ratio was increased to 0.56 from 0.19 in no +plasma-treated pristine graphene, implying structural defect formation in the +-1 +graphene plane. At 100 W, one additional peak near 1620 cm (D’) appeared in +addition to further increase of D-band intensity (D/G intensity ratio is 1.66), +indicating plausible formation of structural defects. No peak splitting of G-band ++ - +into G and G peaks indicates that our process does not involve strain-induced +effect. Figure 4.12b shows CV diagrams for SLG electrode with different +plasma powers at a scan rate of 0.1 mV/s. It is obvious to see that the redox +131 + +reaction peak intensities of SO and SR related peaks were enhanced and the +related peak positions were also shifted after plasma treatment. Those peaks are a +combination of defect-associated adsorption and SUS substrate reaction, as +mentioned in Figure 4.8a. Additional redox reaction due to the generated basal +plane defects by plasma treatment is provoked. Since the protective layer is +monolayer graphene, extra lithium ions adsorbed on defects could easily reach +nd +the SUS substrate, thus increasing the substrate redox reaction. The 2 +galvanostatic charge/discharge capacity of SLG increased accordingly compared +to the pristine graphene sample, as shown in Figure 4.12c. The enhanced +capacity was attributed to the increased adsorption of Li ions on defects and +nd +increased substrate reaction, as mentioned in Figure 4.12b. The 2 charge +capacity kept increasing with increasing plasma power, independent of the +number of graphene layers, as summarized in Figure 4.12d. The substrate redox +reaction was also suppressed, which is identified by the capacity decrease with +increasing number of graphene layers similar to that of pristine graphene samples. + +Smaller capacity was increased in FLG electrodes compared to that of SLG +after plasma treatment and generated different slopes, as shown in Figure 4.12d. +The absolute slope increased from 0.26 to 0.56 with increasing the plasma power. +Extrapolation of these slopes, which determines the critical layer thickness to +prohibit substrate reaction, gave rise to lc of ~ 6 layers independent of the plasma +power, i.e., defect population. This is rather surprising, because creation of more +132 + +defects in the basal plane is expected to increase basal-plane diffusion of Li ions +which will eventually increase substrate redox reaction (See Figure 4.12b, c) and +thereby larger critical layer thickness should be required after strong plasma +treatment. In order to explain this contradictory phenomenon, a schematic of Li +diffusion through defects in the basal plane is provided in Figure 4.12e. In the +case of SLG, Li ion diffusion is allowed through defect sites and no lateral +diffusion limitation is expected, since the graphene layer is fully surrounded by +Li ions in electrolyte. Therefore, higher defect population will enhance Li ion +adsorption and also substrate reaction. In the case of FLGs where large area basal +plane is dominant, graphene layers are overlapped with each other so that Li ions +will diffuse through defects perpendicular to the plane of top layer first and +diffuse along the plane of subjacent graphene layer until they meet another defect +site. Since these Li ions may accumulate near the defect sites generated by Ar +plasma, Li diffusion along the plane direction will be limited by the steric +hindrance from aggregated Li atoms, which is different from the SLG case. +Therefore further Li diffusion through graphene basal planes in FLGs is +constrained severely by the lateral diffusion at higher defect density. Thus, when +FLGs are used as a protective layer, the defects-related lithium adsorption on +subjacent graphene layers and actual lithium ion reaction with substrate are +suppressed, which is again consistent with the reduction of reaction with +substrate are suppressed, which is again consistent with the reduction of the +peaks in CV diagram. As a consequence of these phenomena, the critical layer +133 + +thickness gives rise to the same value, independent of the defect population. It +will be worth mentioning the possibility of forming oxygen-related functional +groups on defect sites. Li ions can be also adsorbed on such sites and thus our +argument of lateral diffusion suppression by the steric hindrance is still valid. + + + + +134 + +Figure 4.12. (a) Raman spectra, (b) cyclic voltammograms at a scan +rate of 0.1 mV/s, and (c) 2nd galvanostatic charge/discharge +2 +profiles at a current density of 5 A/cm for monolayer graphene +treated by Ar plasma with different plasma powers (15 W and 100 +nd +W). (d) Capacity of 2 charge as a functional of number of +graphene layers under different Ar plasma powers. Absolute slopes +according to different plasma powers and critical layer thickness (lc) +are indicated in the figure. (e) Schematics of proposed Li diffusion +mechanism through defects on the basal plane with different defect +population. Broad down arrows indicate Li ion diffusion through +defect sites of basal plane. Red glows represent steric hindrance for +Li ion diffusion formed by the accumulated Li ions or functional +groups. The inset in the right indicates the relative magnitude of +diffusion coefficient. (f) Relationship of D/G ratio with the +extracted slope from (d). + +It is intriguing to see the relationship between D/G intensity ratio from +Raman spectra and the slope extracted from charge/discharge profiles, as shown +in Figure 4.12f. The slope which indicates Li diffusion through graphene layers +is correlated to the population of defects in the graphene plane. The larger slope +implies the slower diffusion rate and vice versa. Li ion diffusion is limited by the +Li aggregates adsorbed on the increased defect sites described in the schematic +135 + +Figure 4.12e. Thus, information of Li diffusion obtained from electrochemical +test could be used as a metric for evaluating the graphene crystallinity, an +important material parameter of graphene. + +In order to understand what type of defects allows Li ion diffusion through +basal plane of graphene, we conducted density functional theory calculations for +various defects: ideal hexagonal site (H site), Stone-Wales defect (SW), +monovacancy (V1), and divacancy (V2). The density functional theory +calculations were performed within generalized gradient approximation as +implemented in DMol3 code. All electron Kohn-Sham wave functions were +expanded in a local atomic orbital basis set with each basis function defined +numerically on an atomic centered spherical mesh. A double numeric polarized +basis sets (DNP) were used for all elements. The dangling bonds of graphene +edge were saturated by hydrogen atoms and the atomic cluster structure which +consists of 120 carbon atoms and 48 hydrogen atoms were relaxed fully until the +-4 +force on each atom is less than 10 eV/Å and the total energy change is less than +-5 -6 +5×10 eV. The damped atom-pairwise dispersion corrections of the form C6R +were also considered for calculations. Li adsorption energy was calculated by +Ead(Li) = Etot(Li+carbon) - Etot(Li)- Etot(carbon), where Etot(Li) is the self energy +of lithium atom and Etot(carbon) is the total energy of carbon system. Various +local charges were also calculated using Mulliken, Hirshfeld, and electrostatic +potential (ESP). +136 + + + + +137 + +Figure 4.13. Side and top views of atomic configurations (top +panel), isosurface images of electrostatic potential (second panel), +bond lengths and local charge distributions at the barrier states +(third panel), and the diffusion barrier profiles of Li (bottom panel) +through (a) graphene hexagonal site (H site), (b) Stone-Wales (SW) +defect (c) monovacancy (V1), and (d) divacancy (V2). Isovalue for +3 +rendering isosurfaces is 0.25 e/Å . The insets in the third panel +show isosurface image of electrostatic potential for each +corresponding structure without Li ion. Bond lengths (yellow color) +and electrostatic potential charges (white color) are in units of Å +and electrons, respectively. + +Li atom adsorbs on the H site with a bond length of 2.35 Å above the +graphene plane and with an adsorption energy of -1.69 eV, as shown in the upper +panel of Figure 4.13a and Table 4.1. Li ESP charge at H site is partially depleted +to 0.62 e. The ESP charge of Li atom at barrier state is 0.28 e, much less +compared to that at the binding site. This charge difference between adsorption +and barrier state is an important variable in determining the Coulomb interaction +energy. As the Li approaches to the barrier site, the available space for Li is +narrow with a short separation distance of 1.52 Å, invoking severe charge +overlapping between Li and adjacent carbon atoms, as can be seen in the +electrostatic potential contour in the second panel of Figure 4.13a. This increases +138 + +repulsive forces, giving rise to large diffusion barrier height of 10.2 eV, similar to +the previous report (Table 4.1) validating our approaches. Similar situation takes +place in the SW defect which is abundant in the graphene grain boundary. The Li +adsorption energy near the heptagon is -1.94 eV, slightly stronger than that of H +site. Although the charge overlapping is still severe, a longer separation distance +of 1.60 Å and also much less charge difference between adsorption and barrier +state (0.04 e) forms a relatively smaller activation barrier height of 6.35 eV than +that of H site, as shown in Figure 4.13b. In the case of V1, Li adsorbs at the +vacancy site with an adsorption energy of -3.12 eV, keeping closer distance (2.03 +Å), as shown in the top panel of Figure 4.13c. The excess charge difference of Li +atom between adsorption and barrier site is 0.18 e and the closest separation +distance at the barrier site is 1.36 Å. Charges are distributed not only on the Li +and carbon sites but also between them, implying both covalent bonding and +ionic bonding characters due to charge depletion from Li atom. This produces a +large diffusion barrier height of 8.86 eV. On the other hand, V2 provides a rather +large open space with an adsorption energy of -2.36 eV near the middle of the +two dimers (top panel of Figure 4.13d) such that a large separation distance of +2.90 Å is maintained. This gives minimizes electrostatic charge overlapping and +a large bond length of 1.83 Å at the barrier state, i.e., steric hindrance is +minimized, as shown in the second and third panels in Figure 4.13d. The charge +difference between the adsorption and the barrier states is 0.04 e. All of these +factors induced a smallest diffusion barrier height (2.36 eV) among the defects +139 + +we studied. This barrier height can be overcome under the typical charging +conditions of the battery. + +4.3 Summary of Chapter Four +We have studied lithium diffusion pathways with two types of graphene +samples prepared by CVD; i) well-defined basal plane graphene grown on Cu +foil and ii) edge plane-enriched graphene layers grown on Ni film. We have +discovered that electrochemical reaction of electrode (substrate/graphene) not +only is related to the number of graphene layers but also relies on the defect sites +on the basal plane of graphene. The experimental and calculated results related to +the specific type of defects such as divacancies and higher order defects that can +assist lithium ion diffusion through basal plane could help us in designing high +capacity and highly conductive corrosion-free electrode for lithium ion battery. It +would be reasonable to expect that substrate protective nature of few-layer +graphenes could be the basis of further investigation of preparing original +substrate which remains unaltered properties and has longer lifetime under severe +electrochemical corrosion conditions for battery. 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B 2009, 79, 205433. + +146 + +SUMMARY + +Carbon-Based Nanomaterials as an Anode for Lithium Ion +Battery +The improvement of the capacity of raw CNF mat has been realized in the +current research through electrochemical deposition of Si. The Si/CNF mat +prevents the use of metal substrate, binder, and conducting polymers. However, +several drawbacks of the current free-standing Si/CNF mat structure need to be +mentioned: (i) The as-fabricated CNF mat exhibited a rather lower conductivity +compared to that of CNTs which could be the reason for the original low capacity +(< 300 mAh/g) of raw CNF mat. (ii) The flexibly of the as-fabricated CNF mat +reduces after high temperature annealing which hinders the further investigation +for flexible anode applications. These two factors can be further improved by the +incorporation of CNTs, graphene flakes or other more advanced materials. (iii) +Although the interfacial binding strength of Si and CNF was improved by the +formation of Si-C bond through annealing as discussed in the context, structural +pulverization of deposited Si film induced by the large volume expansion during +charge/discharge was still observed in the current structure. Therefore, increasing +the Si anchoring sites on the CNF mat by the surface functionalization and +enhancing the degree of entanglement through the introduction of CNTs could +provide better structure stability. The optimization to improve composite +147 + +structures for capacity, charge transfer, and cycle life is further required for +industry applications. + +On the other hand, in order to clarify the Li diffusion pathways through +graphene plane and the role of defects in Li diffusion to reveal the mystery of Li- +C system, graphene was used as a media for the study of this fundamental +science of diffusion in this work. We found that the electrochemical performance +of few-layer graphenes which are overlapped up to three layers of single layer +graphene is strongly affected by the substrate reaction. Experimental results +showed that 6 layers of basal plane-enriched large area graphene were needed to +provide sufficient substrate protection from severe electrolyte attack. Li diffusion +across the pure basal plane of graphene is strongly limited and nevertheless non- +negligible diffusion is still allowed, suggesting possible diffusion through defects +that might be formed on the graphene plane. Combing the experimental results +and density functional theory calculations, we found that divacancies and higher +order defects can be shortcuts for lithium ion diffusion with respect to the +graphene basal plane. Further exploration of high energy density and long +lifetime anode by fabricating high capacity materials on graphene could be an +interesting research direction in the future. + +Key Words: nanocarbon materials, lithium ion battery, carbon nanofiber, silicon, + Graphene +148 + +CURRICULUM VITAE + +FEI YAO + +LPICM-École Polytechnique, CNRS (UMR 7647) +Laboratoire de Physique des Interfaces et Couches Minces +Route de Saclay; 91128 PALAISEAU Cedex, France + +IBS Center for Integrated Nanostructure Physics, Institute for Basic Science, Department of +Energy Science, Sungkyunkwan University +Room 85689, Corporate Collaboration Center, 300 Cheoncheon-dong, Jangan-gu, Suwon, +Gyeonggi-do 440-746, Korea · 82-31-299-6509 · +Mobile: +82-10-2757-1299 +E-mail: apaperyao@gmail.com, yaofei@skku.edu + + +Education +______________________________________________________ + + +2010.08 ~ P h .D . candidate +LPICM-École Polytechnique +Laboratoire de Physique des Interfaces et Couches Minces, +Route de Saclay; 91128 PALAISEAU Cedex , France; + + +IBS Center for Integrated Nanostructure Physics, Institute for +Basic Science, Department of Energy Science, +Sungkyunkwan University, +Korea. +Advisor: Professor Young Hee Lee + + Dr. Costel-Sorin Cojocaru + +2008.03 ~ 2010.08 M .S +Sungkyunkwan Advanced Institute of Nanotechnology + Sungkyunkwan University +Korea. + Advisor: Professor Young Hee Lee +149 + +2003.09~2007.09 B . S +Department of Electronic Information Engineering + Shandong Normal University +China. + + + +RESEARCH EXPERIENCE +_____________________________________________________________________ + +1. CNT gas sensor fabrication +- Enhancement of sensitivity to NO2, SO2, NH3 gases etc. +- Selectivity among NO2, SO2, NH3 gases etc. +2. Dispersion of SWCNTs / MWCNTs +- In water with surfactant (SDS, NaDDBS etc) +- In organic solution (NMP, DCE etc) +3. Synthesis of graphene and carbon nanotubes by chemical vapor deposition +- Large-area few-layer graphene synthesis on metal substrates (Ni, Cu), etching & +transfer onto desired substrates (SiO2, PET etc.) +- Large-area monolayer graphene growth on Cu foil, etching & transfer processes +- Synthesis of SWCNTs network and MWCNTs by chemical vapor deposition +4. Doping of graphene for electrode applications + - P-type doping by metal-salts and acid solutions for enhancement of conductivity +for flexible transparent conducting film applications + - Multiple-layered graphene film preparation and investigation of conductivity +enhancement by Layer-by-Layer (LBL) doping +5. Carbon nanofiber fabrication using electrospinning method for energy application +- Carbon nanofibers with CNT composite +- Carbon nanofiber with Si composite +6. Si-based material synthesis and energy storage applications +- Si thin film deposition by PECVD for energy application (lithium ion battery, +solar cell) +- Si nanoparticle deposition by electrochemical method for battery application. +7. Fuel cell application with carbon-based materials + + + + +150 + +EQUIPMENTS +_____________________________________________________________________ + +- Plasma enhanced CVD, Thermal CVD, Atomosphere pressure CVD +- E-beam and thermal evaporator +- Magnetron sputter +- Micro Raman and confocal Raman spectroscopy +- High resolution scanning electron microscope (HR-SEM) +- Atomic force microscope (AFM) +- UV-NIR absorption spectroscopy +- Potentiostat /Galvanostat equipment +- Spray equipment +- Electrospinning equipment + + + +PUBLICATIONS (SCI journal) +━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ + +12. Fethullah Gunes ,⃰ Fei Yao ,⃰ Hongyan Yue, Hung T. Nguyen, Bing Li, and Young +Hee Lee, 'A direct synthesis of Si-nanowires on a 3D porous graphene as high +performance anode material for Li-ion batteries', 2013, submitted. + +11. M. Jin, Fei Yao, J. Chang, and Y. H. Lee, 'Graphene sheets as anode materials with +super high rate and large capacity for Lithium ion batteries' 2013, in preparation. + +10. Jian Chang, Meihua Jin, Fei Yao, and Young Hee Lee, 'Asymmetric Supercapacitors +Based on Graphene/MnO2 Nanospheres and Graphene/MoO3 Nanosheets with High +Energy Density ' 2013, Adv. Func. Mater., accepted. + +9. Seung Mi Lee, Fei Yao, and Young Hee Lee, 'Lithium ion diffusion through basal +plane of graphene: A density functional theory study' 2013, J. Nanoscience and +nanotechnology, submitted. + +8. Fei Yao, Bing Li., Fethullah Gunes, Costel Sorin Cojocaru, and Lee, Y. H. 'Silicon +and carbon nanofiber composite as an anode material for lithium ion battery' 2013, +Nanoscale, submitted. + +151 + + +7. Thuc Hue Ly, Dinh Loc Duong,Quang Huy Ta, Fei Yao, Quoc An Vu, Hye Yun Jeong, +Sang Hoon Chae, and Young Hee Lee, 'Nondestructive Characterization of Graphene +Defects' 2013, Adv. Func. Mater, accepted. + +6. Fei Yao, Fethullah Gunes, Huy Quang Ta, Seung Mi Lee, Seung Jin Chae, Kyeu +Yoon Sheem, Costel Sorin Cojocaru, Si Shen Xie, and Young Hee Lee, 'Diffusion +Mechanism of Lithium Ion through Basal Plane of Layered Graphene', J. Am. Chem. +Soc., 134(20), 8646-8654, (May 23, 2012). + +5. Hung T. Nguyen, Fei Yao, Mihai R. Zamfir, Chandan Biswas, Kang Pyo So, Young +Hee Lee, Seong Min Kim, Seung Nam Cha, Jong Min Kim, Didier Pribat, 'Highly +Interconnected Si Nanowires for Improved Stability Li-Ion Battery Anodes', Advanced +Energy Materials ,1(6), 1154–1161, (Nov, 2011). + +4. Fethullah Güneş, Gang Hee Han, Hyeon-Jin Shin, Si Young Lee, Meihua Jin, Dinh +Loc Duong, Seung Jin Chae, Eun Sung Kim, Fei Yao, Anass Benayad, Jae-Young Choi +and Young Hee Lee, ‘UV Light-Assisted Oxidative Sp3-Hybridization of Graphene’, +NANO, 6 (5),409–418, (May 26, 2011). + +3. Fei Yao, Dinh Loc Duong, Seong Chu Lim, Seung Bum Yang, Ha Ryong Hwang, +Woo Jong Yu, Il Ha Lee, Fethullah Gunes, and Young Hee Lee, 'Humidity-assisted +selective reactivity between NO2 and SO2 gas on carbon nanotubes', J. Mat. Chem., +21(12), 4502-4508, (Mar. 28, 2011). + +2.Il Ha Lee, Un Jeong Kim, Hyung Bin Son, Seon-Mi Yoon, Fei Yao, Woo Jong Yu, +Dinh Loc Duong, Jae-Young Choi, Jong Min Kim, Eun Hong Lee and Young Hee Lee, +'Hygroscopic Effects on AuCl3-Doped Carbon Nanotubes', Journal of Physical +Chemistry C, 114(26), 11618-11622 ,(Jun. 10. 2010). + +1. Fei Yao, Seong Chu Lim, Woo Jong Yu, Il Ha Lee, Fethullah Gunes, Ha Ryong +Hwang, Seung Bum Yang, Kang Pyo So, Gang Hee Han, and Young Hee Lee, 'AC +Response to Gas Exposure in Vertically Aligned Multiwalled Carbon Nanotube +Electrode', J. Phys. Chem. C, 114(8), 3659-3663, (Feb. 5, 2010). + + +PATENTS (Korea) +━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ + +152 + +Large Area Graphene as a Protecting Layer for Metal Corrosion, submitted. +Presentations +━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ +6. Fei Yao, Bing Li, Kangpyo So, Jian Chang, Vu Quoc An, Didier Priba1, Costel Sorin +Cojocaru, Hongyan Yue, Sishen Xie, Young Hee Lee1, 'Silicon-Coated Carbon +Nanofiber Mat for Anode of Lithium Ion Battery', Imaginenano 2013, Bilbao, Spain, +April 23~26, 2013, oral. + +5. Fei Yao, Fethullah Gunes, Ta Quang Huy, Seung Mi Lee, Seung Jin Chae, Kyeu Yoon +Shem, Costel Sorin Cojocaru, Si Shen Xie, Young Hee Lee, 'Lithium Ion Diffusion +Through Basal Plane of Layered Graphene Synthesized by Chemical Vapor Deposition', +16th International Meeting on Lithium Batteries (New Era for Smart Energy Storage) +(IMLB 2012), ICC Jeju, Korea, June 17~22, 2012, p.104. + +4. Fei Yao, Hung Tran Nguyen, Kang Pyo So, Chandan Biswas, Giduk Kwon, Si Thanh +Pham, Zamfir Mihai Robert, Young Hee Lee and Didier Pribat, 'Carbon Nanofiber/Si +Nanowire As an Anodematerial for Li-Ion Battery', 1st Korean-French Seminar On +Nanomaterials for Energy, Sungkyunkwan University, Mar. 6-8,2011, p.50 + +3. Fei Yao, Hung Tran Nguyen, Kang Pyo So, Chandan Biswas, Giduk Kwon, Si Thanh +Pham, Zamfir Mihai Robert, Young Hee Lee, Dider Pribat, 'Carbon Nanofiber/Si +Nanowire as An Anode Material for Li-Ion Battery', A3 Symposium on Emerging +Materials: Nanocarbons and Nanowires for Energy, Core-Riviera Hotel, Jeonju, Nov. 7- +11. 2010, p.61 + +2. Fei Yao, Duong Dinh Loc, Seong Chu Lim, Seung Bum Yang, Ha Ryong Hwang, +Woo Jong Yu, Fethullah Gunes, Young Hee Lee, 'Humidity-assisted selective reactivity +between NO2 and SO2 gas on carbon nanotubes', NT10(11th International Conference +on the Science and Application of Nanotubes 2010), Hilton Bonaventure Montreal, +Quebec, Canada, Jun 27-Jul 2. 2010, p.96 + +1. Fei Yao, Seong Chu Lim, Woo Joong Yu, Fethullah Gunes and Young Hee Lee +'Capacitive Gas Sensor of Vertically Aligned Carbon Nanotubes', International Green +Energy Nanocarbon Conference 2009,Jeollabuk-do provincial office, Jeonju, Korea, +Nov. 3~6. 2009, p.155 + + +153 + + 154 + diff --git a/examples/theses/HalThesis1.pdf b/examples/theses/HalThesis1.pdf new file mode 100644 index 00000000..d8672ac7 Binary files /dev/null and b/examples/theses/HalThesis1.pdf differ diff --git a/examples/theses/HalThesis1/fulltext.pdf b/examples/theses/HalThesis1/fulltext.pdf new file mode 100644 index 00000000..d8672ac7 Binary files /dev/null and b/examples/theses/HalThesis1/fulltext.pdf differ diff --git a/examples/theses/HalThesis2.pdf b/examples/theses/HalThesis2.pdf new file mode 100644 index 00000000..a052067a Binary files /dev/null and b/examples/theses/HalThesis2.pdf differ diff --git a/examples/theses/HalThesis2/fulltext.pdf b/examples/theses/HalThesis2/fulltext.pdf new file mode 100644 index 00000000..a052067a Binary files /dev/null and b/examples/theses/HalThesis2/fulltext.pdf differ diff --git a/examples/theses/HalThesis2/fulltext.pdf.txt b/examples/theses/HalThesis2/fulltext.pdf.txt new file mode 100644 index 00000000..cad8e6ab --- /dev/null +++ b/examples/theses/HalThesis2/fulltext.pdf.txt @@ -0,0 +1,3548 @@ +Development of higher efficiency photocathodes for gas +filleddetectors +Guillaume Potdevin +To cite this version: +Guillaume Potdevin. Development of higher efficiency photocathodes for gas filleddetectors. +Physics. Universite´ Joseph-Fourier - Grenoble I, 2008. English. +HAL Id: tel-00275299 +https://tel.archives-ouvertes.fr/tel-00275299 +Submitted on 23 Apr 2008 +HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est +archive for the deposit and dissemination of sci- destine´e au de´poˆt et a` la diffusion de documents +entific research documents, whether they are pub- scientifiques de niveau recherche, publie´s ou non, +lished or not. The documents may come from e´manant des e´tablissements d’enseignement et de +teaching and research institutions in France or recherche franc¸ais ou e´trangers, des laboratoires +abroad, or from public or private research centers. publics ou prive´s. +THE`SE +pour obtenir le titre de +Docteur de l’Universite´ Joseph Fourier +Discipline : +Physique +pre´sente´e et soutenue publiquement par +Guillaume POTDEVIN +Sujet de the`se : +Development of higher efficiency photocathodes for gas filled +detectors +Soutenance le 29 Janvier 2008 devant le jury compose´ de : +Franc¸ois Montanet LPSC, CNRS, Grenoble Repre´sentant de l’universite´ +Imad Laktineh IPNL, CNRS, Lyon Rapporteur +Ralf Menk Elettra, Trieste Rapporteur +Johann Collot LPSC, CNRS, Grenoble Directeur Acade´mique +Menhard Kocsis ESRF, Grenoble Superviseur a` l’ESRF +2 +Contents +1 Introduction 1 +1.1 Why Detectors ? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 +1.1.1 A small history of X-ray sources . . . . . . . . . . . . . . . . . . . . . . . . . . 2 +1.1.2 A new Science is born: Photon Science . . . . . . . . . . . . . . . . . . . . . . . 4 +1.1.3 A typical experimental setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 +1.1.4 The place of the detector in the chain . . . . . . . . . . . . . . . . . . . . . . . 9 +1.2 Detectors in the hard X-ray energy range . . . . . . . . . . . . . . . . . . . . . . . . . 10 +1.2.1 What are the detector main characteristics? . . . . . . . . . . . . . . . . . . . . 10 +1.2.2 The Detective Quantum Efficiency . . . . . . . . . . . . . . . . . . . . . . . . . 11 +1.2.2.1 The DQE dependence on the Quantum Efficiency. . . . . . . . . . . . 12 +1.2.2.2 The dependence of the DQE on the spatial resolution . . . . . . . . . 13 +1.2.3 The mode of operation, speed and behavior of one detector at large intensities 15 +1.3 Spectroscopy detectors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 +1.4 Imaging detectors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 +1.4.1 current mature technologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 +1.4.2 technologies under developments . . . . . . . . . . . . . . . . . . . . . . . . . . 23 +1.4.2.1 Spectroscopy Detectors under development . . . . . . . . . . . . . . . 23 +1.4.2.2 Imaging Detectors under development . . . . . . . . . . . . . . . . . . 23 +2 The basics of gas-filled detectors 29 +2.1 historical background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 +2.2 Principle of gas-filled detectors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 +2.2.1 The X-ray absorption in the gas . . . . . . . . . . . . . . . . . . . . . . . . . . 30 +2.2.2 The amplification and the modes of operation of gas-filled detectors . . . . . . 31 +2.2.3 The benefits of gas-filled detectors . . . . . . . . . . . . . . . . . . . . . . . . . 33 +2.2.4 The limitations of gas-filled detectors . . . . . . . . . . . . . . . . . . . . . . . . 33 +2.3 Recent Evolutions of gas-filled detectors . . . . . . . . . . . . . . . . . . . . . . . . . . 35 +ii CONTENTS +2.4 Gas amplification compared to Microchannel plates . . . . . . . . . . . . . . . . . . . . 37 +2.5 A promising approach to overcome Gas-filled detectors limitations . . . . . . . . . . . 38 +3 Photocathode for gas-filled detectors 41 +3.1 Basics of Photocathodes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 +3.2 Improved Models of Photocathodes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 +3.3 Major technologies of photocathodes currently available . . . . . . . . . . . . . . . . . 45 +3.3.1 Metallic Photocathode . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 +3.3.2 Semiconducting Photocathode . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 +3.3.3 Organic Photocathode . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 +3.3.4 CsI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 +3.3.5 Conclusions on available technologies of Photocathodes and the issues related +to their use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 +4 The Simulations by Monte Carlo Method 55 +4.1 A first approach to Monte Carlo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55 +4.1.1 History . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55 +4.1.2 Description of the Monte Carlo Method . . . . . . . . . . . . . . . . . . . . . . 56 +4.1.3 The Monte Carlo Method in Particle Transport . . . . . . . . . . . . . . . . . . 57 +4.2 The Geant4 toolkit for particle transport into matter . . . . . . . . . . . . . . . . . . . 57 +4.2.1 The way Geant4 computes particle propagation . . . . . . . . . . . . . . . . . . 58 +4.2.1.1 The tracking of the particles . . . . . . . . . . . . . . . . . . . . . . . 58 +4.2.1.2 The physical interactions in Geant4 . . . . . . . . . . . . . . . . . . . 61 +4.2.1.3 Analysis and Representation tools . . . . . . . . . . . . . . . . . . . . 62 +4.2.2 The simulation tool developed . . . . . . . . . . . . . . . . . . . . . . . . . . . 62 +4.2.2.1 Description and Functionalities . . . . . . . . . . . . . . . . . . . . . . 62 +4.2.2.2 The test of the code, comparison with experimental values . . . . . . 64 +4.2.2.3 The limits of the Monte Carlo Method . . . . . . . . . . . . . . . . . 66 +4.3 The simulation performed . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 +4.3.1 The simulations performed . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 +4.3.2 Use of the simulations for thickness optimization . . . . . . . . . . . . . . . . . 70 +4.3.3 Simulation of the impact of structures on the photocathode . . . . . . . . . . . 71 +4.4 Conclusion on this part of the work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 +5 Experimental Setup and Sample Preparation 77 +5.1 Design of the measurement setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77 +5.1.1 A few general considerations . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77 +5.1.2 The chamber and the ammeter . . . . . . . . . . . . . . . . . . . . . . . . . . . 78 +5.1.2.1 The Photocathode holder, the electrical shielding . . . . . . . . . . . 78 +5.1.2.2 The Chamber . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 +5.1.2.3 The Keithley 6430 ammeter . . . . . . . . . . . . . . . . . . . . . . . 81 +CONTENTS iii +5.1.3 Results of calibration and test of the chamber . . . . . . . . . . . . . . . . . . . 81 +5.1.4 Conclusion concerning the setup . . . . . . . . . . . . . . . . . . . . . . . . . . 83 +6 The different concepts to make a photocathode 87 +6.1 Indirect conversion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87 +6.1.1 Photocathodes in visible and UV . . . . . . . . . . . . . . . . . . . . . . . . . . 88 +6.1.2 Scintillation materials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89 +6.1.3 Possible combinations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90 +6.1.4 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91 +6.2 Direct conversion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92 +6.2.1 Modify the geometry to increase the yield of one material . . . . . . . . . . . . 92 +6.2.1.1 Porous Photocathodes . . . . . . . . . . . . . . . . . . . . . . . . . . . 93 +6.2.1.2 Regular Structures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93 +6.2.2 Field emission . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97 +6.2.3 A new material: CsI3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98 +7 Experimental tests and discussion of the results 101 +7.1 Modify the geometry to increase the yield of a material . . . . . . . . . . . . . . . . . 101 +7.1.1 Analysis of the microstructures characteristics . . . . . . . . . . . . . . . . . . . 102 +7.1.2 Efficiency measurements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103 +7.2 Field Emission . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103 +7.2.1 Analysis of the microstructure characteristics . . . . . . . . . . . . . . . . . . . 103 +7.2.2 Efficiency Measurements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104 +7.3 CsI3 as a new photocathodes material . . . . . . . . . . . . . . . . . . . . . . . . . . . 104 +7.3.0.1 Physical and chemical characteristics . . . . . . . . . . . . . . . . . . 104 +7.3.1 The CsI3 samples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105 +7.3.1.1 Preparation of the different samples . . . . . . . . . . . . . . . . . . . 106 +7.3.1.2 Analysis of the microstructures of the samples and their evolution . . 107 +7.3.2 CsI3 quantum efficiency and comparison with CsI. . . . . . . . . . . . . . . . . 110 +7.3.2.1 The quantum efficiency of CsI and its evolution in air . . . . . . . . . 110 +7.3.2.2 The quantum efficiency of CsI3, its evolution in air and comparison +with CsI. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112 +7.3.3 Analysis of the results obtained with CsI3 . . . . . . . . . . . . . . . . . . . . . 118 +7.3.4 Conclusion on the use of CsI3 as a photocathode . . . . . . . . . . . . . . . . . 120 +8 Conclusion 123 +A Detector characteristics 125 +A.1 Position resolution in the case of gas-filled detectors . . . . . . . . . . . . . . . . . . . 125 +A.2 Energy Resolution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125 +A.3 Space Charging in gas-filled detectors . . . . . . . . . . . . . . . . . . . . . . . . . . . 126 +iv CONTENTS +Annexes 125 +B Monte Carlo Application Examples 129 +B.1 Simple Examples of statistical sampling methods . . . . . . . . . . . . . . . . . . . . . 129 +B.1.1 Calculus of an integral . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129 +B.1.2 An historical example: Buffon’s needles . . . . . . . . . . . . . . . . . . . . . . 130 +Chapter 1 +Introduction +1.1 Why Detectors ? +Probably the first human being already was driven by a strong sense of curiosity, as it is some of the +deepest law of human nature. This force has pushed mankind to develop more and more powerful +investigation tools to help him understand its environment. Outstanding examples in the past are the +telescope used by Galile´e to make the first observation for Jupiter’s satellites, or Van Leewenhoek ’s +microscope, which enabled the discovery of microscopic animals... In this frame, X-rays are nothing +but an extension to humans’ capabilities to explore the world, and X-ray detectors are their eyes, +adapted for such investigations. +This work is intended to contribute to the development of modern tools for matter studies. It is part +of a more global program to provide modern light sources with reliable and efficient detectors, able +to answer the growing needs of the scientific community in this domain. +2 Introduction +1.1.1 A small history of X-ray sources +Figure 1.1 : Conrad Wilhelm RO¨NTGEN (March +27, 1845 - February 10, 1923), German physicist. Figure 1.2 : Brilliance of various light sources. +The brilliance enables to measure the quality of a +light source. +Since their first identification by Wilhelm Ro¨ntgen in the late 18th century (for which he was awarded +the first Nobel Prize for Physics in 1901), X-rays have been at the origins of several revolutions in +numerous fields of research. +This broadening of the usefulness of X-rays is mainly due to the fantastic development of X-ray +sources. The following lines give a short history of those sources. +Discharge tubes or Crookes tube +William Crookes, an English physicist, is the inventor of the first artificial source of X-rays: while he +was studying the effects of electric currents in gas at low pressure, he used glass vacuum cylinders, +containing electrodes for discharges of a high voltage electric current1. He noticed that unexposed +photographic plates were shadowed when approached from those tubes, even though he did not +identify this to be caused by a particular sort of radiation. +Fernando Sanford later bettered this principle of emissions and published in 1893 in the Journal +Physical Review an article entitledObserved tubes with energy rays extending from a negative electrode. +It is interesting to note that even after deeper studies by Heinrich Hertz of those specific radiations, +they were not identified as a new sort of radiation. Only the work of Wilhelm Ro¨ntgen with Vacuum +tubes enabled to actually identify X-rays as a new kind of ray. +Those tubes are actually the ancestors of modern X-ray tubes, which are the result of a technological +1this sort of tube had already been used by the physicist Johann Hittorf who observed tubes with energy rays +extending from a negative electrode. +1.1 Why Detectors ? 3 +improvement of the original Crookes tube. +Synchrotron radiation sources +Figure 1.3 : The General electric particle accelerator, at the origin of the discovery of synchrotron radiations. +The arrow indicates the trace of the synchrotron radiation beam on the picture. It is the first observation of +synchrotron radiations. +The history of synchrotron radiations is closely related to that of particle physics. First considered +as a nuisance sapping the energy of the particles, it was later recognized as a powerful tool to study +matter. One usually distinguishes three major steps on the way to modern light sources: +First Generation Sources were mainly synchrotrons built for the study of particle physics (High +Energy Physics HEP), which were refurbished as light sources, as the frontiers of HEP were +pushed forward. This way, it is often said that the use of those synchrotrons as light sources +was a sort of parasitic operation of the synchrotrons. A big step occurred in the 50’s as +the first electron storage rings were built, providing a much more stable, fixed energy, and +continuous beam of particles (and thus photon beam). Those machines have been the models +for all synchrotron light sources until now. +Second Generation Sources were the first machines dedicated for light emission. They were the +first machines able to operate a large number of beamlines, with optimized emittance parameters +(quality of the beam), stable energy and beam position. The development of those machines +4 Introduction +was associated to important developments in optics and gave birth to new types of experiments +such as EXAFS or large protein crystallography. +Third Generation Sources are storage rings optimized to have numerous long straight sections, +in which undulators and wrigglers can take place, so providing a much higher brightness and +flux of photon beams. This is the birth of large facilities (800 to 1400m) offering several tens +of beamlines, typically welcoming several thousands of users every year. +The future of light sources will probably see a parallel development of the third generation light +sources, which keep bettering in terms of performance, and the birth of the fourth generation sources, +also called Free electron lasers (FEL). FEL will be able to offer peak of brightness of several +order of magnitude higher than third generation sources, as well as pulses as short as 100 fs and +highly coherent. FELs will be constituted of very long undulators in high-energy linear accelerators. +Those devices will offer a new range of possibility of investigation of matter, but will not directly +compete with third generation sources as they will not be able to offer the many beamlines that +storage rings have. +Indeed, several projects of third and fourth generation sources have been launched recently or are +even in their commissioning phase (the synchrotrons Diamond and Soleil in Oxford and Paris, the +European X-FEL in Hamburg...). Yet it is unlikely that all those sources will be able to answer the +growing demand for high brightness sources. +1.1.2 A new Science is born: Photon Science +Figure 1.4 : The ESRF seen from top. The ESRF is one the modern lightsources able to provide high +brightness photon beams.©P.Ginter/ESRF. +Photon Sciences encompass all the techniques using high brilliance photon beams, such as those pro- +duced in Synchrotron Radiation Facilities, and Free Electron Lasers. Those sophisticated and perma- +nently evolving machines enable the production of highly intense beams of photons. The brilliance +(which measures the quality of the beam) is now more than 10 orders of magnitudes higher than that +of conventional sources (see Figure 1.2). +1.1 Why Detectors ? 5 +Among those new generation sources, a majority of them are dedicated to the production of X-rays, +and to the development of techniques making use of them. +Since their first direct application (photography of Wilhelm Ro¨ntgen’s wife’s hand), X-rays have +become the base of applications as various as: +Medical imaging and treatment: radiography techniques, scanners, cancer treatments, computer to- +mography, are just some of the numerous applications of X-rays in medicine. +Now modern sources have pushed the development of new techniques, like: high-resolution +3D tomography imaging techniques, therapeutic treatments, drugs research, +Physics: Numerous physical characterization techniques are based on X-rays. If historically X-rays +first enabled the study of crystals by mean of the crystallography, they are now routinely +used to study soft matter (diffuse scattering), the chemical composition of elements (spec- +troscopy), magnetic structures (magnetic scattering-magnetic dichroism), the surface and +interface properties of various materials (small angle scattering) etc... +Biology. Biology always beneficiated from the development of physics techniques for its development +(the structure of DNA was discovered thanks to the X-ray diffraction technique). Now a +wide range of techniques is specifically devoted to biological applications: macromolecular +crystallography has become a science on its own, and more and more techniques benefit +from developments specific to biological applications. +Archeology and art. Archeological and artistic pieces are by definition unique and fragile. Since most +X-ray based techniques are non destructive, they are of prime interest to learn more on +those precious ”samples”. +Figure 1.6 : example of a protein structure resolved +Figure 1.5 : Toumai’s skull, as obtained thanks to by diffraction technique. +a tomographic technique. +For example it is now possible to know with a precision better than one Angstrom, the position of +each atoms in biological macromolecules (typically several thousands of amino acids). One can find +in all kind of samples the rarest traces of impurities, and get extremely useful information on the +history of the sample, or on its composition. It is possible to reconstruct in 3 dimensions the structure +of various samples with a precision of the order of a few microns, to determine the inner structure of +micro-objects, and directly study the properties of nanometer size objects... +6 Introduction +Another big advantage is the fact that those analysis are mostly non destructive. +→ It is possible to study unique samples, like archeological objects or space objects (brought +back by various space missions or even by the fall of asteroids) +→ It is possible to follow in situ complex process like chemical or biological reactions with a time +resolution of the picosecond or even less. +→ It enables eventually to repeat the experiment, which is not always easy to do when the sample +itself is hard to make. +→ It is possible to combine different techniques on the same sample. +As a result, there are more and more ”photon factories” in the world to answer the growing need +of scientists for those techniques of analysis. Experiments, which were just impossible to do even +20 years ago are now routinely achieved in synchrotrons and have become the standard in a lot +of fields. The area of interest for synchrotrons and the future X-FELs also keeps growing as new +applications (such as medical applications, nano-analysis) arise and revolutionize the possibilities in +their respective fields. +In the future, it is likely that the demand for high quality sources will keep growing, especially with +the arrival of more and more hybrid techniques, combining various apparatus like electron imaging +combined with magnetic dichroism imaging or atomic force microscopes combined with nano-focused +photon beams, LEED analysis and photoemission spectroscopy... +1.1.3 A typical experimental setup +An experiment using high quality sources involves a lot of elements, each being highly optimized. +A typical beamline (where the photon beams is shaped and positioned, and where experiments are +carried out ) is almost always composed of four main parts (see fig. 1.7): +• A source +• An optics hutch, +• An experimental hutch, +• A control hutch. +The source is composed of the particles circulating in the storage ring. Charged particles like +electrons or positrons used in synchrotrons emit light when submitted to acceleration. For those +particles have a very high energy (several GeV), the emitted light is tangential to their direction of +motion. This results in a very concentrated beam with a low divergence, and high flux. +1.1 Why Detectors ? 7 +Figure 1.7 : Schematic of a typical beamline. After +Figure 1.8 : Picture of a (blue) bending Mag- +the beam was produced in the storage ring, it en- +net. The bending magnets are one type of source +ters the optic cabin and then the experimental cabin +of photon beam in synchrotron radiation facilities. +where it hits the sample. All elements are remotely +©P.Ginter/ESRF +controlled from the control cabin. +The storage ring in reality is a large polygon. At each of its angles one can find bending magnets, +which produce an intense magnetic field, where the particles trajectory is bent. This is also the place +where light is produced. Beamline find their origins in those bending magnets. +In addition, elements called insertion devices are specifically made to produce a very large flux (see +picture 1.10 for the example of an undulator). Those elements consist of straight sections in which an +alternative magnetic field is applied on the pathway of particles (with a small period and permanent +magnet they are called undulators, and with long period electromagnets, they are called wigglers). +In those elements the particles follow a zigzag trajectory. The quantity of light obtained is largely +increased, as each turn adds light to that of the previous one, and because the emitted light is all +emitted in the direction of the straight section and not spread all along a large curve, like in bending +magnets. +In the case of undulators (small period) the light emitted by the device is coherent enough (spatially +and temporally) to create a phenomenon of interference. This results in the concentration of the +emitted energies at a fundamental frequency and a few harmonics. The Figure 1.9 gives the respective +spectrums of a bending magnet, a wiggler and an undulator. One can clearly see the gain in terms +of flux and monochromaticity (in particular when comparing undulators to bending magnets). +8 Introduction +Figure 1.10 : Photo of an Undulator. Undulators +are the brightest sources of photon beams in syn- +Figure 1.9 : Emission Spectrum of a bending mag- chrotron radiation facilities. ©P.Ginter/ESRF +net, a wriggler, and an undulator +The optics hutch contains the elements, which shape the beam: it usually contains several elements +such as: +→ a shutter, which controls the entrance of the beam in the hutch (this is a crucial element for +the safety of persons). +→ slits. They give its shape to the spot, by removing the non-focused part of the beam (especially +in the case of the bending magnets), +→ monochromator. It selects very precisely the energy (selects the good wavelengths from the +white beam), +→ focusing mirrors and/or lenses. They concentrate the beam to a spot, which can be as small +as a few microns or even less. Alternatively, they can be used to make a very wide and +homogeneous beam (ex. case of medical tomography). +The experimental hutch provides all the sample environment and detection systems needed to +carry out the experiments. +• The sample Environment is made of elements, which control the conditions of the experiment: +vacuum chambers and high pressure gaskets, sample heaters and cryogenic coolers, gas flows +and electrochemistry cells are some examples of systems mandatory to make several sorts of +experiments. +• The detector. The detector is in charge of collecting the information provided by the interaction +of the beam with the sample. It will be further detailed in the next section. +1.1 Why Detectors ? 9 +Figure 1.12 : A beamline seen from the top. The +Figure 1.11 : An example of experimental storage beam is hidden behind the concrete blocks on +setup, illustrating the complexity of experimental the left side of the picture. Photons enter the beam- +setup to provide the right sample environment. line at the top of the photo. ©P.Ginter/ESRF +©P.Ginter/ESRF +1.1.4 The place of the detector in the chain +The detector occupies a central place in the experimental setup, in this that it collects the photons +scattered after the beam/sample interaction. So the detector is a main source of information in any +photon science experiment. +So far, lots of efforts have been put in the production of high quality beams in terms of stability, +monochromaticity... The fantastic progress in this field is highlighted by the exponential rise of the +brilliance of the light sources during the last few decades (see Figure 1.2). +After those great achievements in brilliance, now comes the time to harvest this huge amount of +scattered photons with detectors. Indeed, in a lot of experiments, the main limiting factor is +the detector itself. The ESRF long-term strategy, which defines the future developments at ESRF, +states that ”detectors are generally recognized as the weak link in the modern use of SR”[1]. +Detectors used in the experiments usually suffer from: +• Low efficiency (only a very small fraction of the monitored particle are actually detected, so the +radiation dose received by the sample has to be increased) +• limited speed (fast reactions cannot be recorded. This also increases the dose received by the +sample) +• limited size (lowers the speed of the experiments forcing to make several acquisition.) +• limited dynamic range (a problem for techniques giving a high contrast, like small angle diffusion +scattering analysis). +Now more emphasis is put on instrumentation in the beamlines. Most large facilities have specific +programs for the development of new generation detectors. To answer the high cost associated to +these developments, collaborations among several institutes are created. +Already, various development projects have started to provide the beamlines with detectors, which +would suit the current requirements of experiments carried out in modern lightsources. +10 Introduction +In particular, this thesis is part of a project to develop a new generation of gas-filled +detectors with a high dynamic, large area, good efficiency and good robustness. +This thesis explores the possibility to use a photocathode as a first step photons → electrons +converter to ensure a good efficiency and spatial resolution of the detector. +1.2 Detectors in the hard X-ray energy range +A short introduction to the most common technologies of detectors used in the synchrotron radiation +community can be found in the well-known orange X-ray data booklet [2]. For each technologies an +extensive description can be found in K.Knoll’s Radiation and Measurement [3]. +It should be noted that in what follows only detectors technologies designed for X-rays are described. +Yet, most of those detectors can also be used with other sort of particles/radiations. +1.2.1 What are the detector main characteristics? +Basically, a detector provides information about the: +• position +• time +• eventually energy and direction +• intensity +of an incoming particle/photon beam. +The measurement of one physical quantity is never perfect, but suffers from several imprecision and +uncertainties. Those uncertainties have several origins: +• The measured signal itself suffers from statistical fluctuations. Those intrinsic fluctuations +cannot be avoided, but several measurements of the same quantity enable to determine the +distribution function of the physical quantity. Statistical models then enable to determine more +accurately the physical quantity, and also to calculate the statistical error of the measurement. +• In addition to the intrinsic fluctuations of the measured physical quantity, the detector suffers +from a limited precision in measuring it. The characteristics of one detector give information +on the accuracy of one measurement, and on the error of measurement. +• The signal is never recorded alone, but several fake events appear with the measurement and +tend to blur/hide the physical quantity measured. This contribution is often called background, +and finds its origin both in the detector imperfectness, and in the environment of the detector, +which can be source of such unwanted contributions to the signal. +The last two contributions (fluctuation and background) are usually referred to as Noise. The noise +can be analyzed in terms of power, spectrum, as well as uniformity. The quality of one measurement +is then evaluated thanks to the ( ) +Power A 2 +Signal to Noise ratio = signal = signal , (1.1) +Powernoise Anoise +1.2 Detectors in the hard X-ray energy range 11 +where A is the RMS2 amplitude of the signal. +The detector characteristics give information about: +• The quality of the measurement performed by the detector. This comprises among other aspects: +the resolutions in energy and position, the contrast the detector offers, and the noise it adds to +the signal. +• The speed of the detector: the minimum amount of time between successive measurement (dead +time) and the maximum intensity it can measure. +• The geometrical information about the detector: mainly its active surface. Also the volume of +the detector can be of importance in crowded spaces. +1.2.2 The Detective Quantum Efficiency +Figure 1.13 : Illustration of the effect of the noise and contrast on the quality of one image. +The detective quantum efficiency (DQE) characterizes the measurement uncertainty introduced by a +detector. +It is now recognized as the best figure of merit of a detector. It provides extensive information about +the capabilities of a 1D or 2D detector to return images with sharp and noiseless images. So it +expresses the ability of one detector to sense a signal against a background of radiation, and without +deteriorating the intrinsic noise of the incident beam. +The Detective Quantum Efficiency (sometimes spelled Detection Quantum Efficiency), is defined as +SNR2 +DQE = out2 , (1.2)SNRin +with SNRout and SNRin being the signal-to-noise ratios at input and output of the detector. +√ +2root of mean square: the quadratic mean of the signal < x2 >. +12 Introduction +It differs from the quantum efficiency QE in the sense that it takes into account, not only the fraction +of the photons, which are actually recorded, but also all the system losses due to the limited resolution, +noise performance... of one real detector. +SNRin can be seen as the best achievable detector performance, and in this sense, 0 < DQE < 1. +The DQE is function of several parameters[4, 5, 6]: +• The Quantum Efficiency, +• The spatial frequency, +• The particle energy, +• The signal intensity. +It is often used as a Figure of Merit of the detector, but it strongly varies with the conditions of +acquisition of the data, and as the available data are often incomplete, its utility is still limited. A +lot of discussions are still ongoing to define standard conditions of measurement of the DQE of one +detector. +Yet some methods are now recognized as standard for the evaluation of detectors DQE. Practical +methods of evaluation of the DQE and associated parameters, and more globally of the performance +of one detector can be found in references [6, 7, 8]. +In the following section, some of the most important characteristics of imaging detectors are shown, +through their impact on the DQE. Yet, the DQE is rarely fully measured and in most cases, only +those characteristics of the detectors, which have been measured. +1.2.2.1 The DQE dependence on the Quantum Efficiency. +The Quantum Efficiency QE, in its most fundamental definition is the fraction of the incident quanta, +which participate in the signal formation. So it is evident that the QE is a limiting factor to the DQE +of one detector. +SNR2Indeed, if we go back to the definition of the DQE = out2 (eq. 1.1), by writing SNR = Sx weSNRin +S √ S S √ σ S √ +x σx +obtain out = DQE in and outσ σ S = DQE +out +σ . For σout > σin, and outS = QE the Quantumout in in in in +Efficiency, we have +DQE 6 QE. (1.3) +The quantum efficiency QE acts as an absolute limit to the detective quantum efficiency DQE of the +detector. In particular, a perfect detector (with no intrinsic noise: σout = σin, infinite resolution...) +have a DQE = QE. For a real system, the DQE is equal to the QE of a perfect detector, which +would give the same image statistics for the same input flux [7]. +In conclusion, for an imaging detector, the DQE is best with: +• small detector noise σdno, +• high quantum efficiency QE, +• high input signal Si, +as expected. +1.2 Detectors in the hard X-ray energy range 13 +1.2.2.2 The dependence of the DQE on the spatial resolution +Figure 1.14 : 0.1 mm thick engraved lead line pattern used to test the spatial resolution of detectors +The properties given in the previous section do not show the influence on the detection efficiency +of the spatial resolution of the detector. Indeed, it is well known that detectors have a ”limited +resolution”, meaning they cannot resolve objects smaller than a certain size. This characteristic of +the detector is also known as the Position Resolution. +Several mechanisms can decrease the spatial resolution of one detector +The Position Resolution of one detector +In a position sensitive detector, there is a shift between the incoming position and the detected one +of a particle. This is due to pixel size, as well as by charge spread and parallax errors. The spatial +resolution gives information on the accuracy of the position given by the detector. +It is best measured with the Modulation Transfer Function (M), which gives the system response to +a sine-wave spatial-frequency amplitude. In other words, the modulation transfer function gives the +spatial frequency response of an imaging system or a component. +the modulation, Mi, of the image divided by the modulation of the stimulus Mo +M at a certain spatial frequency ν is defined as the ratio of the modulation of the image at output +and input: +Modulation +( ) = outM ν +Modulationin +with Modulation = Imax−IminI +I , in analogy with Michelson’s definition of visibility of interferencemax min +fringes. +It enables to evaluate easily the response of a complex system as simple product of the individual +MTF’s of the components of the system. For example for a classical Fluorescent screen + Optic + +14 Introduction +CCD camera, the MTF would be given by: +M =MFluo.Screen ·MOptic ·MCCD. +The MTF allows to calculate the output signal, which is basically the input signal multiplied +by the MTF. +Contrast Transfer Function +In practice yet, it is much easier to measure the Contrast Transfer Function (C) defined as the square +wave spatial frequency response. It is related to M by: +pi C(3N) − C(5N) C(7N)M(N) = [C(N) + + − . . .] (1.4) +4 3 5 7 +where N is the signal spatial modulation frequency in ’line pairs’ per unit distance. +In practice, one uses masks with several patterns of lines (see 1.14 of various spaces and thickness to +evaluate the detector response. The resolution is given by the smallest pattern distinguishable by the +detector. +Line spread function +NB. In the same way one can define the Point spread function. +This is the response of the system illuminated by a narrow slit (or small point). It is related to M by +the ’simple’ Four∑ier Transform:+ +M(ν) = k=∞∑ −i2piν−∞ LSF (k∆x)e∞  + +k∆x)+ (1.5) +k=−∞ LSF (k∆x) +So the LSF basically gives the detector response as function of the spatial frequency of the image. +Here again it is easy to measure experimentally for it is enough to measure the response of a detector +to a mask. +In most cases, the LSF (or PSF) can be very well described by a Gaussian. It is then fully described +by the standard deviation σdet (considering that the gaussian is centered at the point/line entry). +σdet is often called (a bit abusively) position resolution. +One can also notice that from the PSF one can determine the output intensity: +Iout(x, y) = PSF (x, y) ∗ Iin(x, y) (1.6) +where ∗ is a convolution. +The dependence of the DQE on the MTF +The dependency of the output intensity from the spatial frequency (cf. the relation between the +MTF M and the contrast transfer function) is taken into account in the DQE. This corresponds to +a dependency of the DQE on the MTF, which fully describes the response of the detector as function +of the spatial frequency. +1.2 Detectors in the hard X-ray energy range 15 +To take into account the impact of the noise in the frequency domain, one has to consider the power +spectrum of this noise, also named Wiener Spectrum3. This notion enables to write, in analogy with +the definition of the DQE, its dependence on the frequency: +The dependence of the SNRo from the MTF can be written as [9]: +2 +So MTF 2 +N2 +DQE = o (1.7) +SNRi +with N2o being the noise power spectrum, and SNRi the signal to noise ratio at the input ; SNRi +corresponds to the inherent fluctuation of the signal at the input, and is often considered to follow a +poisson statistics (like was done in section 1.2.2.1). MTF as well as No are functions of the spatial +frequency. +Details on the dependence of the DQE from the MTF and noise are given in [10]. +1.2.3 The mode of operation, speed and behavior of one detector at large inten- +sities +Integrating vs. Counting detectors +There are two modes of operation of detectors, which differ on two approaches to evaluate the intensity +of the measured signal: +• Counting detectors, which count the deposited quantas of energy one by one ; +• Integrating detectors, which accumulate the deposited energy before it is evaluated. +While counting detectors have been around for a while (for example, the Geiger Muller Counter), +most of the detectors used nowadays are based on the principle of integration of the signal. +In an integrating detector, the charge deposited by the particle(s) is accumulated (integrated) over a +period τ . The measurement of the intensity is obtained from the height of the signal obtained. +The maximum amount of energy the detector can accumulate before the signal is measured cor- +responds to the maximum intensity the detector can measure (saturation level). This maximum +intensity is often limited by physical processes in the detector. +The frequency at which the image is read gives the frame rate of the detector. In the case of area +detectors, the frame rate is typically of a few 10 of hertz / cm2. +In a counting detector, each electrical pulse (corresponding to each particle) will be counted if it +is above a predefined threshold. The intensity is given by the number of single events, which were +counted during the period τ . +The maximum intensity the detector can record is limited by the detector’s maximum count rate, +which is the maximum number of pulses, which can be recorded. Modern electronics allow count +rates as high as several megahertz. +3The power spectrum is the average power of the spectrum of the signal/noise in a unitary bandwidth centered at +the frequency f. +16 Introduction +Figure 1.15 : +Signal as analyzed by an integrating detector and a counting detector. +Counting detectors are considered as superior (especially for flat field detectors) because of their very +low noise (the threshold enables to discriminate real events from noise) and ability to count single +events. Theoretically those detectors are almost noiseless... +This is their higher cost (both for development and manufacturing) as well as the limitation of the +electronics, which have limited their use so far: counting detectors could not answer the needs in +terms of speed. Recently, the fantastic developments in terms of integration and speed of electronics +has made it possible to develop fast detectors with high dynamics and low noise. Now counting +detectors can compete in terms of speed (count rate) with integrating detectors. +In practice yet, counting detectors are not always better. So, as a compromise, some systems try to +adapt their modes of operation according to the incident flux, in order to offer the best efficiency +(DQE -detective quantum efficiency- see 1.2.2) [11]. +Dynamic range +The dynamic range is the range of intensity the detector can measure: [min Nb Quanta;Max Nb Quanta].So +it is the signal to noise ratio, computed from the greatest signal acceptable by the detector: +Max Intensity +Dynamic = (1.8) +Noise +In the case of integrating detectors: the max intensity corresponds to the maximum signal measurable +1.2 Detectors in the hard X-ray energy range 17 +in each picture, while Noise correspond to the detected intensity in the case of no intensity coming +on the detector. +In the case of counting detectors, the dynamic is the maximum count rate over the dark count rate, +which is the mean frequency of appearance of fake events (count rate recorded at zero intensity). +Associated to those definitions, there are a few notions of importance to evaluate the performances +of one detector: +Differential/Integral Non Linearity +The differential and integral non linearities (DNL and INL) measure the dependence of the detector +response as function of the signal intensity. The perfect detector has a constant DNL: ∂Response∂Intensity = Cte +(and a linear INL: Response ∝ Intensity). +Deviations are always present but can be corrected (eventually pixel by pixel in the case of position +sensitive detectors) afterwards. +The maximum intensity a detector can accept is limited by the so called dead time τ of this detector. +The dead time enables to measure the minimum time during, which a detector cannot record another +event. Theoretically, the maximum frequency of events the detector can accept is 1τ . +But there are two behaviors when successive events occur in a time inferior to τ (see Figure 1.16. +Dead Time Behavior +The dead time of one detector is the gap of time after one event was recorded when the detector +is unable to record another event. This minimum time between consecutive events can come from +limitations in the electronic of the detector, or from by physical processes in the detector itself. +For the income of photons on the detector is a random process, the probability that real events can +be lost is non zero. This limitation can be severe in the case of high flux, as a large number of events +are separated by a gap of time inferior to the dead time of the detector. There are two important +models for dead time behavior of the detector: +In the case of a non paralyzable behavior, the detector is able to count a new event immedi- +ately after the dead time of the first event is finished. In this case at high intensity, the detector +records events every τ , and a asymptotic saturation of the recorded signal occurs. +In the case of a paralyzable behavior, if two events occur successively in a time inferior to τ , +then the dead time is prolonged of a value τ from the second event. In the case of high intensities, +the average time between events becomes shorter than τ , and no event can be recorded until +two successive events have a time separation superior to τ . The saturation appears then as a +decrease of the recorded signal. +18 Introduction +Figure 1.16 : The paralyzable and non parlyzable behaviors of detectors. +1.3 Spectroscopy detectors +Spectroscopy detectors focus on high energy resolution. Most often they are position non sensitive +detectors, even if some of the technologies used for imaging detectors can offer energy resolution. For +the most important characteristics of spectroscopy detectors are their energy resolution and noise, +they often come with complex cooling system, which guaranties a minimum noise. +There are various types of technologies for spectroscopic detectors, corresponding to various energy +ranges. In X-ray photon science, the most typical detectors are based on technologies such a: +• Solid state detectors such as Silicon Drift Detectors, silicon crystals doped with lithium (Si(Li) +detectors) or high purity germanium (HPGe) +• Scintillation based detectors with various scintillation materials depending on the energy range. +Photodiode type detectors +In general, they consist of a p-n depleted region where electron-pairs are created by the incident +photons. Then a reverse electric field separates the charges, and a fast current pulse is recorded in +the built-in electronics. They offer a very high speed, and a good energy resolution (only 3.5 eV are +required for the creation of an electron pair in Si). Unfortunately, the small size of the depletion area +and the easy recombination of the charge pairs lower the quantum efficiency of the photodiode to a +very small value. +PIN photodiodes are an evolution of the photodiodes. They are based on the same principle, except +1.3 Spectroscopy detectors 19 +that the depletion zone is made much larger with the use of an undoped layer between the N and P +zones. Still the lack of internal multiplication of the charges makes them unsuitable for low photon +flux experiments even if they offer a good quantum efficiency at low energies. Several suppliers of +PIN diodes are now available4. +Avalanche Photodiodes (APD) are other cousins of the photodiodes: they combine a thick (130 µm) +low field zone combined on both sides with a thin strong electric field p-n-junction. A precise control +of the doping levels makes it possible to have a rather large central depletion zone to ensure a good +quantum efficiency, and side electric fields strong enough to enable an internal multiplication of the +charges with gain up to 104. Arrays of APDs making relatively basic 2D detectors are now commer- +cially available (sizes up to 1 or 2 cm2) 5. +APDs find more and more domains of applications. Unfortunately they cannot be produced in large +areas (Si based technology). +Germanium detectors +Germanium detectors are based on the same principle +as photodiodes, except that they use germanium instead +of silicon as semiconductor. This enables the creation +of very large depletion zones (cm vs.mm) and so bet- +ters dramatically the efficiency for high energy particles. +Their higher intrinsic noise makes the use of liquid nitro- +gen cooling system almost mandatory6. +Si(Li) detectors +The introduction of lithium as a dopant is a way to +create an intrinsic like zone (donors and acceptors ex- +actly compensate) in the semiconductor. This enables +the creation of a much larger zone for pair creation, +such increasing the quantum efficiency for high energy +rays7. +Figure 1.17 : A Photodiode used to monitor +the beam intensity in its protecting case. +4Among them, Hamamatsu, Canberra, Eurisys, Centronic, Sintef, Ontrak... +5again several suppliers: Perkin-Elmer Corporation, Hamamatsu Photonics, Judson technologies. Arrays by Pacific +Sensor, Perkin-Elmer... +6Provider of Ge detectors component: Canberra, XIA electronics... +7company supplying: e2v scientific instruments... +20 Introduction +Scintillator detectors +Figure 1.18 : A Cyberstar scintillator based spectroscopy detector, and its electronics. +Scintillation materials convert high energy photons (or the energy deposited by other particles) into +visible, UV or infrared light. The intensity of the light produced is proportional to the energy +deposited over a wide range of energy (the usual unit is [photons/MeV]), thus enabling a simple +intensity measurement to determine the energy of the incoming photon. Yet this approach suffers +some limitations, which limit its use for spectroscopy applications: +• For the intensity is proportional to the deposited +energy, it is hard to use a scintillator in the case of +large numbers of incoming photons. +• Scintillators providing a good yield, also suffer +from a long response time, which is another limitation +to the dynamic range of those detectors. +Yet, photomultipliers tube, which provide an excellent efficiency to collect the weak light emitted +from scintillators, and convert it into an electrical signal, have made this approach a prime choice for +spectroscopy applications for a number of decades. +Conclusion +Current spectroscopic detectors mostly suit the current needs of the scientific community. New +developments now go in the direction of area detectors, and speed in order to enable new types of +experiments. +1.4 Imaging detectors 21 +1.4 Imaging detectors +Imaging detectors include all line or area detectors. They are used both for imaging applications, +and to speed up the collection of data (with respect to a dimensionless detector, which would move +to cover the same area). This goes beyond a simple speed up of the whole experiment, for a lot of +samples, and in particular biological samples, suffer from long exposure into the beam. So imaging +detector can be an absolute necessity in certain fields in order to guaranty a good quality of data. +Imaging Detectors are the kind of detectors which need most of the developments in order to satisfy +the requirements of the experiments that scientists want to carry out nowadays. +1.4.1 current mature technologies +CCD based detectors +CCD detectors consist typically of a 2 dimensional arrays of silicon wells of a few 10’s of µm, which +store the charges created by light absorption. After this charge was accumulated, it is read out +sequentially with use of an integrated amplifier. They exhibit a very wide spectral sensitivity with +attractive quantum efficiency characteristics, but also present a large noise background. They are +typically used in photo-cameras, video-cameras, scanners, and other massively produced devices. As +such they are rather inexpensive, except in the case of very fast and large area components. +When used with hard X-rays, they are usually coupled with a fluorescent screen, which converts +X-rays into visible light. An optical system (based on common optics elements or on optical fibers) +is often used to reduce the fluorescent screen size to that of the actual CCD system. +CCD systems8 are nowadays one of the best way to achieve both large areas (eventually by coupling +several systems) with a high speed readout9. Unfortunately the optical system, and especially the +fluorescent screen largely degrade to resolution of those systems. In addition those systems present +an intrinsic high noise as compared to other technologies of detectors, which reduce their domains of +application. +Ongoing developments focus on new scintillator materials used to convert X-rays into visible light. +Thinner layers would increase the resolution especially with high energy photons, and faster scintil- +lators would enable higher frame rates. Also faster electronics are being developed, as it is also a +limitation to the frame rate of cameras. +8various systems used in the synchrotron world. Some examples: Dalsa-Medoptics CCD, Hamamatsu Photonics, +Philips, GE Medical Systems, The FRELON system developed at ESRF[12]... +9Typical systems offer readout speed of a few seconds (up to 15), but new highspeed systems are able to have frame +rates as high as 20Hz. +22 Introduction +Figure 1.19 : A CCD camera from the MAR Com- +pany with its optical coupling system visible. Figure 1.20 : The image plate MAR 345 detector. +Image plates +Image plates10 (sometimes called memory phosphors, storage phosphors or photo stimulated phos- +phors) are based on thermoluminescent materials, also referred to as thermoluminescent dosimeters +(TLD). In this type of materials, the absorption of the incoming ionizing particle leads to the cre- +ation of electron-holes pairs, which are trapped in purposely introduced defects in the crystal. So +the material acts as an integrating detector, in which the number of ”stored” electrons and holes in +the defects of the crystal, reflect the intensity of the incoming beam. To obtain the image, energy +has to be provided so that electrons and holes can escape from the traps and recombine, giving a +luminescent signal. So classical systems consist of a laser scanning the plate after the acquisition, an +optics (usually an array of optic fibers), which collects the luminescent signal and a photomultiplier +or a avalanche photodiode to collect the signal. +Image plates are available in very large areas (the mar345 is as large as 300 mm in diameter), and offer +a large dynamics. Their drawbacks lie mainly in the presence of noise, and in their very limited speed +(the plate has to be scanned to readout the image and typically several minutes are needed per image). +Gas-filled detectors +Gas-filled detectors use a gas both for the absorption of the ionizing radiations, and for the ampli- +fication stage of the signal (electron multiplication). This is now a mature technology, which is still +interesting because of the major advantages it offers. Unfortunately, gas-filled detectors also suffer +from certain drawbacks, which prevent their generalized use nowadays. +A more extensive description of gas-filled detectors is given in the section 2, as well as the description +of this project, which aims in overpassing their limitations. +10Mar produces the most common image plates used in the synchrotron world, especially in Macromolecular crystal- +lography. +1.4 Imaging detectors 23 +1.4.2 technologies under developments +1.4.2.1 Spectroscopy Detectors under development +Development focus on new technologies such as Silicon Drift Detectors in which the created charges +drift in a high resistivity, fully depleted silicon wafer. Electrons are collected on the edge of the +detector. Those detectors enable the measurement of simultaneous events occurring at different +places of the detectors, by being able to distinguish several rise times of the collected charge. +Already used techniques explained in the previous section are also under permanent development. +Also multielement detectors are being developed to offer higher count rates capabilities and larger +surfaces. +1.4.2.2 Imaging Detectors under development +CCD detectors and image plates are currently the most common imaging detectors. CCDs are used +when high speed is mandatory, while image plates offer large areas as well as a very good dynamic. +To answer the growing needs of the imaging community, strong progress have to be achieved in the +domains of dynamics, noise, and readout speed. +So the next step for imaging lies in the use of detectors operated in counting mode with a massively +parallel electronics (meaning each pixel is connected to a built in electronics where the first stage of +amplification and signal processing is performed, before the image is read out). This new approach is +possible thanks to the recent developments in the semiconductor industry, which offers components +small enough for this level of integration. +This approach will force the use of other technologies, for current CCD based systems as well as image +plates cannot be used in counting mode: the physical processes involved in the detection are too slow +to enable this approach (fluorescent materials as well as thermoluminescent materials have decay time +constants which are incompatible with single photon counting). So systems using a direct conversion +of the photon into the electric signal must be used (instead of a several steps conversion system like +in fluorescent+CCD or trapping+luminescence+photomultiplier). The 2 major possibilities are the +use of solid materials (Pixel and amorphous selenium detectors) or gas amplification based systems +(using the photoelectric effect to produce the initial charge). +24 Introduction +Pixel detectors +Figure 1.22 : A large area Gas Filled +Figure 1.21 : Schematic of pixel detectors. detector. +Photon-counting pixel detectors arrays are hybrid devices made of a semiconductor sensor connected +to a parallel CMOS readout circuit. The sensor is a Silicon (or another semiconductor) die with a +pixel electrode structure connected to the CMOS circuit by bump-bonding flip-chip technology (see +1.21). The sensor is fully depleted by applying a sufficient voltage bias. The photoelectric charge +created after X-ray absorption in the sensor is collected to the closest pixel of the CMOS circuit +along the bias field. Each pixel acts as an independent particle detector, including a complete pulse +processing chain as well as an event counter. +This kind of detectors currently achieves the best performance in terms of speed, and resolution. +Unfortunately, only small sizes can be manufactured yet11, and for large areas, arrays of detectors +have to be assembled. This results in inhomogeneities, which have to be compensated and dead zones. +The leading projects in this field are Pilatus (developed at the Paul Scherrer Institute (SLS detector +Group) in Switzerland [13, 14] and the MaxiPix project developed by the Medipix consortium [15]. +Here again, the integration of the readout electronics is a challenge! +Amorphous selenium/silicon detectors +Amorphous semiconductor detectors are based on the liquid crystal display technology. Essentially, +they are a matrix of capacitances charged (or discharged) by the current generated in the X-ray +irradiated amorphous semiconductor (often selenium). The charge is read by the TFT transistor +switches present at each pixel capacity. The main difficulty lies in the availability of a good quality +material, to permit the drift of the created charges to the transistors. +They are integrating detectors. +Gas-filled detectors +Very few technologies currently offer perspectives for large areas, especially in the case of fast detectors +(used in counting mode, with low noise...). +11typically 14 ∗ 14 mm2 +1.4 Imaging detectors 25 +Gas-filled detectors can offer a solution. More details on gas detectors, and on the link of this project +with gas detectors are given in the next section. + +Bibliography +[1] ESRF, “European synchrotron radiation facility long-term strategy,” tech. rep., ESRF, 2006. +http://www.esrf.eu/AboutUs/Upgrade/. +[2] Albert Thompson et al., X-Ray data booklet. Lawrance Berckley National Laboratory, available +at http://xdb.lbl.gov/ ed., 2001. +[3] G.F.Knoll, Radiation Detection and Measurement. Willey, 2000. +[4] G.Zanella et al., “The detective quantum efficiency of an imaging detector,” Nucl. Inst. and +Meth. A, vol. 359, pp. 474–477, 1995. +[5] G.Zanella et al., “The role of the quantum efficiency on the dqe of an imaging detector,” Nucl. +Inst. and Meth. A, vol. 381, pp. 157–160, 1996. +[6] S.M.Gruner et al, “Charge-coupled device area x-ray detectors,” Review of Scientific Instru- +ments, vol. 73,8, pp. 2815–2842, 2002. +[7] C.Ponchut, “Characterization of x-ray area detector for synchrotron beamlines,” Journal of +Synchrotron Radiation, vol. 13, pp. 195–203, 2006. +[8] C.Ponchut et al., “Experimental comparison of pixel detector arrays and ccd-based systems for x- +ray area detection on synchrotron beamlines,” IEEE Trans. Nucl. Sci., vol. 52,5, pp. 1760–1765, +2005. +[9] W.Hillen et al., “Imaging performances of a digital phosphor system,” Med.Phys., vol. 14,5, +pp. 744–751, 1987. +[10] J.P.Moy, “Signal-to-noise ratio and spatial resolution in x-ray electronic imagers: Is the mtf a +relevant parameter?,” Med. Phys., vol. 27,1, pp. 86–93, 2000. +[11] R.H.Menk et al, “Novel detector systems for time resolved saxs experiments,” J. Appl. Cryst., +vol. 33, pp. 778–781, 2000. +28 BIBLIOGRAPHY +[12] J.C.Labiche et al., “Frelon camera: Fast readout low noise,” ESRF Newsletter, vol. 8, no. 25, +pp. 41–43, 1996. +[13] C.Broennimann et al., “The pilatus 1m detector,” Journal of Synchrotron Radiation, vol. 13, +pp. 120–130, 2006. +[14] “Pilatus website.” http://pilatus.web.psi.ch/. +[15] “Medipix website.” http://medipix.web.cern.ch/MEDIPIX/. +Chapter 2 +The basics of gas-filled detectors +2.1 historical background +The history of gas-filled detectors starts around 100 years ago when Rutherford and Geiger (working +at the Manchester University) discovered electron multiplication gas-filled tube with a thin wire at +the axis position. +In 1928, Geiger and Mueller introduced the well known (and still used!) Geiger Tube, one of the +oldest type of ionizing particle detector. The Geiger Counter was the first electronic ionizing particle +detector. +Later, in the Manhattan Project [1], the gas-filled detector technology was largely improved. The +multiple wire proportional counter (MWPC) was invented. It was later implemented in high energy +physics by Georges Charpak, and revolutionized this field of physics. +Figure 2.2 : Schematic of the Geiger Mueller +Figure 2.1 : A modern Geiger Mueller Counter. +Counter. +Nowadays, gas-filled detectors are used in a large variety of research fields as well as for various +30 The basics of gas-filled detectors +industrial applications. They are routinely used for the detection of fast and heavy particles (high +energy physics), for the monitoring of nuclear facilities and other radioactive environment, for photon +detection and imaging (medical applications, non destructive analysis), etc... +2.2 Principle of gas-filled detectors +A detailed description of modern gas-filled detectors can be found in G. C. Smith’s article [2]. A +deeper analysis of the principles of gas filled detectors (with delay lines) is in A.-M. Petrascu’s article +[3]. Status of development of gas-filled detectors at the ESRF (giving more details on the specificity +of gas-filled detectors used in the synchrotron radiation world) is found in M.Kocsis article [4]. +In a gas-filled filled detector, the gas is used for two purposes: +• First it absorbs a fraction of the energy of the incoming photon/ionizing particle. In result of +this interaction, one or several electron-ion pairs are created (ionization of one particle of the +gas). +• Secondly, an internal multiplication of the electrons. This internal multiplication (typically +a gain factor of 104 to 105) is sufficient to enable each photon to be directly and separately +counted by some electronics. +2.2.1 The X-ray absorption in the gas +Figure 2.3 : The cross sections of various interaction processes in the case of Lead. +In a gas-filled detector, the first function of the gas is to absorb part of energy of the incoming photon +to create an electron, as a base of the electric signal. +2.2 Principle of gas-filled detectors 31 +In the case of the travel of one X-ray photon through matter, several of sorts of interactions can occur +between this photon, and the atoms (in our case those of the gas), but mainly three are of importance +for photon measurements (see Figure 2.3): the photoelectric absorption (τ in Figure 2.3), the compton +scattering (σincoh in Figure 2.3), and the pair production (κn and κe in Figure 2.3). The later one +can occur only in the case of highly energetic photons (more than 1.02 MeV = 2∗Masselectron, more +often called gamma rays), so it will not play any role in the case of low energy X-rays. +The two other govern the law of absorption of the photon in the gas. Their respective probability +is measured by their respective cross sections, which in general depends on the element, the density +and the energy of the photon. +The photoelectric effect is dominant for energies up to a few 100s of keV depending on the element +atomic number. Then Compton scattering becomes increasingly important, until it is dominated by +pair-creation. +Compton Scattering +The interaction process of Compton Scattering takes place between the incident X-ray, and an elec- +tron in the gas. It is an elastic scattering process. The photon is deflected through a certain angle +θ with respect to its original direction, while leaving part of its energy to the electron, then called +recoil electron. The energy deposited depends on the angle of deflection, and is increasing with θ. +Photoelectric absorption +The photoelectric process is the very process at the source of the electron production in the gas. When +a photon is absorbed by an atom following such a way, its energy is in fully transferred to an electron, +ejected by the atom from one of its bound shells. The result is the creation of an electron-ion pair, +with the electron energy being Ee− = hν − Eb, where Eb is the binding energy of the photoelectron +in the original shell. +In the case of X-rays, the most probable absorption occurs with electrons from the inner shells. +Shortly after the photoemission process, there is a rearrangement of the electrons inside the atom, or +the absorption of a free electron from the medium. Either one (or more) characteristic X-ray photons +may be emitted, or an Auger electron will be created to enable the excited ion to reach a more stable +state. In the case of an X-ray photon re-emission, this photon often is reabsorbed via photoelectric +effect, such creating another electron in pair, but with less energy. +2.2.2 The amplification and the modes of operation of gas-filled detectors +The internal amplification of the signal +After the first ionization of a gas particle occurred (by the incoming detected particle), the created +electron is thermalized and under moderate fields, the gained energy is lost in collisions with the +gas molecules. In the regions where the gained energy between two collisions is exceeding a certain +level (typically ∼ 35eV ), it becomes a ionizing particle, which will later ionize another gas particle, +creating a second electron, and finally leading to cascade of ionization (as secondary electrons are +32 The basics of gas-filled detectors +produced). +The amplification of the signal will then depend on several factors such as +• The type of gas, +• its density, +• the accelerating electric field and its shape. +This leads to various Modes of operation, which are classified for a certain gas, as function of the +applied electric field. +Modes of operation of gas-filled detectors +Depending on the applied accelerating potential, various modes of operations of gas amplification are +distinguished. The Figure 2.4 (extracted from [5]) gives the amplitude of the signal collected after the +absorption of a particle and the corresponding amplification modes. The two curves correspond to +two different amounts of energy deposited in the gas. The result with two X-rays of different energies +would be alike. +The different modes of operation of gas amplification are: +Recombination region When the electric field is very low, the field is insufficient to prevent re- +combination of the ions pairs. The current collected on the electrodes is very low, as only the +fraction of the created ions pairs, which did not recombine is collected. +Ion Saturation From a certain value of applied voltage, the electric field is strong enough to effec- +tively separate the charges created after absorption of the energy of the ionizing particle. Then +almost all pairs are collected and the intensity corresponds to the rate of creation of charges in +the volume of the detector. +Proportional region When the applied tension is further increased, the mean energy gained by +electrons between collisions is higher than the ionization energy. From this moment an ampli- +fication of the signal occurs. For a certain tension, the intensity collected is proportional to the +original number of ions pairs created. This is the region of true proportionality. +Limited proportional region and Geiger mode Higher electric field result in the apparition of +non linearities: when the electric field becomes very strong, the amount of charges present in the +gas becomes high enough to alter severally the electric field resulting from the applied tension. +Eventually, this Space Charge can become completely dominant and fully determine the pulse +shape. This last mode is the Geiger mode of operation of the detector. +In order to avoid a dependence of the amplification on the localization of the deposited charge in the +detector chamber, and to improve the stability of the system, the strong electric field is applied only +in a thin region of the chamber. In the rest of the chamber, where electrons are created, only a drift +field is applied. This also limits the spread of the electron cloud (going exponentially with distance), +which occurs during the multiplication and limits the loss of resolution while preserving an absorbing +area sufficiently large. +2.2 Principle of gas-filled detectors 33 +Figure 2.4 : Regions of operation of gas-filled detectors for two deposited energies. +Usually the collection of the electrons is performed with a 2D array of wires, which enables propor- +tional amplification mode (the so called multiwire proportional counters introduced by Charpak and +coworkers in 1968 [6]). +Classical gas mixtures are composed of Xenon, Krypton, Argon, Methane, CF4 etc... (see [2]). +2.2.3 The benefits of gas-filled detectors +The main advantaged of gas-filled detectors as compared to the previously described types of detectors +are: +• their intrinsic speed mainly limited by the electronics +• their dynamic range, also limited by the memory depth +• their available size (among the largest detectors) +• their cost of development and manufacturing +• their easiness of operation, and robustness. +Gas detectors find domains of applications in most fields of photon science. They are some of the very +few types of detectors, which can be built in very large areas. In the high energy physics experiments, +it is common to find detectors of several square meters, and covering solid angles of almost 4pi. +2.2.4 The limitations of gas-filled detectors +Main limitation +As compared to other technologies of detectors, gas-filled detectors suffer mainly from one disad- +vantage, which made them almost abandoned in whole fields of photon science: They have an +34 The basics of gas-filled detectors +intrinsic low quantum efficiency, they leave a great number of incoming particles undetected +(said another way, they are photon hungry). +This is simply due to the very low density of gases, and so very low stopping power. To overcome +this, it is possible to increase the pressure of the gas, but this is at the expense of amplification +characteristics, which are best at low pressures... +They also suffer from sever parallax error leading to a loss of resolution as soon as the incoming +particles do not have a direction perpendicular to the detector (see Figure 2.5). +Figure 2.5 : Parallax error is the loss of resolution due to the absorption of non perpendicular photons all +along the depth of the ionizing chamber, thus broadening the position response of the detector. +So when considering their application in photon research, other technologies less photon hungry are +usually used, even if they offer poorer performances in most other characteristics. +other limitations Another weakness is linked to the use of wires to collect the charges after +multiplication (MWPC). The small radius of those wires makes them very sensitive to discharges in +the detectors (more likely with increasing acceleration voltages/gains). It is indeed very difficult to +repair broken wires in the detector. In addition the broken wires are likely to create short circuits +and create further damages). +Modern gas-filled detectors overpass this by using microstructures in place of the traditional wires. +2.3 Recent Evolutions of gas-filled detectors 35 +2.3 Recent Evolutions of gas-filled detectors +There has been various recent evolutions of the classical gas-filled detectors to overcome their weak- +nesses and keep their advantages. +The main attempts of improvements of gas-filled detectors over the last few years have been stripped +detectors, as well as hybrid gaseous multipliers. Interesting Parallax Reduction Techniques were also +introduced. +Parallax reduction techniques +The simplest technique to reduce parallax errors, is to build a curved detector. This technique has +been successfully used at ESRF ([7]) and later at the Rutherford Appleton Laboratory ([8]). In +addition it largely suppresses the charge spread problem. +Figure 2.6 : Curved gas-filled detectors do not suffer from parallax errors. +Other methods of correction such as off line correction by determination of the X-ray absorption +depth were also demonstrated ([9]) but never used in the synchrotron world. +For area detectors, solutions to reduce parallax were offered very early after the idea of MWPC was +published. Charpak’s group at CERN proposed to add a spherical drift chamber to the front of the +MWPC [10]. This idea was successfully applied to a working device, which became the workhorse of +the synchrotron LURE in the 80’s ([11]). The idea was then bettered in the late 90’s [12]. +Micro-Pattern +Strip detectors are an answer to the fragility of MWPC’s wires and limited amplifications character- +istics (limited by space between wires). They also permit to avoid the difficult manufacturing of the +chambers (to place the wires of the chamber). +A large number of structures have been proposed over the last 20 years such as micro-strip gas +36 The basics of gas-filled detectors +chambers [13], the microgap chamber [14], the compteur a` trous [15], the gas electron multiplier [16], +the micro-mesh gaseous structure [17], or the micro-pin array [12]. +Figure 2.7 : GEMs are thin metal-clad polymer foils pierced by a high density of holes. On application of a +difference of potential, between the two electrodes (sides) electrons drift and multiply in the holes. +Among those detectors, GEMs (Gas Electron Multiplier) created the largest interest. Introduced +in 1996 by F. Sauli and his colleagues from CERN [16], GEM’s key feature is a three-layer (metal- +insulator-metal) grid which is used both for the amplification of the signal, and for ion feedbacks +prevention (to protect the photocathode, used to convert electrons). Several of such grids can be as- +sociated to increase the amplification of the system. Working devices were reported in various groups +in the world and developments are ongoing to improve this technology. GEMs foils are routinely pro- +duced at CERN, and are now commercially available thanks to the company Tech-Etch Inc.[18, 19]. +Resolution and speed improvements +The limiting factor of spatial resolution of the detector is the photoelectron range. +The center of mass of the produced electrons during multiplication reflects the position of the original +ionization process, and so of the detected particle. Delay-line encoding or charge division methods +are naturally determining the center of gravity of the electron cloud below the anode spacing. The +speed of the above system is limited to Mega counts per seconds (Mcps) range. For example, the +RAPID (Refined ADC Per Input Detector) system [20] developed at the Daresbury synchrotron in +the UK, is able to determine the position of this center of mass by comparing the amount of charges +on the different anodes reached by the cloud of electrons. As a result, the detector is able to position +the original impact with a speed of 107 counts per second. +2.4 Gas amplification compared to Microchannel plates 37 +2.4 Gas amplification compared to Microchannel plates +Microchannel plates (MCP) are devices able to amplify signal with a very large gain in vacuum. +Figure 2.8 : A two slab Micro Channel Plate (Chevron configuration) +They consist of a thick slab of highly resistive material (glass, silicates) riddled with small tubes +(diameter ∅ ∼ 10 µm, and interspace ↔∼ 15 µm) leading one face to the other: the microchannels. +The face of the tubes is covered by a continuous-dynode electron multiplier. The application of a +strong potential between each face (∼ 500 V ) enables the acceleration of electrons in the tubes, which +hit the surface of the tube, leading to an amplification of the signal as they create secondary electrons +at each impact. +Modern MCPs usually consist of several slabs of MCPs with an angle between the successive tubes +(chevron or V-like geometry). This geometry leads to a greater amplification for the same applied +voltage, and to an excellent compactness. +Unfortunately, MCPs suffer from major problems: +• Especially for single events, the gain of MCPs is very dispersed. If used in saturation mode, the +pulse height is stable and the time jitter small, but the pulse decay is long and not constant. +If used in linear mode and associated to a constant fraction discriminator, the pulse shape is +assumed to an impulse response with variable height, but fixed shape from a single particle. +• They suffer from a limited speed, meaning they cannot reach high count rates (∼ 150 kHz). +• They can amplify a fix charge during their lifetime, so they need to be replaced frequently. +• They are not available in very large surfaces (diameter area ∼ 10 cm). +38 The basics of gas-filled detectors +Compared to gas amplification system, they offer for the same stability in operation, a better gain +and a very good compactness. Unfortunately, this is a much slower system, which degrades over time +and is less easy to maintain. In addition they cannot be built in very large areas (several 10s of +centimeter). +Those reasons, especially their limited count rate capabilities make them a difficult choice for high +count rates detectors. +2.5 A promising approach to overcome Gas-filled detectors limita- +tions +A promising approach to overcome the parallax of gas filled detectors (see 2.2.4) is the use of a solid +converter called Photocathode. The solid state materials density is roughly 1000 times that of a gas. +As a result a few microns are enough to absorb the incoming photons and convert them in electric +signal. This presents several advantages, including the absence of parallax errors (see Figure 2.5), a +better efficiency, and a higher compactness of the detector. +Bibliography +[1] M. P. T. S. National nuclear Series, Ionization Chambers and Counters. Experimental Techniques. +McGraw-Hill Book Company, Inc, 1949. p97. +[2] G.C.Smith, “Gas-based detectors for synchrotron radiation,” Journal of Synchrotron Radiation, +vol. 13, pp. 172–179, March 2006. +[3] A.-M. P. et al., “A beginners’ guide to gas-filled proportional detectors with delay line readout,” +Journal of Macromolecular Science, vol. B37:4, pp. 463–483, 1998. +[4] M.Kocsis, “The status of gas-filled detector developments at a third generation synchrotron +source (esrf),” Nucl. Inst. and Meth. A, vol. 471, pp. 103–108, September 2001. +[5] G.F.Knoll, Radiation Detection and Measurement. Willey, 2000. +[6] G.Charpak et al., “The use of multiwire proportional counters to select and localize charged +particles,” Nucl. Inst. and Meth., vol. 62, pp. 262–+, 1968. +[7] V.Zhukov et al., “A curved micro-strip gas counter for synchrotron radiation time resolved +saxs/waxs experiments,” Nucl. Inst. and Meth. A, vol. 392, pp. 83–88, 1997. +[8] J.E.Bateman et al., “A gas microstrip wide angle x-ray detector for application in synchrotron +radiation experiments,” Nucl. Inst. and Meth. A, vol. 477, pp. 340–346, 2002. +[9] J.E.Bateman et al., “Improving the performance of the mwpc x-ray imaging detector by means +of the multi-step avalanche technique,” Nucl. Inst. and Meth. A, vol. 239, pp. 251–259, 1985. +[10] G.Charpak et al., “The spherical drift chamber for x-ray imaging applications,” Nucl. Inst. and +Meth., vol. 122, pp. 307–312, 1974. +[11] R.Kahn et al., “An area-detector diffractometer for the collection of high resolution and mul- +tiwavelength anomalous diffraction data in macromolecular crystallography,” Nucl. Inst. and +Meth. A, vol. 246, pp. 596–603, 1986. +40 BIBLIOGRAPHY +[12] P.Rehak et al., “Mipa: A new micro-pattern detector,” IEEE. Trans. on Nucl. Sci., vol. ns-44, +pp. 651–655, 1997. +[13] A.Oed et al., “Position-sensitive detector with microstrip anode for electron multiplication with +gases,” Nucl. Inst. and Meth. A, vol. 263, pp. 351–359, 1988. +[14] R.Bellazzini et al., “The microgap chamber: a new detector for the next generation of high +energy, high rate experiments,” Nucl. Inst. and Meth. A, vol. 368, pp. 259–264, 1995. +[15] F.Bartol et al., “The c.a.t. pixel proportional gas counter detector,” Journal de Physique III, +vol. 6, pp. 337–347, 1996. +[16] F.Sauli et al., “Gem: A new concept for electron amplification in gas detectors,” Nucl. Inst. and +Meth. A, vol. 386, pp. 531–534, 1996. +[17] Y.Giomataris et al., “Micromegas: a high-granularity position-sensitive gaseous detector for high +particle-flux environments,” Nucl. Inst. and Meth. A, vol. 376, pp. 29–35, 1996. +[18] “Tech-etch inc..” http://www.tech-etch.com/. +[19] B.Surrow et al., “Development of tracking detectors with industrially produced gem foils,” Nucl. +Inst. and Meth. A, vol. 572, pp. 201–202, 2007. +[20] R.A.Lewis et al., “The ”rapid” high rate large area x-ray detector system,” Nucl. Inst. and Meth. +A, vol. 392, pp. 32–41, 1997. +Chapter 3 +Photocathode for gas-filled detectors +What is a photocathode? +A photocathode is a solid converter: it converts photons into electrons. The energy deposited by the +incident particle enables the creation of hot electrons (more energetic than free electrons), which exit +the photocathode at a position very close to the entry of the incoming particle. +Photocathodes have to suit the following requirements: +• Good conversion efficiency +• Chemical stability : as the photocathode has to operate in a gas, it must be reasonably chemically +stable +3.1 Basics of Photocathodes +There is currently no theory to describe precisely and predict numerically the characteristics of pho- +tocathodes. Only phenomenological models can be made to help predicting the characteristics of +materials as good photocathodes. +This comes from the extreme complexity of the physics of electron transport into matter, as the +cascade of events varies not only with the type of material (chemical nature and related physical +properties), but also with the microscopic structure of the material (most defects, grain boundaries, +or impurities act like traps for electrons). +42 Photocathode for gas-filled detectors +Figure 3.1 : After its creation, the hot electron rapidly looses +its energy because of several interactions with the lattice or other Figure 3.2 : The region of the photocath- +electrons. Few electrons actually reach the surface. ode contributing to yield. L is the scatter- +ing length, la is the absorption length. +As a result only the physics of the absorption of the incoming photon into the matter is well described. +To go further, one has to use approximate models, which cannot lead to numerical predictions of the +efficiency and speed of the photocathode. +The best (phenomenological) model to describe photocathodes is called the Spicer Three Step Model. +It was developed approximately forty years ago by William E. Spicer, when he was working for SLAC +(The Stanford Linear Accelerator Center)[1]. +This model basically separates the process in three major steps: +• Absorption +• Electron transport to the surface +• Extraction from the surface. +More precisely, the model consists in examining the contribution of a slab dx at a distance x from +the surface to the emitted electrons. +This contribution depends on: + the amount of photons, which arrive at this depth. + the probability of an electron photoemitted in this slab to join the surface, +The total yield of the photocathode is then obtained by integrating di(x) over the whole volume. +To help comparing materials, the model defines two lengths: +• la is the absorption length in witch most of the photons are absorbed. It is the 1/e length where +the intensity of the incident beam has dropped to 1/e. +3.1 Basics of Photocathodes 43 +• L is the scattering length: the distance electrons can go over before they are thermalized. +The quality of a material can then be examined with the ratio laL , which should be as small as possible, +and ideally, inferior to unity. +The model also enables to define the active volume as the portion of the photocathode next to the +surface, which is at a distant inferior to both la and L (see Figure 3.2 in page 42). This is the region +of the photocathode, which is close enough to the surface to enable electrons to escape, and at the +same time in the region of absorption of the photons, so contributing to the yield. +Absorption +From the presented model, it is evident that a material with a high stopping power (small la) will +produce more electrons close to the surface, so more electrons with a high probability to escape the +material. In practice, these are materials with a high Z (superior to 50, or ideally to 70), which +present the best stopping powers. +Figure 3.3 : Electrons with energy EC < E < EC + EG have higher mean free path. +Electron Transport +The capacity of the Photocathode to transport hot electrons to the surface depends strongly on the +type and quality of the material it is made of. This is measured in the Spicer model by the value of +the ”scattering length” L. This value is closely related to the value of the mean free path and that of +the average loss of energy of electrons in the material. +To maximize the value of L, it is best to have a semiconductor. First because in metals, hot electrons +get thermalized very easily by the many free electrons. Secondly, in semiconductors, there is the +44 Photocathode for gas-filled detectors +appearance of the so called Magic window. The magic window is a region in the conduction band +(Ec < E < Ec + EG) where electrons have a much higher mean free path. Indeed, electrons having +such an energy cannot excite another electron in the conduction band, for this would result in two +electrons in the forbidden gap of energy. The electron ion pair creation being a dominant process at +those energies, this results in a much higher mean free path of electrons in the window. +It is also of strong importance to have defect free materials: each defect in the material (vacancy, dis- +location, grain boundaries...) acts like a trap for hot electrons, for they often result in dangling bonds. +To have further details, one can look at Henke’s papers [2, 3], in which a more precise model for +electron transport is given (especially concerning electron-electron and electron-plasmon interactions). +Those references also highlight how the efficiency of the photocathodes is closely related to the prod- +uct Eµ(E), where E is the energy of the incoming photons, and µ(E) the mass absorption coefficient +of the photocathode material. +Extraction +Electrons close to the surface do not necessarily go in the vacuum: they have to overcome a poten- +tial barrier called work function φm in metals or electronic affinity χsc in semiconductors (Figure 3.4). +Figure 3.4 : To exit the solid, e− have to overcome Figure 3.5 : The Band structure of a NEA semi- +the workfunction φm or electronic affinity χsc conductor close to the surface +This barrier is often several eV high, so very few electron can overpass it, leading to a poor yield. +To maximize the photocathode efficiency, one must select materials with a very low electronic affinity. +There are materials such as CsI, or hydrogenated diamond, which offer a Negative Electron Affinity +(NEA). Those materials are of course of special interest for they act like a kind of hot electron +fountain: hot electrons close to the surface see an attracting potential, which tends to eject them +from the material. The quantum efficiency of this sort of material is of course much better than that +3.2 Improved Models of Photocathodes 45 +of classical materials. +Their main disadvantage comes from their very high chemical sensitivity. For the potential tends +also to attract anions, the negative affinity rapidly disappears as the surface gets polluted. So they +require special cleanness of the environment, which is hard to achieve when the photocathode is in a +gas chamber. It was also found that the coating of the surface with materials like caesium or TMAE +can improve this efficiency (see adding details in the following section, or see [4] published in 1936 !). +This effect is usually explained by the appearance of dipoles at the surface of the materials, which +lower the electronic affinity. +The Contradictions +Already several contradictory requirements appear for the photocathode : +• The photocathode must be thick to absorb the incoming particles, but thin to let electrons +escape. +• It should be made of high Z materials, but should be defect free. In terms of availability, there +are very few high Z materials (especially in the case of semiconductors), which can be processed +with a good purity and few defects. +• It would better be NEA but has to be chemically very stable. +So one has to choose the best compromise to finally achieve an optimal quantum efficiency in a certain +energy range. +3.2 Improved Models of Photocathodes +Obviously the model presented in the previous section is very simple, and it cannot be used for +quantitative analysis. It is yet the only general model. +Yet more accurate models were developed to predict quantitative secondary emission yield, as well +as the energy distribution of both photoemitted electrons, and secondary emitted electrons. +Unfortunately all those models are material specific (they usually study CsI, considered as the most +interesting material for photocathode application [5, 19, 7]), for they use extensively fitted parameters. +Most of them were developed for Monte Carlo based analysis. So it is difficult to use this sort of +models for prediction of efficiencies of new materials. +More details will be given in the section dedicated to the Monte Carlo Analysis. +3.3 Major technologies of photocathodes currently available +Most materials now used as photocathodes have been known for a long time. A compilation by +P. Mine´ then at Ecole Polytechnique in 1993 [8] is still valid (this publication deals with photoemissive +materials in the UV, but the state of knowledge in the X-ray energy range is not really different). +Jochen Teichert, Rong Xiang, Guy Suberlucq and Jeroen W.J Verschuur also made a Report on +46 Photocathode for gas-filled detectors +Photocathodes in 2004 but again, mainly focused on photocathodes in UV and Visible range for +electron injection system applications [9]. Focus was given on a better control of the fabrication +process to ensure the best quality of cathodes. +3.3.1 Metallic Photocathode +Metallic photocathodes are the oldest type of photocathodes. +Classical materials include gold, copper, and silver. Gold is of all those materials the best, for it offers +the best efficiency (highest atomic number so excellent stopping power), an excellent speed, as well +as the best chemical stability (noble metal) . +Gold is used for photocathodes in a wide range of application where high chemical stability, high +conductivity and speed are mandatory. This is especially the case for photo-injectors in synchrotrons +and X-fels (injectors made of photocathode excited with pulsed UV-laser to create the packets of +electrons) where high quality pulses of electrons (in terms of intensity and shortness) are mandatory. +The photocathode is often used in RF cavities coupled with the pulsed laser to enable the creation +of extra short/very high intensity electron packets. +NB. RF cavities cannot be used to improve the efficiency of gas-filled photodetectors, because they +work exclusively under ultra high vacuum (discharge problem) so are incompatible with gas amplifi- +cation. +Past studies of metallic photocathodes +Metallic photocathodes were mostly studied during the 70’s and early 80’s (though, some older +references can be found). Classical references include: +• for Gold, Copper and Silver: [10, 11, 3, 12, 13]. +• for Aluminum and Al2O3: again [3, 13, 12]. +• other materials such as Tungsten, Molybdenum, Silver, and Palladium are presented in +[10] +For the X-ray energy range as well as for the UV energy range, gold is the most suitable metallic +photocathode. Recent measurement using synchrotron radiation facilities [14, 15] report all with good +agreement efficiencies of a few tenths of a percents in the 1-10 keV energy range. [16, 17] also provide +interesting results even if the quantum efficiency is not directly measured. Lastly H.Henneken et al. +reported measurements of the efficiency of gold in the case of the specific Au(111) surface [15]. +3.3.2 Semiconducting Photocathode +As previously discussed, semiconductors are theoretically much better materials in terms of quantum +efficiency. Their availability in excellent purities and almost defect free bulk materials make them a +very attractive choice. +In practice several compounds offer excellent efficiencies in the visible or infrared ranges (Alkali +antimonides such as Cs3Sb, K3Sb, Na2KSb, K2CsSb). Unfortunately they all present a high +3.3 Major technologies of photocathodes currently available 47 +reactivity to moisture and oxygen, which makes their manipulation difficult, and also completely +unsuitable for gas amplification based systems. +Other systems were studied because of their insensitivity to visible photons, and high efficiency in +the UV range (solar blind photocathodes for spatial application). Those photocathodes reacting +to wavelength smaller than 380nm, often exhibit a negative electron affinity (eventually after an +activation with Cs or another material). +Theoretical analysis of secondary emission by semiconductors can be found in [3, 2]. +Materials, which created interest include +• boron nitrides BN reported to present NEA characteristics [18] +• Gallium Arsenide GaAs also reported to present NEA when Cs activated (see [19], which +compares GaAs with other semiconductors, as well as [20, 21] +• Gallium nitride, Indium Gallium Nitrides and Aluminum Gallium Nitrides GaN, +INGaN and AlxGa1−xN were extensively studied because of their potential for solar blind +detectors ([22, 23, 24, 25]). +Unfortunately when it comes to X-rays, common semiconductors such as gallium arsenide, silicon or +germanium are completely inefficient. Indeed those materials do not have the stopping power suitable +for energetic photons, for electrons cannot reach the surface before they are thermalized. In addition, +those materials are available only in small dimensions. +Heavier materials being much harder to process in good quality, there are very few materials, which +are actually used as photocathodes. CsI is the exception, and it will be later described. +3.3.3 Organic Photocathode +Organic photocathode such as TMAE (tetrakis dimethyl-amino!ethylene), or C6H5, have created +great interest in the 80’s for they exhibit a negative electron affinity. They were also used as activator +(like Cs). Unfortunately, they are of no interest in the X-ray energy range, because of their very low +stopping power. The interested reader can find information in P. Mine´’s [8]. +3.3.4 CsI +Since its first discovery by Taft and Philipp in 1957 [26] and its further studies by J. Edgecumbe +and E. L. Garwin in 1965 [27, 28], CsI has probably been the material, which was the most widely +studied. This comes from several advantages it offers: +• Excellent quantum efficiency: the material exhibit NEA properties, and an excellent stopping +power (high Z). +• A rather good chemical stability, at least if compared to most other materials with similar +characteristics. Still the material is hygroscopic and suffers from degradation with time. +• Easiness of synthesis and deposition. +48 Photocathode for gas-filled detectors +From the beginning, a lot of efforts were put in attempts to reduce its sensitivity to moisture and +need for cleanness (UHV conditions) [29, 8, 13, 32, 11, 34, 35]1. +Efficiencies measured vary among authors. This is probably due to the high reactivity of the material, +and the importance of the deposition/synthesis conditions. +• [32] report a quantum efficiency of 2 to 4% in the 5 to 10 keV energy range. +• [13] report a quantum efficiency of 1 to 5% in the same range of energies. +The ALICE collaboration made a systematic study of the effect of water and oxygen on the quantum +efficiency of CsI [36]. [32] provides information on the effect of heating to resorb the loss of efficiency +after exposure to moisture. +Effects of electric field [12], Gas amplification with various mixtures [38, 39], polarization of X-rays +[40], as well as various Monte Carlo dedicated codes [38, 5] were also studied. This shows the wide +interest and hopes that this material created. +Now, CsI is still considered as a reference, and a lot of projects are still based on the use of this +material. Unfortunately, the sensitivity of CsI as a photocathode is still an issue, and few success +were recorded. +Lastly, a sensitivity of CsI to radiation was recorded [8, 41]. This is of course an issue regarding the +stability in time of a detector using CsI. Fortunately, this sensitivity seems to be limited in the X-ray +energy range [41]. +The key feature of CsI is its negative electron affinity. This NEA is explained by the appearance +of dipole charges at the surface of the material, leading to a bending of the band structure, and the +presence of an attractive potential to electrons at the surface. +Those dipoles are of course very attracting to all sorts of impurities, which easily form chemical +bounding with the surface charges, so destroying the NEA of the surface. +As a result, CsI photocathodes usually loose their high quantum efficiency after a few hours of +exposure to moisture, and even much faster in an unclean environment. +There were a lot of attempts to protect the CsI from degradation in unclean environment. Another +approach was to try developing online cleaning processes (like [32] already cited). But none of these +approaches were able to provide a solution acceptable in terms of robustness and efficiency. +It remains that CsI offers an attractive efficiency, and in addition it is widely available (it was also +successfully used as a scintillator material by addition of dopants like Tb or Na). +3.3.5 Conclusions on available technologies of Photocathodes and the issues re- +lated to their use +A wide variety of photocathodes is available on the market. But most of them are suitable only for +low energy applications (visible, ultra-violet and infrared applications). +There are mainly two families of photocathodes suitable for the hard X-ray energy range: +• Metallic photocathodes, mainly gold, which offers a poor efficiency but an excellent robustness +1It should be noted that a number of those publications come from A.Breskin’s group from the Weizmann Institute +of Science in Israel, which has been very active in developing this technology. +3.3 Major technologies of photocathodes currently available 49 +Gold CsI +Efficiency few 110 ’s of a percents [16, 17] few percent [32, 13] +Sensitivity none To moisture, impurities in gas +Table 3.1 : Technologies of photocathode +• CsI photocathodes, which offers the best efficiency, but a sensitivity to moisture and contami- +nation leading to huge technological problems, especially in the case of gas-filled detectors. +Recapitulation tabular (Table 3.1): +Other classical photocathodes such as tetraminoethylene (TMAE), the organometallics ((C2H5)Cr, +(C2H5)Fe...), are not suitable for X-rays for their stopping power is not good enough and so do not +achieve a good efficiency (this is mainly due to their low Z). +The same restrictions apply to GaAs and parents (InGaAs, InGaAsP) usually used after activation +with Cs. In addition, those materials can be used only with gases of very high purities. +TMAE was successfully used to increase to quantum efficiency of CsI and other photocathodes, but +no good stability could be achieved. + +Bibliography +[1] W.E.Spicer, “Photoemissive, photoconductive, and optical absorption studies of alkali-antimony +compounds,” Phys. Rev., vol. 112, no. 1, pp. 114–122, 1958. +[2] B.L.Henke et al., “Soft x-ray induced secondary-electron emission from semiconductors and +insulators: Models and measurements,” Phys.Rev.B, vol. 19, pp. 3004–3021, 1979. +[3] B.L.Henke et al., “0.1-10kev x-ray induced electron emissions from solids-models and secondary +electron measurements,” J.Appl.Phys., vol. 48, pp. 1852–1866, 1977. +[4] L.Malter, “Thin film field emission,” Phys.Rev., vol. 50, pp. 48–58, 1936. +[5] A.Akkerman et al., “Monte carlo simulations of secondary electron emission from csi, induced +by 1 10 kev x rays and electrons,” J.Appl.Phys., vol. 72(11), pp. 5429–5436, 1992. +[6] A.Gibrekhterman et al., “Characteristics of secondary electron emission from csi induced by x +rays with energies up to 100 kev,” J.Appl.Phys, vol. 74, pp. 7506–7509, 1993. +[7] A.Gibrekhterman et al., “Spatial characteristics of electron- and photon- induced secondary +electron cascades in csi,” J.Appl.Phys, vol. 76, pp. 1676–1680, 1994. +[8] P.Mine´, “Photoemissive materials and their application to gaseous detectors,” Nucl. Inst. and +Meth. A, vol. 343, pp. 99–108, 1994. +[9] J.Teichert et al., “Report on photocathodes,” tech. rep., CARE/JRA-PHIN, 2004. +http://www.fzd.de/projects/CARE/index.files/reports/report.pdf. +[10] W.C.Walker et al., “Photoelectric yield in the ultraviolet,” J.Appl.Phys., vol. 26(11), pp. 1366– +1371, 1955. +[11] W.F.Krolikowski et al., “Photoemission studies of the noble metals. ii. gold,” Phys.Rev.B, +vol. 1(2), pp. 478–487, 1970. +52 BIBLIOGRAPHY +[12] R.H.Day et al., “Photoelectric quantum efficiencies and filter window absorption coefficients from +20ev to 10kev,” J.Appl.Phys., vol. 52(11), pp. 6965–6973, 1981. +[13] B.L.Henke et al., “The characterization of x-ray photocathodes in the 0.1-10kev photon energy +range,” J.Appl.Phys., vol. 52(3), pp. 1509–1520, 1981. +[14] G.W.Fraser et al., “The characterization of gold x-ray photocathodes,” Nucl. Inst. and Meth. A, +vol. 321, pp. 376–380, 1992. +[15] H.Henneken et al., “Absolute total yield of au(111) and cu(111) surfaces,” Journal of Electron +Spectroscopy and Related Phenomena, vol. 101-103, pp. 1019–1024, 1999. +[16] M.Hirata et al., “X-ray detection characterization of gold photocathodes and microchannel plates +using synchrotron radiation (10ev-82.5 kev),” Nucl. Inst. and Meth. B, vol. B66, pp. 479–484, +1991. +[17] S.Gosavi et al., “Stability improvement at high emission densities for gold thin film photocathodes +used in advances electron beam lithography,” J. Vac Sci. Technol. B, vol. B19(6), pp. 2591–2597, +2001. +[18] M.J.Powers et al., “Observation of a negative electron affinity for boron nitride,” Appl.Phys.Lett, +vol. 26, pp. 3912–3914, 1995. +[19] G.A.Allen, “The performance of negative electron affinity photocathodes,” J. Phys. D, vol. 4, +pp. 308–317, 1971. +[20] S.H.Kong et al., “Photocathodes for free electron lasers,” Nucl. Inst. and Meth. A, vol. A358, +pp. 272–275, 1995. +[21] K.A.Elamrawi et al., “Preparation and operation of hydrogen cleaned gaas(100) negative electron +affinity photocathodes,” J. Vac Sci. Technol. A, vol. A17(3), pp. 823–831, 1999. +[22] F.S.Shahedipour et al., “Efficient gan photocathodes for low-level ultraviolet signaldetection,” +IEEE Journal of Quantum Electronics, vol. 38(4), pp. 333–335, 2002. +[23] M.P.Ulmer et al., “Progress in the fabrication of gan photocathodes,” Proc. SPIE, vol. 4288, +pp. 246–253, 2001. +[24] P.Sandvik et al., “alxga1−xn for solar blind uv detectors,” J. Cryst. Grow., vol. 231, pp. 366–370, +2001. +[25] D.J.Leopold et al., “High quantum efficiency ultraviolet/blue algan/ingan photocathodes grown +by molecular epitaxy,” J.Appl.Phys., vol. 98, pp. 043525–1,5, 2005. +[26] E.A.Taft et al., “X-ray induced radiation damage in csi, gadox, y2o2s, and y2o3 thin films,” Phys. +Chem. Solids, vol. 3, p. 1, 1957. +BIBLIOGRAPHY 53 +[27] J.Edgecumbe et al., “Attenuation length for secondary electrons in bulk-density kcl and csi,” +J.Appl.Phys., vol. 37, pp. 2916–2917, 1965. +[28] J.Edgecumbe et al., “Csi as a high-gain secondary emission material,” J.Appl.Phys., vol. 37, +pp. 3321–3322, 1966. +[29] V.Dandendorf et al., “Progress in ultrafast csi-photocathode gaseous imaging photomultipliers,” +Nucl. Inst. and Meth. A, vol. A308, pp. 519–532, 1991. +[30] E.Shefer et al., “Photoelectron transport in csi and csbr coating films of alkali antimonide and +csi photocathodes,” J.Appl.Phys., vol. 92(8), pp. 4758–4771, 1993. +[31] A.Breskin et al., “New ideas in csi-based photon detectors: Wire multiplication and protection +of the photocathode,” IEEE Trans.Nucl.Sci, vol. 42(4), pp. 298–305, 1995. +[32] J.E.Lees et al., “Thermally annealed soft x-ray photocathodes,” Nucl. Inst. and Meth. A, vol. 381, +pp. 453–461, 1996. +[33] H.S.Cho et al., “A columnar cesium iodide (csi) drift plane layer for gas avalanche microdetec- +tors,” IEEE transaction on Nuclear Science, vol. 45(3), pp. 275–279, 1998. +[34] L.Periale et al., “Evaluation of planar gaseous detectors with csi photocathodes for the +detection of primary scintillation light from noble gases,” conference paper Presented at +the 1st Topical Symposium on Functional Breast Imaging with Advanced Detectors, 2001. +http://arxiv.org/pdf/physics/0106070. +[35] E.Schyns et al., “Status of large area csi photocathodes developments,” Nucl. Inst. and Meth. +A, vol. 494, pp. 441–446, 2002. +[36] A.Di.Mauro et al., “Study of the quantum efficiency of csi photo-cathodes exposed to oxygen +and water vapour,” Nucl. Inst. and Meth. A, vol. 461, pp. 584–586, 2001. +[37] A.Breskin et al., “Electric field effects on the quantum efficiency of csi photocathodes in gas +media,” Nucl. Inst. and Meth. A, vol. 344, pp. 537–546, 1994. +[38] T.H.V.T.Dias et al., “The transmission of photoelectrons emitted from csi into xe, ar, ne, and +their mixtures: a monte carlo study of the dependence on e/n and incident vuv photon energy,” +J.Appl.Phys., vol. 37, pp. 540–549, 2002. +[39] R.Aleksan et al., “Measurement of csi photocathode quantum efficiency in methane,” Nucl. Inst. +and Meth. A, vol. 343, pp. 173–191, 1994. +[40] S.Hanany et al., “Measeurement of the electron yield of csi with polarized x rays,” Phys.Rev.B, +vol. 48(2), pp. 701–709, 1993. +[41] A.S.Tremsin et al., “X-ray induced radiation damage in csi, gadox, y2o2s, and y2o3 thin films,” +Nucl. Inst. and Meth. A, vol. 459, pp. 543–551, 2001. + +Chapter 4 +The Simulations by Monte Carlo Method +This chapter presents the study by Monte Carlo of the photocathodes performed in this work. +The chapter is divided into four parts : +1. A general introduction to the Monte Carlo Method, +2. a description of the Monte Carlo code developed in this work is given, +3. a detailed analysis of the limits of Monte Carlo methods in the case of particle tracking into +matter is given, and the reason why these limitations forbid the use of this method in the case +of photocathode analysis +4. Conclusions on this part of the work. +4.1 A first approach to Monte Carlo +4.1.1 History +The Monte Carlo Method is called after the city of the Princi- +pality of Monaco, because of the roulette (and similar games), +seen as a random number generator. This name and the sys- +tematic development of the Monte Carlo Method date from +about 1944. +Before, there had been several isolated instances of this method, +some of them on much earlier occasions (see the examples given +in B.1). Those methods were only rarely actually used for sci- +Figure 4.1 : Monaco’s Casino entific purpose. A reason for this is the necessity to make a +large number of repetitive operations to achieve ”a good pre- +cision”. This is the arrival of computers, which created a greater interest for this sort of simulations. +56 The Simulations by Monte Carlo Method +The principles of the Monte Carlo Method are due to the polish mathematician Stanislaw Ulam, +when he was working in Los Alamo for the Manhattan Project[1]. +Those developments were implied by the work on the atomic bomb, which needed a direct simula- +tion of the probabilistic problems of neutron diffusion in fissile materials. But even at an early stage +of the project, Stanislaw Ulam and John von Neumann refined the method to a more general theory[2]. +Finally, the systematic development of the method occurred only in 1948 with the work of Harris +and Herman Kahn. From this moment, the method had a fast development, and already in 1948, +Fermi, Metropolis, and Ulam obtained estimations for the eigenvalues of Schrodinger’s equation. The +Method became intensively used in extremely various fields from 1970, thanks to the new generation +of computers. +4.1.2 Description of the Monte Carlo Method +A possible definition: The Monte Carlo Method, as it is understood now, encompasses any tech- +nique of statistical sampling employed to approximate solutions to quantitative problems. +Said another way, the Monte Carlo Method gives an approximate solution to a problem using a sta- +tistical approach. The method consists in performing statistical sampling experiments, and applying +the central limit theorem1 to determine the general behavior of the studied system. It applies to +problems with no probabilistic content, as well as to those with inherent probabilistic structure. +The progress in terms of performance of modern computers has enabled the use of the Monte Carlo +Method in an increasing number of problems, and it has now several fields of applications: the most +common problem treated via a Monte Carlo approach are: +• Particle Transport through matter (detailed in 4.1.3), +• Astrophysics models, +• Molecular studies (”classical”, ”quantum”, ”path-integral”, ”volumetric”, molecular dynamic, +etc...), +• Evaluation of multi dimensional integrals (see example in annex B.1.1), +• solving the integro-differential equations defining the radiance field. +All those applications have lead to new development in various areas, for example the last application +has been used in global illumination computations, which is a way to produce photo-realistic images. +As a Result, Monte Carlo Methods have been usefully employed in industries as various as that of +Graphics industry (in the case of ray tracing softwares, see the case of the Radiance software [3]), +Finance [4], or Search And Rescue and Counter-Pollution, where models are used to predict the drift +of a life raft or of an oil slick on the sea. +1The Central Limit Theorem states that if the sum of independent random variables has a finite variance, then it +will be approximately normally distributed. +said another way: Given a population with a mean of µ and a deviation σ, then the sampling distribution of the mean +has a mean of µ and deviation of σ (N being the sample size). +N +4.2 The Geant4 toolkit for particle transport into matter 57 +4.1.3 The Monte Carlo Method in Particle Transport +There are mainly two different approaches to study the transport of particles through matter: +• The deterministic methods, in which the transport equation is solved. +• The Monte Carlo approach, in which single particle transports are computed. +It is said sometimes that, while the deterministic approach consists in solving the integral transport +equation, the Monte Carlo approach consists in solving the integro-differential transport equation. +This statement (which is incorrect, for the integral and integro-differential equations, are +actually a single one put in two different forms) illustrates the difference between the two approaches: +The deterministic methods return a general law of behavior of the particles, and a complete set of +information (flux, penetration, etc...). +In contrast, the Monte Carlo Method does not solve an explicit equation, but obtains the solution +by simulating individual particle transports and interactions with matter and by recording all the +information along the trajectories of the particle. Then the central limit theorem enables to determine +the general behavior of the particles by making a statistic analysis of the recorded information. +The particle transport simulation consists in tracking the particles one by one, by evaluating at each +step the probability of interaction with matter. The probability densities of interaction (calculated +according to various parameters such as the particles energy, type, bias... and the material type, +density...) are used in addition to a random number generator to determine the step length, and the +interaction type, which will happen. Thus, the particle behavior is not deterministic but governed by +probabilistic laws, following the quantum nature of fundamental interactions. +The interaction laws used in the simulation are obtained from the quantum mechanics theory (for +their analytical form), and from experimental measurements (the cross sections, which describe ”the +probability of interaction”). +The major problem of the Monte Carlo Methods for particle tracking is the need of computer power +to achieve simulations with an acceptable precision (i.e. enough particles tracked to achieve a good +statistics). Only modern powerful computers are able to perform the simulations in an acceptable +time (a few hours). +4.2 The Geant4 toolkit for particle transport into matter +The development of a Monte Carlo code is a very ambitious project, especially if it is meant to study +many materials. So it was preferred to use a general toolkit with proven capacities at low energies. +Several codes were considered (Penelope, MCNPX, EGSnrc, Geant4). Geant4 was chosen because +of various reasons, including: +• It has become a standard among Monte Carlo codes. +• It is well documented and open source, thus it gives straighter access to code and physics +verification. +58 The Simulations by Monte Carlo Method +• It is provided with numerous tools, which simplify data analysis. +• It has a series of libraries dedicated to low energies. +Among the disadvantages of Geant4 when compared to other codes: +• It is harder to program, as the user has to make the program himself (no script language to +command Geant4). It is written in C++. So the user needs basic notions of object-oriented +programming. +• Complex setup of the program (compilation, configuration settings...) +Those difficulties are also the strength of Geant4, for they find their origin in the very high versatility +of the toolkit, and in its cross-platform nature. +Geant -for GEometry ANd Tracking- is a simulation toolkit developed for the tracking of particles +through matter. It has been developed by more than 100 scientists from 10 institutions and has now +become a worldwide reference. +The first version was developed at CERN and dates from 1974. Up to version 3.21, Geant was made +in Fortran, and was mainly dedicated to high energy physics. From 1994, a new version completely +written in C++ and with modern object oriented structure was developed. +The toolkit includes facilities for handling complex geometries, tracking particles, simulating detector +response, handling run management and the user interface. +Its possibilities were also expanded, and Geant4 is now routinely used in fields as various as: +• High energy and nuclear physics, +• Medical applications, +• Space industry development, +• Accelerator physics, +• Lower energy physics ... +The reference article for Geant42 was published in Nuclear Instrument and Methods in Physics Re- +search A: [5]. +4.2.1 The way Geant4 computes particle propagation +4.2.1.1 The tracking of the particles +The core of the method consists in tracking the particles one by one, letting them having all possible +physical interaction with matter3. It takes into account: +• the particle intrinsic properties, its direction, energy... +2The reference webpage of Geant is currently : http://cern.ch/geant4/ +3Geant uses a combination of the composition and rejection Monte Carlo Method . The exact description of those +two methods will not be done here, but those who have interest can have a look at the book from H.Messel and al. [6], +at the article from J.C.Butcher and al. [7], and at the EGS4 Code System Manual [8]. +4.2 The Geant4 toolkit for particle transport into matter 59 +• all physical processes applicable to the current particle (ex. for a photon the photoelectric +effect, for an electron the bremsstrahlung ...). +• the volume boundaries, the material characteristics (geometrical information), +• the electromagnetic fields. +One usually makes the difference between the primary particles, which are generated by the program- +mer with defined type, momentum, position, etc... and the secondary particles, which are generated +by previous interactions of other particles with the matter or their disintegration (unstable particles). +Of course the secondaries can generate other secondaries. In Geant4 any created particle is tracked +until it has a zero energy (absorption). +In Geant4, the basic element of the tracking is the Step. It consists of two points (start and end +point) and the ”delta” information of the particle: +• step length, +• energy loss during step, +• change in elapsed time, +• change of direction, etc. +A step can be summarized the following way (see table 4.2): +→ The particle velocity is calculated, +→ A step length is associated to each physical process: +The probability of interaction weighed by a random number is computed, and converted into +a distance. +The minimum of all computed distances (ie. the limiting physical process) defines the physical +step length. +→ The navigator finds ”safety”: the distance to nearest boundary in the direction of the particle. +→ the minimum of physical step length and safety is kept as the step length +→ If the physics process has limited the step, the interaction is done (interaction before the +boundary of the volume). Otherwise the particle is transported to the next volume. +→ If the particle was not killed during the track, it is ready for the next step. Eventually, +secondary particles are stored for later tracking. +Before the following step is performed, Along step physical processes are applied (for example +scattering). +→ Last, the track properties are updated (momentum, position, time, etc...). +60 The Simulations by Monte Carlo Method +Figure 4.2 : Tracking procedure of particles in Geant4 +At the end of the tracking process of one particle, one can eventually store the trajectory, which is +the compilation of steps, which happened when tracking the particle. +To have a better description of the tracking processes4, the interested reader should refer to chapter +5.1 of the Geant4 Users Guide [9]. Alternatively, the reference publication of Geant4 published by +the Geant4 community in Nuclear Instrument and Methods in Physics Research A: [5] gives a rapid +overview of the way particles are tracked. +4Especially to have a proper description of the way discreet and continuous processes are taken into account, and +the way boundaries are treated. +4.2 The Geant4 toolkit for particle transport into matter 61 +4.2.1.2 The physical interactions in Geant4 +The sets of physical processes +Geant4 offers two sets of processes describing particle interactions with matter: +• The historical one, dedicated to the high energy physics. +• The low energy extension of electromagnetic process, which has been developed since 1997, +intends to extend the validity of Geant4 down to low energy. It can now simulate physical +process down to 250 eV (and up to 100 GeV) with atomic numbers between 1 and 99. +This extension is described both in the User Guide [9] and in the Physics Reference Manual +[10] 5 +In addition, Geant4 also enables the user to use the set of processes from the Penelope Monte Carlo +toolkit [11]. This way the users are offered two flavors of Low Energy physical processes, and rapid +comparison can be obtained. +Cross Sections +The physical processes involved in particle transport through matter have a quantum nature, meaning +that they do not follow a deterministic behavior. +On the other hand, their behavior is very well described by a probabilistic approach: the probability +of interaction of a particle with a material is fixed. It is measured by the cross section σ and expressed +in unit of area (usually in barn ≡ 10−28 m2). The cross section can be understood as the apparent +surface as seen from an incoming particle of an atom. In the case of a thin foil, the probability of +interaction of the incoming particle is n σ/S with S the surface of the foil and n the number of atoms +contained in the foil. +In practice σ varies greatly with the nature of the particle, and its energy. +The various sorts of interactions of the particle with matter have corresponding cross sections. +The differential cross section dσdΩ describes the probability to observe a scattered particle per unit of +solid angle Ω. +Cross sections used in Geant4 result from measurements as often as possible. When those data are +unavailable, then only an analytic formula is used to build the cross section data. For the data are +provided as series of discrete values, an interpolation formula is used to have access to any value of +the energy: +log(σ1) log(E2/E)− log(σ2) log(E1/E)log(σ(E)) = . (4.1) +log(E2/E1) +The set of data used in Geant4 for the determination of the cross sections and for sampling of the +final states are extracted from a set of publicly distributed evaluated data libraries (for the low energy +extension): +5The low energy extension has its website here http://www.ge.infn.it/geant4/lowE/index.html +62 The Simulations by Monte Carlo Method +• EPDL97 (Evaluated Photon Data Library) : [12] +• EEDL (Evaluated Electron Data Libraries) : [13] +• EADL (Evaluated Atomic Data Libraries) : [14] +• stopping power data : [15, 16, 17, 18] +Those sets of data are well described in their reference manual which can be obtained from Lawrence +Livermore National Laboratory’s website6. +4.2.1.3 Analysis and Representation tools +The Geant4 toolkit offers numerous interfaces to access all physical parameters while the simulation +is running. It has also dedicated libraries for trajectories and other data storing. So the user can +record the information it has interest for later analysis. +But Geant4 is also AIDA compliant, meaning it has access to all the functionalities AIDA offers for +online data analysis and histogramming/tuppleing. +AIDA is a set of abstract interfaces and formats for data representation. There are various imple- +mentations of AIDA, offering all sorts of tools for data analysis (filtering, combination, etc...), and +representation (histograms, ntupples/data trees...). +For Geant4 possesses a direct interface with AIDA compliant tools, it is possible to make the analysis +of the simulations performed online and to store the results of those simulations. This is of particular +importance, as Monte Carlo simulations produce enormous amounts of data, which can be very long +to analyze. +Of course the data recorded can be further studied and exported thanks to dedicated softwares, which +are also AIDA compliant. +In addition, Geant4 possesses interfaces for 3D representation of the geometry and particles trajec- +tories in the volume. This is of strong help for complex geometries definitions. +4.2.2 The simulation tool developed +4.2.2.1 Description and Functionalities +The code developed was expected to +• help understanding the physics of the photocathodes in the X-ray energy range, +• compare various geometries of photocathodes, +• help predicting the efficiencies of unstudied materials. +For the description of the physical processes is rather straightforward in the Geant4 toolkit, the +hardest part was the implementation of the tools to perform detailed analysis of the simulations. +The following libraries of Geant4 or common associated tools were chosen for the implementation: +6http://www.llnl.gov/cullen1/photon.htm +4.2 The Geant4 toolkit for particle transport into matter 63 +Concerning the Physics +The Low Energy Extension was used to perform all the simulations. +All processes involving photons were activated except the pair creation, which has no sense for sim- +ulations of photons having energies lower than 100 keV. +So the following processes were activated: +• The Photoelectric effect (G4LowEnergyPhotoElectric library). +Both Fluorescence and Auger de-excitations of photoionized atoms were activated. +By default, the photoemitted electron has the same direction as the incident photon. Instead, +the use of the standard electron angular emission generator was forced. Unfortunately, this an- +gular distribution corresponds only to electrons emitted from the K-shell. For most interactions +of X-rays in the targeted energy range occur with electrons from the K-shell, this limitation is +not a real problem. +• The Compton Scattering process (G4LowEnergyCompton Library). +• The Rayleigh Scattering process (G4LowEnergyRayleigh). +Concerning electrons, all the processes were also activated: +• Electron Ionization (Library G4LowEnergyIonisation). +Here again Auger and Fluorescence desexcitations of the ionized atom were activated. +• The Bremsstrahlung continuous loss of energy of electrons (Library G4LowEnergyBremsstrahlung). +• Electron scattering, which corrects path lengths and lateral displacements after each step for +charged particles (Library G4MultipleScattering). Identically Auger as well as Fluorescent +desexcitations were activated, for accurate simulations. +Cut Lengths (corresponding in Geant4 to energies under which no secondary particles are created), +were always set to their minimum values (≡ 250 eV). +Concerning the data analysis tools +Nb emitted e−To calculate the overall efficiency of the photocathode (calculated as Queff = Nb incoming photons), a +direct implementation was used. A csv (comma separated value file format) file was happened after +each simulations with Quantum Efficiency, and the photocathode parameters (Material, geometrical +information...). +All other information extracted from the simulations were recorded thanks to the AIDA interface. +A global Tupple Manager was created and linked to the various manager of the code (RunManager, +EventActionManager...), in order to enable information to be grabbed in the proper instances of the +code7. +More than 20 histograms, 2D clouds... were created to enable a proper track of the simulations. +7For example, Information regarding physical processes in the StepManager, +Information regarding the deposition of the photons/electrons in the EventActionManager... +64 The Simulations by Monte Carlo Method +4.2.2.2 The test of the code, comparison with experimental values +Various tests were made to confront the code with experimental data. Unfortunately, it turned out +that the code is not able to simulate properly the photocathodes. +In this part, success and failures of the code are exposed, and an explanation is given to those limi- +tations. +The aim of the simulations +Various authors were able historically to create codes based on the Monte Carlo Method calculating +successfully the efficiencies of photocathodes (especially for CsI, [19, 20] already cited in section 3.2). +So it was natural to try to develop a code based on the latest technologies to help studying new +materials for photocathode applications. +The code was expected to provide reasonable predictions of the efficiency of one material, the influence +of the geometry, and the influence of an electric field. +It was planed to use it to study novel sorts of photocathodes, with materials and geometries untested +so far. +In none of those expectations, an exact value was considered as mandatory, but an error of less +than 10 % can be considered as a minimum requirement to be able to use the code for predictions +on the efficiency of new materials. +Unfortunately, it turned out rapidly that this precision could not be reached with the code developed: +the calculated values were always largely underestimated and with an error for some materials of more +than one order of magnitude ! +It is likely that this error can be bettered by a refinement of the code for each material studied. But +this process is long and uncertain, and it involves several experimental tests to adjust the physical +model used for each material. +This study was out of purpose in the scope of this work, which aims in testing several materials. +Examples of results returned by the code and discussion +Gold and CsI were taken as reference materials to test the code. As both materials were intensively +studied, it was easy to find reliable measurements of their absolute efficiencies. +For Gold, the measurements made by B. L. Henke et al. at the BESSY-I and II light sources [21] +were taken as a reference (Figure 4.4, and for CsI, the measurement by G.W.Fraser were taken (Figure +4.3). +In the simulation, the photocathode thickness is 1 µm, and the efficiency is calculated from the +electrons escaping the photocathode on the side of the incident photons (following the corresponding +measurements in the cited publications). +4.2 The Geant4 toolkit for particle transport into matter 65 +Figure 4.3 : Quantum Efficiency of CsI as computed by the code, and measured +Figure 4.4 : Quantum Efficiency of Gold as computed by the code, and measured +66 The Simulations by Monte Carlo Method +4.2.2.3 The limits of the Monte Carlo Method +A deep investigation of the code and of the Monte Carlo Method was performed to understand why +the simulations were providing such bad results. +First the Geant4 toolkit was compared with another well known code: Penelope, developed mainly +at the University of Barcelona (PENetration and Energy Loss Of Electrons and Positrons in matter, +[22, 23]). This toolkit did not give better results. The same toolkit was also tested through its +implementation into Geant4. +After some investigation it became clear that several problems could explain why the code would +return wrong results: +• A problem of Approach: The Monte Carlo Method is based on a particle/nucleus interaction +approach. The models do not include a priori, differences between the various chemical states +and physical structures, which coexist in one material (chemical bounding, crystalline structure, +grain joins, etc...). Yet those states can have a large impact on the dynamic of electrons in the +material, for any defect in the crystallinity of the material corresponds to a trap. In particular, +a semiconductors and metals are treated mainly the same way. +In the case of X-rays and energetic electrons, this approximation can be considered as not too +rough for at high energies, most interactions occur with electrons of the core shells of the atoms. +Those inner shells being practically unperturbed, the corresponding cross sections do not vary +sensibly. +But when it comes to lower energy electrons, most interactions occur with the outer shell +electrons or with free electrons, so the result becomes largely affected by the precise form of +the material (chemical state, bounding to neighboring atoms, etc...), as well by its purity and +its structure (change of band structure, traps, etc...). This is the main limiting factor for +simulations at low energies[24] . +Unfortunately, concerning photocathodes, the key phenomenons occur at this energy, for most escap- +ing electrons have an energy of only a few eV. +In addition, a number of other difficulties appear at small energy: +• The quality of experimental data at low energies. Experimental cross sections at low +energies are extremely hard to obtain with a good precision. Actually, only some indirect data +can be used, like the stopping power for electrons through a thin slab, characteristic energy losses +(plasmon excitations), and the total mean free path for inelastic scattering. +On the other hand it is not possible to theoretically determine the values of the cross sections, +as this implies solving the many-body interaction problem in solids. +In practice, while cross sections are provided down to very low energies, their precision is +considered as extremely poor. +• The infrared divergence. As explained previously, at low energies, particles tend to create +large numbers of secondaries, which in turn create an even greater number of daughter particles. +4.3 The simulation performed 67 +To avoid this, the Monte Carlo codes block the creation of secondary particles under a certain +cut off energy. This is extremely bad for the simulation of photocathodes, as it turns out that +secondary electrons are the main contributors to the total yield (from 80 % for materials like +gold to more than 99.5 % in the case of CsI[21]). +• The specific problem of electron extraction from the material. As emphasized by the +Spicer model, the extraction of the hot electrons from the surface is a key problem, for the +electrons have to overpass a barrier of potential to reach vacuum. Those potentials are of the +order of a few eV high, so they are far too small to be properly simulated by Monte Carlo codes. +Moreover, according to B.L.Henke et al.[21], most secondary electrons have an energy inferior +to 10 eV . The interested reader can also read the publication by A.Gibrekhterman et al., which +details the proportions of primary to secondary electrons contributing to the emitted current +in [19] in the case of CsI. Also B.L.Henke et al.[25] detail how the conditions of cleanness of the +surface can have a major impact on the emission efficiency. +So the major difficulties arise from the strong dependence of the photocathode quantum efficiency on +physical effects, which occur at energies unreachable by conventional general purpose Monte Carlo +codes. +The few codes, which succeeded to overcome this difficulty are based on analytical formula with free +parameters such as the probability of loss of an energy ~ω per unit energy, momentum, and path. +This method enables to obtain codes in very good agreement with experimental data, but they are +material specific and cannot be extended to other materials in general (see the very interesting work +by T. Boutboul et al.[20] in the specific case of CsI). +In conclusion, if the transport of the X-rays is well simulated by the Monte Carlo codes, the simulation +of the very low electron dynamics in solid state materials is far from being enough refined to enable +a proper simulation of the photocathodes. +4.3 The simulation performed +Despite of the bad performance of the code to reproduce quantitatively the efficiency of the pho- +tocathodes, simulations were performed to study the possibility of a qualitative description of the +enhancement of the efficiency by varying the geometrical structure of the photocathode. +The result of those simulations is presented in this section. +4.3.1 The simulations performed +The simulation of flat photocathodes was performed to check the validity of the code. The results were +presented in the section 4.2.2.2. They serve as the basis to compare with the efficiency of structured +photocathodes. +Different types of structures were simulated: +• Structures with ”pillars” +68 The Simulations by Monte Carlo Method +• Structures with ”pyramids” +• Chevron like structures +• Structures randomly or periodically placed... +Those studies enabled to optimize the thickness of the photocathodes as function of the energy of +the incoming photons. Indeed, the most energetic electrons are those, which exit the photocathode +from the deepest places, and they are also those which are correctly simulated by the code, for their +energy is high. +For example Figure 4.5 shows the position of photoemission of the electrons, which reached the vac- +uum in the simulation for two different energies. It clearly appears that, from the point of view of the +escape length of the electrons, a photocathode of thickness 0.5 µm is too thick for low energies (here +10 keV) but well adapted for higher energies (50 keV). Both the pillar structures and the underlying +layer are made of the photoemissive material (gold). +Figure 4.6 shows the simulation of a pyramidal structure with only the outer layer being photoemis- +sive. This corresponds to the case of structures, which are covered with the photoemissive material +(gold). The underlying structure would be made of a low absorbing material (like capton), which is +not simulated. +4.3 The simulation performed 69 +Figure 4.5 : Simulation of Pillars structures on a photocathode of sizes 0.8 µm height and 0.4 ∗ 0.4 µm2 +size. Each dot corresponds to the creation of one electron, which exited the bulk. Top Picture corresponds to +a photon energy of 10 keV, and Bottom picture to photon energy 50 keV. +70 The Simulations by Monte Carlo Method +Position of escaping electrons (transmited and reflected) X vs Z (in mum) +0,0020 +0,0019 +0,0018 +0,0017 +0,0016 +0,0015 +0,0014 +0,0013 +0,0012 +0,0011 +0,0010 +0,0009 +0,0008 +0,0007 +0,0006 +0,0005 +0,0004 +0,0003 +0,0002 +0,0001 +0,0000 +-0,0001 +-0,0002 +-0,0003 +-0,0004 +-0,0005 +-0,0006 +-0,0007 +-0,0008 +-0,0009 +-0,0010 +-0,0011 +-0,0012 +-0,0013 +-0,0014 +-0,0015 +-0,0016 +-0,0017 +-0,0018 +-0,0019 +-0,0020 +-0,00020 -0,00015 -0,00010 -0,00005 0,00000 0,00005 0,00010 0,00015 0,00020 0,00025 0,00030 0,00035 0,00040 0,00045 0,00050 +Position of escaping electrons (transmited and reflected) X vs Z (in mum) + Entries : 11293 +0,0021 XMean : 1.3861E-4 +0,0020 XRms : 1.4593E-4 +0,0019 YMean : 1.3237E-4 + YRms : 5.7028E-3 +0,0018 +0,0017 +0,0016 +0,0015 +0,0014 +0,0013 +0,0012 +0,0011 +0,0010 +0,0009 +0,0008 +0,0007 +0,0006 +0,0005 +0,0004 +0,0003 +0,0002 +0,0001 +0,0000 +-0,0001 +-0,0002 +-0,0003 +-0,0004 +-0,0005 +-0,0006 +-0,0007 +-0,0008 +-0,0009 +-0,0010 +-0,0011 +-0,0012 +-0,0013 +-0,0014 +-0,0015 +-0,0016 +-0,0017 +-0,0018 +-0,0019 +-0,0020 +-0,00020 -0,00015 -0,00010 -0,00005 0,00000 0,00005 0,00010 0,00015 0,00020 0,00025 0,00030 0,00035 0,00040 0,00045 0,00050 +Figure 4.6 : Simulation of periodically placed pyramidal structures with a photon energy of 5 keV. The top +picture is a photocathode of thickness 0.1 µm and height 3 µm. The bottom picture is a photocathode with the +same parameters except the thickness: 2.5 µm. +4.3.2 Use of the simulations for thickness optimization +The simulations performed enabled to confirm that the electrons photoemitted have a very short mean +free path in the photocathode. No quantitative differences in terms of efficiency could be extracted +for the different thickness. Only a qualitative analysis thanks to diagrams like on figures 4.5 or 4.6 +4.4 Conclusion on this part of the work 71 +enabled to define optimized thickness. +According to this analysis, for energies in the order of a few keV (as the main target of energy range +in this application), thickness of the order of a fraction of a micron seem to be the most suitable, for +all tested material. Larger thickness indeed result in dead zone in the middle of the photocathode, +and imply larger structures, which corresponds to a smaller surface of the photocathode, and so to a +lower efficiency. +This result was predictable from the known mean free paths of electrons in photoemissive materials. +4.3.3 Simulation of the impact of structures on the photocathode +Even if the code cannot simulate properly the quantum efficiencies of photocathodes for X-ray de- +tectors, it is a priori not out of hope that it can help to evaluate the effect of structures on the +photocathodes. +To test the validity of the code for this, after the first experimental test of structures had been done, +the simulations were compared to the experimental results. +The measurements to perform this verification are detailed in section 7.1.2. The sample Trizact 143 +is constituted of periodic square pyramids of sizes 500 µm length and height ∼ 160 µm (see Figure +7.4 and 7.5). The faces form an angular of 57oC with respect to the base plane. The sample was +covered with a gold layer of thickness 0.3 µm. +The measurement indicate an increase of quantum efficiency of a factor ∼ 1.9 in good agreement with +the theoretical value of 1cos(57) = 1.9 (see section 6.2.1). +The simulation by Monte Carlo of the flat surface calculated a quantum efficiency of 0.088 % (cf +Figure 4.4) for an energy of 5 keV. +With the geometry of the trizact sample, the code returns a quantum efficiency of 0.12 %. This +corresponds to a gain of a factor: ∼ 1.4. +So here again, the code fails to predict correctly the increase of quantum efficiency due to the struc- +tures on the surface. +4.4 Conclusion on this part of the work +Use of the code for photocathode simulations +Unfortunately, the application developed cannot be used to predict theoretically the quantum effi- +ciencies of novel photocathodes. +The limits of the Monte Carlo Method for Photocathodes Simulations. +The impossibility to simulate properly the photocathodes properties, lies in the poor simulation of +the particles interactions with matter. This is due to the incomplete cross section knowledge +for very low energy particle-matter interaction. +72 The Simulations by Monte Carlo Method +More precisely, in the case of the photocathode simulations, the electrons behavior could not be +simulated with a sufficient precision (while the simulation of the photons interaction were precise +enough). +So, in order to use a monte carlo approach to simulate X-ray photocathodes, one must first determine +precisely cross sections at energies down to a few eV. +To obtain those cross sections at such energies, it is not possible to study each material and combine +the obtained cross sections to simulate mixtures of them like it is usually done at high energy for +such an approach cannot take into account the chemical state of the atoms. +So each material has to be studied one by one. +Is is possible to use Monte Carlo codes for photocathode simulations ? +It is possible to overcome the lack of knowledge of the cross sections at low energies by introducing +free parameters, which are then fitted on experimental data. This approach was successfully used to +study CsI [20] and enabled a much better understanding of the material. +Of course this sort of method is material specific and cannot be used for general purpose photocath- +odes simulations (to study a great number of photocathode material). +This sort of analysis being out of the scope of this thesis work, the code was not further used, except +for trivial thickness optimization analysis. +It should also be noted that the developped application would likely have been more successful in +simulating the photocathode properties used with more energetic photons. +As with increasing photon energies, the fraction of energetic electrons contributing to the yield in- +creases [21], the code is more capable of simulating the photocathodes properties. +The lack of experimental data at higher energies did not permit to test further the code, and here +again it was not in the scope of this thesis work to investigate further the limits of the code. +So it is not hopeless to use a Monte Carlo code to simulate the efficiency of photocathodes in the +case of photocathodes used with more energetic photons. +In particular, Geant4 offers all the needed flexibility to implement cross sections with better precision, +and to adapt the Monte Carlo method to the specific case of very low energies particles. +The only limitation would be the power of the computer, as the number of secondary particles would +increase dramatically (infrared divergence). +Possible other methods for the simulations of photocathode simulations +with low energy photons. +Other methods to simulate photocathodes properties are analytical methods like the three step model +introduced by Spicer (see section 3.1) or more simply an evaluation of the efficiency by considering +the product Eµ(E) (with E the energy, and µ the photoionization cross sections). +Those methods do not provide quantitative evaluations of photocathodes quantum efficiencies Yet. +4.4 Conclusion on this part of the work 73 +It remains that this part of the work was of great help to understand the various processes and +parameters, which are key for the quantum efficiency of photocathodes in the hard X-ray energy +range. This has proven to be of great help for the following research of new materials for photocathode +applications. + +Bibliography +[1] S. U. et al., “Statistical methods in neutron diffusion,” LAMS-551, Los Alamos National Labo- +ratory, 1947. +[2] S. U. et al., “The monte carlo method,” Journal of American Statistical Association, vol. 44, +p. 335, 1949. +[3] G.Ward et al., “The holodeck ray cache: An interactive rendering system for global illumination +in nondiffuse environments,” ACM Transactions on Graphics, vol. 18(4), pp. 361–98, 1999. +[4] P.Jaeckel, Monte Carlo Methods in Finance. John Wiley and Sons, 2002. +[5] Agostinelli et al., “Geant4-a simulation toolkit,” Nucl. Inst. and Meth. A, no. 506, pp. 250–303, +2003. +[6] H.Messel et al., Electron-Photon shower distribution. Pergamon Press, 1970. +[7] J.C.Butcher et al., “Electron number distribution in electron-photon showers in air and aluminum +absorbers,” Nucl. Phys., no. 20, 1960. +[8] R.Ford et al., “The egs4 code system,” Tech. Rep. 265, Slac, Stanford, 1985. +[9] Geant4 Community, Geant4 User Guide-for application developers. +[10] Geant4 Community, Physics Reference Manual. +[11] F.Salvat et al., “A code system for monte carlo simulation of electron and pho- +ton transport,” Workshop Proceedings, Barcelona, Spain, 4-7 July 2006: OCDE NEA, +p. http://www.nea.fr/html/dbprog/peneloperef.html, 2006. +[12] D.Cullen et al., “Epdl97: the evaluated photon data library, 97 version.” +[13] S.T.Perkins et al., “Tables and graphs of electron-interaction cross-sections from 10 ev to 100 +gev derived from the llnl evaluated electron data library (eedl), z=1-100.” +76 BIBLIOGRAPHY +[14] S.T.Perkins et al., “Tables and graphs of atomic subshell and relaxation data derived from the +llnl evaluated atomic data library (eadl), z=1-100.” +[15] H.H.Andersen et al., The stopping and ranges of ions in Matter, vol. 3. Pergamon Press, 1977. +[16] J.F.Ziegler et al., The stopping and ranges of ions in Matter, vol. 4. Pergamon Press, 1977. +[17] H.H.Andersen et al., The stopping and ranges of ions in Solid, vol. 1. Pergamon Press, 1985. +[18] A.Allisly et al., “Stopping powers and ranges for protons and alpha particles,” tech. rep., ICRU, +1993. +[19] A.Gibrekhterman et al., “Characteristics of secondary electron emission from csi induced by x +rays with energies up to 100 kev,” J.Appl.Phys, vol. 74, pp. 7506–7509, 1993. +[20] T.Boutboul et al., “An improved model for ultraviolet- and x-ray- induced electron emission +from csi,” J.Appl.Phys, vol. 86, pp. 5841–5849, 1999. +[21] B.L.Henke et al., “The characterization of x-ray photocathodes in the 0.1-10kev photon energy +range,” J.Appl.Phys., vol. 52(3), pp. 1509–1520, 1981. +[22] J.Barba et al., “Penelope: An algorithm for monte carlo simulation of the penetration and energy +loss of electrons and positrons in matter,” Nucl. Inst. and Meth. B, vol. 100, pp. 31–46, 1995. +[23] F.Salvat et al., “Penelope, a code system for monte carlo simulation of electron and photon +transport,” in Proceedings of a Workshop/Training Course, OECD/NEA 5-7 November 2001, +vol. 19, 2001. ISBN:92-64-18475-9. +[24] J.M.Ferna´ndez-Varea, “Private communication during hands on session of the workshop on use +of monte carlo techniques for design and analysis,” 09 2006. +[25] B.L.Henke et al., “0.1-10kev x-ray induced electron emissions from solids-models and secondary +electron measurements,” J.Appl.Phys., vol. 48, pp. 1852–1866, 1977. +Chapter 5 +Experimental Setup and Sample Preparation +5.1 Design of the measurement setup +5.1.1 A few general considerations +The measurement of the quantum efficiency of a photocathode is not a trivial task. The actual effi- +ciency varies greatly with the experimental conditions, and with the material quality and the shape +of the photocathode material. +The main factor is the cleanness of the photocathode surface, as it has a strong impact on the work +function of the material, which is the main parameter determining the quantum efficiency. +To reach the maximum quantum efficiency of one material, one has to deposit it in an ultra clean +environment (ultra-high vacuum), and to perform the measurement in situ without any vacuum break. +Yet, in this work a perfect environment was not targeted as this does not enable to test the photo- +cathode in real conditions (gas-filled detectors). Indeed maintenance operations often require to open +the detector. +The preparation and mounting conditions of the samples are those typical for the preparation of +gas-filled detectors (clean room environment, special care in cleaning...). +The main requirements for the photocathode quantum efficiency measurement setup are: +• Adaptability to all available sources (synchrotron, but also X-ray tube and radioactive sources). +This implies the ability to work with very small X-rays flux. +• The possibility to work with samples of various sizes and shapes. +This requires a system to keep a constant distance between the photocathode and the polarizing +grid. +• The possibility to use the system both in reflection and transmission modes (electrons collected +on the side of incident X-rays or on the opposite side). +78 Experimental Setup and Sample Preparation +Parameters Value +Electrons acceleration 20 kV +Current Intensity 20 mA +Slits 1 aperture 7 mm +Slits 2 aperture 7 mm +Filter Ø +Table 5.1 : X-ray tube source parameters +The main difficulty arises from the necessity to work with very low currents. Indeed, a 55Fe ra- +dioactive source of activity 30µCi, encapsulated in the protection case typically offers a flux of +∼ 106 photons/s/4pi (an avalanche photodiode measurement gives 4 ·106counts/s). If the photocath- +ode has a quantum efficiency of 1% at the k line of 55α Mn (5.9keV), then the expected current is of +106 ∗ 0.01 ∗ 1.6 ∗ 10−19 ≡ 10−15A ≡ 1 fA. +So the setup must be able to measure currents of less than a femtoamper. +The source used to perform the measurement was mainly an X-ray tube, mounted with a copper +anode. Apart from measurements made for calibration purposes, the tube was used with the param- +eters indicated in table 5.1. +The setup was also tested on the ID15c ESRF synchrotron radiation beamline, which has a fixed +energy of 39.5keV. For the signal to noise ratio was not actually better than the one obtained with +the X-ray tube (flux ∼ 1010 photons/s, but in the meantime much lower quantum efficiencies of the +photocathodes), the beamline was not often used. +5.1.2 The chamber and the ammeter +5.1.2.1 The Photocathode holder, the electrical shielding +The electrical scheme used to perform the measurements is given in figure 5.1. +It was chosen to bias the photocathode at a negative potential and to place the collection grid at +ground potential, rather than polarizing the collection grid. This presents several advantages: +• a smaller sensitivity to the geometrical parameters, +• no contribution to the measured current of electrons photoemitted by surrounding materials at +ground potential, +• a better use of the ammeter, which has a dedicated mode for such mounting (see later for a +description of the ammeter). +Indeed, some earlier tests with the grid being polarized showed higher leakage currents (typically +several fA), any other parameters being identical. +5.1 Design of the measurement setup 79 +Figure 5.1 : Schematics of the experimental setup used to make the measurements +The holder is mainly made of PEEK, a UHV compatible, hard plastic. It also shows a high electrical +resistivity (around 1014 Ωm at room temperature). To reduce as much as possible the surface con- +ductivity, a cleaning with ethanol (and eventually acetone to remove traces of glue due to the copper +tape -see next) was systematically performed. +Figure 5.2 : The photocathode peek support +The circuit is fully shielded with guard rings. A copper tape was used to adapt the shielding to each +photocathode. Special care was taken to hide the copper from the X-Rays (to avoid contribution +from the copper). +80 Experimental Setup and Sample Preparation +The grid used to polarize the photocathode (actually it is at ground potential) is mounted on a copper +holder, with an iron ring to put it under voltage. +After mounting and cleaning of the photocathode, the resistance between the photocathode and the +other parts of the circuit (guard-rings and collecting grid) was typically of a few 100s G Ω to a few +T Ω (as measured by the Keithley 6430, see later). When applying a voltage of −100 V , typical +measured leakage currents were inferior to 0.4 fA. +5.1.2.2 The Chamber +Figure 5.3 : The chamber with some of the connectors +The chamber has a volume of 2.5 dm3. It is made of standard and custom components. It has various +coaxial and triaxial connectors, as well as a KF-connector for pumping. The entrance window is a +thin Beryllium window of 2 ∗ 1 cm2 size. +Connections with the ammeter are performed with triaxial feedthrough connectors (by Pomona)1. +1For the connectors to the ammeter are 3 slot-male triaxial connectors, while the Pomona feedthrough are 2 slot-male +triaxial male connectors, 2 to 3 slot-female triaxial connectors made by Trompeter. +5.1 Design of the measurement setup 81 +The preamplifier of the ammeter (see later) was directly connected to the chamber (via the adaptors) +without any adding extra wire. +The chamber was pumped thanks to a turbo-molecular pump. Yet no precaution was taken to reach +ultra high vacuum. Only high vacuum was used to perform the measurements (to suppress any +contribution of gas molecules to the measured quantum efficiency). This is justified by the need to +develop photocathodes for gas-filled detectors, which have to work effectively in unclean environments. +5.1.2.3 The Keithley 6430 ammeter +The Keithley 6430 sub-femto ammeter is a high +end electrometer by Keithley, whose main charac- +teristic is the presence of a remote pre-amplifier +with triaxial connectors, which reduces as much as +possible the contribution of the leading cable to the +measured signal. +The 6430 possess several ways of operation, includ- +ing the possibility to measure very small currents +while polarizing the sensor to a voltage in a range +−210 V < U < 210 V (Source-Measure Concept). +This mode was used to polarize the photocathode +according to the schematic on figure 5.1. This +Figure 5.4 : The Keithley 6430 ammeter +mode is also the one providing the best internal +precision of measurement [1, 2]. +The 6430 can also be used to measure electrical resistances up to 20T Ω (the measurement is performed +between the guard and the source). This mode was used to check the quality of the insulation +(∼ cleanness) of the setup before each measurement. +5.1.3 Results of calibration and test of the chamber +To ensure that the setup provides reliable measurements of the photocathode quantum efficiency, a +tests were performed with the X-ray tube (all tests performed with a copper cathode, acceleration +parameters being 20 mA current, and 20 kV accelerating voltage). +First the setup was tested without any photocathode. This enabled to measure the contribution +of the grid (parasitic photoemission). For this, the schematics presented on figure 5.1 had to be +inverted, so that the ammeter would actually measure the current emitted from the grid (as a negative +contribution to the measures intensity). This intensity I0 was I0 < 2 pA. This contribution is superior +to the typical leaking currents, but can be considered as negligible when compared to typical measured +photo-currents (typical measured currents are of the order of 20pA to several hundred pA, see 7.1.2). +In addition, this measurement corresponds to the absence of any electric field (no photocathode). In +presence of electric field, the amount of grid photo-emitted electrons is reduced to its most energetic +fraction. Other electron cannot escape the attracting potential. +82 Experimental Setup and Sample Preparation +Figure 5.5 : Current-Voltage (I-U) characteristics of the experimental setup in presence of X-rays with a +gold photocathode. +With the same configuration (ammeter connected to the grid), tests were performed with a ”non +emitting photocathode”: a thick kapton foil with copper on the back layer to bias it. This was used +to measure an hypothetical contribution of the surrounding materials (from the PEEK made holder). +Again this contribution was extremely small, for no current could be recorded (contribution inferior +to the intrinsic noise of the system ∼ 0.1 fA). +This measurement also confirms according the previous measurement (no bias, ammeter connected +to the grid) that the contribution of the grid is very small. +Last a reference system (gold deposited on a kapton foil by sputtering) was used to study the de- +pendence of the electrons collection quantum efficiency on the bias voltage. The result is depicted in +figure 5.5. +A current saturation clearly appears for voltages inferior to −40 V . The non zero intensity for posi- +tive bias can be explained by the proportion of photoemitted electrons with high kinetic energy (see +[3]). Electrons emitted with energies superior to 100 eV (theoretically up to 20 keV for the tube was +used with an acceleration of 20 kV ) have a sufficient energy to escape the attractive potential of the +photocathode and so are counted. The small current value at positive voltages highlights the small +proportion of photoemitted energetic photons. +Photoemitted currents as function of the electron intensity on the cathode also follows a very good +5.1 Design of the measurement setup 83 +linearity with the X-ray tube current in the range [10 mA; 40 mA]: the photoemission is proportional +to the flux of X-rays. This indicates that there is no saturation effect at those intensities (like charging +of the surrounding material, which would affect the extraction electric field). +5.1.4 Conclusion concerning the setup +The test of the setup was a success: the setup shows very good characteristics for the measurement +of very low currents. Its intrinsic noise is inferior to the fA, and can measure the typical currents +emitted by the photocathodes (pA ← nA). The Keithley ammeter guaranties 512 digits at those +currents. +Its high modularity enables the test of photocathode samples of very diverse sizes and characteris- +tics. The setup can be used with various sources of X-rays: radioactive sources, X-ray tubes, and +synchrotron beamlines. + +Bibliography +[1] keithley Instruments Inc., Private Communication with Keithley, 2004. +[2] keithley Instruments Inc., Keithley 6430 Manual, Chapter 5, 2000. +[3] B.L.Henke et al., “The characterization of x-ray photocathodes in the 0.1-10kev photon energy +range,” J.Appl.Phys., vol. 52(3), pp. 1509–1520, 1981. + +Chapter 6 +The different concepts to make a photocathode +Different approaches were taken to try to increase the photocathode quantum efficiencies. Some ideas +were explored only theoretically, while others -more promising- lead to the fabrication of test-samples +to compare them with reference photocathodes. +6.1 Indirect conversion +Figure 6.1 : A two step photons to electron conversion +In this section, an indirect conversion of the X-rays into electrons is evaluated. The X-rays are first +converted into lower energy photons thanks to a scintillating material, and then the photocathode +converts those photons into electrons. +The origin of this idea is the availability of photocathodes offering good quantum efficiencies in the +visible or UV energy range (infra-red sensitive photocathodes were not considered as they involve +88 The different concepts to make a photocathode +cooling systems to suppress their intrinsic noise -due to thermal emission), while one can benefit from +the yield of scintillators (several UV/visible photons created per incoming X-ray). In addition with +this technique one can hope to convert 100 % of the X-rays into visible/UV photons, and so avoiding +the presence of X-ray photons in the back-end electronic, which can be problematic (for the noise of +the system mainly). +If a fluorescent material can produce low energy photons with yields as high as 50, 000 photons/MeV , +if about one hundredth of those photons hit the photocathode (the solid angle corresponding to angle +without total reflections is small), and if this photocathode has a quantum efficiency of 10 %, then +for 10 keV incoming photons, the expected yield is: +∗ ∗ 150, 000 0.01 ∗ 1 ∼ 0.5 e−/photon. +100 10 +This is of course only a theoretical value. +Several aspects have to be considered when making such a system, including the predictable time +response, which has to be compatible with high count rates and the resolution of the system, which +must be compatible with the targeted pixel size. +Some prototypes (like [1, 2, 3]) exploiting such an approach were already made for PET application +(so with much higher photon energies), but none of them could provide good results until now. This +study explore the principle in the case of lower energy X-rays. +6.1.1 Photocathodes in visible and UV +The requirement for the photocathode to work in the visible range are the same as for those working +in the X-ray energy range. Yet, because of the difference of energy, one does not have to limit +the research to high Z materials, so providing a much wider range of possibilities. This is very +interesting as in general there are more materials with well controlled physical and chemical properties. +Lastly, photocathodes working at low energies find a lot of applications in astronomy, photo-injectors +(coupled with short-pulse lasers). At those energies they are typically found in photomultipliers and +phototubes. +The most common photocathodes in the visible/UV energy range (available industrially) are: +Bialkali photocathodes such as Sb−Rb−Cs, Sb−K −Cs. They feature a spectral responses in +the optical and close UV. They are usually not very stable, and so their use cannot be envisaged. +Multialkali photocathodes especially Na − K − Sb − Cs, which exhibit a very wide spectral +response, from ultraviolet to wavelength as long as 930 nm. +GaAs also with a very wide spectral response. Eventually GaAs photocathodes are covered with Cs +to make them NEA (negative electron affinity), but this is at the cost of a higher sensibility to +pollution. +Solar Blind Photocathode especially GaN , KBr, CsBr, InGaN and AlxGa1−xN . Most were +developed for space applications (UV cameras, insensible to light pollution due to the sun). +Those photocathodes often exhibit quantum efficiencies of more than 30 %, at wavelength +inferior to 350 nm. Among those photocathodes, GaN is the material which offers the most +promising characteristics. +6.1 Indirect conversion 89 +Diamond (C*) is a relatively new photocathode, which offers several advantages: it is rather stable +[4] and NEA[5, 6] when plasma-hydrogenated. In addition in principle it suffers less than +other materials from pollution due to organic gases such as methane (which is a good gas for +amplification). Diamond photocathodes are obtained by CVD1, or by low energy ion deposition +of carbon. They are amorphous materials, which exhibit a mixture of sp2 (graphite like) and +sp3 (diamond like) bonds (CVD deposited diamonds are usually better as they exhibit a higher +proportion of diamond like bonds, and a better crystallinity). The surfaces are then treated by +plasma hydrogenation in order to make the surface NEA. The problem comes from its sensitivity +limited to wavelength inferior to 210 nm (large band gap semiconductor: 5.47 eV ). +6.1.2 Scintillation materials +There are various materials able to provide fluorescence photons at various energies. They are char- +acterized by four main parameters: +• The fluorescence yield, usually given in photons / MeV. The linearity of the yield is excellent +for energies up to a few MeV. +• The energie(s) of emitted photons. +• The time response of the scintillator, often there is a fast response corresponding to few photons +and a slower one corresponding to a much higher yield, and to an energy slightly different. +• The achievable resolution with the scintillator. This is strongly related to the thickness of the +deposited layer. But in average, with a resolution of a few µm, most materials can absorb 100 % +of the photons with wavelengths inferior to 30 keV . +To obtain a competitive quantum efficiency, as shown in the calculus made in the introduction, a +minimum yield of 10, 000 photons/MeV is necessary. +As said previously, it would be best to have a photocathode sensible to UV light. So the fluorescent +material needs to have a good yield at those wavelength (typically less than 350 nm). +Also, the aim of the project is to build a detector able to work in counting mode, and with a typical +count rate of the order of 1 MHz. This means the decay time constant of the fluorescence must be +at least one order of magnitude smaller, so of the order of 100 ns. +Here is a list of the most commonly used scintillation materials with high yields, small decay times, +and maximum of emission at energies inferior to 500 nm [7]: +NaI(T l) is one of the most common scintillators. PureNaI offers a maximum yield of 76, 000 photons/MeV +at λmax = 303 nm, and with a scintillation decay time constant of 60 ns. It is more often used +doped with thallium, and then has the following parameters: λmax = 415 nm, with yield +38, 000 photons/Mev and a decay time constant of 230 ns. +BaF2 is interesting because it emits very energetic photons: the fast component, which is 25 % of +the total yield is at 220 nm with a yield of 2500 photons/MeV and a decay time constant of +0.6 ns. The main maximum is at 310 nm with a decay time constant of 630 ns. +1CVD stands for Chemical Vapor Deposition +90 The different concepts to make a photocathode +CsI(Na) has a maximum emission at 420 nm, with a total yield of 38, 000 photons/MeV and a +decay time constant of 630 ns. +CaF2(Eu) has its maximum at 435 nm, a yield of 19, 000 photons/MeV , and a decay time constant +of 630 ns. +K2LaCl5(Ce) has its maximum at 380 nm, with a yield of 30, 000 photons/MeV , and a decay time +constant of 80 ns. +LaCl3(Ce) has its maximums at 330 − 352 nm with a yield of 49, 000, with several components, +which have all a decay time constant inferior to 200 ns. +LaBr3(Ce) has its maximums at 358− 387 nm, a total yield of 61, 000 photons/MeV , and 90 % of +the emission occurring before 90 ns. +Lu2Si2O7(Ce) (LPS) has a total yield of 23, 000 photons/MeV , with maximums of emission at +380− 385 nm, and a decay time constant of 38 ns. +LuI3(Ce) has a maximum emission at 465 nm, with a yield of 33, 000 photons/MeV , and a decay +time constant of 34 ns. +RbGd2Br7(Ce) has a maximum of emission at 420 nm, with a yield of 56, 000 Photons/MeV , and +a decay time constant of 43 ns. +BrilLancer 350 and 380 of formula LaCl3(10%) and LaBr3(5%) by the Company St Gobain are +also very interesting: BrilLancer350 for example offers a maximum of emission at 350 nm, +with a yield of 49, 000 photons/MeV , and a decay time constant of 28 ns. +In conclusion, there are a lot of materials providing maximums of emissions in the close ultra-violet +energy range, with acceptable decay time constants, and good yields. Unfortunately, all high yield +materials are limited to wavelengths superior to 300 nm, which is a problem as shown next. +6.1.3 Possible combinations +To obtain a good quantum efficiency, it is of course mandatory that the maximum of emission (and +more generally, the whole spectrum of emission) of the scintillation material be contained in the +spectrum of sensitivity of the photocathode. +For the same reasons as previously exposed, it is also necessary that the photocathode exhibits a good +robustness to pollution and to irradiation damages. The robustness to pollution of the scintillator +is less important, as it can be well protected if enough care is taken by the photocathode and the +substrate. +This leaves few choices of photocathode. +Diamond +In spite of its very interesting characteristics of quantum efficiency, diamond cannot be chosen, for +its sensitivity starts at energies unreachable by scintillation processes. In addition, diamond is not +yet well known as a material, and only a few groups can produce diamond with a sufficient quality +(in terms of crystallinity, hydrogen activation quality, purity of the material). Yet diamond is now +6.1 Indirect conversion 91 +a subject of great interest for applications in the field of photocathodes (solar blind, for space ap- +plications), so it might become an interesting alternative in the future, also if suitable scintillation +materials are discovered in the future. +Bialkali and Multialkali +Bialkali and Multialkali are very interesting because they offer a good sensitivity at the emission peaks +of high yield scintillators. Unfortunately they are also extremely sensitive to pollution and moisture, +and even protective layers do not prevent loss of yield after short exposure to polluting environments +[8]. +GaN and relatives +Those photocathodes have been the subject of a lot of studies for they offer a very good quantum +efficiency below the long-wavelength cut off (typically Q.E. ∼ 0.4) while having a very low quantum +efficiency above this cut-off. This is of special interest for solar-blind detectors in space applications. +In our case this means that they could be coupled to high-yield scintillators to form a two step X-ray +photocathode. In particular an association of a NaI scintillator and GaN photocathode seems to be +a promising combination. +Alas, those photocathodes also require a good vacuum to work effectively. So for the same reasons +as previously, they cannot be used in detectors using gas amplification. +Protected photocathodes +Studies have been made to try protecting UV and visible photocathodes for the specific case of gas- +filled detectors [8]. The possibility exists to effectively reduce the sensitivity of the photocathodes to +moisture and oxygen (the main contributors to the degradation of the photocathodes in unclean envi- +ronments), but at the cost of a highly-reduced quantum efficiency (at maximum 10 %, the protection +depending on the thickness of the protecting layer). +6.1.4 Conclusion +It appears clearly that in spite of its promises it will be difficult to build a 2 steps photocathode for +X-ray detection. +Diamond seems to be the most promising material, for it is a robust material (yet no real studies of +the stability of the hydrogenated surface -by plasma activation or else- could be found), but short +wavelength scintillators have still to be found. Otherwise carbon does not offer the stopping power +mandatory to enable a good quantum efficiency with X-rays without a first conversion stage. +The other materials unfortunately do not offer a stability good enough to guaranty a good reliability +when used in gas-filled detectors. +92 The different concepts to make a photocathode +6.2 Direct conversion +As an indirect conversion does not seem to be a good way of designing a photocathode for gas-filled +detectors, a direct conversion has to be used. +There are various possibilities to better the quantum efficiency of the photocathodes presented in +section 3.3. Three approaches were studied theoretically and experimentally in the scope of this work +to try bettering the quantum efficiency of photocathodes in the X-ray energy range: +• Modify the geometry of the photocathode in order to maximize the yield of a material, +• Use of sharp tips to profit from a field emission phenomena, +• Investigate new materials in order to find one with better properties. +All three approaches are detailed in the following subsections: +6.2.1 Modify the geometry to increase the yield of one material +As explained in section 3.1, the yield of the photocathode depends directly on the ratio laL , where la +is the absorption length and L is the scattering length. +Figure 6.2 : The impact of the incidence angle of photons on the active area (contributing to the yield). +This formula is valid in the case of photons with a direction perpendicular to the surface. Indeed +in the case of photons with slanted directions, the apparent thickness is increased, leading to more +photons absorbed in the active area (distance to the surface inferior to L). With the definition of the +angle α of Figure 6.2, the theoretical increase of quantum efficiency is a factor 1cos(α) : +∝ laEfficiency · 1 . (6.1) +L cos(α) +This was measured by D.P.Lowney et al. in [9] in the case of CsI, and the measurements show a +good agreement with the formula. +6.2 Direct conversion 93 +To use this effect, the classical way is the use of a grazing incidence. Unfortunately, this leads also +to technological problems, and to the impossibility of making large areas detectors. So in this work +the possibility to use microstructures was investigated. +More generally this approach consists in increasing the surface to volume ratio of the material, as +this increases the active area. In fact the best available photocathodes have a controlled microstruc- +ture, which maximizes this surface to volume ratio (often a columnar structure obtained during the +deposition of the material). +The main requirement for the microstructures concerns their size: they should be much smaller than +the pixel size (collecting anodes in the case of a gas amplification), which means structures with +typical sizes of less than a micron. +Various ways of playing with the geometry were tested during this study, as will be shown in the +coming subsections. Only systems which can be obtained on large surfaces for a reasonable price were +used during this study. +6.2.1.1 Porous Photocathodes +The most straightforward way of creating a structure is the use of a porous material. Indeed this +enables the creation of a much larger surface (so a greater active area) actually reached by the photons +(then the absorption length becomes la , where Porosity is the fraction VporesPorosity V in the material).total +But as explained in the previous section, with increasing porosity, the probability that emitted elec- +trons reach the actual surface of the photocathode also decreases for the electrons have to find their +way through the connected pores or even through thin walls between pores to then exit the pho- +tocathode. While M.P Lorikyan [10] published interesting results using this sort of materials, the +measurements could not be later confirmed, and doubts subsist concerning a possible amplification +inside the pores, which would affect the measurement of the quantum efficiency (as several electrons +would be detected per single detected photon). +Still a similar approach was used for some of the samples prepared, and results are given in the next +chapter. +6.2.1.2 Regular Structures +Modern photocathode always have a microstructure, which maximizes the surface to volume ratio, +in order to have a maximum active area. Yet the structure is not fully controlled as it is most often +obtained by carefully controlling the deposition parameters so that the photocathode material adopts +a columnar growth [11]. So there is little control on the actual structure of the deposited material. +Another approach can be the use of a patterned substrate or a process able to imprint the desired +structure in the material. So that the geometry of the deposited material is well controlled and opti- +mized. +The main problem of structured photocathodes lies in the lack of escape path for electrons reaching +vacuum (or the gas) at a point far from the surface of the photocathode. The solid angle is indeed +94 The different concepts to make a photocathode +inversely proportional to the square of the aspect ratio of the structure2 +Figure 6.3 : Two examples of regular Structures. +There are some requirements to respect to guarantee a minimum quantum efficiency of the photo- +cathode: +• For the photocathode has to work in transmission, special care must be taken to guaranty an +excellent transparency to X-rays of the substrate. Ideally the substrate is thin, made of low Z +material, and flexible in order to guarantee a good mechanical robustness. Organic materials +like kapton or some sorts of polymers are good candidates. +• The process used to create the structures must be adaptable to large surfaces at an acceptable +price. In particular, etching technologies or holographic-based technologies, which are common +in the semiconductor industry should be avoided, for their costs increase dramatically with large +surfaces. On the other hand, physical engraving technologies are well adapted (see the example +of the Trizact Sample in the next Chapter). +• The uniformity of the pattern has to be good enough to guaranty a good homogeneity of the +conversion efficiency. +As said before, typical sizes of the structures must be small enough to ensure that they will have no +impact on the uniformity of the image. +In addition, in theory it would be best to match the typical escape length3 of the emitter material. +Indeed smaller sizes will not enable to minimize the transparency and larger sizes will result in a loss +of flux in the active area of the photocathode. +But in practice the typical values of L are very hard to obtain (for example L(Gold) ≈ 2 nm and +L(CsI) ≈ 50 nm), and as the photocathode works in transmission, it is better to deposit a thin +layer of the high yield material (thus high stopping power) on top of a low stopping power structured +material, so that a maximum flux of photons reaches the active area of the material. +Concerning the shape, a trade-off must be done between two different requirements: +2For example, in the case of a square well of surface l2 and deepness h, the solid angle from the bottom of the well +l2is 2 ∝ 1 2 ).4pih (Aspect Ratio) +3the escape length is inferior to the scattering length because of the work-function/electron affinity of the material. +6.2 Direct conversion 95 +1. The higher the aspect ratio, and the higher the angle with the surface of the structure, the +larger the active area, +2. The smaller and the more separated the structures are, the higher the electron escape solid +angle is, and so the higher the escape probability. +It is also better to have non rectangular like shapes, as the active area is very thin. Pyramidal, or +conic like shapes, offer a larger surface of the photocathode with an oblique surface with respect to +the X-rays. +Those shapes also enable a better penetration of the electric field between the structures, and offer +a larger solid angle for electrons allowing exit from the bulk of the material far from the top of the +structures. Indeed, the surface of the material often exhibits an attractive potential to electrons in +the gas (except in the case of NEA materials), so electrons are likely to return back in the material +again before reaching the surface of the photocathode. +To increase the escape probability of the electrons, one has to use an electric field. Unfortunately, +also the efficiency of the electric field is limited: Figure 6.4 depicts the result of the simulations of +the electric field in the case of metallic structures with rectangular and triangular shape by means +of a Finite Element Method (the simulations were performed with Comsol Multiphysics). The back +surface (flat) of the structure was at ground potential, while a ”collecting plane” above the structures +was at a potential of 100 V . +It appears in the simulation, that the electric field penetrates more into the triangular structures. In +both cases yet, the values reached are very small. Fortunately, most electrons exit the bulk material +with energies of only a few eV , so even a small electric field can have a strong impact on the collection +of the electrons. +In conclusion, the simulations show that the aspect ratio (HeightWidth ) of the structures cannot be very +high, otherwise the electrons created far from the surface will be not extracted. +96 The different concepts to make a photocathode +Figure 6.4 : Simulations of the electric field in triangular and rectangular structures. +6.2 Direct conversion 97 +6.2.2 Field emission +Figure 6.5 : Simulation of the electric field in the case of silicon sharp tips. +As explained in section 3.1, the most important parameter for photocathode quantum efficiencies con- +cerns the electrons extraction of the material. Several studies [12, 13, 9] were performed to evaluate +the effect of an electric field to diminish the potential barrier electrons have to overpass to reach vac- +uum (the electron affinity/work function). Those studies showed that strong electric field is needed to +have a real impact on the quantum efficiency of the photocathodes. This can be explained by the much +higher value of the dielectric permittivity in solid materials (ex. ε(CsI) = 6.3 and ε(Si) = 12) than +in gas/vacuum (ε(vac.) = 1): in the case of two dielectrics superposed, the proportion of the energy +stored in both materials is the inverse of the ratio of the electric permittivities. As a result the electric +field has a very small value inside the material, and does not effect much the dynamics of the electrons +in the material (see the simulations by finite elements of metal microstructures on Figure 6.4). To +create a strong field inside the material, one has to connect electrodes to the photocathode, which is +of course not possible in the case of electro-emitters (the electrode would take the role of the emitter). +In order to improve the electric field, it was envisaged to use sharp tips to profit from the concentration +of the electric field around sharp tips (Tip effect), and so create a field emission system. +Figure 6.5 depicts the result of the simulation by the finite element method of such sharp silicon tips. +98 The different concepts to make a photocathode +Indeed, a strong electric field appears at the top of the tips. +Such arrays were already successfully used in association with short pulse UV-lasers for photo-injectors +systems [14], and could be interesting for photon-detection systems. Tests were performed with +silicon-made tips arrays in order to test the efficiency with X-rays. +6.2.3 A new material: CsI3 +In parallel to the work made to enhance the emission properties of known materials by changing the +geometry of those materials, new materials were investigated. Following the example of CsI, which +is currently the best material in terms of quantum efficiency, various iodide were studied. +In particular, CsI3 as a derivative material of CsI was found to share some interesting physical +properties with CsI, while solving some issues specific to CsI. +Bibliography +[1] G. Charpak et al., “Some studies of the application of csi photocathodes in gaseous detectors,” +Nucl. Inst. and Meth. A, vol. 333, pp. 391–398, 1993. +[2] J. Van der Marel et al, “A microgap photomultiplier for the read-out of a laf3 : Nd(10÷) +scintillator,” Nucl. Inst. and Meth. A, vol. 410, pp. 229–237, 1998. +[3] F.Garibaldi et al, “A pet scanner employing csi films as photocathode,” Nucl. Inst. and Meth. +A, vol. 525, pp. 263–267, 2004. +[4] A.Laikhtman et al., “Absolute quantum photoyield of diamond thin films: Dependence on sur- +face preparation and stability under ambient conditions,” Nucl. Inst. and Meth. A, vol. 73,10, +pp. 1433–1435, 1998. +[5] J.Roberston et al., “Band diagram of diamond and diamond-like carbon surfaces,” Diamond and +Related Materials, vol. 7, pp. 620–625, 1998. +[6] D.Vouagner et al., “Photoemission properties and hydrogen surface coverage of cvd diamond +films,” Diamond and Related Materials, vol. 13, pp. 969–974, 2004. +[7] M.Globus et al., Inorganic Scintillators For Modern And Traditional Applications. National +Academy of Sciences of Ukraine., 2005. +[8] E.Shefer et al., “Photoelectron transport in csi and csbr coating films of alkali antimonide and +csi photocathodes,” J.Appl.Phys., vol. 92(8), pp. 4758–4771, 1993. +[9] D.P.Lowney et al., “Characterization of csi photocathodes at grazing incidence for use in a unit +quantum efficiency x-ray streak camera,” Review of scientific instruments, vol. 75,10, pp. 3131– +3137, 2004. +[10] M. P. Lorikyan, “Study of counting characteristics of porous dielectric detectors of radiations,” +Nucl. Inst. and Meth. A, vol. 515, pp. 701–717, 2003. +100 BIBLIOGRAPHY +[11] H.S.Cho et al., “A columnar cesium iodide (csi) drift plane layer for gas avalanche microdetec- +tors,” IEEE transaction on Nuclear Science, vol. 45(3), pp. 275–279, 1998. +[12] A.Breskin et al., “Electric field effects on the quantum efficiency of csi photocathodes in gas +media,” Nucl. Inst. and Meth. A, vol. 344, pp. 537–546, 1994. +[13] A.Breskin et al., “New ideas in csi-based photon detectors: Wire multiplication and protection +of the photocathode,” IEEE Trans.Nucl.Sci, vol. 42(4), pp. 298–305, 1995. +[14] e. J. M. Nation, “Advances in cold cathode physics and technology,” Proceedings of the IEEE., +vol. 87, 5, pp. 865–889, 1999. +Chapter 7 +Experimental tests and discussion of the +results +Not all the different approaches to improve the photocathodes were experimentally tested. In partic- +ular, the indirect conversion photocathodes were not actually fabricated, for no good combinations +of scintillators and emitters could be found. Otherwise, most ideas to improve the photocathode +quantum efficiencies were tested. This section follows the structure of the previous one and gives the +experimental results obtained. +7.1 Modify the geometry to increase the yield of a material +As previously explained, the approach of modifying the geometry of one material consists in benefiting +from the increasing of the quantum efficiency in the case of an oblique incidence of photons on the +surface of the photocathode material. Only samples potentially manufacturable as large surfaces were +used. +Mainly two types of structured photocathodes were tested: +Random Structures were actually sand paper materials normally used for the coarsing of surfaces. +The different grades of papers enabled to test further the impact of the structure sizes on the +quantum efficiency. +Periodic Pyramidal Structures were special sorts of sand paper available in a very special and +periodic shape. They are normally used for highly demanding polishing applications (in terms +of uniformity, and robustness of the paper). +The reference sample was a flat Kapton foil. +Those samples were covered with 0.2−0.4 µm of gold by argon ion sputtering (the thickness could not +be precisely controlled, so the thickness was evaluated thanks to the given deposition characteristics +of the machine). This thickness was sufficient to ensure a maximum yield (thickness greater than the +escape length) while not changing radically the structure shapes. +102 Experimental tests and discussion of the results +7.1.1 Analysis of the microstructures characteristics +Several samples were created and their structures were analyzed both with an optical and a scanning +electron microscope (SEM). +First a flat kapton foil was taken as a reference photocathode. +For the random structures, the samples were the following (SEM images): +Figure 7.1 : Grade 280 sam- Figure 7.2 : Grade 800 sam- Figure 7.3 : Grade 1200 sam- +ple: Random structures of sizes ∼ ple: Random structures of sizes ∼ ple. Random structures of sizes ∼ +100 µm. 20 µm. 10 µm. +Those samples were made with normal sand paper, normally used for grinding of surfaces. Higher +grades correspond to a finer smoothening, so structures are smaller and more numerous. The sizes +indicated under each pictures (7.1, 7.2, 7.3) are those of the largest structures (covering most of the +surface), and are always surrounded with smaller structures. +For the periodic structures, the special Trizact 143 paper by the company 3M was used. Those +structures are obtained by positive engraving in a special polymer and are available in large areas. +Figure 7.5 : Periodic Structure seen from the +Figure 7.4 : Periodic Structures seen from side Optical Microscope. +top SEM image, size of structures ∼ 500 µm +The side surfaces form an angle of∼ 57o with respect to the base plane (averaged on several pyramids). +7.2 Field Emission 103 +7.1.2 Efficiency measurements +The different samples presented were all covered with a layer of gold of thickness ∼ 0.3 µm. This +thickness is far bigger than the escape length of gold (a few nm), so there is no contribution to the +yield from the substrate. The structures are much larger than the gold thickness, and there was +no attenuation observed of the quantum efficiency due to a ”smoothening” of the surface by the +deposited layer (different thickness of deposited gold gave the same results). +The results are presented compared to a flat surface of gold obtained in the same conditions in table +7.1 (X-ray tube parameters: 20kV acceleration voltage, 20mA intensity, with Cu anode): +Substrate Gold Thickness (µm) Measured Current (pA) +Kapton 0.3 18.5± 0.9 +Sand Paper Grad 280 0.3 22.4± 1.1 +Sand Paper Grad 800 0.3 20.8± 1.0 +Sand Paper Grad 1200 0.3 19.4± 0.9 +Trizact 143 0.3 34.65± 1.7 +Table 7.1 : Results intensities of gold covered structured paper +The best sample is the Trizact 143, which indeed offers the largest inclined surface (so a higher active +area). It should be noted that with respect to the flat Kapton sample, there is a factor +34.65 ≈ 11.87 = = 1.83 +18.5 cos(57) +as predicted by the formula in section 6.2.1. +Sand Paper do not give results as good as the periodic trizact samples, probably because the structure +covered surface is much smaller than that of the trizact samples. +7.2 Field Emission +Silicon sharp tips were obtained and tested to evaluate their potential in the case of X-ray photo- +cathodes. +7.2.1 Analysis of the microstructure characteristics +The sample is formed of a periodic array of 4.5 µm separated tips, engraved in a silicon wafer. +104 Experimental tests and discussion of the results +Figure 7.6 : Si Tips Array SEM images at 10 µm and 2 µm resolution. No better image could be obtained +because of space charge effects. +Due to the small dimension of the tips, neither the SEM images nor the optical ones enabled us to +obtain detailed information about their shape. Yet the SEM images do show an effect of emission +enhancement at the tips tops (Figure 7.6). +7.2.2 Efficiency Measurements +The measurement of the quantum efficiency of silicon tips as X-ray photocathodes showed that silicon +tips are not a good choice for no signal could be detected. This demonstrates that the yield is very +small. +This can be explained by the small stopping power of silicon in the case of X-ray photons. For +photons penetrate deeply in the material before being stopped, the electrons are created too far +from the surface to drift and exit the bulk (in the case of moderate electric field as presented in the +simulations detailed in section 6.2.2). +It is likely that a strong electric field could enhance the yield, but such a field is not compatible with +gas amplification. +7.3 CsI3 as a new photocathodes material +7.3.0.1 Physical and chemical characteristics +CsI is a dark reddish-brown solid material, with a standard density of 4.51 g/cm−33 , and melting +point of 207.5oC. Its crystal structure was first studied in 1925 by Bozorth et al.[?], and later refined +by H.A.Tasman et al. and by J.Runsink et al.[?, ?] and belongs to space group Pmcn. +Extensive studies (complete phase diagram) on the manufacturing of polyiodides of caesium can be +found in [?] ; the material is also available from major chemicals companies such as Sigma-Aldrich +or Alfa Aesar or can be easily synthesized from CsI and I2 [?]. +7.3 CsI3 as a new photocathodes material 105 +It is not stable under vacuum at room temperature but it releases I2. L.E.Topol indicates in [?] that +the partial vapor pressure can be obtained from the formula +−4269 + 0.20(T − 273) +log(PCsI3 [Torr]) = − 2.013 log T + 16.2548. (7.1)T +In particular, at a temperature of 25oC, P ≈ 10−3Torr = 1.33 · 10−3 mBar and at 40oCsI3 C: +P ≈ 4.14 · 10−3 Torr = 5.51 · 10−3CsI3 mBar. +More detail (including (E−Eo), ∆G associated to the system CsI −CsI3) can be found in [?]. The +differential free enthalpy is ∆o = −358 kJmol−1f . +Indeed when CsI3 was left on the photocathode holder in vacuum, a layer on surroundings metals +appeared, which is a sign of reaction with I2 (the layer showed the same aspect as when exposed to +vapors of I2 obtained from solid iodide). Also the color of the sample rapidly changed to a brighter +one (yellowish, after a few hours in vacuum), which is also a sign of the appearance of CsI at the +surface (CsI is white or transparent, depending on its crystallinity). After 1 week in vacuum at a +pressure of ∼ 10−5 the sample had lost as much as 12 % of its weight. Unfortunately we could not +leave it under vacuum for a longer time to test further the stability of solid blocks (to check whether +there is only surface transformation, which acts like a passivation layer, or deeper degradation and +if a denser block would degrade the same way). The scanning electron microscope (SEM) analysis +confirms an evolution of the material microstructure (see figures 7.7 and 7.8): +Kept in air at atmospheric pressure, there was no visible evolution after several months, apart from +the plastic box, which turned into red (like it did with other compounds such as AuI, known to re- +lease I2), which indicates that the evolution is slow, as soon as the equilibrium pressure of I2 is reached. +7.3.1 The CsI3 samples +Different flavors of CsI3 samples were obtained and tested. For each the analysis of the microstructure +and the quantum efficiency measurements were performed. CsI3 is unstable under vacuum, so an +analysis of the microstructure evolution under vacuum was performed. +Samples of CsI3 were created following two ways: +1. CsI3 was ordered from the company Sigma-Aldrich, and pressed into a pellet with a die-press +set. A pressure of 3.5 GPa was enough to obtain a solid sample. +2. CsI samples were exposed to I2 vapors (CsI with solid I2 in a closed bottle in a furnace at +30oC). The solid state reaction is very slow. We had to wait several days to observe a reaction +of the bulk of the material. This method has the advantage that it is possible to compare +directly nearly identical CsI and CsI3 samples. +CsI3 samples obtained were tested and compared with CsI and gold. CsI is an isolator, therefore +it is hard to test due to charging effects. To overcome the space charge, conductive CsI(C) samples +were made, and compared with CsI3(C). +106 Experimental tests and discussion of the results +7.3.1.1 Preparation of the different samples +Samples obtained from CsI3 as supplied +CsI3 was obtained from the company Sigma-Aldrich (the vendor guaranties a purity better than +99.99x %). +The product came as a fine powder, which was then pressed into a pellet in an hydraulic press die, +at a pressure of 4GPa for 5 minutes. +Samples obtained from a CsI crystals, in presence of I2 vapors +Samples of CsI(T l) crystals grown for fluorescence applications were obtained from the company +Saint-Gobain. +The samples come in the form of a polished crystal (transparent to light, colorless). It was then +exposed to I vapors at a temperature of ∼ 40o2 C for several days. Already after a few minutes, the +color of the crystal had changed into one very close to that of CsI3. After several weeks in presence +of I2, the sample is hard to distinguish from the one obtained from the CsI3 powder. +CsI was also tested. To do this, it was placed rapidly after opening (less than 5 minutes in air) on the +experimental setup in vacuum and tested. Unfortunately, this test was not relevant, as explained later. +Samples obtained from a powder of CsI mixed with carbon in order to reduce +the space charge +The CsI crystals from St Gobain could not be tested directly because of charging effects. So high +purity CsI powder (from the company Sigma-Aldrich) was mixed with graphite in order to increase +its conductivity. Those samples enabled to have a direct comparison of CsI and CsI3. +Because CsI is an hygroscopic material, all manipulations were done under protecting atmosphere, in +a glove box. The sample was then rapidly mounted on the experimental setup (less than 5 minutes) +and put under vacuum for testing. +The received CsI was grained and mixed with graphite in a mortar. The sample composition was +0.5 % of graphite-carbon and 99.5 % high purity CsI. +It was then removed from the glove box, put in a die and pressed at 6 GPa for 2 minutes. Immediately +after it was mounted and put under vacuum. Such a way, the sample stayed less than 5 minutes in +air between its removal from the glove box, and the start of the pump. +A second sample prepared the same way, was treated in iodine vapors in order to transform it to +CsI (C) (left in a furnace at a temperature of 40o3 C for one week). +Porous CsI Photocathodes +Porous CsI photocathodes by the company Luxel were tested for comparison purpose. Those pho- +tocathodes have a microstructure, which is optimized for a use in X-ray cameras. They give an +indication of the maximum yield obtainable with CsI. Those photocathode are shipped in a sealed +flask filled with an inert gas to protect them from moisture. As for the previous samples, they were +mounted in the clean room and evacuated in less than five minutes. +7.3 CsI3 as a new photocathodes material 107 +7.3.1.2 Analysis of the microstructures of the samples and their evolution +The CsI3 samples were stored in the clean room, in non hermetic plastic boxes. No visible change +of aspect could be observed after several months, and no evolution of the microstructure was visible +with the scanning electron microscope. +However, under vacuum a clear evolution was observed. Details of the sample evolution under vac- +uum are the following: +Samples obtained from pure CsI3 +The evolution of the microstructure of the sample was observed by SEM (a Gemini Leo 1530 ): +The surface microstructure of the pressed sample is depicted in the Figure 7.7. +Figure 7.7 : CsI3 as pressed SEM images. Left image is a large field picture with resolution ∼ 10 µm, +right image is a closer view with resolution ∼ 2 µm. +This sample was left for one week under vacuum at a pressure of ∼ 10−6 mbar. The sample was then +re-examined by SEM. The result is depicted in Figure 7.8. +Figure 7.8 : CsI3 samples SEM images, after the sample was placed for one week in vacuum. Left image +is a large field picture with resolution ∼ 2 µm, right image is a closer view with resolution ∼ 1 µm. +108 Experimental tests and discussion of the results +There is a clear evolution in the microstructure, which has become much more porous. In the mean +time, the color of the sample changed from dark to a white yellowish one (close to the color of CsI). +This is further indication of the reaction +CsI3 + CsI + I2. (7.2) +Samples obtained from CsI exposed to I2 +The study of the samples made from CsI3 enabled to study the microstructure evolution of the +material in vacuum. It is also interesting to study the evolution of microstructure of samples of CsI +after they were exposed to I2 and then placed in vacuum. +The following pictures depict the evolution of the samples made of pure CsI mixed with 0.5 % of +carbon: ”CsI(C)”. +As pressed, the microstructure of this sample is depicted in Figure 7.9. +Figure 7.9 : CsI(C) at 20 (left), 10(center), and 2 µm resolution (right). +After exposure to I2 for two days, no visible evolution of the microstructure was observed. +But after one night in vacuum, the structure becomes the following (Figure 7.10). +Figure 7.10 : CsI(C) at 20 (left), 10 (center), and 2 µm resolution (right) after the sample was exposed to +I2 and placed one night in vacuum. +The samples obtained from the CsI(T l) crystals show the same evolution (visible on Figure 7.11). +7.3 CsI3 as a new photocathodes material 109 +Figure 7.11 : CsI(T l) Crystal by St Gobain Before any treatment (left), and after it was exposed to +I2, and placed one night in vacuum (right). +Before any treatment, most of the surface is flat like on picture 7.11 left (polished sample). The +right picture highlights the complete change of the surface after the exposure to I2 and vacuum. +This evolution follows the same trend as for the compacted CsI3 samples. The difference of obtained +microstructure can be explained by the difference of the CsI microstructure before exposure to I2. +When the structures are left in vacuum for longer periods, no visible change occurs at the surface. +Porous samples of CsI +Those samples are obtained from the company Luxel and have a microstructure optimized for the +detection of X-rays in streak cameras. +Indeed they show a spongy structure as depicted in pictures 7.12. +Figure 7.12 : CsI optimized for streak cameras from the company Luxel. The left SEM image is shot +with a resolution of ∼ 20µm, the right one with a resolution of ∼ 1µm. Space charges on the sample prevented +us from obtaining a better image. +As presented in section 6.2.1.1, this sort of structure is a way to obtain a large surface of the material +110 Experimental tests and discussion of the results +and then, a large active area (cf. 6.2.1). +It should be noted that this sample has a microstructure which is similar to that of the CsI samples +exposed to I2 and then placed in vacuum. +So the exposure to I2 appears as a way to obtain a granular microstructure of the CsI. +This is an important result, as this method is much easier than the complex deposition +processes normally used to obtain such materials. +This result will be further detailed in the conclusion concerning the use of CsI3 as a photocathode +material. +7.3.2 CsI3 quantum efficiency and comparison with CsI. +The quantum efficiency of CsI3 was evaluated and compared to that of CsI, both before and after +exposure to air. See chapter 5 for details concerning the experimental setup. +7.3.2.1 The quantum efficiency of CsI and its evolution in air +measurement of the quantum efficiency of clean CsI +Those measurements were done for calibration and comparison purpose, as this subject was already +widely studied in the past. +Yet, few authors provide results of the quantum efficiency after exposure to air (at best short exposures +and techniques to recover the virgin quantum efficiency [29, ?, ?, ?, 32]). +The best quantum efficiency one can obtain is measured in our case by the quantum efficiency of +the samples provided by the Luxel company. Those samples are optimized for a very high quantum +efficiency: thick deposited layers, with an adapted microstructure. +The best quantum efficiency, was obtained right after introduction of the sample in the chamber. +With our setup, a maximum current of 1144 ± 57 pA was recorded. The second sample gave +1115± 55 pA (3% difference, can be attributed to a slight degradation of the sample during its ma- +nipulation, or to a difference in the sample itself). +Those results were compared with the samples obtained from the CsI mixed with 0.5 % of carbon. +The intensity obtained was 144± 7.2 pA. +While this lower intensity can be explained by an effect of the structure of the sample (as explained +before, prior exposure to I2, the surface of the CsI(C) sample was very flat), it is likely that the +condition of cleanness during the preparation of the chamber cannot guaranty a maximum quantum +efficiency of the CsI photocathode prepared this way: the quantum efficiency of CsI as a secondary +emitter depend strongly on the state of cleanness of the sample surface (cf. section 3.3.4). For +the CsI used to prepare the sample was grained and pressed during the preparation process (see sec- +7.3 CsI3 as a new photocathodes material 111 +Time in air Intensity measured (pA) +0 1144± 57 +1 day 736± 36 +30 days 113± 5.6 +Table 7.2 : Evolution of the current of the porous CsI sample after it was left in air. +tion 7.3.1.1), it can have been polluted, despite of the care taken to clean the mortar and the die used. +Evolution of the quantum efficiency of the porous CsI in vacuum and after +exposure to air +CsI is known for being sensitive to pollution, and in particular to moisture. Tests were performed in +order to compare its stability with that of CsI3. +• Evolution of the quantum efficiency of CsI in vacuum. +The vacuum in which the measurements were performed is not ultra high. The measured pressure +next to the chamber was in the range 10−5 to 10−4 mbar. This pressure is high enough to cause +contamination of the surface on the long-term. +Under such conditions, a degradation of the quantum efficiency of the porous CsI was recorded +only after a few days: the quantum efficiency after 2 days was at a value of 1040 ± 52 pA. This +corresponds to a drop of quantum efficiency of 9%. +This highlights the necessity to keep the photocathode in a very clean environment, as already +reported. +In the same time, no drop of intensity was recorded in the case of the sample CsI(C). +• Evolution of the quantum efficiency of CsI in air. +The evolution of the quantum efficiency after exposure to air is just a way to study the evolution of +the quantum efficiency of the photocathode when it is left in a more aggressive environment. +The different samples of CsI were just left in a protecting box, inside the clean room. So the samples +are still in a controlled environment, but in particular there was no protection against moisture, which +is known as the worst enemy of CsI photocathodes. +It turns out the evolution of the quantum efficiency is much more dramatic, than when the photo- +cathode is kept in vacuum (table 7.2): +After one night in air, the intensity was 736 ± 36 pA, which corresponds to a relative drop of +35 % of the quantum efficiency. +After one month in air, the intensity was only 113± 5.6 pA. So only 10% of the original quantum +efficiency was left. +No change of intensity was recorded for the sample of CsI(C) in the same time. This is a further +indication that the sample was already degraded at the time of the first measurement. +112 Experimental tests and discussion of the results +Time (in hours) Intensity measured (pA) +Introduction 160± 8 +0.5 188± 9.4 +1 217± 10 +2 230± 11 +∞ did not increase further +Table 7.3 : Evolution of the current returned by the sample CsI3(C) when placed in vacuum. +7.3.2.2 The quantum efficiency of CsI3, its evolution in air and comparison with CsI. +The quantum efficiency of CsI3 was evaluated the same way as CsI, except that in addition to +those measurements, after exposure to air, CsI3 samples were eventually put back in an atmosphere +saturated with I2 and then they were tested again. +Following the evolution of the microstructure presented in the last section, there is an evolution of +the CsI3 photocathode quantum efficiency when left in vacuum. +For all the samples of CsI3 prepared do not have the same microstructure, all the quantum efficiencies +of the various samples are not equal. Yet they all follow the same trend concerning the evolution of +their quantum efficiencies. +First, the sample made of ”CsI3(C)” is detailed here. Then a comparison of the maxi- +mum intensities of the different samples is given. +The sample ”CsI3(C)” +• Evolution of the quantum efficiency after introduction in the chamber under vacuum. +The sample made of CsI(C) after it was tested as a CsI sample was put in presence of I2 vapors for +two days, at a temperature of 40oC. The obtained CsI3(C) was then tested. +At the introduction in the chamber, the intensity was 160± 8.0 pA and rapidly evolved (table 7.3). +The maximum intensity was then ∼ 230 ± 11 pA. The microstructure then corresponds to Figure +7.10. +No further evolution of the intensity was recorded, so the sample was removed from the chamber. +• Evolution of the quantum efficiency when left in air. +The sample was then left for a long period (1 month) in air in the clean room (storage in a plastic +box). After only one day the sample had lost a great part of its quantum efficiency, for the measured +intensity was then 93± 4.6 pA. This evolution did not go further, and after one month, the quantum +efficiency was still 92± 4.6 pA (table 7.4). +7.3 CsI3 as a new photocathodes material 113 +Time in air Intensity measured (pA) +Introduction 230± 11 +1 day 93± 4.6 +30 days 92± 4.6 +Table 7.4 : Evolution of the current of the sample CsI3(C) sample after it was removed from vacuum, and +left in air. +Time (in hours) Intensity measured (pA) +Introduction 160± 8 +0.5 260± 13 +1.5 299± 14 +3 314± 15 +4 320± 16 +15 340± 17 +∞ did not increase further +Table 7.5 : Evolution of the quantum efficiency of the sample CsI3(C) in air after re-exposure to I2. +• Evolution of the quantum efficiency after re-exposure of the sample to I2. +Lastly the sample was put back in presence of I2 for a few days, and the quantum efficiency was +retested. The quantum efficiency then evolved according to the data of table 7.5. +In conclusion, the history of this peculiar sample can be plotted like on Figure 7.13. +114 Experimental tests and discussion of the results +Intensity +(pA) Vacuum Air Vacuum I2 Vacuum +320 +300 +280 +260 +240 +220 +200 +180 +160 +140 +120 +100 +80 +60 +40 Time +(Hours) +20 +1 Month +1 2 3 4 1 Month1 2 1 2 3 4 5 6 +Figure 7.13 : Summary of the evolution of the quantum efficiency of the sample of CsI3(C). after first +introduction in vacuum, one month stay in air, and Re-exposure to I2. +After the CsI sample was exposed to I2, there is an increase of efficiency when it is left in air. The +sample then becomes sensitive to pollution, and an exposure to air results in a drop of efficiency. +A re-exposure to I2 enables to recover the lost efficiency, and is even beneficial for the maximum +intensity obtained is then higher than after direct introduction of the sample. +A further cycle of exposure to I2 and stay in vacuum gave the same results. +CsI crystal from St Gobain. +As already explained, the performances of the CsI crystal by St Gobain could not be measured, +because of space charging. Only after it was exposed to I2 it became conductive enough to enable +measurements. +After a long exposure to I2, as highlighted by the microstructure and color changes, a part of the +sample turned into CsI3. +7.3 CsI3 as a new photocathodes material 115 +Time (in hours) Intensity measured (pA) +Introduction 120± 6 +2 130± 6.5 +10 151± 7.5 +∞ did not increase further +Table 7.6 : Evolution in vacuum of the intensity for the CsI(T l) sample by St Gobain, after exposure to I2. +The performances and behavior after exposure to vacuum and I2 of this sample are similar to those +of the ”CsI(C)” and pressed pellet samples (table 7.6). +Then, after only one week in air, the intensity recorded was only 68± 3.4 pA. +After it was exposed to I2 for a few days, the intensity rose to approximately the same value of +154± 7.7 pA again. +So this sample follows the same trend as the previous one except that a second exposure to I2 does +not enable a bettering of the efficiency, but only a recovery of this efficiency after pollution of the +sample by air. +Figure 7.14 : Exposure of the Luxel Sample to I2 in open air. +The CsI photocathode from Luxel. +A tentative was made to use the CsI photocathode from Luxel to make a CsI3 one as with the crystal +by St Gobain. Unfortunately, it turned out that the Aluminized mylar substrate used to grow the +photocathode is very reactive to I2. It was not the CsI of the photocathode, which reacted with I2, +but the aluminum of the substrate itself. +So the only way to obtain a CsI3 photocathode from this sample was to put in open air, a solid iodine +grain on the CsI deposited layer (Figure 7.14). The grains were deposited around the measured area, +116 Experimental tests and discussion of the results +Time (in hours) Intensity measured (pA) +Introduction 390± 19 +1 412± 20 +2 580± 29 +4 812± 40 +∞ did not increase further +Table 7.7 : Evolution in vacuum of the quantum efficiency of the porous CsI sample after exposure to I2 +Time (in hours) Intensity measured (pA) +Introduction 120± 6.0 +0.5 141± 7.0 +2 177± 8.8 +4 200± 10 +∞ did not increase further +Table 7.8 : Evolution of the current of the CsI3 pressed pellet in vacuum +on place invisible to the X-rays (far from the 7 ∗ 7 mm2 enlightened area). Table 7.7 gives the results +of the measurements of the photocurrent. +It is evident that such a method cannot guaranty a good homogeneity of the CsI3 surface. So the +result of those measurement must be taken with caution. +When the sample was removed from the chamber, it was completely white. So, if the value at the +time of introduction is likely to be a measurement of the quantum efficiency of CsI3, then, the sample +progressively changed back into CsI. +This measurement was performed right after measuring the quantum efficiency of CsI, so the last +value is a measurement of clean (less than a few minutes in air in total) but transformed -see struc- +tural analysis- CsI. +CsI3 pressed pellets +The evolution of the quantum efficiency of the samples made of compacted CsI3 follows the same +trend as those obtained from CsI exposed to I2. At the introduction, the samples typically return +an intensity of 120± 6 pA, and this values rises in a few hours to typical values of 200± 10 pA (table +7.8). +In the meantime, as explained earlier, the surface changes color, and the microstructure evolves as +depicted earlier. +A tentative of study of the stability on the long-term was performed by leaving one of the samples +of compacted CsI3 in vacuum. But after one week, two pumps had broken, so the experiment was +stopped (it is likely that the I2 release was at the origin of this failure). +Still, the transformation of this sample had probably gone deeper than with the other samples, and +7.3 CsI3 as a new photocathodes material 117 +Intensity measured (pA) +few hours 1 week +188± 9.4 31± 1.5 +Table 7.9 : The photocurrent at the reintroduction of the CsI3 pressed pellets according to the time passed +in vacuum, and after one month in air. +Time in hours Intensity measured (pA) +Time in vacuum before left in air few hours 1 week +Introduction 130± 6.5 31± 1.5 +1 177± 8.8 32± 1.6 +2 257± 12 35± 1.7 +4 274± 13 37± 1.8 +∞ did not increase further did not increase further +Table 7.10 : Recovery of the photocurrent in vacuum, for two CsI3 pressed pellets, which stayed a few hours +or one week in vacuum, and then one months in air and two days in presence of I2. +the color of surface had change to a brighter color than the one of the samples, which stayed only +one or two complete days in vacuum. +After this, the two samples (the one pumped 1 week, and the one pumped only for the primary +measurements: few hours) were left for one month in a plastic box in the clean room, and were tested +again. +It turned out that the quantum efficiency of both samples evolved very differently. +At their reintroduction in the chamber, the intensities were rather different (table 7.9): +• The sample, which had stayed only a few hours in vacuum had an intensity of 188± 9.4 pA. +• The sample, which had stayed one week in vacuum had an intensity of only 31± 1.5 pA. +No real evolution was then recorded. So the samples were put in presence of I2 vapors. After two +days, the sample, which had been left only a few hours in vacuum was dark again, while the color of +the sample which had been left in vacuum for one week did not change color. The quantum efficiencies +of the two samples were tested again (table 7.10). +The sample which had stayed only a few hours recovered like the other samples its quantum efficiency, +while the one which had stayed a long time in vacuum, kept a very low quantum efficiency. No further +stay in I2 of the sample left 1 week in vacuum could change its color, and its quantum efficiency did +not change neither (same value of ∼ 35± 1.75pA). +Later, a tentative to remove mechanically the bright layer was successful: it detached easily when +pressed by tweezers. +The uncovered layer was then tested, and showed similar properties to those of the freshly made +118 Experimental tests and discussion of the results +sample. +Summary +The typical values obtained with the different samples can be found in the table 7.11. +It appears that, despite the variations in the precise values, the general trend is the same for the +different samples. +Some general conclusions can be already given when looking at the different values: +• Contrary to CsI, CsI3 seems to be insensitive to air. +• The quantum efficiency of CsI3 is lower than clean CsI (from the Luxel sample, probably a +factor 7), but better than exposed to air CsI. +• When exposed to I2 and then put in vacuum at least twice, the quantum efficiency is increased. +This does not further increase after two cycles yet. +• A too long stay of CsI3 in vacuum makes the sensitivity to air rise, and I2 treatment does not +enable to recover the best efficiency. +Also, both ways to obtain CsI3 samples (from CsI and CsI3) seem to be equivalent as they offer +similar values at the time of introduction. +7.3.3 Analysis of the results obtained with CsI3 +The behavior of the CsI3 as a photocathode can be explained by a transformation of the outer layer, +following the reaction +CsI3 + CsI + I2 (1) +The CsI3 samples, when put in vacuum transform according to the reaction (1) in the left to right +direction, so a layer of fresh CsI is formed at the surface of the sample. This is visible by the change +of color from dark red (CsI3) to yellow-white (CsI). +The different test with pure CsI and CsI3 show that CsI is a better emitter, so there is an increase +of quantum efficiency when this reaction occurs, until all the CsI3 of the active layer of the photo- +cathode transformed in CsI. +The reaction does not stop as the I2 released in the chamber is pumped, so the equilibrium vapor +pressure is never reached. Eventually, a thick layer of CsI is formed on top of the sample, which +corresponds to the one removed mechanically from the CsI3 pressed pellet after it stayed one week +in vacuum. +When left in a plastic box, there is no evolution of the microstructure, or of the emission character- +istics, at least in the time scale of a few months. This indicates that when the equilibrium vapor +pressure of I2 is reached, there is no evolution of CsI3. +When I2 is released, there is a change of the surface microstructure as shown by the SEM pictures. +This evolution is in favor of a greater quantum efficiency of the CsI left: the microstructure becomes +7.3 CsI3 as a new photocathodes material 119 +Test of CsI Test of CsI3 +Before After After exposure After exposure After (re)exposure +Samples +exposure to air exposure to Air to I2 to air to I2 +CsI(C) 144± 7.2 91± 4.5 160± 8→ 230± 11 92± 4.6 340± 17 +CsI Crystal From Saint Gobain Charging 120± 6→ 151± 7.5 68± 3.4 154± 7.7 +CsI from Luxel 1140± 57→ 760± 38 113± 5.6 390 ∗ ±19→ 812± 40 370± 18 XXX +± → ± short stay in vacuum 118± 5.9 270± 13CsI3 XXX ** 130 6.5 200 10 long stay in vacuum 31± 1.5 37± 1.8 +*: this value must be taken with caution. +**: No sense. +Table 7.11 : CsI3 measurements summary. +120 Experimental tests and discussion of the results +porous, which betters the quantum efficiency of CsI as already known. +If the samples of CsI3 are left in air after a long stay under vacuum, the thick layer of CsI gets +polluted and the quantum efficiency of the photocathode drops rapidly, like it does for pure CsI +samples. After a short stay in vacuum, CsI3 seem to be less sensible to air pollution. +It seems that the state of degradation of the CsI layer (after a stay in air, so after exposure to +moisture) has an impact on the possibility to re-transform in CsI3. +In conclusion: +• If the CsI3 did not stay too long in vacuum, it can be ”recovered” (the formed CsI layer can +retransform in CsI3) even after a long stay in air. +• If the CsI3 stayed a long time in vacuum, the recover can occur only after a short exposure to +air. +This indicates that exposure to I2 does not enable to regenerate a thick layer of degraded CsI (or +that the reaction is much slower). +7.3.4 Conclusion on the use of CsI3 as a photocathode +The study performed on CsI3 show that it is itself an interesting photocathode, providing a good +quantum efficiency, and a good robustness to pollution and moisture. It has the disadvantage that it +is unstable in vacuum, so it is mandatory to let the gas in the detector reach the equilibrium vapor +pressure to enable its use as a photocathode. +The most promising approach is its use as a precursor to CsI. Indeed, CsI3 is not an emitter +as good as CsI in terms of quantum efficiency. But its instability under vacuum and its insensitivity +to air degradation makes it a very attractive choice to create porous CsI photocathode. +Indeed, as the material is very easy to manipulate in air, it is very easy to place the photocathode in +gas-filled detectors. Then, simply pumping the chamber enables to obtain a porous CsI photocathode, +which is the best photocathode available (eventually several cycles of pumping and exposure to I2 +can be necessary to obtain the best structure / quantum efficiency). +Later maintenance operations are also easier to perform if the photocathode is first exposed to I2, it +then transforms in CsI3, which makes it much more robust to air damages. This method does not +enable to recover the efficiency of a CsI which was severely polluted though. +This study shows that CsI3 can potentially be a good way to fabricate porous CsI photocathodes. +Bibliography +[1] R.M.Bozorth et al., “Unknown title,” The Journal of American Chemical Society, vol. 47, p. 1561, +1925. This reference could not be obtained. +[2] H.A.Tasman et al., “Re-investigation of the crystal structure of csi3,” Acta Cryst., vol. 8, 59, +pp. 59–60, 1955. +[3] J.Runsink et al., “Refinement of the crystal structure of (c h ) asi and csi at 20o6 5 4 3 3 c and at +−160oc,” Acta Cryst., vol. B28, pp. 1331–1335, 1972. +[4] T.R.Briggs et al., “The polyiodides of cesium, cesium iodide, iodine, and water at 25oc,” The +Journal of Physical Chemistry, vol. 34, pp. 1951 – 1960, 1930. +[5] L.E.Topol et al, “Thermodynamic studies in the polyiodides systems rbi−rbi3, nh4i−nh4i3, csi− +csi3, and csi3 − csi4.,” Inorganic Chemistry, vol. 7, pp. 451–454, 1968. +[6] V.Dandendorf et al., “Progress in ultrafast csi-photocathode gaseous imaging photomultipliers,” +Nucl. Inst. and Meth. A, vol. A308, pp. 519–532, 1991. +[7] E.Shefer et al., “Photoelectron transport in csi and csbr coating films of alkali antimonide and +csi photocathodes,” J.Appl.Phys., vol. 92(8), pp. 4758–4771, 1993. +[8] A.Breskin et al., “New ideas in csi-based photon detectors: Wire multiplication and protection +of the photocathode,” IEEE Trans.Nucl.Sci, vol. 42(4), pp. 298–305, 1995. +[9] B.L.Henke et al., “The characterization of x-ray photocathodes in the 0.1-10kev photon energy +range,” J.Appl.Phys., vol. 52(3), pp. 1509–1520, 1981. +[10] J.E.Lees et al., “Thermally annealed soft x-ray photocathodes,” Nucl. Inst. and Meth. A, vol. 381, +pp. 453–461, 1996. + +Chapter 8 +Conclusion +The aim of this work was to develop new photocathodes with improved quantum efficiency and ro- +bustness to allow their use as a first stage X-ray electron converter in gas-filled detectors. +This implied both theoretical studies and practical experiments to identify the most promising tech- +niques to develop such device. +This work allowed the development of a simulation tool using a Monte Carlo method for prospecting +new materials and structures. It turned out that the tool could not simulate properly the photocath- +odes’ physics, leading to unreliable results. Deep investigations highlighted that it was the method +and not the specific program, which is adequate for such simulations. The Monte Carlo method can +be used to develop material already well known and better understand them, by developing specific +codes for this material. Unfortunately, this approach is of no help to investigate prospective materials, +which properties are not known. This limit finds its root in the strong variation of the electrons dy- +namic in the bulk and at the surface of the material with its precise structure and chemical state. So +any Monte Carlo Study of a photocathode material implies a deep study of the materials properties, +which is just longer than a direct experimental study. +Still the development of this tool helped in understanding the key parameters which govern one pho- +tocathode quantum efficiency. +In order to enable reliable tests of the quantum efficiency of the photocathodes, an experimental setup +was developed and built. This setup showed excellent characteristics, as it was able to measure very +weak photocurrents, while being very flexible. Currents of less than 1 fA were successfully measured. +The setup then served as a basis for all study of the quantum efficiency of prospective photocathodes. +The last part of the work consisted in developing methods to better the quantum efficiency of photo- +cathodes. Various approaches were investigated, and eventually experimentally tested. In particular, +the study of the impact of microstructures on the material efficiency was performed, and the in- +124 Conclusion +vestigation of a scintillator-low energy photocathode system was performed. The most promising +approach, and which was more extensively investigated is the use of CsI3 as a precursor to CsI, +which is currently the best known photocathode. +The use of CsI3 as a photocathode is advantageous in several ways: +• Contrary to CsI, CsI3 is not hygroscopic, and is rather resistant to pollution. Thus, it can be +easily manipulated in air. +• When put in vacuum, it releases I2, and transforms in CsI with a porous structure. Porous +CsI is known for being the best photocathode in terms of quantum efficiency. So CsI3 is a way +to obtain structured photocathodes, without using complex evaporation systems, which enable +the growth of porous CsI photocathode. A simple deposition of CsI3 or even of unstructured +CsI later exposed to I2 vapors is enough to obtain a structured CsI photocathode. +• The reaction CsI3 + CsI + I2 is reversible. So one can protect CsI from air pollution by +exposing it to an atmosphere saturated with iodine. This is a very attracting method for it +simplifies dramatically the maintenance operations. +So the use of CsI3 as a photocathode is technologically promising. It can lead to the fabrication +of gas-filled detectors, which can answer the growing need of fast, large areas counting detectors in +photon science... +Further study will need to validate experimentally this approach to create and protect CsI photo- +cathodes. +Appendix A +Detector characteristics +A.1 Position resolution in the case of gas-filled detectors +The spatial resolution gives information on the accuracy of the position returned by the detector. +The position resolution is the result of four main contributions [1]: +σ = (σ2 + σ2 + σ2 + σ2 )1/2det noise diff er aval . +where +• σnoise is the r.m.s contribution from the electronic noise. I depends on the type of readout. +• σdiff is the contribution due to electrons diffusion. +• σer is the contribution from Auger electrons and photoelectrons. +• σaval is the contribution from avalanche centroid fluctuation. It is due to statistical variations +and varies greatly with gas gain. It is often the main contributor and depends on both pressure +and gas mixture. +More details on each contributions can be found in [1] and in chapter 4 of [2]. +A.2 Energy Resolution +The Energy resolution is usually defined as the full width half maximum of the spectral response of +the detector to a given energy. +Indeed, with an excellent prec√ision(∼ 1%), the response has a gaussian shape. More precisely, The +resolution R is given by: R = (electronic noise)2 + (Fano)2: +→ Electronic noise gives the contribution of the electronic to the error of measurement. This +term is itself the result of several contributions. +→ Fano is the contribution due to the Fano Statistics: the generation of electrons and holes +charges is the result of a statistical process. The energy of the incoming particle/photon is +126 Detector characteristics +shared between lattice excitation (∼ 2/3) and the√generation of charge carriers (∼ 1/3). The +resultant spread in energy is FWHMFano = 2.35 FεE with ε being the charge pair creation +energy (ex. 3.63eV/e-h for Si), F the Fano factor (F ≈ 0.12 for Si, F is not a constant), and +E the energy. +A.3 Space Charging in gas-filled detectors +The space charging effect is important because it can be physical limitation to counting rate char- +acteristics. Two methods have been given by Sipilia et al. in 1980 and later by Mathieson et al. in +1992 [3, 4]. +It concerns the reduction of the electric field between the anode and cathode due to ions in the volume. +This presence is unavoidable for the amplification process necessarily creates such ions (ionization +avalanche). The two models calculate the effective field reduction at the anode surface. +Bibliography +[1] G.C.Smith, “Gas-based detectors for synchrotron radiation,” Journal of Synchrotron Radiation, +vol. 13, pp. 172–179, March 2006. +[2] G.F.Knoll, Radiation Detection and Measurement. Willey, 2000. +[3] H.Sipila et al., “Mathematical treatment of space charge effects in proportional counters,” Nucl. +Inst. and Meth., vol. 176, pp. 381–387, 1980. +[4] E.Mathieson et al., “Gain reduction due to space charge in a multiwire proportional chamber +irradiated by a uniform beam of rectangular section,” Nucl. Inst. and Meth. A, vol. 316, pp. 246– +251, 1992. + +Appendix B +Monte Carlo Application Examples +B.1 Simple Examples of statistical sampling methods +In this section, some of the most classical example of statistical sampling methods are given. Those +methods can be considered as particular application of the Monte Carlo Method1. +B.1.1 Calculus of an integral +As a first approach to the Monte Carlo method, an example of calculation of an integral is given: +Let assume the function φ is to be integrated between a and b: +∫ b N∑−1 b− a 1 b− a +Φ(t)dt = Φ(xi) +O( ) with xi = a+ − i.a N N N 1i=0 +This is the classical formula of the trapezoidal rule. +Instead of a uniform sampling, imagine an evaluation where the positions {xi} are random numbers +uniformly distributed in the interval [a, b]; this yields a Monte Carlo integration: +∫ b ∑N b− a √1Φ(t)dt = Φ(xi) +O( ) with a ≤ xi ≤ b. +a N Ni=1 +In this particular exa√mple, the methods appears to be less efficient than the trapezoidal rule for its +absolute error is in 1/ N instead of 1/N . Though the Monte Carlo approach has a strong advantage +over it: it is independent of the number of dimensions. So, contrary to the uniform sampling, which +has an error scaling as N−1/d, the Monte Carlo Method will stay with an error scaling as N−1/2. +This is a direct consequence of the central limit theorem. +1The name statistical sampling method is used instead of Monte Carlo Method, for those methods were developed +before the name Monte Carlo Method was given and presented as a general method. +130 Monte Carlo Application Examples +B.1.2 An historical example: Buffon’s needles +One of the first statistical approach to solve a mathematical problem is due to the mathematician +Comte de Buffon. +Figure B.1 : Georges Louis Leclerc Comte de Buffon Figure B.2 : The needle problem by Buffon +He invented a method to calculate an approximation of pi. Here is the problem he solved, which leads +to the approximation method of pi: if a needle of length l is dropped several times on a horizontal +surface ruled of parallel lines separated of a distance d¿l, what is the probability ℘ that the needle +cross one line? +That outcome will happen only if 0 6 A 6 d and 0 6 θ < pi. +If we assume that the vector (A, θ) is randomly distributed on the region [0, d[×[0, pi[, then the +probability 1∫d∫ensity function is dpi , and the probability that the needle cross the line is:pi l sin θ 1 +℘ = dAdθ +0 0 dpi +2l E(M) +So the probability is ℘ = = if M is the random variable for the number of times the needle +dpi n +cross the line, and n the number of drops. +n 2l +It appears that is a statistical estimator for pi. So to determine pi, one can evaluate E(M), +E(M) d +which is easily done, just dropping needles. +De´veloppement de photocathode de meilleures +efficacite´s quantiques pour de´tecteurs a` gaz +Re´sume´ en franc¸ais. +Introduction +Ce travail de the`se vise a` explorer diffe´rentes voies d’ame´lioration de l’efficacite´ des photocathodes. +Plus ge´ne´ralement, il prend place dans le de´veloppement de de´tecteurs a` gaz de rayons X de grandes +surfaces, susceptibles de re´pondre aux besoins croissants en matie`re de vitesse et de taille des de´tecteurs +utilise´s dans les domaines du me´dical et de la recherche mobilisant le rayonnement synchrotron. +Les photocathodes pour de´tecteurs a` amplification par gaz +De´tecteurs a` 2 dimensions +Les de´tecteurs a` 2 dimensions (ou a` 1 dimension) sont par opposition aux de´tecteurs ponctuels +capables de fournir une information spatiale sur la particule de´tecte´e. +Ce type de de´tecteur pre´sente l’e´norme avantage qu’il dispense de syste`mes me´caniques pour couvrir +l’ensemble de l’espace (dans le cas de l’espace re´el comme re´ciproque). Ainsi il est possible d’effectuer +beaucoup plus rapidement les expe´riences d’imagerie. Certaines expe´riences ne´cessitent meˆme l’utili- +sation de de´tecteur 2D, soit pour des raisons de temps d’exe´cution autrement trop longs (cas de la +tomographie 3D par exemple) soit meˆme pour des raisons de de´gradation de l’e´chantillon qui ne peut +supporter le faisceau qu’un temps tre`s court (notamment dans les domaines de la biologie ou dans le +cas des analyses me´dicales !). +Les de´tecteurs a` amplification par gaz +Les de´tecteurs a` amplification par gaz (aussi appele´s  de´tecteurs gazeux ), sont parmi les plus +vieux syste`mes de de´tection de rayonnement ionisant. Ils sont en particulier les premiers a` avoir offert +132 Re´sume´ +une de´tection e´lectronique du passage d’un rayonnement ou d’une particule ionisante. +L’exemple le plus ce´le`bre de ce type de de´tecteur est le Tube Geiger introduit par Geiger etMueller +en 1928 apre`s que Geiger et Rutherford aient de´couvert le principe de la multiplication e´lectronique +dans un gaz. +Ces de´tecteurs sont base´s sur une multiplication interne des e´lectrons ionise´s a` la suite d’un de´poˆt +d’e´nergie par la particule/le rayonnement traversant le gaz. Cette multiplication des e´lectrons est +rendue possible par la pre´sence d’un champ e´lectrique au sein de la chambre a` gaz, qui acce´le`re +les charges pre´sentes. Si l’e´nergie cine´tique gagne´e par ces charges entre deux collisions avec une +mole´cule du gaz est supe´rieure a` l’e´nergie d’ionisation d’une particule de gaz (typiquement 35eV), +alors la particule devient susceptible de ioniser une particule de gaz, et est donc a` la source d’une +cascade de ionisation. L’augmentation exponentielle du nombre de charges permet alors une de´tection +aise´e par simple collection des charges sur des e´lectrodes. +Les de´tecteurs a` gaz constituent maintenant une technologie mature. Ils ont comme avantage principal +de permettre la fabrication de de´tecteurs de grande dimension et rapides a` un couˆt acceptable, tout +en permettant un fonctionnement en comptage (par opposition aux de´tecteurs fonctionnants avec +des e´crans fluorescents, qui impliquent un mode d’ope´ration en inte´gration, et donc un bruit plus +important). +Ils pre´sentent aussi des inconve´nients, notamment un phe´nome`ne de parallax, qui de´grade fortement +la re´solution dans le cas des incidences obliques, et une efficacite´ quantique limite´e notamment aux +e´nergies supe´rieures a` 10keV. En effet, l’efficacite´ d’absorption du gaz augmente avec la pression, +alors que l’efficacite´ d’amplification est optimum pour les faibles pressions. +Une approche pour contrebalancer ces deux inconve´nients, consiste en l’utilisation de photocathodes +solides comme convertisseurs photon → e´lectrons, permettant ainsi une se´paration (et donc une +optimisation se´pare´e) des deux fonctions d’absorption et d’amplification. +Les photocathodes de´die´s a` une utilisation dans des de´tecteurs a` gaz +Les photocathodes permettent une conversion de la lumie`re incidente en e´lectrons par le biais de +l’effet photoe´lectrique. +Les photocathodes ont principalement e´te´ utilise´es au sein de photomultiplicateurs, dans lesquels elles +sont couple´es a` une se´rie de dynodes, capables d’amplifier fortement le signal e´lectrique. +Le me´canisme qui me`ne a` l’e´jection de l’e´lectron a` l’exte´rieur de la photocathode est en fait complexe : +l’e´lectron(s) e´mis a` la suite de l’absorption par effet photoe´lectrique du photon incident subit une se´rie +d’interactions avec les autres e´lectrons pre´sents dans le mate´riau et perd rapidement cette e´nergie. +Au cours de ce trajet, il ionise lui-meˆme d’autres atomes et cre´e ainsi une se´rie d’e´lectrons chauds +secondaires au sein du mate´riau. Eventuellement, un ou plusieurs de ces e´lectrons peuvent atteindre +la surface et quitter la photocathode. +Cependant, pour quitter le mate´riau, l’e´lectron doit passer une barrie`re de potentiel appele´e affinite´ +e´lectronique dans le cas des semi-conducteurs, ou travail de sortie dans le cas des me´taux. Du fait +de leur thermalisation rapide apre`s e´jection de l’atome, peu d’e´lectrons peuvent effectivement passer +cette barrie`re et les rendements d’e´mission sont en ge´ne´ral faibles. +133 +Les photocathodes pre´sentant les meilleurs rendements pre´sentent la particularite´ de pre´senter une +affinite´ e´lectronique ne´gative. Ainsi, les e´lectrons chauds pre´sents dans le mate´riau sont facilement +e´jecte´s et les rendements sont e´leve´s. Cependant, ces mate´riaux pre´sentent aussi une grande sensibilite´ +a` toute forme de pollution de leur surface, qui leur fait perdre cette affinite´ e´lectronique ne´gative. +En conclusion, ide´alement une photocathode pour de´tecteurs a` gaz pre´sente les caracte´ristiques sui- +vantes : +Une affinite´ e´lectronique ne´gative : afin de laisser sortir un maximum d’e´lectrons chauds cre´e´s +a` la suite de l’absorption du photon incident. +Un grand pouvoir d’arreˆt : afin de garantir que les photons seront absorbe´s pre`s de la surface +d’e´jection des e´lectrons. Le pouvoir d’arreˆt est en ge´ne´ral plus e´leve´ avec des e´le´ments de nume´ro +atomique Z e´leve´. +Une faible re´activite´ chimique : afin d’e´viter une trop grande sensibilite´ de la photocathode a` la +pollution par le gaz utilise´ pour l’amplification du signal (en particulier, les ions ge´ne´re´s lors de +l’avalanche e´lectronique sont une grande source de pollution). +Modalite´s de l’e´tude de photocathodes a` efficacite´ quantique supe´rieure +L’e´tude entreprise lors du travail de the`se comporte Trois e´tapes principales : +1. Une e´tude the´orique des photocathodes. En particulier un code de simulation par Monte Carlo +a e´te´ de´veloppe´ pour simuler l’efficacite´ des photocathodes. +2. L’e´tude et la fabrication d’un dispositif expe´rimental permettant de tester concre`tement des +photocathodes. +3. L’e´tude de diffe´rentes me´thodes pour ame´liorer l’efficacite´ des photocathodes, et l’e´tude de +nouveaux mate´riaux potentiellement bons photo-e´metteurs. +Chacune de ces e´tapes est de´crite brie`vement ci-dessous. +Le de´veloppement d’un code de simulation par me´thode Monte Carlo +introduction a` la me´thode Monte Carlo +A la suite de sa premie`re utilisation au cours du Projet Manhattan a` Los Alamos au lendemain de la +seconde guerre mondiale pour le de´veloppement de la bombe nucle´aire ame´ricaine, la me´thode Monte +Carlo pour la simulation du transport de particules dans la matie`re est devenue un outil standard de +la physique des particules. +Cette me´thode permet de rendre compte de l’aspect ale´atoire de l’interaction des particules avec la +matie`re. Elle consiste a` simuler le trajet des particules en calculant la probabilite´ d’interaction d’une +particule au moyen d’un ge´ne´rateur de nombres ale´atoires, et des densite´s de probabilite´s d’interac- +tions pour chacun des me´canismes d’interaction connus. Ces densite´s de probabilite´s sont e´value´es au +moyen des tables de sections efficaces, qui sont des grandeurs expe´rimentales. +134 Re´sume´ +le code de´veloppe´ +Le de´veloppement d’un code de simulation par Monte Carlo est un projet tre`s ambitieux en soi, aussi +une librairie standard de simulation par Monte Carlo a-t-elle e´te´ utilise´e pour e´crire le code. +Le choix a e´te´ porte´ surGeant4, une librairie de´veloppe´e par un consortium de laboratoires et pilote´e +par le CERN. L’ensemble du code ainsi qu’une documentation de´taille´e est disponible sur le site du +CERN, ce qui a fortement participe´ a` la popularite´ du code, outre ses performances de simulations +reconnues. +En particulier, c’est la pre´sence de plusieurs bibliothe`ques de´die´es aux basses e´nergies qui a justifie´ +l’adoption de Geant4 comme base du code. +Les simulations devaient permettre de pre´dire le gain en efficacite´ de certaines microstructures, et de +pre´dire les efficacite´s quantiques de certains mate´riaux encore non e´tudie´s. +Malheureusement, il s’est ave´re´ que le code e´tait beaucoup trop impre´cis pour mener a` bien ce type +de calcul. Les efficacite´s pre´vues par le code se sont ave´re´es comple`tement fausses dans un certain +nombre de cas de´ja` connus. +Une e´tude plus approfondie a montre´ que la simulation de photocathodes est actuellement impossible +avec ce type de simulations. Deux facteurs principaux expliquent cela : +Les tables de sections efficaces utilise´es par les codes Monte Carlo sont trop impre´cises. En effet, +l’obtention de valeurs de sections efficaces a` basse e´nergie est beaucoup plus difficile qu’a` haute +e´nergie, du fait du nombre d’interactions que subissent les particules a` ces e´nergies. De ce fait, +les tables de sections efficaces a` basse e´nergie sont base´es sur des mode`les semi-empiriques, et +sont entache´es de nombreuses incertitudes. +L’approche interaction particule/atome qui est utilise´e est globalement trop grossie`re : elle ne +permet pas de rendre compte efficacement de l’e´tat chimique du mate´riau et de sa surface. En +particulier, l’e´tat de surface, qui s’ave`re eˆtre une donne´e cruciale n’est pas mode´lisable par une +approche purement atomistique. +Le code n’a donc pas pu eˆtre utilise´ pour effectuer des simulations de photocathodes. +Etude et construction d’un dispositif expe´rimental +Afin de pouvoir tester expe´rimentalement les photocathodes envisage´es, un dispositif adapte´ a e´te´ +cre´e´. +Il consiste essentiellement en une chambre a` vide munie de connecteurs et d’une feneˆtre adapte´e, et +d’un ampe`reme`tre tre`s pre´cis : la chambre posse`de une fine feneˆtre de beryllium permettant de laisser +passer une large proportion du flux de rayons X. Des connecteurs triaxs permettent de connecter +directement sur la chambre le pre´-amplificateur associe´ a` l’ampe`reme`tre. Au sein de la chambre, +l’ensemble des pie`ces supportant la photocathode au plus pre`s de la feneˆtre est re´alise´ en PEEK, +mate´riau pre´sentant a` la fois une grande durete´ et une re´sistance e´lectrique e´leve´e. Une grille de +collection est monte´e environ 5mm au-dessus de la photocathode teste´e. Enfin, un connecteur CF +standard permet la connection a` une pompe. +135 +L’ampe`reme`tre utilise´ est un Keithley 6430. Cet appareil est capable de mesurer des courants infe´rieurs +au fA, graˆce a` la pre´sence d’un pre´-ampli exte´rieur, qui permet d’approcher autant que possible les +connecteurs de la source de courant. +Le dispositif de mesure a e´te´ teste´ avec succe`s avec une source radioactive a` des courants de l’ordre +de 0,5fA. Le courant de fuite e´tant infe´rieur a` 10% de la valeur mesure´e. +Cependant, le dispositif a e´te´ essentiellement utilise´ avec un tube conventionnel de rayons X, cathode +de cuivre. L’ensemble des ope´rations de montages du dispositif et des e´chantillons s’est de´roule´ en +salle blanche. +Les photocathodes e´tudie´es et leur efficacite´ +Principalement deux approches ont e´te´ adopte´es pour ame´liorer l’efficacite´ des photocathodes exis- +tantes : +– L’e´tude de certaines microstructures et de leurs effets +– L’e´tude de nouveaux mate´riaux +Des microstructures pour ame´liorer les mate´riaux de´ja` connus +L’effet de microstructures sur l’efficacite´ des e´missions a e´te´ e´tudie´. +Deux types d’effets ont e´te´ recherche´s : +– Un effet purement ge´ome´trique afin de profiter de l’augmentation du rendement d’e´mission dans le +cas d’incidence oblique. +– Un effet d’e´mission de champ a e´te´ recherche´ par l’e´tude de micro-pointes de silicium. +Emission de champ +Dans le cas de structures tre`s pointues, telles que des pointes de silicium, il se produit une concentra- +tion du champ e´lectrique aux alentours de la pointe. L’ide´e e´tait donc de profiter de cette concentration +du champ e´lectrique normalement utilise´ pour faire migrer les e´lectrons photo e´mis vers la grille de +collection, pour e´tudier un e´ventuel phe´nome`ne d’augmentation du rendement d’e´mission par effet de +champ. +Malheureusement, aucun courant n’a pu eˆtre de´tecte´ par ce biais. C’est probablement le faible pouvoir +stoppant du silicium qui peut expliquer la tre`s faible efficacite´ quantique du silicium dans ce cas. En +effet, si les e´lectrons sont cre´e´s trop loin de la surface de la photocathode, une tre`s faible proportion +d’entre eux parvient a` la surface, ce qui se traduit par un rendement global tre`s faible. +Effet de l’angle +Dans le cas d’une incidence oblique des rayons X sur la surface du mate´riau, il se produit une +augmentation du rendement de la photocathode. En effet, une plus large proportion (facteur 1cosα +si α est l’angle d’incidence vis-a`-vis de la normale a` la surface) des photons est absorbe´e au sein de +la zone active de la photocathode (imme´diatement a` proximite´ de la surface). Il s’en suit donc une +augmentation du nombre d’e´lectrons qui peuvent s’e´chapper. +136 Re´sume´ +L’effet de structures, facile a` obtenir sur de larges surfaces (il s’agissait en fait de papier de verre clas- +sique ou de type Trizact), a re´ve´le´ que l’on obtient facilement un doublement de l’efficacite´ quantique +avec de simples structures pyramidales re´gulie`rement place´es a` la surface de la photocathode. +Le CsI3 comme nouveau mate´riau de photocathode +Le mate´riau le plus efficace actuellement connu est le CsI. En effet, ce sel de deux compose´s de +nume´ro atomique Z e´leve´ pre´sente un pouvoir stoppeur important, double´ d’une affinite´ e´lectronique +ne´gative. +De ce fait, le CsI peut revendiquer des efficacite´s de plusieurs pour-cents a` des e´nergies de quelques +keV. +Malheureusement, comme tous les mate´riaux a` affinite´ ne´gative, il est aussi fortement sensible a` la +pollution due a` son environnement, et, a` moins de le laisser sous ultra-vide (ce qui est re´alisable au +sein des photomultiplicateurs scelle´s) son utilisation ne peut eˆtre envisage´e au sein d’un de´tecteur a` +gaz (et ce malgre´ de tre`s nombreuses e´tudes dans ce sens). +En substitution a` ce mate´riau, le CsI3 : un de ses de´rive´s, peut constituer une alternative inte´ressante. +Le CsI3 est un mate´riau de couleur marron-orange´, instable sous vide (il se de´compose selon la +re´action CsI → CsI + I ), pre´sentant une densite´ de 4, 51gc˙m−33 2 . C’est un cristal dont la structure +appartient au groupe Pmcn. +Le mate´riau est commercialise´ par des entreprises telles que Sigma-Aldrich ou peut eˆtre obtenu en +mettant un e´chantillon de CsI au sein d’un atmosphe`re sature´e d’iode. +Les tests du CsI3 ont montre´ une efficacite´ intrinse`que inte´ressante, qui de plus augmente apre`s +quelques heures place´ sous vide (pression de l’ordre de 10−4 mBar). +Une e´tude plus pousse´e de ce mate´riau a permis d’e´tablir un sce´nario permettant d’expliquer cette +ame´lioration. +Lorsque la photocathode est laisse´e sous vide, le CsI3 se de´compose en CsI. Ceci explique l’ame´lioration +de l’efficacite´ alors constate´e, en effet le CsI est actuellement le meilleur mate´riau connu pour la +constitution de photocathodes. Il pre´sente cependant le de´faut d’eˆtre particulie`rement sensible a` la +pollution par le milieu, et en particulier, il est tre`s hygroscopique. +A l’inverse le CsI3 semble eˆtre particulie`rement peu sensible a` la pollution. Il peut de plus eˆtre +re´ge´ne´re´ apre`s un passage sous vide (et donc la transformation de sa surface en CsI) par mise dans +une enceinte contenant de l’iode solide, et donc ou` la pression partielle de I2 est importante. +L’e´tude a aussi montre´ une modification de la structure de la surface qui prend un caracte`re poreux +lors de la transformation CsI3 → CsI + I2. Ainsi, lorsque le processus de mise en contact avec I2 +puis mise sous enceinte sous vide est re´pe´te´, l’efficacite´ s’en trouve ame´liore´e. +L’utilisation de CsI3 comme pre´curseur du CsI est donc inte´ressante en soi, car elle permet une +structuration du CsI. On perd cependant la plus grande insensibilite´ du CsI3 en regard a` celle du +CsI. Ainsi, meˆme si le CsI pur est plus efficace que le CsI3 (facteur 8 environ), une fois pollue´, le +CsI est beaucoup moins efficace que le CsI3. +Cette approche peut s’ave´rer tre`s utile pour permettre l’utilisation du CsI comme photocathode dans +137 +le cas des de´tecteurs a` gaz. En effet il est possible de fabriquer les de´tecteurs munis de la photocathode +sous forme de CsI3 ce qui permet sa manipulation sous air. Ensuite, le de´tecteur e´tant herme´tique, +la transformation du CsI3 en CsI permet l’obtention d’une photocathode pre´sentant un caracte`re +poreux, et donc d’une grande efficacite´. Ceci apporte aussi une solution au proble`me de la maintenance +qui ne´cessite souvent l’ouverture du de´tecteur. On peut en effet prote´ger la photocathode de CsI en +l’exposant pre´alablement a` de l’iode (I2) ce qui la rend re´sistante a` l’humidite´. Ainsi il n’est plus +ne´cessaire d’ouvrir le de´tecteur en enceinte prote´ge´e de l’humidite´. + +Acknowledgements / Remerciements +The first thank of course goes to my supervisor Menyhert Menhard Kocsis. +Not much to say, apart that I would not have done much without his help and support. He did not +help only for the work, but he also showed great courage to defend me at a moment I had a very bad +time. +Thanks a lot Menhard ! +I would like to thank then people in chronological order : +Mes parents, ma famille pour leur soutient avant et pendant ce travail. +Mes grands parents car ils ont eu une importance de´cisive dans mes choix d’e´tude, et l’orien- +tation que j’ai donne´e a` mon travail. +Mlle. Lenoble ma professeur de physique en classe de 1e`re qui a su rendre une matie`re alors +bien fatiguante beaucoup plus attractive ! Vous voyez Mlle. Lenoble, j’ai fini par vous e´couter et aller +chercher tout seul les re´ponses aux questions auxquelles la physique n’a pas encore re´pondu... +Julie ! Et oui elle a certainement duˆ m’aider meˆme lorsque je ne m’en rendais pas compte... +My colleagues from the ESRF : +The whole ISG group. +In particular Christophe, Francis, Thierry, Cedric who provided me with a great and constant support +and taught me so much. +Also thanks a lot to Joel, Jose-Maria, Emmanuel, Laurent, Marc, Paul-Antoine, Pablo, Herve, Ri- +cardo, Jean-Claude, John, Ernesto, Cyril, Roland, Jean-Jacques, Denis... And last, as a former guy +140 Thanks / Merci ! +from ISG, Heinz who certainly had a peculiar place in this work... +Narayanan for being my tutor during this PhD. Thesis. +The Scisoft Group In particular Claudio and Romeu for sharing their knowledge concerning the +Monte Carlo method and programming. +The whole id15 beamline For their support each time they could give me a hand. +And also : Irina for the SEM images, Harald for the help in preparing the samples in the chemistry +lab, Gemma for the access to the die/press, Elizabeth for her help in preparing job interviews, Philippe +for providing me with a Pump, Fabienne for her daily help, and her bread ! Delphine for her help with +the administration from the University, Werner for his help with the mechanical pieces, Stephanie +and Patrick for the help with the safety aspects... +.. Guillaume, Andy, Virgile, Anne, Alex, Sylvain, Manuel, Chantal, Julio, Jorge, Davide, Valentina, +Simo, Moritz, Paul-Antoine, Paul, Adeline, Oier, Gemma, Florian, Yvonne, Frank, Delphine, Pas- +cal, Benoit, Sebastian, Sebastian (bis), Ioana, Olivia, Irmi, Jean-Michel, Wolfgang, Claudio, Romeu, +Rainer, Olivier, Mohamed, Bertrand, Christian, Julia, Peter, Till, Andreas, Stefen, Alex, Roberta, +Caroline, Elizabeth, Benedicte, Jose, Riccardo, Kieran, Nicolas... and those I forget, but who still +have a place in my heart ! +for all the good moments I had at the ESRF. +Mes tuteurs de l’Universite´ +Vincent Comparat et Johann Collot qui ont assure´ le suivi acade´mique et ont e´te´ de patientes +et passionnantes sources de conseils pour ce travail de the`se. +, diff --git a/examples/theses/TH2013PEST1177.pdf b/examples/theses/TH2013PEST1177.pdf new file mode 100644 index 00000000..f9462e78 Binary files /dev/null and b/examples/theses/TH2013PEST1177.pdf differ diff --git a/examples/theses/TH2013PEST1177/fulltext.pdf b/examples/theses/TH2013PEST1177/fulltext.pdf new file mode 100644 index 00000000..f9462e78 Binary files /dev/null and b/examples/theses/TH2013PEST1177/fulltext.pdf differ diff --git a/examples/theses/TH2013PEST1177/fulltext.pdf.txt b/examples/theses/TH2013PEST1177/fulltext.pdf.txt new file mode 100644 index 00000000..430a9e50 --- /dev/null +++ b/examples/theses/TH2013PEST1177/fulltext.pdf.txt @@ -0,0 +1,4937 @@ +Bio-methanation tests and mathematical modelling to +assess the role of moisture content on anaerobic +digestion of organic waste +Flavia Liotta +To cite this version: +Flavia Liotta. Bio-methanation tests and mathematical modelling to assess the role of mois- +ture content on anaerobic digestion of organic waste. Earth Sciences. Universite´ Paris-Est; +Universite´ de Cassino, 2013. English. . +HAL Id: tel-00967951 +https://tel.archives-ouvertes.fr/tel-00967951 +Submitted on 31 Mar 2014 +HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est +archive for the deposit and dissemination of sci- destine´e au de´poˆt et a` la diffusion de documents +entific research documents, whether they are pub- scientifiques de niveau recherche, publie´s ou non, +lished or not. The documents may come from e´manant des e´tablissements d’enseignement et de +teaching and research institutions in France or recherche franc¸ais ou e´trangers, des laboratoires +abroad, or from public or private research centers. publics ou prive´s. + Joint  PhD  degree  in  Env  ironmental  Technology   +Spécialité:D  Socciteenucre    deet    Tl’Uecnhivneiqrsuieté  d  Pea    lr’Eisn-­‐vEi +  srto  nnement   +Dottore  di  Ricerca  in  T  ecnologi  e  Ambientali   +   Degree  of  Doctor  in  Environmental  Tech  nology     Thèse – Tesi dFi laDvoiat  Ltoiortatato   – PhD thesis   + +Bio-Methanation tests and Mathematical Models to assess the effect of moisture content +on anaerobic digestion of complex organic substrates + +Defended 12/12/2013 + +In front of the PhD committee + +Dr. Renaud Escudiè Reviewer +Prof. Francesca Malpei Reviewer +Dr. Hab.E.D. Eric van Hullebusch Co-Promotor +Prof. dr.ir. Piet N.L. Lens Co-Promotor +Dr. Giovanni Esposito Promotor +Prof. Massimiliano Fabbricino Co-Promotor + +Erasmus  Joint  doctorate  prog r a m me  in   Environ men(EtaTl  eT CeocSh3n)o       +lo gy  for  Co ntamina t e d   S o l i d s ,   S o ils   and  Sedim enit  s             + +                      “Love  the  truth,  show  yourself  as  you  are,  without  claim,  without  fears  and  cares.  And  if  the  truth   +costs  you  persecution,  accept  it,  and  if  the  torment,  bear  it.  And  if  for  the  truth  you  have  to  sacrifice   +yourself  and  your  life,  be  strong  in  your  sacrifice”.   +   +San  Giuseppe  Moscati               +       +To  my  fami  mlyy,    msoyn  b  Cealorlvoe  dw  hhuos  ibs  asntidll    Cinla  mudyi  ob  ealnlyd.                   +       +     +   + + + + + + +     i  i           + Acknowledgment + +I would like to thank the European Commission for providing financial support through the Erasmus +Mundus Joint Doctorate Programme ETeCoS3(Environmental Technologies for Contaminated Solids, +Soils and Sediments under the EU grant agreement FPA No 2010-0009 and the French Ministry of +Foreign Affairs in the framework of MOY Programme under Moy Grant N°2010/038/01. +My gratitude also to the committee members, Dr. Renaud Escudiè and Prof. Francesca Malpei for their +helpful comments, constructive criticisms and valuable discussions. +I also would like to thank my PhD Supervisors, Prof. Giovanni Esposito and Prof. Massimiliano +Fabbricino for their invaluable suggestions, patient advices and continuous encouragement extended +throughout three years of this research. My special thanks go also to Prof. Francesco Pirozzi, Prof. Piet +Lens, Prof. Eric van Hullebusch and Prof. Patrice Chatellier for supporting my during my PhD mobility +and for scientific contribution on my research. +Special thanks to all friends, MariaRosaria, Jaka, Alberto, Stefano, Antonio, Anish, Rosita and Mario, +who were working with me in DIGA Department of University Federico II of Napoli and in DIMSAT +Department of University of Cassino and Lazio Meridionale. +Special thanks also to Ludovico, the head of the LARA (Laboratory of Environmental analysis and +research) for helping me with patience and enthusiasm in sample analysis and equipment operation. +I also would like to thank Luigi for all useful suggestions for the research and his help on mathematical +modelling and paper writing. +I can not forget all my international friends, in particular Rohan, Anna, Wendy, Alexandra and Mani, +who I met during my mobility period in UNESCO-IHE and in University of Paris Est, with whom I +shared my research and moments of fun! +To conclude, tanks to my parents, my sister and Claudio for supporting and encouraging my during my +PhD studies. +I would like also to express my thank to God for giving me the inspiration, courage and the patience +during the course of these three years and the little Carlo, who still has to born but accompanied me on +the last months of my PhD studies. So small, but he already gave to me the power for a brilliant final +defence and the hope for a prosperous and smiley future. +     + +   i  ii           + PhD Thesis Index +Abstract .................................................................................................................................................... 1 +Sommario ................................................................................................................................................. 2 +Resumè ..................................................................................................................................................... 4 +Samenvatting ........................................................................................................................................... 5 +Chapter 1. Introduction .......................................................................................................................... 7 +1.1 Problem Description ..................................................................................................................... 8 +1.2. Objectives of the Study ................................................................................................................ 9 +Chapter 2. Effect of moisture content on wet anaerobic digestion of complex organic substrates 12 +2.1 Introduction ................................................................................................................................. 13 +2.2. Materials and Methods .............................................................................................................. 15 +2.2.1 Digester set-up and analytical measurements ........................................................................ 15 +2.2.2 Preliminary tests: Drying procedure ...................................................................................... 15 + 2.2.3 Effect of particle size on AD ................................................................................................. 17 + 2.2.4 Effect of moisture content on AD ......................................................................................... 19 + 2.2.5 Mathematical model .............................................................................................................. 19 +2.3. Results and discussions .............................................................................................................. 21 +2.3.1 Effect of particle size on AD performance ............................................................................ 21 + 2.3.2. Effect of TS content on AD performances ........................................................................... 23 +2.4. Modelling results ........................................................................................................................ 24 +2.4.1. Modelling the effect of particle size on AD .......................................................................... 24 +2.4.2. Modelling the effect of TS on AD ........................................................................................ 27 +2.5 Conclusion .................................................................................................................................... 30 +Chapter 3. Effect of moisture content on anaerobic digestion of food waste .................................. 32 +3.1. Introduction ................................................................................................................................ 33 +3.2. Materials and Methods .............................................................................................................. 34 + 3.2.1 Experimental set-up ............................................................................................................... 34 + 3.2.2. Substrate and inoculum preparation ...................................................................................... 35 + 3.2.3. Analytical methods ............................................................................................................... 36 + 3.2.3.1 Methane production ......................................................................................................... 36 + 3.2.3.2 VFAs analysis .................................................................................................................. 36 + 3.2.3.3 Other parameters .............................................................................................................. 37 +3.3. Results and Discussion ............................................................................................................... 37 + 3.3.1 Bio-methane production .......................................................................................................... 37 + 3.3.2 VFAs production ..................................................................................................................... 39 +3.4 Conclusions .................................................................................................................................. 44 +Chapter 4. Effect of moisture content on anaerobic digestion of rice straw. .................................. 45 +4.1 Introduction ................................................................................................................................. 46 +4.2. Material Methods ....................................................................................................................... 47 + 4.2.1 Experimental set-up ................................................................................................................ 47 + 4.2.2. Substrate and inoculum preparation ....................................................................................... 47 + 4.2.3. Analytical methods ................................................................................................................ 48 +   4.2.3.1 Methane production, COD, TS, VS. .  ...............................................................................i.  v 4  8         + 4.2.3.2 VFAs and phenols analysis ................................................................................................. 48 +4.3. Results and Discussion ............................................................................................................... 49 + 4.3.1 Methane production ................................................................................................................ 49 + 4.3.2 Analysis of process intermediates ........................................................................................... 51 +4.4 Comparative process efficiency ................................................................................................. 55 +4.5. Conclusions ................................................................................................................................. 55 +Chapter 5. Modified ADM1 for dry and semi-dry anaerobic digestion of solid organic waste ..... 57 +5.1 Introduction ................................................................................................................................. 58 +5.2 Model description ........................................................................................................................ 59 +5.3 Model calibration ........................................................................................................................ 63 +5.4. Results and discussion ............................................................................................................... 68 +5.5 Conclusion .................................................................................................................................... 71 +Chapter 6. Literature Review .............................................................................................................. 72 +6.1 Mathematical modelling of aerobic plug flow reactor and non-ideal flow reactor .............. 73 + 6.1.1 Introduction ............................................................................................................................ 73 + 6.1.2. Design models and performance-prediction models ............................................................. 74 +6.1.3 Modeling approaches ............................................................................................................. 76 +6.1.4.Mathematical modeling of Activated Sludge plug flow reactors .......................................... 79 + 6.1.4.1 Process description ........................................................................................................... 79 +6.1.5. Model development ............................................................................................................... 80 + 6.1.5.1 Ideal PFR and CSTR in series .......................................................................................... 80 + 6.1.5.2 Non ideal flow reactor models ......................................................................................... 82 + 6.1.5.3 Computational fluid dynamics model development ........................................................ 84 + 6.1.5.4 Models comparisons ........................................................................................................ 86 +6.1.6. Mathematical modeling of fluidized bed reactors ................................................................. 86 + 6.1.6.1 Process description ........................................................................................................... 86 + 6.1.6.2 Model development .......................................................................................................... 87 + 6.1.6.2.1 Ideal flow reactor models ........................................................................................... 87 + 6.1.6.2.2 Non ideal flow reactor models ................................................................................... 88 + 6.1.6.2.3 Models comparisons .................................................................................................. 90 +6.1.7 Mathematical modeling of biofilter reactors .......................................................................... 90 + 6.1.7.1 Process description ........................................................................................................... 90 + 6.1.7.2 Model development .......................................................................................................... 91 + 6.1.7.2.1 Ideal flow reactor model ............................................................................................... 91 + 6.1.7.2.2 Non-ideal flow reactor model ....................................................................................... 92 + 6.1.7.2.3 Models comparisons ..................................................................................................... 95 +6.1.8 Model comparisons and validation and calibration ............................................................... 96 + 6.1.8.1 Models comparisons ........................................................................................................ 96 + 6.1.8.2 Activated sludge reactor ................................................................................................... 98 + 6.1.8.2.1 Ideal PFR and CSTR in series .................................................................................... 98 + 6.1.8.2.2 Non ideal flow reactor models ................................................................................... 99 + 6.1.8.3 Fluidized Bed Reactors ................................................................................................. 100 + 6.1.8.4 Biofilter reactors ........................................................................................................... 101 +6.2 Mathematical modelling of anaerobic plug flow reactor and non-ideal flow reactor .... 104 + 6.2.1 Introduction ....................................................................................................................... 104 + 6.2.2 Mathematical modelling of UASB Reactors .................................................................... 104 +   6.2.2.1 Hydrodynamic based models ........  .............................................................................. v1    06         + 6.2.2.2 Models coupling hydrodynamic with anaerobic digestion conversions ...................... 111 + 6.2.2.3 Models comparisons .................................................................................................... 112 + 6.2.3. Mathematical modelling of Anaerobic Biofilters ............................................................ 113 + 6.2.3.2 Models comparisons .................................................................................................... 116 + 6.2.4 Mathematical modeling of Anaerobic Biological Fluidized Bed Reactors ....................... 116 + 6.2.4.1 Models comparisons .................................................................................................... 118 + 6.2.5. Mathematical modeling of wet and dry digesters treating bio-solids ............................... 119 + 6.2.5.1 Models comparisons .................................................................................................... 123 + 6.2.6. Model comparisons and validation and calibration .......................................................... 123 + 6.2.6.1 Models comparisons .................................................................................................... 123 + 6.2.6.2 UASB reactor model validation and calibration .......................................................... 123 + 6.2.6.3 Anaerobic Biofilters model validation and calibration ................................................ 125 + 6.2.6.4 Anaerobic Fluidized Bed Reactor model validation and calibration ........................... 127 + 6.2.6.5 Wet and dry digesters model validation and calibration .............................................. 128 + 6.2.7. Conclusion ........................................................................................................................ 129 +Chapter 7. Discussion and Conclusions ............................................................................................ 130 +References ............................................................................................................................................ 135 +     v   i           +   +  Abstract +Dry Anaerobic Digestion (AD) presents different advantages if compared to wet AD, i.e. smaller +reactor size, lesser water addition, digestate production and pretreatment needed, although several +studies have demonstrated that water promotes substrate hydrolysis and enables the transfer of process +intermediates and nutrients to bacterial sites. +To better understand the role of water on AD, dry and semidry digestion tests of selected complex +organic substrates (food waste, rice straw, carrot waste), with various TS contents of the treated +biomass have been carried out in the present study. The results confirm that water plays an essential +role on the specific methane production rate, final methane yield and Volatile Solids (VS) +degradation. The final methane yield in semi-dry and dry conditions was 51% and 59% lower for rice +straw and 4% and 41% lower for food waste, respectively, if compared with wet conditions. +Inhibition tests, based on Volatile Fatty Acid (VFA) analysis, were carried out to investigate the +specific inhibition processes that take place with the selected substrates at different TS contents. In +wet AD of carrot waste no VFA accumulation was found, and all VFA concentrations were lower than +the inhibition limits. A direct correlation between TS content and total VFA (TVFA) concentration +was noticed for rice straw and food waste AD. For rice straw a maximum TVFA concentration of 2.1 +g/kg was found in dry condition, 1 g/kg in semidry conditions and 0.2 g/kg in wet conditions, whereas +for food waste the TVFA concentration was 10 g/kg in dry condition, 9 g/kg in semidry conditions +and 3 g/kg in wet conditions. +A Mathematical model of complex organic substrate AD in dry and semidry conditions has been +proposed to simulate the effect of TS content on the process. The data obtained from batch +experiments, in terms of methane production and VFA concentrations, were used to calibrate the +proposed model. The kinetic parameters of VFA production and degradation, calibrated using the +experimental data, resulted highly dependent on the TS content and different from wet AD literature +values. This is due to VFA accumulation in dry conditions, which implies lower values of the kinetic +constants function of the TS content introduced in the model. +Finally, as dry AD takes usually place in Plug Flow (PF) reactors, an historical and critical review on +the role of hydrodynamics in PF bioreactors has been carried out. +     1             + Sommario + +La digestione anaerobica (DA) a secco presenta diversi vantaggi rispetto a quella ad umido legati alla +riduzione delle dimensioni del reattore, al minore consumo di acqua, alla più facile gestione del +digestato prodotto, e alla mancata richiesta di pretrattamenti. Al contempo, tuttavia, il minor contenuto +di umidità può comportare dei problemi nello svolgimento delle reazioni di trasformazione, giacché +l’acqua promuove l’idrolisi dei substrati in trattamento, ha una azione di diluizione nei confronti di +eventuali intermedi di processo che potrebbero inibire il metabolismo microbico, e permette il +passaggio dei nutrienti e dei metaboliti attraverso il protoplasma cellulare. +Per meglio comprendere il ruolo dell’acqua sulla DA sono state effettuate prove di digestione batch a +secco, semi-secco, ed umido, adoperando tre substrati diversi, vale a dire: scarti alimentari misti, +paglia di riso e carote. Ai substrati è stato aggiunto un inoculo pre-digerito, il cui contenuto di solidi +sospesi è stato opportunamente variato attraverso un processo di disidratazione. I risultati ottenuti +hanno confermato che l’acqua svolge un ruolo fondamentale nello sviluppo del processo, +influenzando sia il tasso di produzione specifica di metano che la produzione complessiva di +quest’ultimo, oltre che le cinetiche di degradazione del substrato, e quindi il rendimento di riduzione +dei Solidi Volatili. +Nello specifico, prendendo a riferimento la produzione complessiva di metano ottenuta nel processo +ad umido, adoperando come substrato la paglia di riso i valori sono risultati ridotti di circa il 50% +nella digestione a semi-secco, e di circa il 60% nella digestione a secco. La riduzione è risultata meno +sensibile nel trattamento degli scarti alimentari misti, per i quali si è avuta un decremento del 4% nel +corso del processo a semi-secco, e di poco più del 40% nel corso del processo a secco. +Il monitoraggio della concentrazione degli acidi grassi volatili (AGV) nel corso delle prove ha +consentito di evidenziare gli eventuali accumuli di composti inibitori in funzione del substrato trattato +e della concentrazione di solidi totali (ST). A riguardo si è osservato che nel caso della DA ad umido +delle carote, non si è avuto alcun accumulo di AGV e tutte le concentrazioni misurate sono risultate +sempre inferiori al valore limite d’inibizione. Nel caso della DA della paglia di riso e del rifiuto +alimentare, è stata invece individuata una relazione lineare tra il contenuto di ST e la concentrazione +di AGV. Più in dettaglio per la paglia di riso è stato trovato un valore di concentrazione massimo degli +  AGV pari a 2,1 g·kg +-1 nel processo a secco, ed un   valore minimo di 0,2 g·kg +-1 nel processo ad umi2d    o,         + mentre nel processo a semi-secco la concentrazione si è attestata su un valore intermedio, pari ad 1 +g·kg-1. Nel caso della paglia di riso le concentrazioni rilevate sono state di 10 g·kg-1 nella digestione a +secco, di 9 g·kg-1 nella digestione a semi-secco, e di 3 g·kg-1 nel processo ad umido. +I risultati ottenuti nel corso delle prove sperimentali sono stati interpretati alla luce di un modello +matematico all’uopo sviluppato, in grado di simulare il processo di digestione di substrati organici +complessi, tenendo conto del diverso contenuto dei ST che caratterizzano i processi a secco, semi- +secco ed umido. La calibrazione del modello, effettuata sulla base di valori misurati relativi alla +produzione di metano ed alla concentrazione degli AGV, ha consentito di verificare come i parametri +cinetici relativi alla produzione ed alla degradazione di tali acidi siano fortemente dipendenti dal +contenuto di ST, e, nel caso dei processi a basso contenuto di umidità, notevolmente diversi dai dati +proposti in letteratura per la DA ad umido. Questo risultato è legato all’accumulo di acidi che +comporta una riduzione delle cinetiche di degradazione dei substrati organici complessi di partenza e +dei successivi intermedi delle trasformazioni in fase acquosa. Considerato che la DA a secco viene +solitamente sviluppata in reattori con flusso a pistone, la parte conclusiva del lavoro è stata infine +dedicata all’analisi storico-critica dei lavori presenti in letteratura relativi alla modellazione +idrodinamica dei processi biologici, ed al ruolo che le diverse configurazioni reattoristiche possono +avere nello sviluppo delle cinetiche di trasformazione, nell’ottica di porre le basi per una modellazione +c   ompleta della digestione a secco, comprensiva sia della parte idrodinamica che di quella biochimica. + + + + + + + + +     3             +  Resumè +La méthanisation par voie sèche possède différents avantages par rapport à la méthanisation par voie +humide. Les réacteurs sont plus petits, les besoins en eau sont moindres, la production de digestat et le +prétraitement nécessaire sont également moins importants. Cependant, plusieurs études ont démontré +que l'eau favorise l'hydrolyse du substrat et permet le transport des sous-produits d’hydrolyse et des +nutriments vers les bactéries. +Pour mieux comprendre le rôle de l'eau lors de la méthanisation, des tests de digestion sèche et semi- +sèche à partir de substrats organiques complexes (déchets alimentaires, paille de riz, déchets de +carotte), avec différentes teneurs en matière sèche de substrat traité ont été réalisées. Les résultats +confirment que l'eau joue un rôle essentiel sur le taux de production spécifique de méthane, le +rendement final de méthane généré et la dégradation de la matière volatile sèche (MVS). Le +rendement final de méthane produit dans des conditions semi-sèches et sèches est respectivement de +51% et de 59% inférieur avec la paille de riz et 4% et 41% de moins pour les déchets alimentaires en +comparaison avec des conditions humides. +Des tests d'inhibition basés sur l’analyse des acides gras volatils (AGV) ont été menées pour étudier +les processus d'inhibition spécifiques qui ont lieu avec les substrats sélectionnés à différentes teneurs +en matière sèche. Pour le cas de la méthanisation par voie humide des déchets de carotte, aucune +accumulation d’AGV a été trouvé, et toutes les concentrations d'AGV étaient inférieurs aux seuils +d'inhibition. Une corrélation directe entre la teneur en matière sèche et la concentration totale d’AGV +(AGVtot) a été mise en évidence pour la paille de riz et les déchets alimentaires. Pour la paille de riz, +une concentration d’AGVtot maximale de 2,1 g / kg a été trouvé pour la voie sèche, 1 g / kg dans les +conditions semi-sèche et 0,2 g / kg dans les conditions humides, alors que pour les déchets +alimentaires la concentration d’AGVtot était de 10 g / kg à l'état sec, 9 g / kg dans les conditions semi- +sèche et 3 g / kg dans les conditions humides. +Un modèle mathématique de la méthanisation de substrats organiques complexes dans des conditions +sèches et semi-sèche a été proposé pour simuler l'effet de la teneur en matière sèche sur le processus. +Les données obtenues à partir d'expériences en mode batch, en termes de production de méthane et de +concentration d'AGV, ont été utilisées pour calibrer le modèle proposé. Les paramètres cinétiques de +production et d’élimination d’AGV ont été calibrés à l'aide des données expérimentales, et il a été +  montré qu’ils sont fortement dépendants de la te  neur en matière sèche et différent des valeurs de4    la         + littérature concernant la méthanisation par voie humide. Cela est dû à l'accumulation d’AGV dans les +conditions sèches, ce qui implique d’utiliser des valeurs plus reduit concernant les constantes +d'inhibition introduites dans le modèle. +Enfin, comme la méthanisation par voie sèche a généralement lieu dans des réacteurs à écoulement +piston, une étude historique et critique de la littérature concernant la compréhension du rôle de +  l'hydrodynamique dans des bioréacteurs à écoulement piston a été réalisée. +  Samenvatting +Droge Anaërobe Vergisting (AD) biedt verschillende voordelen in vergelijking met natte AD: kleinere +reactorvolumes, minder water toevoeging, lagere digestaat productie en minder voorbehandeling nodig, +ondanks dat verscheidene studies hebben aangetoond dat water de substraat hydrolyse en de +uitwisseling van tussenproducten en nutriënten van en naar de bacteriële sites bevordert. +Om de rol van het water in AD beter te begrijpen, zijn in deze studie droge en halfdroge afbraaktests +uitgevoerd met geselecteerde complexe organische substraten (voedselafval, rijststro en wortelafval), +met verschillende Totale Vaste Stof (TS) gehaltes van de behandelde biomassa. De resultaten +bevestigen dat water een essentiële rol speelt in de specifieke methaan productiesnelheid, de +uiteindelijke methaanopbrengst en de afbraak van de organische stof (VS). De uiteindelijke +methaanopbrengst onder semi-droge en droge omstandigheden was, respectievelijk, 51% en 59% +lager voor rijststro en 4% en 41% lager voor voedselafval in vergelijking met natte omstandigheden. +Remmingsproeven, gebaseerd op vluchtige vetzuren (VFA) analyses, werden uitgevoerd om de +specifieke remming van de geselecteerde substraten bij verschillende TS concentraties te +onderzoeken. Gedurende de natte AD van wortelafval werd geen VFA accumulatie gevonden, en de +VFA concentraties bleven lager dan de inhibitiewaarden. Bij de AD van rijststro en voedselafval werd +een direct verband tussen het TS gehalte en de totale VFA concentratie gevonden. De maximale totale +VFA concentratie bedroeg 2,1 g/kg voor rijststro bij droge, 1 g/kg bij halfdroge en 0,2 g/kg bij natte +AD, terwijl voor voedselafval de totale VFA concentratie 10 g/kg bij droge, 9 g/kg bij halfdroge en 3 +g/kg bij natte AD bedroeg. +Een wiskundig model voor de AD van complexe organische substraten onder droge en halfdroge +condities werd ontwikkeld om het effect van de TS concentratie te simuleren. De data van +  batchexperimenten, met name methaanproductie   en VFA concentraties, werden gebruikt om 5h    et         + ontwikkelde model te kalibreren. De kinetische parameters van VFA productie en afbraak, +gekalibreerd met experimentele data, bleken sterk afhankelijk van de TS concentratie en verschilden +aanzienlijk van de natte AD literatuurwaardes. Dit komt door de VFA accumulatie onder droge +omstandigheden, dit leidt tot lagere inhibitiewaarden die in het model zijn opgenomen. +Ten slotte, omdat droge AD gewoonlijk plaats vindt in Plug Flow (PF) reactoren, werd een overzicht +van de geschiedenis van dit reactortype gemaakt en de rol van de hydrodynamica in deze PF +bioreactoren kritisch geëvalueerd. +     6             +   + + + +CHAPTER 1 + +     +Introduction +                 +     +     7             +CHAPTER 1 - INTRODUCTION +1.1 Problem Description + +Anaerobic Digestion (AD) is a biological process historically applied to wastewater treatment sludge, +that reduces Chemical Oxygen Demand (COD) of complex organic substrate and converts it into a gas, +which is mainly composed by methane and carbon dioxide. During this process organic matter is +progressively converted into simpler and smaller sized organic compounds obtaining biogas and +digestate as final products. This digestate is rich in nutrients and microelements and it is suitable for +utilization in agricultural contexts (Esposito et al. 2012a,b). Nowadays there is a pressing need to +manage correctly bio-waste from its generation stage to its safe disposal and to reduce its impact on +the environment. Therefore AD can be used as biological treatment as it is one of the best option to +achieve at the same time the objectives of the Kyoto Protocol and the EU Policies concerning +renewable energy and organic waste disposal. +Based on the solid content of the influent bio-waste, AD can be defined dry, semidry and wet. In dry +AD (high-solids digestion), the feedstock to be digested has a Total Solids (TS) content higher than +15%. In semidry AD the solid substrate to be digested has a TS content ranging between 10%-15%. In +contrast, wet AD (low-solids digestion) deals with diluted feedstock having a TS content lower than +10% (Li et al. 2011; Zeshan and Annachatre, 2012). In the last decades, dry AD has got much +attention due to its many advantages: smaller reactor volume, reduced amount of water addition, +easier handling of digested residues, minimal nutrient loss (Karthikeyan and Visvanathan, 2012; +Zeshan and Annachatre, 2012) and simplified pre-treatments compared to wet systems. The only pre- +treatment which is necessary before feeding the wastes into a dry AD reactor is the removal of coarse +materials larger than 40 mm (Vandevivere 1999). Because of the high viscosity of the treated bio- +waste, in dry AD, the substrate moves via plug flow inside the reactor. Plug flow conditions within the +reactor offer the advantage of technical simplicity. They leave however the problem of mixing, which +is crucial to guarantee adequate inoculation and reduce acidification problems. +The economical differences between wet and dry systems are small, both in terms of investment and +operational costs. The differences between those systems are more substantial in terms of +environmental issues. For instance, while wet systems typically consume one m3 of fresh water per +ton of treated Organic Fraction of Municipal Solid Waste (OFMSW), the water consumption of their +  dry counterparts is ten-fold less. As a conseque  nce, the volume of wastewater to be discharged8    is         +CHAPTER 1 - INTRODUCTION +several-fold less for dry systems (Vendevivere 1999). +Despite the listed advantages, this high solid contents determine also several technical disadvantages +in terms of transport, handling and mixing compared to wet processes (Lissens et al. 2001; De Baere +et al. 2010; Bollon et al. 2013). Moreover the low amount of water affects the process development. +The water content in fact is a key parameter of dry AD as several studies have demonstrated that +water promotes substrate hydrolysis and enables the transfer of process intermediates and ease the +bacterial community access to nutrients (Lay et al. 1997a, b; Mora-Naranjo et al. 2004; Pommier et al. +2007; Bollon et al. 2013). +The present study is aimed at better understanding the role of water on AD, discussing in detail the +experimental data obtained during dry and semidry digestion tests of selected complex organic +substrates by varying the TS percentages of the treated biomass. Obtained data are used to model the +effect of water content during dry AD. Moreover, considering, as mentioned previously, that AD takes +usually place in Plug Flow reactors, this study analyses also in detail the hydrodynamic conditions of +different bioreactors through an historical and critical literature review of the role of the +hydrodynamic behaviour on biological processes. This review was done to create the premises for the +development of a mathematical model able to simulate the dry AD in real biological reactor. +1.2. Objectives of the Study +The main objective of this research is to investigate the process performances of AD reactors, studying +the effect of moisture content on process development. The research was carried out at lab-scale in +batch reactor on the following substrates: rice straw and food waste. These two substrates were +selected because food waste is representative of readily biodegradable bio-waste, while rice straw is +representative of slowly biodegradable ones. Moreover both of them are produced in large amount and +there is a practical need to define a proper treatment for them. Further investigations are conducted on +carrot waste to study the effect of moisture content also in the case of wet AD and to analyse the effect +of particle size on methane production. This substrate was selected because it presents a shape and a +consistency that can be easily modelled. Mathematical modelling aimed at upgrading the Anaerobic +Digestion Model n. 1 (ADM1) proposed by Batstone et al. 2002 by considering the effect of moisture +on the process performances is also an objective of this thesis. The experimental data obtained during +batch studies were used to calibrate the proposed model. The specific objectives of the research 9ar  e               +CHAPTER 1 - INTRODUCTION +listed below: +• Assess the effect of moisture content on semidry and dry AD of a selected easily biodegradable +substrate (i.e. food waste); +• Model the dry AD of food waste and determine the kinetic parameters of the model by +considering the effect of moisture content; +• Assess the effect of moisture content on semidry and dry AD of slowly biodegradable +substrate, i.e. rice-straw; +• Model the dry AD of rice straw and determine the kinetic parameters of the model by +considering the effect of moisture content; +• Assess the effect of moisture content on wet AD of carrot waste; +• Model the wet AD of carrot waste and determine the kinetic parameters of the model by +considering the effect of moisture content; +• Individuate possible process inhibitions that could occur in dry anaerobic conditions by +studying process intermediates, such as VFAs and model these parameters varying TS content. +• Review the hydrodynamic models described in literature for aerobic and anaerobic treatment of +wastewater to give the premises for the development of a coupled model able to simulate the +dry anaerobic digestion process, considering both the effect of the hydrodynamic conditions. +The specific objectives are addressed in the following chapters of this thesis. In chapter 2 are +described the experimental and modelling results obtained on carrot waste wet AD. The batch tests +results are used to discuss the effect of different particle size and moisture content on methane +production. In chapter 3, the experimental results obtained on wet, semidry and dry AD of food +waste are described. The effect of different moisture contents on methane production, VFA +concentration and anaerobic degradation in terms of VS and COD is discussed. In chapter 4, the +experimental results obtained on wet, semidry and dry AD of rice straw are described and +discussed following the same approach used in chapter 3 for food waste. In chapter 5, an up- +graded version of the ADM1 model for dry and semidry anaerobic digestion is proposed. Mo1d0el                 +CHAPTER 1 - INTRODUCTION +calibration is performed by fitting the experimental data (methane production and VFA +concentrations obtained during the batch tests described in chapter 3 and 4) on food waste and rice +straw in wet, semidry and dry AD conditions. In chapter 6 are reviewed mathematical models of +anaerobic and aerobic non-ideal flow reactor in wastewater treatment are reviewed. Finally, in +chapter 7 an overall discussion and conclusion of the results is reported. + + + + + + + + + + +     1   1           +CHAPTER 2 - EFFECT OF MOISTURE CONTENT ON WET ANAEROBIC DIGESTION OF +COMPLEX ORGANIC SUBSTRATES + + + +CHAPTER 2 +Effect of moisture content on wet anaerobic digestion of complex +organic substrates +   +     +       +This chapter has been published as: + +Liotta, F., d’Antonio, G., Esposito, G., Fabbricino, M., Frunzo, L., van Hullebusch, E. D., Lens, +N.L. and Pirozzi, F. (2014). Effect of moisture on disintegration kinetics during anaerobic +digestion of complex organic substrates. Waste Manage. Res. 32, 40-48. +     1   2           +CHAPTER 3 - EFFECT OF MOISTURE CONTENT ON ANAEROBIC DIGESTION OF FOOD +WASTE +2.1 Introduction +Anaerobic digestion is a multi-step process, that involves several micro-organisms: hydrolytic, +fermentative, acetogenic and methanogenic bacteria. The limiting step of the AD process can not be +unequivocally defined. Acetogenesis (Hills and Robert 1981; Bryers 1985; Costello et al. 1991a, b; +Siegrist et al. 1993) and methanogenesis (Graef and Andrews 1974; Moletta et al. 1986; Smith et al. +1988), as well as hydrolysis (Vavilin et al. 2001) and disintegration (ADM1, Batstone et al. 2002, +Esposito et al. 2008, 2011a,b, 2012a,b), can constitute the rate-determining steps. +When considering complex organic matter, the hydrolysis of complex polymeric + substances becomes the rate-limiting step and modelling of this process has to be improved +(Pavlostathis and Giraldo-Gomez 1991; Vavilin et al. 1996b, 1997, 1999; Batstone et al. 2002). In +particular, several models showed that the presence of OFMSW particles can be better described with +the introduction of a disintegration step. This step individuates the physical break and transformation +of the complex organic matter in soluble particulate organics, and represents the rate-limiting step of +the process (Hills and Nakano 1984; Sharma et al. 1988; Esposito et al. 2008, 2011a, 2012a; Batstone +et al. 2002). +Several authors investigated the rate of hydrolysis and disintegration as a function of different +parameters such as pH, temperature, hydrolytic biomass concentration, type of particulate organic +matter and particle size (Pavlostathis and Giraldo-Gomez, 1991; Veeken et al. 1999; Hill and Nakano +1984; Esposito et al. 2008; Sharma et al. 1988; Sanders et al. 2000). However, it is less understood +how the TS content can affect hydrolysis and in particular the disintegration step of complex organic +substrate. There are several attempts in the literature to model the effect of moisture content on dry +and semi-dry AD process. In particular in their work, Abbassi-Guendouz et al. (2012), by the +application of ADM1 model, found a decreasing first-order hydrolysis rate constant for carbohydrates +by increasing TS content. This constant was calibrated using batch experimental data with cardboard +as initial substrate and imposing the TS content in the range of 15-30%. This finding is in agreement +with results presented by Bollon et al. (2011). There are also several attempts in literature to +investigate the effect of TS content on methane production by operating Specific Methanogenic +Activity (SMA) tests and by simulating experimental data by using the Gompertz model (Le Hyaric et +al. 2011; Le Hyaric et al. 2012; Lay et al. 1997a, 1997b, 1998). These authors suggested also that high +TS content could reduce substrate degradation, resulting in a lower methanogenic activity. These +CHAPTER 2 - EFFECT OF MOISTURE CONTENT ON WET ANAEROBIC DIGESTION OF +COMPLEX ORGANIC SUBSTRATES +results are consistent with several studies performed by Qu et al. (2009), Fernández et al. (2010), +Forster-Carneiro et al. (2008), Pommier et al. (2007), who found a reduction of methane production +with higher TS. All these studies showed that the moisture content plays an essential rule in the biogas +formation as the nutrients and substrates for the microorganisms must dissolve in water phase prior +they can be assimilated. Furthermore, the moisture content is an important factor also in the low-solids +(wet) anaerobic digestion because it supports the bacterial movement and helps substrate and product +diffusion through the porous medium (solid waste) to bacterial cell membrane (Lay et al. 1997a; Lay +et al. 1997b; Mora Naranjo et al. 2004; Le Hyaric et al. 2012; Pommier et al. 2007). +The aim of this chapter is, therefore, to assess the impact of the moisture content on wet anaerobic +digestion of a selected complex organic substrate. To better evaluate the impact of the water content +on the AD performances, computer solution using a new version of the ADM1 of complex organic +substrate, proposed by Esposito et al. (2008, 2011a,b) is applied. The model is used to describe the +experimental data and to define the dependence of the disintegration kinetic parameter on the particle +size and moisture content. +More in detail, this chapter includes the following objectives: +• propose an experimental procedure for obtaining an inoculum at different moisture contents; +• investigate the effect of PS effect on the disintegration step of AD process of complex organic +matter, i.e. greengrocery waste (carrot waste); +• investigate the TS effect on methane production; +• propose a new mathematical modelling approach to describe the effect of TS on the +disintegration step of AD by using a new version of ADM1 model proposed by Esposito et al. +(2008, 2011a, b). +• determine the surface based kinetic constant for the cited selected substrate, using the model +proposed by Esposito et al. (2008). + +     1   4           +CHAPTER 2 - EFFECT OF MOISTURE CONTENT ON WET ANAEROBIC DIGESTION OF +COMPLEX ORGANIC SUBSTRATES +2.2. Materials and Methods +2.2.1 Digester set-up and analytical measurements +Biomethanation Tests (BMTs) were performed on a small scale under controlled and reproducible +conditions in a 1000 mL glass bottle GL 45 (Schott Duran, Germany). Small amounts of Na2CO3 +powder were also added to control pH value. Each bottle was sealed with a 5 mm silicone disc that +was held tightly to the bottle head by a plastic screw cap punched in the middle (Schott Duran, +Germany). All digesters were immersed up to half of their height in hot water kept at a constant +temperature of 308.15 K by 200 W A-763 submersible heaters (Hagen, Germany). Once a day, each +digester was connected by a capillary tube to an inverted 1000 mL glass bottle containing an alkaline +solution (2% NaOH). The inverted 1000 mL glass bottle was sealed in the same way as the digesters. +To enable gas transfer through the two connected bottles, the capillary tube was equipped on both +ends with a needle sharp enough to pierce the silicone disc. The weight, TS and VS concentration of +the anaerobic sludge as well as the dry matter, moisture organic matter and ash content of substrate +were determined according to Standard Methods (APHA/AWWA/WEF, 1998). Temperature and pH +of all mixtures investigated were monitored for at least once a day with a TFK 325 thermometer +(WTW, Germany) and a pH meter (Carlo Erba, Italy), respectively (Esposito et al. 2012a). + +2.2.2 Preliminary tests: Drying procedure +In order to evaluate the effect of different moisture contents during AD, experiments at different TS +contents are necessary. With the objective to evaluate only the effect of moisture content, these +experiments must be conducted using the same inoculum, at the same operational conditions, varying +only the TS content. Therefore fresh digestate was collected from a mesophilic AD of a buffalo farm +and stored in 10 L buckets at 4°C and used as inoculum source. The initial inoculum characteristics in +terms of TS, VS, carbohydrates fraction (Ch), proteins fraction (Pr) and lipids fraction (Li) are shown +in Table 1. + +     1   5           +CHAPTER 2 - EFFECT OF MOISTURE CONTENT ON WET ANAEROBIC DIGESTION OF +COMPLEX ORGANIC SUBSTRATES +Table 1. Main characteristics of Anaerobic Sludge +Initial Initial Ch Pr Li + +TS [%] VS [%] [%] [%] [%] +Wet anaerobic sludge 2 1.2 2.1 56 41.9 + +The inoculum was dried by testing three different procedures: overnight drying of fresh digestate at +50°C until constant weight, centrifugation with 6000 rpm, 10 min and membrane filtration with a +Kubota 203 microfiltration module. The selected drying procedures were aimed at removing water +from inoculum, obtaining a final value of 4% TS. +In order to evaluate the effects of different drying treatments, the concentrated inoculum was reported +at the initial TS content of 2% adding distilled water and was compared with the untreated inoculum +in terms of biomethane potential. The aim of these tests was to individuate the drying procedure that +does not modify the inoculum characteristics in terms of biomass activity and methane production. +Therefore the inoculum obtained from each adopted drying procedure was used to carry out BMTs. +These experiments were performed using pasta and cheese with known carbohydrate, protein and lipid +concentrations (Table 2). The choice of the substrates was aimed at balancing the quantity of +carbohydrates, proteins and lipids in the digester influent. The selected substrate allows the +development of all microbial species involved in degradation of carbohydrates, proteins and lipids in +order to evaluate the pre-treatment effect on all these species. +Table 2. Mass composition of organic substrate +Pasta [g] Cheese [g] Anaerobic Sludge [g] Na2CO3 [g] +2.63 5.24 500 0.32 + +The methane production is expressed under standard conditions and takes into account the gas content +variation in the headspace of the reactor. The calculated methane production accounts for the global +methane production without the residual endogenous methane production measured with the blank +assay, which represent the reactor filled only with digestate without substrate addition. +     1   6           +CHAPTER 2 - EFFECT OF MOISTURE CONTENT ON WET ANAEROBIC DIGESTION OF +COMPLEX ORGANIC SUBSTRATES +5000 +4000 +3000 +2000 +1000 +0 0 10 20 30 40 50 60 70 +Time [days] +Thermal Filtration Centrifugation Untreated   +Figure 1. Cumulative methane production of different tests. + +Figure 1 shows the cumulative methane production obtained using the different inoculums resulting +from the different drying procedures and the untreated inoculum. The Bio-methanation Potential +(BMP) is the same for all tests, but only adopting the centrifugation it is possible to observe a similar +trend as for the untreated digestate. These results indicate that all the tested methods are suitable +drying procedures that do not change the inoculum characteristics. For the following experiments, +centrifugation was selected as drying procedure because it gives the minimum alteration of the +inoculum and it is the most simple and cheaper method to apply in the laboratory. + +2.2.3 Effect of particle size on AD +Bio-methanation experiments were performed using as initial substrate a selected greengrocery waste, +(i.e. carrot waste) as initial substrate with the chemical composition in terms of TS, VS and +concentrations of carbohydrates, proteins and lipids reported in Table 3. This substrate was selected +for modelling purposes, due to the ease to obtain a cylindrical shape (Fig. 2). That shape was obtained +by using cylindrical steel tube with a selected diameter. For each particle the same diameter and +height was imposed in order to obtain a ratio between area and mass equal to a particle with spherical +  shape. The tests were conducted using four diffe  rent PS: 0.25 mm, 4 mm, 9 mm, 15 mm (Table 1  47).           +CH4 [mL] +CHAPTER 2 - EFFECT OF MOISTURE CONTENT ON WET ANAEROBIC DIGESTION OF +COMPLEX ORGANIC SUBSTRATES +The selected ratio between organic matter and anaerobic sludge was 0.5 organic matter/anaerobic +sludge (i.e. Food/Mass ratio (F/M)). The selected digestate was collected from a mesophilic AD of a +farm treating buffalo manure. The mass composition adopted for all tests is described in Table 4. +BMTs were operated in triplicate and a blank assay was also carried out. In total 15 BMTs were +performed. +Table 3. Substrate characteristics. +Initial TS Initial Ch Pr Li + +[%] VS [%] [%] [%] [%] +Carrot 12.7 11.4 0.121* 0.025* 0.006* +*Buffière et al. (2006). +Table 4. Composition of the organic mixture in terms of F/M ratio, PS, input substrate and inoculum +for the experiments T1-T4 +Initial radius Carrots Anaerobic Tests F/M sludge Na2CO3 [mm] [g] [g] [g] +T1 0.5 15 48.2 (±0.5) 500 (±1) 0.30-0.40 (±0.001) +T2 0.5 9 48.2 (±0.5) 500 (±1) 0.30-0.40 (±0.001) +T3 0.5 4 48.2 (±0.5) 500 (±1) 0.30-0.40 (±0.001) +T4 0.5 0.25 48.2 (±0.5) 500 (±1) 0.30-0.40 (±0.001) + +   +Figure 2. Different PS of Carrots with cylindrical shape. +     1   8           +CHAPTER 2 - EFFECT OF MOISTURE CONTENT ON WET ANAEROBIC DIGESTION OF +COMPLEX ORGANIC SUBSTRATES +2.2.4 Effect of moisture content on AD +BMTs were performed using carrot with a cylindrical shape and buffalo manure anaerobic digestate. +A specific value of PS = 15 mm was selected in order to get the disintegration step as rate limiting +step. +The initial TS content of the fresh digestate was 2%, that was dried by operating centrifugation in +order to obtain the desired moisture contents. A fixed substrate amount of substrate was defined and +only the digestate volume was changed to obtain different moisture contents. All the tests were +performed imposing a selected ratio between organic matter and anaerobic sludge of 0.5 organic +matter/inoculum. All the tests were conducted in triplicate. A total of nine bottles were operated with +three TS contents: 4.98%, 7.5%, 11.3%. The mixture composition of each BMT test is reported in +Table 5. +Nine further tests were conducted using only anaerobic sludge as substrate to estimate the volume of +methane resulting from the fermentation of the organics contained in the anaerobic sludge. Totally 18 +tests were performed. +Table 5. Mixture composition +TS mixture VS mixture Carrot Dried +Test +[%] [%] amount [g] Anaerobic sludge [g] +T5 11.3 8.57 40 120 +T6 7.5 4.6 40 245 +T7 4.98 3.7 40 320 + +2.2.5 Mathematical model +For better understanding the effect of TS and PS on the anaerobic degradation of complex organic +substrates, the anaerobic co-digestion model for complex organic substrates proposed by Esposito et +al. (2011a,b) was used. The model was calibrated with the experimental data of the batch experiments +to estimate the kinetic constant of the surface based disintegration process, K -2 -1sbk (ML T ). The +differential mass balance equations and the process kinetics and stoichiometry, described in detail in +Esposito et al. (2011a,b), are based on the ADM1 approach. +  The disintegration kinetic is based on the surface  -based kinetic expression proposed by Sanders et1  a9l.           +CHAPTER 2 - EFFECT OF MOISTURE CONTENT ON WET ANAEROBIC DIGESTION OF +COMPLEX ORGANIC SUBSTRATES +(2000) and reformulated by Esposito et al. (2008, 2011a,b) by including a*, which characterize the +disintegration process: +a* A= (1) +M +dC += −Ksbk ⋅a* ⋅C (2) dt +where: +C = concentration of the complex organic substrate in the digester [ML-3]; +A = disintegration surface area [L2]; +M = complex organic substrate mass [M]. +Assuming that all the organic solid particles have the same initial size and cylindrical shape with h = +2R, that they are progressively and uniformly degraded, a* equation is given by the following +equation: +n +∑Ai +a*= i=1 nA 3= i = (3) n +∑M nMi δRi +i=1 +where: +A = disintegration surface area of the organic solid particle i [L2i ]; +Mi = mass of the organic solid particle i [M]; +n = total number of organic solid particles [ad.]; +δ = complex organic substrate density [ML-3]; +R = organic solid particles radius [L], assumed to be time dependent according to the following +expression proposed by Sanders et al. (2000): +R R K t= 0 − sbk (4) δ +where: +R0 = initial organic solid particle radius [L], specified as the initial condition for model +application. +     2   0           +CHAPTER 2 - EFFECT OF MOISTURE CONTENT ON WET ANAEROBIC DIGESTION OF +COMPLEX ORGANIC SUBSTRATES +The a* coefficient is different than the one proposed by Esposito et al. (2011a,b) as the solid particle +present cylindrical instead of spherical shape. +Integration of the differential algebraic equations is performed using a multi-step solution algorithm +based on the numerical differentiation formulas in the software tool MATLAB®. +Model calibration and validation was also performed to estimate K (ML-2T-1sbk ) constant, the surface +constant of the surface-based disintegration process. +Calibration was performed by comparing model results with experimental data of cumulative methane +production for a selected particle size and define the unknown parameter by fitting experimental data +with model results. +The calibration and validation procedure proposed by Esposito et al. (2011a,b) was performed. A +comparison between experimental data and model results was performed by applying the Root Mean +Square Error (RMSE) (Esposito et al. 2012a,b; Janssen and Heuberger 1995). +2.3. Results and discussions +2.3.1 Effect of particle size on AD performance +Figure 3 shows the cumulated methane production for the reactors operated at four different PS during +the whole experiments. Each curve represents the average of three replicates. The results clearly show +a different initial trend for the four curves indicating a cumulative methane production rate inversely +proportional to the PS. The cumulative methane production rate was inversely proportional to the PS. +The methane yield of all curves is in the range of 460(±30) mL/gVS. There are no large differences as +all reactors were filled with the same substrate amount (Fig. 3). +     2   1           +CHAPTER 2 - EFFECT OF MOISTURE CONTENT ON WET ANAEROBIC DIGESTION OF +COMPLEX ORGANIC SUBSTRATES +4000 +3000 +2000 +1000 +0 0 10 20 30 40 50 60 70 +Time [days] +2.5 mm 4 mm 9 mm 15 mm   +Figure 3. Effect of PS on the cumulative methane production + +Figure 4 shows a logarithm relationship between PS and initial methane production rate for the +substrate added, evaluated by dividing the specific net methane production by the number of days (3 +days) from the start of the experiment. The Figure 4 indicates a strong impact of the PS on the kinetic +rates and individuates the disintegration process as the rate-limiting step for methane production. +These results are consistent with the findings of previous studies (Hills and Nakano 1984; Sharma et +al. 1988; Esposito et al. 2008, 2011a,b). Hills and Nakano, (1984) plotting the methane gas production +relative to the parameter 1/ΦsDm (where Φs represent the sphericity of the particles and Dm the average +particle diameter) found a linear correlation between these parameters. The similar correlation was +implicitly considered in the model proposed by Esposito et al. (2008, 2011a).   +70 +60 +50 +40 +30 +200.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 +1/D [mm-1]   +Figure 4. Influence of particle size on initial methane production rate. + +     2   2           +Initial methane pro +[mLCH grVS-1 +duction rate +4 in d +-1] CH4 [mL] +CHAPTER 2 - EFFECT OF MOISTURE CONTENT ON WET ANAEROBIC DIGESTION OF +COMPLEX ORGANIC SUBSTRATES +2.3.2. Effect of TS content on AD performances +Figure 5 shows the cumulated methane production for the reactors operated at 3 different TS contents +during the whole experiments. Each curve represents the average of 3 replicates. Lag-phase and the +initial methane production rate, resulted inversely proportional to the TS content. These results are +consistent with previous studies performed by Lay et al. (1997a,b), who made batch tests in +mesophilic digesters at different pH values by testing the effect of moisture content in the range of wet +digestion. The final methane yield, measured at the end of each experiment can be assumed for all +tests coincident and equal to the mean value of 450 mL/gVS with a standard deviation of 14.23 (Table +6). This is apparently not in agreement with the findings of Abbassi-Guendouz et al. (2012), +Fernández et al. (2008) and Dong et al. (2010), who found higher methane yields with lower TS in the +range of dry and semidry AD. The difference is due to the different moisture content range +investigated, as the present experiments were carried out in wet conditions. The conversion of acids to +methane by methanogenic bacteria can thus be influenced by the lack of water (Lay et al. 1997b; +Ghosh 1985) that can occur with higher TS content in the range of dry and semidry digestion +(Abbassi-Guendouz et al. 2012; Fernández et al. 2008; Dong et al. 2010). +3500 +3000 +2500 +2000 +1500 +1000 +500 +0 0 5 10 15 20 25 30 35 40 45 50 55 +Time [days] +4.95% 7.50% 11.50%   +Figure 5. Effect of TS on the cumulated methane production from anaerobic digestion of carrots +waste. + +Figure 6 indicates a linear relationship between TS content and initial methane production rate. Such +linear relationship was observed also by Lay et al. (1997b) on AD of selected dry organic waste (e.g. +  sludge cake, meat, carrot, rice, potato and cabb  age), Le Hyaric et al. (2012) on AD of cellulo2  s3e,           +CH4 [mL] +CHAPTER 2 - EFFECT OF MOISTURE CONTENT ON WET ANAEROBIC DIGESTION OF +COMPLEX ORGANIC SUBSTRATES +Abbassi-Guendouz et al. (2012) on AD of cardboard, Mora-Naranjo et al. (2004) for waste samples +excavated from landfill and Pommier et al. (2007) for paper waste. The presented results confirm that +the TS content, also in wet AD, has a strong effect on the kinetic rates. In particular, at lower TS, due +to the increasing water content and better transport and mass transfer conditions, it seems to be +plausible that the microorganisms are better sustained with soluble substrates (Mora-Naranjo et al. +2004). +50 +40 +IMPR=-740.3TS+84.34 +30 R2=0.9987 +20 +10 +0 4 5 6 7 8 9 10 11 12 +TS [%] +Experimental data Regression line +Figure 6. Influence of the TS on initial methane production rate. + +Table 6. Cumulative methane production. +TS mixture [%] 4.98 7.5 11.3 +Cumulative methane production [mL] 3410 3210 2830 +Cumulative methane production of blank [mL] 1340 1230 725 +Net cumulative methane production [mL] 2070 1980 2105 +Specific Final Methane Yield [mL/gVSfeed] 455 430 460 + +2.4. Modelling results +2.4.1. Modelling the effect of particle size on AD +Model calibration was used to estimate the kinetic constant of the surface based disintegration +process, K -2 -1sbk (M L T ). Calibration was performed by comparing model results with experimental +measurements of methane production and adjusting the unknown parameters until the model results +  adequately fit the experimental observations. Th  e measured data of experiment T1 (Table 7) w2e   r4e           +Initial methane producti +[mLCH grVS-1 d-1 +on rate +4 in ] +CHAPTER 2 - EFFECT OF MOISTURE CONTENT ON WET ANAEROBIC DIGESTION OF +COMPLEX ORGANIC SUBSTRATES +used, and a calibration procedure introduced by Esposito et al. (2011a,b) was applied. Using the +previously calibrated Ksbk model, validation was performed by calculating RMSE for T2, T3 and T4 +experiments. +The model calibration performed resulted in setting the kinetic constant Ksbk equal to 0.28 kg m-2s-1. +Ksbk was the value that minimizes RMSE (Fig. 7), that show a single monotone reversal trend that +proves the existence of one and only one solution to the specific optimization problem. +In Figure 8A a good overlap between the simulated and model data is shown. A small shift between +experimental data and model results was observed.   +0.025 +0.02 +0.015 +Ksbk=0.28 +RMSE=0.063 +0.01 +0.005 0.25 0.5 0.75 1 +Ksbk[kgm-2s-1]   +Figure 7. Calibration procedure for PS = 15 mm: dependence of RMSE on Ksbk. + +(A) (B) +0.2 0.16 +0.15 0.12 +0.1 0.08 +0.05 0.04 +0 0 +0 10 20 30 40 50 60 70 0 0.04 0.08 0.12 0.16 +Time [d] Measured CH4 [mol]   +Figure 8. Comparison of measured and simulated cumulative methane production for experiments +with PS = 15 mm: overlapping between measured and simulated data (a); comparison between +s   imulated and experimental data with line of perfect fit (b). +The results of experiments T2, T3 and T4 were used to validate the mathematical model, assessing the +  agreement between simulated and observed dat  a for the cumulative methane production with 2t  h5e           +CH4 [mol] RMSE +Simulated CH4 [mol] +CHAPTER 2 - EFFECT OF MOISTURE CONTENT ON WET ANAEROBIC DIGESTION OF +COMPLEX ORGANIC SUBSTRATES +parameter RMSE. Figures 9, 10 and 11 show a very good agreement between the simulated and +experimental data. This agreement is confirmed in Table 8, where the values of a* constant evaluated +for different PS are also reported. +(A) (B) +0.2 0.16 +0.15 0.12 +0.1 0.08 +0.05 0.04 +0 0 +0 10 20 30 40 50 60 70 0 0.04 0.08 0.12 0.16 +Time [d] Measured CH4 [mol]   +Figure 9. Comparison of measured and simulated by cumulative methane production for experiments +with PS = 9 mm: overlapping between measured and simulated data (a); comparison between +s   imulated and experimental data with line of perfect fit (b). +(A) (B) +0.2 0.16 +0.15 0.12 +0.1 0.08 +0.05 0.04 +0 0 +0 10 20 30 40 50 60 70 0 0.04 0.08 0.12 0.16 +Time [d] Measured CH4 [mol]   +Figure 10. Comparison of measured and simulated cumulative methane production for experiments +with PS = 4 mm: overlapping between measured and simulated data (a); comparison between +  simulated and experimental data with line of perfect fit (b). +     2   6           +CH4 [mol] CH4 [mol] +Simulated CH4 [mol] Simulated CH4 [mol] +CHAPTER 2 - EFFECT OF MOISTURE CONTENT ON WET ANAEROBIC DIGESTION OF +COMPLEX ORGANIC SUBSTRATES +(A) (B) +0.2 0.16 +0.15 0.12 +0.1 0.08 +0.05 0.04 +0 0 +0 10 20 30 40 50 60 70 0 0.04 0.08 0.12 0.16 +Time [d] Measured CH4 [mol]   +Figure 11. Comparison of measured and simulated cumulative methane production for experiments +with PS = 0.25 mm: overlapping between measured and simulated data (a); comparison between +simulated and experimental data with line of perfect fit (b). + +Table 7. Results of the model calibration procedure. +Test PS [mm] a* [m2kg-1] Ksbk [kg m-2s-1] RMSE +T1 15 0.561 0.28 0.083 + +Table 8. Results of the model validation procedure. +Test PS a* Ksbk [mm] [m2kg-1] [kg m-2s-1] RMSE +T2 0.25 12.632 0.28 0.063 +T3 4.0 1.579 0.28 0.0627 +T4 9.0 0.702 0.28 0.067 + + 2.4.2. Modelling the effect of TS on AD +The mathematical model proposed by Esposito et al. (2008, 2011a,b) was calibrated to set different +values of the kinetic disintegration constant K -1dis[T ] = Ksbk a*, for different TS contents. For a selected +PS = 15 mm, the value of a* constant was 0.561 m2kg-1. The measured data of experiment (Table 4) +were used, a calibration procedure introduced by Esposito et al. (2011a,b) was applied and RMSE for +T5, T6 and T7 experiments were evaluated. +The results (Fig. 12-14) show a good agreement between the simulated and experimental data; this +     2   7           +CH4 [mol] +Simulated CH4 [mol] +CHAPTER 2 - EFFECT OF MOISTURE CONTENT ON WET ANAEROBIC DIGESTION OF +COMPLEX ORGANIC SUBSTRATES +agreement is confirmed in Table 9, where the values of the Kdis constant, evaluated for different TS, +are also reported. In particular the good fitting between simulated and experimental concentrations +shows the capability of the model to simulate the AD process of substrates with different initial TS. +(A) (B) +0.2 0.16 +0.15 0.12 +0.1 0.08 +0.05 0.04 +0 0 +0 10 20 30 40 50 0 0.04 0.08 0.12 0.16 +Time [d] Measured CH [mol] +4   +Figure 12. Comparison of measured and simulated by proposed model cumulative methane production +for experiments with PS=15 mm and TS= 4.98%:overlapping between measured and simulated data +(a); comparison between simulated and experimental data with line of perfect fit (b). +(A) (B) +0.2 0.16 +0.15 0.12 +0.1 0.08 +0.05 0.04 +0 0 +0 10 20 30 40 50 0 0.04 0.08 0.12 0.16 +Time [d] Measured CH4 [mol]   +Figure 13. Comparison of measured and simulated by proposed model cumulative methane production +for experiments with PS = 15 mm and TS= 7.48%: overlapping between measured and simulated data +  (a); comparison between simulated and experimental data with line of perfect fit (b). +(A) (B) +0.15 0.16 +0.12 +0.12 +0.08 0.08 +0.04 0.04 +00 10 20 30 40 50 00 0.02 0.04 0.06 0.08 0.1 0.12 0.14 +Time [d] Measured CH4 [mol]   +Figure 14. Comparison of measured and simulated by proposed model cumulative methane production +for experiments with PS= 15 mm and TS= 11.34%:overlapping between measured and simulated data +  (a); comparison between simulated and experimen   tal data with line of perfect fit (b). 2   8           +CH4 [mol] CH4 [mol] CH4 [mol] +Simulated CH4 [mol] +Simulated CH4 [mol] Simulated CH4 [mol] +CHAPTER 2 - EFFECT OF MOISTURE CONTENT ON WET ANAEROBIC DIGESTION OF +C   OMPLEX ORGANIC SUBSTRATES +Table 9. Disintegration constant and RMSE for different TS. + +Test a* [m2kg-1] K -1dis[s ] RMSE + +T5 0.561 0.1 0.0084 +T6 0.561 0.3 0.0088 +T7 0.561 0.55 0.0087 + +Figure 15 indicates a linear relationship between TS and the disintegration kinetic constant obtained +with the model proposed by Esposito et al. (2008, 2011a,b) implementation: +0.6 +0.5 +0.4 IMPR = -740.3 TS+84.34 +R2 = 0.9987 +0.3 +0.2 +0.1 +04 5 6 7 8 9 10 11 12 +TS [%]   +Figure 15. Correlation between TS content and disintegration rate constant. +The linear correlation represented in Figure 15 can be expressed using the following linear equation: +d [CH4 ]0 = −740.3⋅ (TS%)+84.34 (5) dt +By considering the presence of a limiting step (i.e. disintegration process) the rate of the overall AD +process can be modelled by one equation. If first order kinetics is assumed for the disintegration +process, the methane production rate can be expressed by equation (6): +d [CH ]4 = Kdis[C] (6) dt +where: +[C] = substrate concentration [ML-3]. +By including the following two parameters: +     2   9           +Disintegration rate constant +[kg m2 s-1] +CHAPTER 2 - EFFECT OF MOISTURE CONTENT ON WET ANAEROBIC DIGESTION OF +COMPLEX ORGANIC SUBSTRATES +l = angular coefficient of the interpolation line (-2961.2) +f = intercept value of the interpolation line on the axis of the initial methane production rate +(337.36) +and integrating and making simplifications it is possible to obtain the following equation: +K ln(l ⋅(TS%)+ f ) ⋅tdis = C (7) 0 +where: +t = integration time for the initial bio-methane production rate evaluation [T]; +Co = initial substrate concentration [ML-3]. +Table 10. Disintegration kinetic constants obtained with equation (7) and with the mathematical +model. +K [s-1] K [s-1Test dis dis ] +[with Esposito et al., 2011a,b)] [with eq. (7)] +T5 0.1 0.19 +T6 0.3 0.22 +T7 0.55 0.55 + +In Table 10 the values of the disintegration constant, obtained with equation (7) and with the +mathematical model proposed by Esposito et al. (2008, 2011a,b) are reported, showing a good +agreement of the results of the two methods. This confirms that a simplified model (i.e. a one equation +model) can approximate the results of a full model when a rate-limiting step of the biological process +is clearly present. +2.5 Conclusion +This chapter focused on the effect of TS content and PS on anaerobic digestion of complex organic +substrates. A linear correlation between initial methane production rate and TS content was +individuated. An inverse correlation between the Particle Size and the specific methane production +was found and also a linear relationship between 1/PS and initial methane production rate for the +substrate added were found. These results underline a strong impact of the PS on the kinetic rates and +  individuating the disintegration process as the rat  e-limiting step for methane production. The surfa3c   e0-           +CHAPTER 2 - EFFECT OF MOISTURE CONTENT ON WET ANAEROBIC DIGESTION OF +COMPLEX ORGANIC SUBSTRATES +based kinetic constant Ksbk for the disintegration equation of carrot waste was determined. Also the +values of the disintegration constant for different TS content were assessed. Finally a simple equation +correlating TS and the disintegration constant was proposed, that showed a good agreement with the +results of new version of ADM1 of complex organic substrate proposed by Esposito et al. (2008, +2011a,b). +     3   1           +CHAPTER 3 - EFFECT OF MOISTURE CONTENT ON ANAEROBIC DIGESTION OF FOOD +WASTE + + + + + + + + + + +CHAPTER 3 +Effect of moisture content on anaerobic digestion of food waste + + + + + + + + + +This chapter is the modified version of the article “Effect of total solids content on methane and +VFA production in anaerobic digestion of food waste ” submitted to the Journal Waste +Management and Research (under revision). +CHAPTER 3 - EFFECT OF MOISTURE CONTENT ON ANAEROBIC DIGESTION OF FOOD +WASTE +   +3.1. Introduction +The environmental challenges related to the global population growth and the global energy demand +are continuously promoting research efforts to develop innovative technologies aimed at producing +energy from non-conventional sources (Lay et al. 1997a, b; Mora-Naranjo et al. 2004; Pommier et al. +2007; Bollon et al. 2013). The Kyoto Protocol imposed to the major EU industrial countries to reduce +their total Greenhouse Gas (GHG) emissions by 8% from the 1990 level by the end of 2012 (Kyoto, +1997). To achieve this, the EU policies have set forward the task of supplying 5% of the European +energy demands from Anaerobic Digestion (AD) biogas by the year 2020 (Kim and Oh 2011). +AD is a biological process for degradation of organic substrates under anaerobic conditions (Esposito et +al., 2012a; Esposito et al., 2008) Based on the TS of waste used in the process, three types of AD can +be distinguished: dry AD, characterized by a TS above 15%, semi-dry AD with a TS ranging between +15% and 10%, and wet digestion with a TS lower than 10% (Li et al., 2011; Liotta, 2014; Zeshan and +Annachhatre, 2012). The dry and semi-dry systems most widely applied at industrial scale are Valorga, +Dranco, Kompogas and Bekon (Reith et al., 2003), but further applications have also been tested at +pilot and farm-scale (Lianhua et al. 2010; Mussoline 2012; Mussoline et al. 2013; Zhang and Zhang +1999). +The key parameter of the dry AD process is the water content, that is essential for the biological +process as water promotes substrate hydrolysis and enables the transfer of process intermediates and +nutrients to the bacteria (Bollon et al., 2013; De Baere et al., 2010; Lissens et al., 2001). Hence, the +first aim of this paper is to investigate the effect of TS on the AD of Food Waste (FW) under +mesophilic conditions in batch reactors. BMTs were performed to compare methane yield, methane +production rate, COD, VS and TS degradation in wet, semi-dry and dry conditions. In particular, +VFAs composition and concentrations were also investigated as a useful indicator of process stress +and instability (Ahring et al. 1995). VFAs are also valuable products that can be used as carbon source +in biological processes (Elefsiniotis et al. 2004). However, the role of these parameters on the process +development remains still little studied. Therefore, the second aim and main novelty of this chapter is +to assess the TS effect on VFAs production from FW, and the VFAs effect on the process evolution. + +     3   3           +CHAPTER 3 - EFFECT OF MOISTURE CONTENT ON ANAEROBIC DIGESTION OF FOOD +WASTE + 3.2. Materials and Methods +3.2.1 Experimental set-up +BMTs were performed at laboratory scale under controlled and reproducible conditions (Esposito et +al. 2012b; Esposito et al. 2011a, b; Esposito et al. 2012c) using 2000 mL glass bottles GL 45 (Schott +Duran, Germany). Each bottle was sealed with a 5 mm silicone disc, held tightly to the bottle head by +a plastic screw cap punched in the middle (Schott Duran, Germany). A plastic tube hermetically +closed to the top was inserted in the plastic screw cap to permit sample withdrawing. All digesters +were immersed up to half of their height in hot water kept at a constant temperature of 308.15 K by +200 WA-763 submersible heaters (Hagen, Germany). Small amounts of Na2CO3 powder were also +added to control the pH and alkalinity values (Esposito et al. 2012b,c) . +     3   4           +CHAPTER 3 - EFFECT OF MOISTURE CONTENT ON ANAEROBIC DIGESTION OF FOOD +WASTE +3.2.2. Substrate and inoculum preparation +BMTs were conducted in triplicate using FW and Buffalo Manure (BM) anaerobic digestate as +inoculum. The FW was prepared according to Valorgas report (Valorgas, 2012) as indicated in Table +11. +Table 11. Food waste composition of the synthetic substrate used. +Amount + Food type (gr wet) +Potatoes 200 +Tomatoes 170 +Eggplants 170 +Salad leaves 180 +Broccoli 180 +Carrots 140 +Apples 150 +Tangerines 170 +Banana 150 +Chicken 70 +Pork 70 +Fish 70 +Cheese 20 +Milk 20 +Bread 70 +Biscuits 70 +Rice 50 +Pasta 50 + +Particles size smaller than 0.5 mm were obtained by grinding the FW substrate before starting the +experimental tests. The BM digestate, sampled from a mesophilic anaerobic digester, was dehydrated +by filtration to obtain a final TS content of 17.82%. BMTs were carried out in wet (TS = 4.52%), semi- +dry (TS= 12.87%) and dry (TS = 19.02%) conditions as indicted in Table 12. The different TS +contents of the mixture were obtained by adding 500 g of inoculum, differently diluted with distilled +water and varying the amount of the substrate calculated in order to keep the ratio between organic +matter and anaerobic sludge equal to 1:2. Blank BMTs were also conducted on BM without addition of +substrate to estimate, as a control, the volume of methane resulting from the fermentation of the +inoculum. Table 12 gives the mixture composition of each BMTs and reports the BM and substrate +     3   5           +CHAPTER 3 - EFFECT OF MOISTURE CONTENT ON ANAEROBIC DIGESTION OF FOOD +WASTE +amount as well as the TS and VS concentration of the substrate mixture. + +Table 12. Composition of inoculum and FW substrate in BMT. +Inoculum TS Substrate TS TS VS Tests [g] inoculum amount substrate mixture Mixture [%] [g] [%] [%] [%] +T1 500 (±1) 3.45 27.26 24.21 4.52 3.61 +T2 500 (±1) 10.88 87.80 24.21 12.87 10.45 +T3 500 (±1) 17.82 139.10 24.21 19.02 15.25 + +3.2.3. Analytical methods +3.2.3.1 Methane production +Volumetric methane production was measured once a day, by connecting each digester by a small +pipe to an inverted 1000 mL glass bottle containing a strong alkaline solution (12% NaOH). The +inverted 1000 mL glass bottle was sealed in the same way as the digesters. The adopted procedure is +described in detail in the Chapter 2. + + 3.2.3.2 VFAs analysis +VFAs concentration and speciation were monitored throughout the process. VFAs were analysed +collecting 100 mg of digestate sampled from each reactor and diluted with ultrapure water. The +samples were vigorously stirred for three minutes and centrifuged at 8000 rpm for 5 min. VFAs were +extracted from the supernatant by SPME prior to GC-MS injection following the procedure proposed +by Ábalos et al. (2000). 50 µL of a 2,2 dimethyl butanoic acid solution was added as internal standard. +85 µm polyacrilate coated fibers from SUPELCO were used for the extraction and analysed after +thermal desorption by an Agilent 6850 GC coupled with a 5973 Network MSD detector. + +     3   6           +CHAPTER 3 - EFFECT OF MOISTURE CONTENT ON ANAEROBIC DIGESTION OF FOOD +WASTE +3.2.3.3 Other parameters +The weight, TS and VS concentration of the anaerobic sludge were determined by gravimetry +according to EPA Standard Method 1684 (U.S.E.P.A, 2001). Temperature of all mixtures investigated +was monitored for at least once a day with a TFK 325 thermometer (WTW, Germany). COD was +determined by the closed reflux method, followed by photometric determination according to APHA +standard method 5220D (APHA, 1998) and by applying the method proposed Zu +The photometer used was a WTW Photolab Spektral visible spectrophotometer.    pančič & Roš (2012). + + 3.3. Results and Discussion +3.3.1 Bio-methane production +Results of BMTs are summarized in Figures 16-18. Figure 16 reports the specific cumulative methane +production versus time in reactors operated with different TS content. Each curve represents the +average of 3 replicates (max standard deviation = 4%). The specific cumulative methane production +was obtained dividing the cumulative methane production of each test by the initial substrate-inoculum +VS mixture. Figure 17 reports the final specific methane yield, measured at the end of each +experiment, as a function of the TS content and subtracted of the respective blank production. Finally +Figure 18 illustrates the initial methane production rate versus the TS content, evaluated by dividing +the specific net methane production by the number of days (3 days) from the start of the experiment. +A lower TS content favours both the cumulative methane production and the final methane yield. +Such a result is consistent with previous findings (Abbassi-Guendouz et al. 2012; Fernández et al. +2008; Le Hyaric et al. 2012; Li et al. 2011; Liotta et al. 2014) obtained using different biodegradable +substrates (Table 13), and confirms that the conversion of acids to methane by methanogenic bacteria +can be negatively influenced by the lack of water (Lay et al. 1997a; Lay et al. 1997b). It is worth +noting that the initial methane production rate is linearly and negatively correlated with the TS +percentage (Fig. 18), as already observed during the AD of other organic wastes more or less rapidly +biodegradable: dehydrated sludge mixed with dry kitchen waste (Lay et al. 1997a), waste excavated +from a sanitary landfill (Mora-Naranjo et al. 2004), paper waste (Pommier et al. 2007), cellulose (Le +Hyaric et al. 2012) and cardboard (Abbassi-Guendouz et al. 2012). At lower TS concentration, due to +  the increasing water content and to the more fa  vourable transport and mass transfer conditions3,   7it           +CHAPTER 3 - EFFECT OF MOISTURE CONTENT ON ANAEROBIC DIGESTION OF FOOD +WASTE +seems plausible that the microorganisms are better sustained with soluble substrates (Mora-Naranjo et +al. 2004), so that the process takes place more rapidly. + +Figure 16. Specific cumulative methane production of FW at different TS content (Tests T1-T3). +   +Figure 17. Final methane yield of FW with different TS content +   +Figure 18. Linear correlation between the specific initial methane production rate and the TS content of +F   W.   3   8           +CHAPTER 3 - EFFECT OF MOISTURE CONTENT ON ANAEROBIC DIGESTION OF FOOD +WASTE + +Table 13. Final methane yields improvement in wet conditions compared with semi-dry and dry +conditions. + +Substrates used Final methane yield TS and References +in BMTs improvement with Temperature +lower TS content [%] +FW 57 TS = 30%, Fernández et al. +20%; (2008) +T=35°C +Water sorted +organic fraction of 15 TS = 16%, Dong. et al. (2010) +municipal solid 11%; +waste T=30 °C + +Cellulose 11.6 TS = 25%, Abbassi-Guendouz +18%; et al. (2012) +T=35°C +Cardboard 24 TS = 30%, Le Hyaric et al. +10% (2012) +T = 35 °C +Carrot Waste 1 TS =11.3%, Liotta et al.2014 +TS = 5% +T =35°C +FW 69 TS=19.2 %, This study +4.5%;T= 35°C + +3.3.2 VFAs production +A deeper understanding of the TS effect on process development can be obtained by comparing the +trend of daily methane production (Fig. 19) and the corresponding concentration and speciation of +VFAs (Fig. 20). A first peak of methane production can be detected in all reactors on the second day +(Fig. 19). This peak, most likely due to the degradation of fast biodegradable compounds, corresponds +to the peak of Total Volatile Fatty Acids (TVFAs) related to acid accumulation at the start-up of the +process (Fig. 20). This means that the methanization is the rate-limiting step at the beginning of the +process. +Once the methanization has begun, the rate-limiting step becomes the hydrolysis process, and the +TVFAs concentration slowly decreases. Two more peaks of methane production can be observed on +  day 15 and day 36. This finding is in agreement  with Charles et al. 2009 and Dong et al. 2010 w3  h9o           +CHAPTER 3 - EFFECT OF MOISTURE CONTENT ON ANAEROBIC DIGESTION OF FOOD +WASTE +found two peaks of methane production during anaerobic digestion of organic fraction of municipal +solid waste. Dong et al. 2010 correlated this finding to the inhibitory effect of an elevated H2 partial +pressure on the acetoclastic methanogenesis. It is likely that the two peaks correspond to the +degradation of easily and slowly biodegradable compounds contained in the FW. +The maximum TVFAs concentration found in the case of 12.9% and 19.2% were respectively 127 +mmol/kg and 135 mmol/kg (Fig. 20): in these cases TVFAs concentrations exceed the threshold +values reported by Karthikeyan and Visvanathan, 2012 over that a sensible reduction of process +kinetics occurs. The same occurs for the concentration of acetic acid, which reaches values higher +than 33 mmol/L. The lower specific methane yield detected at the higher TS content can be correlated +to acid inhibition during the process, which is more important for TS 12.9% and 19.2%. Indeed, high +TVFAs concentrations induce acidification of the medium, leading to the presence of TVFAs in their +un-dissociated forms, which are more toxic for microorganisms (Amani et al. 2010). A lower water +content in the fermenting mixture makes the TVFAs concentration higher due to a lack of solvent. +Therefore, even if the amount of produced TVFAs is the same, their concentration in the reactor will +be much higher in dry AD. +It has to be stressed that because of the lack of the mixing device inside the reactor higher TS +concentrations imply higher heterogeneities and possible accumulation of inhibitory compounds +inside specific reactor zones is likely to occur. Furthermore, at the highest TS concentrations +investigated, environmental conditions do not allow the growth of acetoclastic, methanogens or +acetate-oxidizing bacteria because of too high VFA concentrations and too low pH values (Abbassi- +Guendouz et al. 2012). During the first stage (0-4 days), acetic acid accumulation occurs (Fig. 21a) +because hydrolysis and acidogenesis take place and the easy biodegradable fraction of FW is +converted to TVFAs. During the second stage (5-35 days), acetoclastic methanogens are in the +exponential growth phase and the acetic acid consumption rate is higher than its generation rate (Dong +et al. 2010). Therefore, hydrolysis and acidogenesis become the rate-limiting steps and the produced +acids are consumed to produce methane (Dong et al. 2010). +     4   0           +CHAPTER 3 - EFFECT OF MOISTURE CONTENT ON ANAEROBIC DIGESTION OF FOOD +WASTE + +Figure 19. Daily methane production of FW at different TS content +   +Figure 20. Evolution of TVFAs concentration in AD of FW at different TS contents + +The maximum concentration of propionic acid (Fig. 21b) occurs sooner for lower TS concentrations +(day 13) and later for higher TS concentrations (day 17). This accumulation, common also to formic +acid (Fig. 21e), can be correlated to the limited transformation of propionate to other VFAs as pointed +out also by Hanaki et al. 1994. Also butyrate and valeric acid isomers present higher values with +higher TS (Fig. 21c and 21d), probably a consequence of the process instability occurring during the +acid production, which determines the formation of isomeric compounds. About the propionic acid, +although an accumulation (8-12 days) can also be seen for TS = 4.5% during days 7-12, in this case the +concentration starts immediately to decrease and drops regularly to zero (Fig. 21b). Such behavior can +be attributed to the fact that the concentration of propionate is directly related to that of acetate in the +reactor and the lowest acetate accumulation occurs during test T1 (TS = 4.5%) (Fig. 21a). During tests +T2 and T3 the concentration of acetate is twice higher and lasts for about 5 days longer. This leads to +an accumulation of propionate that is contemporary to the accumulation of acetate. A long acetate and +propionate accumulation is instead not present in the reactor with TS content of 4.5%. The +a   ccumulation of butyric and propionic acid that ta  kes place only in the dry and semidry reactors mi4g   h1t           +CHAPTER 3 - EFFECT OF MOISTURE CONTENT ON ANAEROBIC DIGESTION OF FOOD +WASTE +be attributed to the co-presence of alternative fermentation pathways, that yield to butyric acid +accumulation. This pathway is alternative to the acetic fermentation and can have different process +kinetics. +   +a) Acetic acid + +b) Propionic acid + +c) Butyric acid +     4   2           +CHAPTER 3 - EFFECT OF MOISTURE CONTENT ON ANAEROBIC DIGESTION OF FOOD +WASTE + +d) Valeric acid + +e) Formic acid +Figure 21. Evolution of the VFAs concentration of FW AD: a) acetic acid; b) propionic acid; c) butyric +acid; d) valeric acid; e) formic acid. + +The Total COD concentration in the reactor at different initial TS concentrations was also investigated. +As expected, the COD degradation decreased under all TS conditions. The COD values at the end of +the experiment were higher for higher TS content as COD removal decreased from 74 ± 6% (TS = +4.5%) to 62 ± 8% (TS = 12.9%), down to 56±7% (TS = 19.2%), confirming the slowdown of process +kinetics taking place at higher TS content due to high VFA concentration (Figs. 20 and 21). + + + +   +     4   3           +CHAPTER 3 - EFFECT OF MOISTURE CONTENT ON ANAEROBIC DIGESTION OF FOOD +WASTE + 3.4 Conclusions +This chapter focused on the effect of the TS content on the anaerobic digestion of FW. The +experimental results show a decrease of the specific final methane yield of 4.3% and 40.8% in semi- +dry and dry conditions, respectively, compared to wet conditions. A higher specific cumulative +methane production rate and better process performance in terms of COD reduction were also +achieved at lower TS content. A linear correlation between the initial methane production rate and the +TS content was observed. High TVFA concentrations of 135 mmol/kg and 127 mmol/kg were found +in dry and semidry conditions, respectively, resulting in a slowdown of process kinetics +     4   4           +CHAPTER 4 - EFFECT OF MOISTURE CONTENT ON ANAEROBIC DIGESTION OF RICE +STRAW + + +CHAPTER 4 +Effect of moisture content on anaerobic digestion of rice straw. +CHAPTER 4- EFFECT OF MOISTURE CONTENT ON ANAEROBIC DIGESTION OF RICE +STRAW + + 4.1 Introduction +Rice straw is one of the most abundant residues and is a potential renewable source for energy +generation. AD may offer a promising alternative to solve imminent rice straw disposal problems in +rice production regions (Zhang and Zhang 1999). Different advantages are connected to the AD of +rice straw. This substrate is a very common agricultural waste and the biogas production potential is +appealing to both developed and developing countries (Mussoline et al. 2013). However, one of the +main disadvantages is related to the ligno-cellulosic structure of rice straw that is well attested to be +difficult to biologically degrade (Sambusiti, 2013). Rice straw as lignocellulosic material is thus +mainly composed as follow: cellulose (37.4%), hemi-cellulose (44.9%), lignin (4.9%) and silicon ash +(13%) (Hills and Robert 1981). +Dry AD is well suited to handle lingo-cellulosic biomass and provides a reduction of problems +encountered in liquid, such as floating and stratification of solids. Dry AD of rice straw received much +attention due to the high TS content of rice straw, that requires less sludge addition and smaller +reactor volumes and pre-treatment. However, such high solid contents involve several technical +disadvantages in terms of transport, handling and mixing to those encountered in wet processes (De +Baere et al. 2010). The key parameter of dry AD processes is the water content, that is essential for +the biological organic waste conversion. Water promotes substrate hydrolysis and enables the transfer +of process intermediates and nutrients to bacterial sites (Lay et al. 1997a,b; Mora-Naranjo et al. 2004; +Pommier et al. 2007). +The aim of this chapter is to investigate the effect of the moisture content relating the AD performance +to the process parameters monitored during the rice straw degradation. More in detail, by varying the +TS in the range of 4.85-23.41% TS, the final specific methane production yield, VS, COD, VFA and +total and soluble phenols concentration were analysed. In particular, this chapter focuses on inhibition +problems and final methane yield reduction that occurs at elevated TS concentrations caused by VFAs +and high concentration of soluble phenolic compounds. +     4   6           +CHAPTER 4- EFFECT OF MOISTURE CONTENT ON ANAEROBIC DIGESTION OF RICE +STRAW + + 4.2. Material Methods +4.2.1 Experimental set-up +During the biogas production, samples were taken from the reactor, where pH, COD, VFAs and +phenols concentrations were monitored. BMT were performed on a small scale under controlled and +reproducible conditions in a 2000 mL glass bottle GL 45 (Schott Duran, Germany). Each bottle was +sealed with a 5 mm silicone disc that was held tightly to the bottle head by a plastic screw cap +punched in the middle (Schott Duran, Germany). A plastic tube hermetically closed at the top was +inserted in the plastic screw cap to permit sampling. All digesters were immersed up to half of their +height in hot water kept at a constant temperature of 308 +/- 1 K by 200 WA-763 submersible heaters +(Hagen, Germany). Small amounts of Na2CO3 powder were also added to the medium to control pH +values (Esposito et al., 2012a,b). + +4.2.2. Substrate and inoculum preparation +BMTs were performed using rice straw and the anaerobic digestate of BM. The value of particle size +smaller than 0.5 mm was obtained by grinding the rice straw prior to starting experimental tests. +The initial TS content of the fresh digestate was 10.88%, this high value is related to the nature of the +digestate, that is an effluent of the dewatering system of a mesophilic Anaerobic Reactor. To increase +the TS content, the digestate was dewatered by filtration to obtain a final TS content of 17.20%. Then, +the sample was diluted with water to obtain the designed moisture content for batch tests with lower +TS content (Table 14). A fixed amount of BM digestate equal to 500 g was defined for each batch test +and only the amount of substrate was changed to obtain different moisture contents. All the tests were +performed imposing a selected organic matter/inoculum ratio of 0.5 and conducted in triplicate. A +total of nine bottles were operated with a final TS content of the mixture: 4.84%, 14.86%, 23.40%, +which represents, respectively, wet, semi-dry and dry conditions. Table 14 gives the mixture +composition of each BMT test. +Nine further tests were conducted using only BM as the substrate to estimate the volume of methane +  resulting from the fermentation of the organics  contained in the anaerobic sludge. Totally 18 te4  s7ts           +CHAPTER 4- EFFECT OF MOISTURE CONTENT ON ANAEROBIC DIGESTION OF RICE +STRAW + +were performed. +Table 14. Inoculum and substrate characteristics. +Anaerobic TS Substrate TS VS +Tests sludge inoculum amount substrate TS mixture [%] Mixture [g] [%] [g] [%] [%] +T1 500(±1) 3.45 8.09 91.00 4.85 3.75 +T2 500(±1) 10.88 26.05 91.00 14.86 11.68 +T3 500(±1) 17.82 41.27 91.00 23.41 17.98 + +4.2.3. Analytical methods +4.2.3.1 Methane production, COD, TS, VS. +Volumetric methane production was measured once a day, by connecting each digester by a capillary +tube to an inverted 1000 mL glass bottle containing an alkaline solution (12% NaOH). The inverted +1000 mL glass bottle was sealed in the same way as the digesters. To enable gas transfer through the +two connected bottles, the capillary tube was equipped on both ends with a needle sharp enough to +pierce the silicone disc. +The weight, TS and VS concentration of the anaerobic sludge as well as the dry matter, moisture +organic matter and ash content of the substrate were determined by gravimetry according to Standard +Methods (APHA, 1998). Temperature of all mixtures investigated was monitored for at least once a +day with a TFK 325 thermometer (WTW, Germany). COD was determined by the closed reflux +method, followed by photometric determination using a WTW Photolab Spektral visible +spectrophotometer   according to the APHA standard method 5220D and by applying the method +proposed by Zupančič and Roš (2012).   + +4.2.3.2 VFAs and phenols analysis +VFAs concentration and speciation were monitored throughout the process. VFAs were analysed +collecting 100 mg of digestate sampled from each reactor and diluted with ultrapure water. The +  samples were vigorously stirred for three minutes   and centrifuged at 8000 rpm for 5 min. VFAs w4e   r8e           +CHAPTER 4- EFFECT OF MOISTURE CONTENT ON ANAEROBIC DIGESTION OF RICE +STRAW + +extracted from the supernatant by SPME prior to GC-MS injection following the procedure proposed +by Ábalos et al. (2000). 50 µL of a 2,2 dimethyl butanoic acid solution were added as internal +standard. 85 µm polyacrilate coated fibers from SUPELCO were used for the extraction and analysed +after thermal desorption by an Agilent 6850 GC coupled with a 5973 Network MSD detector. +Total Phenols determination is according to APHA standard method 5550 B (APHA, 1998), by the +use of the Folin reagent. The method is sensitive for any compound containing aromatic hydroxyl +group. The calibration curve was built preparing standards at increasing concentration of phenol +(C6H5OH). + 4.3. Results and Discussion +4.3.1 Methane production +Results of BMTs are summarized in Figures 22-24. Figure 22 reports the specific cumulative methane +production versus time in reactors operated with different TS content. Each curve represents the +average of 3 replicates (max standard deviation = 3%). The specific cumulative methane production +was obtained dividing the cumulative methane production of each test by the initial substrate-inoculum +VS mixture. Figure 23 reports the final specific methane yield, measured at the end of each +experiment, as a function of the TS content and subtracted of the respective blank production. +Figures 22-23 show that the lower TS content was favourable for improving the cumulative methane +production and the final methane production yield. +Figure 24 illustrates the daily methane production during the first 60 days. One initial peak of methane +production was detected in all reactors. This peak is connected to the anaerobic degradation of +biodegradable substrates, corresponding to the TVFA (Fig. 26) peak related to acid accumulation at +the start-up of the process. This means that the hydrolysis is the rate-limiting step of the process. The +results obtained with the final methane yield for different TS are consistent with previous studies +operated with different types of substrate performed by Lay et al. (1997a, b), Abbassi-Guendouz et al. +(2012), Fernández et al. (2008), Dong et al. (2010), Le Hyaric et al. (2012) and Shi et al. (2014). All +authors do agree that higher methane yields can be obtained with a lower TS. Thus, the conversion of +acids to methane by methanogenic bacteria might be influenced by the lack of the free water (Lay et +  al. 1997b; Ghosh 1985) that can occur with a h   igher TS content in the range of dry and semid4   r9y           +CHAPTER 4- EFFECT OF MOISTURE CONTENT ON ANAEROBIC DIGESTION OF RICE +STRAW + +digestion (Abbassi-Guendouz et al. 2012; Fernández et al. 2008; Li et al. 2011). Figure 25 indicates a +non-linear relationship between TS content and initial methane production rate. This behaviour is not +in agreement with several author findings, who found a linear relationship between the two parameters +(Lay et al. 1997b; Le Hyaric et al. 2012; Abbassi-Guendouz et al. 2012; Mora-Naranjo et al. 2004; +Pommier et al. 2007). The different behaviour can be explained because of the different substrate +composition, the complex nature of lingo-cellulosic compounds, the low bio-availability of cellulose, +the substrate crystalline structure and the presence of hemicellulose. + +Figure 22. Specific cumulative methane production of rice straw in mesophilic conditions at different +TS content. + +Figure 23. Final methane yield of rice straw AD at different TS content. +     5   0           +CHAPTER 4- EFFECT OF MOISTURE CONTENT ON ANAEROBIC DIGESTION OF RICE +STRAW + +   +Figure 24. Daily methane production of rice straw anaerobic digestion at different TS content. +   +Figure 25. Not linear correlation between specific methane production and TS content. + +4.3.2 Analysis of process intermediates +To explain the obtained results it was monitored the concentration of VFAs, that is considered an +useful indicator of process stress and instability (Ahring et al. 1995). Figure 26 illustrates the temporal +evolution of selected VFAs (acetate, butyrate, propionate, valerate and formic acid) for the three TS +concentrations investigated. The lower methane yield detected with a higher TS content corresponded +to an higher concentration of acids. The highest concentrations were observed at TS = 23.41%, with +maximum values of 8.73 mmol acetic acid/kg on the 2nd day, 9.52 mmol formic acid/kg on the 8th day, +19.18 mg propionic acid/kg on the 2nd day and 2.02 mmol butyric acid/kg on the 8th day were found. +In the case of TS = 14.86%, the maximum values of 5.16 mmol acetic acid/kg on the 8th day, 2.57 +mmol formic acid/kg on the 8th day, 6.82 mg propionic acid/kg on the 8th day and 0.43 mmol butyric +  acid/kg on the 9 +th day were found. For a TS co  ntent of 4.85% the maximum values of 2.56 mm5   o1l           +CHAPTER 4- EFFECT OF MOISTURE CONTENT ON ANAEROBIC DIGESTION OF RICE +STRAW + +acetic acid/kg on the 3rd day, 0.4 mmol formic acid/kg on the 1st day, 1.57 mmol propionic acid/kg on +the 8th day and 0.21 mmol butyric acid/kg on the 3rd day were found. +An insufficient amount of methanogenic archaea may be the cause of such high concentrations of +VFAs. Indeed, high VFA concentrations induce acidification of the medium, and result in the +presence of VFAs in their un-dissociated form which is more toxic for microorganisms (Amani et al. +2010). Furthermore, at the highest TS concentrations, environmental conditions did not allow the +growth of acetoclastic methanogens or acetate-oxidizing bacteria on account of high VFA +concentrations and low pH values (Abbassi-Guendouz et al. 2012). Also during the first days, acid +accumulation occurred (Fig. 27a-e), because the hydrolysis and acidogenesis took place and the easy +biodegradable fraction of rice straw was converted to VFAs. During the second stage, acetoclastic +methanogens where in the exponential growth phase and the acetic acid consumption rate exceeded its +generation rate, also if the hydrolysis and acidogenesis were still going on. In the final stage, the +balance between the hydrodysis/acidogenesis and methanogenesis was formed and the produced acids +were consumed to produce methane (Dong et al. 2010). +Is finally possible to notice how the accumulation of butyric and formic acids takes place only in the +dry and semidry reactors and lasts until the 8th day, while both this acids concentrations are close to +zero during almost the whole experiment. This might be attributed to the co-presence of an alternative +fermentation pathway, that brings to the formation of butyric acid. This pathway is alternative to the +acetic fermentation and determine different process kinetics. This indicates that in the studied reactors +the border conditions are different for the fermenting microorganisms, probably originating bacterial +growths with different distributions and degradation pathways. + +     5   2           +CHAPTER 4- EFFECT OF MOISTURE CONTENT ON ANAEROBIC DIGESTION OF RICE +STRAW + +   +Figure 26. Evolution of TVFA concentration of rice straw at different TS content. +     +a) Acetic acid   +     +b) Propionic acid +     5   3           +CHAPTER 4- EFFECT OF MOISTURE CONTENT ON ANAEROBIC DIGESTION OF RICE +STRAW + +     +c) Butyric acid   +     +d) Valeric acid +   +e) Formic acid +Figure 27. Evolution of VFA concentration of rice straw anaerobic digestion with different TS content: +a) Acetic acid; b) propionic acid; c) butyric acid; d) valeric acid; e) formic acid. + +Despite the observed differences among the three TS concentrations, each detected VFA +c   oncentrations never reached the inhibition limit (  Fig. 27). The maximum TVFA concentrations w5e   r4e           +CHAPTER 4- EFFECT OF MOISTURE CONTENT ON ANAEROBIC DIGESTION OF RICE +STRAW + +3 mmol/kg, 15 mmol/kg and 33 mmol/kg, respectively, i.e. much lower respect to the threshold value +indicated by Karthikeyan and Visvanathan, 2012. It was therefore supposed that the inhibition +occurred because of higher total phenols content at higher TS concentration (Fig. 28). +   +Figure 28. Total phenol degradation in anaerobic digestion of rice straw for different TS. + + 4.4 Comparative process efficiency +The reactor performances are reported for all TS concentrations in terms of VS reduction, evolution of +COD removal and specific final methane production yield. In terms of VS removal efficiency, the +better performances were observed at a lower TS content. This finding is in agreement with the +measured final methane production yield. +The COD values at the end of the experiment were higher for higher TS content as COD removal +decreased from 63 ± 6% (TS = 4.85%) to 59 ± 8% (TS = 14.86%), down to 48 ± 7% (TS = 23.4%), +confirming the slowdown of process kinetics taking place at higher TS content due to high VFA +concentration. + + 4.5. Conclusions +This chapter focuses on the effect of the moisture content on the anaerobic digestion of rice straw. A +higher specific methane production yield and process performance in terms of VS and COD +reductions were achieved at a lower TS content. This suggests that a wet anaerobic digestion gives +     5   5           +CHAPTER 4- EFFECT OF MOISTURE CONTENT ON ANAEROBIC DIGESTION OF RICE +STRAW + +better performances compared with dry processes. An inhibition correlated to the TVFA accumulation +was found at higher TS content. In fact maximum TVFA concentration of 2.1 g/kg was found in dry +condition, 1 g/kg in semidry conditions and 0.2 g/kg in wet conditions. Higher total phenol +concentration was also found at higher TS content. This could determine inhibition phenomena and +reduction of methane production. +     5   6           +CHAPTER 5 - ADM1 FOR DRY AND SEMI-DRY ANAEROBIC DIGESTION OF SOLID +ORGANIC WASTE + + + + + + + + + + + +CHAPTER 5 +Modified ADM1 for dry and semi-dry anaerobic digestion of solid +organic waste + + +   +   + + + + + +This chapter is the modified version of the article “Modified ADM1 for dry and semi-dry anaerobic +digestion of solid organic waste” submitted to Bioresource Technology Journal (under revision). +     5   7           +CHAPTER 5 - ADM1 FOR DRY AND SEMI-DRY ANAEROBIC DIGESTION OF SOLID +ORGANIC WASTE +5.1 Introduction +Experimental research carried out in recent years on AD have definitely established that the TS content +plays an important role on process development (Dong et al. 2010; Brown and Yebo 2013; Fernàndez +et al. 2008; Forster-Carneiro et al. 2007; Forster-Carneiro et al. 2008; Le Hyaric et al. 2012; Lü et al. +2012; Jha et al. 2013; Wang et al. 2013; Xu and Li 2012; Liotta et al. 2014; Shi et al. 2014; Zhu et al. +2014). As a consequence, several studies have been lead recently to adapt and calibrate the existing +mathematical models to take into account the effect of the TS content (Lay et al. 1997a, 1997b; Fdez- +Güelfo et al. 2012; Brown et al. 2012; Le Hyaric et al. 2012; Motte et al. 2013). Le Hyaric et al. (2012) +and Lay et al. (1997a, 1997b) applying the Gompertz model to simulate the results of Specific +Methanogenic Activity test, found that a high TS content (15%-25%) reduces substrate degradation +because of water and nutrients limitation, resulting in a lower methanogenic activity. Brown et al. +(2012) used the first-order kinetic models to characterize the methane production of lignocellulosic +biomass and found a linear relationship between logarithmic methane production and reaction time in +both in wet and dry anaerobic digestion of switchgrass, corn stover, wheat straw, leaves, yard waste +and maple. Dry anaerobic digestion generally exhibits a poor start-up performance, thus several models +assume the hydrolysis as the rate-limiting step of the process (Jha et al. 2013). In particular, Abbassi- +Guendouz et al. (2012), applying the ADM1 (Batstone et al. 2002) to cardboard treatment, found a +decreasing first-order hydrolysis rate constant for carbohydrates degradation when increasing the TS +content between 15-30%. Liotta et al. (2014) also found a decreasing disintegration rate when +increasing the TS content in the range of wet digestion. Bollon et al. (2011) found a similar result using +municipal solid waste digestate. +Moreover recent studies demonstrated the important role of the mechanisms associated to VFAs uptake +on process performances (Ward et al., 2008, Bolzonella et al., 2003, Dai et al., 2013, Jha et al., 2013, +Pohl et al., 2013). As intermediate products, VFAs have been treated as an indicator of the digestion +efficiency, but high concentrations of VFAs can determine a decrease of pH leading to performance +failure of the digester (Gerardi, 2003, Jha et al., 2013, Motte et al., 2013, Vavilin et al., 1996a). +An attempt to model dry anaerobic digestion considering also the role of VFA uptake was done by +Guendouz et al. (2010), who found a transitory accumulation of VFA during the batch tests indicating +that not only the hydrolysis is the rate-limiting step during dry anaerobic digestion of the solid wastes. +Motte et al. (2013) proposed a quadratic model able to descript dynamically the effect of TS, PS and +s   ubstrate/inoculum ratio on methane production  , pH and VFA concentration. The model resu5l  t8ed           +CHAPTER 5 - ADM1 FOR DRY AND SEMI-DRY ANAEROBIC DIGESTION OF SOLID +ORGANIC WASTE +highly significant (p-value < 0.05) and the coefficient of determination reach also 80%, however the +authors have not implemented a complete model, like ADM1, and have not calibrated any kinetic +constant varying TS content. +The aim of the present chapter is to develop a kinetic model that can specifically characterize the +disintegration, the acetogenesis and methanogenis steps of selected complex organic substrates as a +function of TS content in order to obtain a model able to predict and interpret results from anaerobic +digesters in wet, semi-dry and dry AD. In the following section, an overview of the model structure, +assumptions and main model parameters is presented. The proposed model is based on the cited ADM1 +model (Batstone et al., 2002) as modified by Esposito et al. (2008, 2011a,b, 2012a,b) for complex +organic substrates (modified ADM1). The kinetic equations are reformulated to consider the direct +effect of TS content and the effect of the intermediate compounds, which can affect, as a function of +the TS content, the whole process development. The dynamics of acetate, propionate and methane +production presented in Chapter 3 and 4 and obtained from two different series of batch anaerobic +digestion of food waste and rice straw were used to calibrate the proposed model. Food waste was +selected as representative of easily, highly biodegradable and heterogeneous substrates (Zhang et al. +2007), while rice straw as representative of slowly biodegradable and model of lignocellulosic residues. + +5.2 Model description +The proposed model is based on the Modified ADM1 (MADM1), extended to take into account the +presence of complex organic substrates in the feedstock, and the operation of the digester in semi-dry +and dry conditions. It is applied for Completely Stirred Tank Reactor (CSTR) and batch systems. The +MADM1 is a structured biological model that simulates the major conversion mechanisms of organic +substrates into biogas and the degradation of by-products. It assumes that composite materials are +converted into carbohydrates, proteins and lipids by a disintegration step (Esposito et al. 2012a,b). +These components are further hydrolysed into simple sugars, amino acids and long chain fatty acids. +Then, during the acidogenic step, fermentative micro-organisms convert these products into acetic, +propionic, butyric and valeric acids, hydrogen and carbon dioxide. The uptake of fatty acids yields +acetate (acetogenic step), which is converted into methane by methanogens. +The disintegration and hydrolysis steps are modelled by first-order kinetics. The disintegration used +  surface based kinetic, while hydrolysis step   a classical first order kinetic. All the oth5e   r9           +CHAPTER 5 - ADM1 FOR DRY AND SEMI-DRY ANAEROBIC DIGESTION OF SOLID +ORGANIC WASTE +transformations are classical biochemical transformations performed by specific bacterial groups, and +are described by a Monod-type equation, where the substrate uptake is associated to the microbial +growth. The kinetics of microbial growth and decay are also included in the model. +The overall model consists of 28 mass balance equations (Batstone et al. 2002) applied to the 28 state +variables (13 substrates and 15 biomasses) summarized in Tables 15-16. The kinetic constants and +processes of the modelled substrates in the MADM1 are listed in Table 17. It is worth noting that, +according to the MADM1, only the parameter Ksbk, not included in the original version of the ADM1, +is function of the substrate intrinsic characteristics and therefore depends also on the TS content of +the substrate (Liotta et al. 2014). +Table 15. Substrate variables in the MADM1 model. + +Substrate variables [ML-3] Symbol + Initial Substrate C +Soluble Inert Si + Total Propionate Spro +Total Acetate Sac + Total Butyrate Sb +Total Valerate S + vGaseous Hydrogen Shg + Gaseous Methane Shm +Inorganic carbon Sc + Nitrogen SN +LCFA SLCFA + Sugar SS +Amino acids Sam + + + + + + + + +     6   0           +CHAPTER 5 - ADM1 FOR DRY AND SEMI-DRY ANAEROBIC DIGESTION OF SOLID +ORGANIC WASTE + +Table 16. Biomass variables in the MADM1 model + +Biomass variables [ML-3] Symbol +Particulate inert Xi + Propionate degraders Xpro +Acetate Degraders Xac + Butyrate and Valerate +degraders Xb/v + Hydrogen degraders Xh +Readily and slowly +degradable carbohydrates Xcb-S/Xcb-R + Readily and slowly +degradable lipids Xl-S /Xl-R + Readily and slowly Xp-S/Xp-R +degradable protein + +LCFA Degraders XLCFA + Sugar Degraders Xs +Amminoacids Degraders Xam + +Sludge concentration Xsl + + + + + + + + + +     6   1           +CHAPTER 5 - ADM1 FOR DRY AND SEMI-DRY ANAEROBIC DIGESTION OF SOLID +ORGANIC WASTE + +Table 17. Kinetic constants of the MADM1 model. + Kinetic Kinetic + Substrate constants Process (ρ j) [T-1]* + Complex Organic Disintegration of +Substrate Ksbk complex organic matter + Propionate Kpro Uptake of +Propionate + Acetate Kac Uptake of acetate +Total Valerate and Uptake of Valerate + Butyrate +Kc4 and Butyrate +Hydrogen Kh Uptake of hydrogen +Methane K + mCarbohydrate Hydrolysis of +(slowly and readily Kc-S/Kc-R carbohydrates + biodegradable) +Lipids Hydrolysis of lipids + (slowly and readily Kl-S/Kl-R +biodegradable) +Proteins Hydrolysis of + (slowly and readily Kp-S/Kl-R proteins +biodegradable) + LCFA KLCFA Uptake of LCFA + Sugars Ks Uptake of Sugars + Amino acids K Uptake of amino am acids +*only in the case of Ksbk constant dimension is [ML-2T-1]. +With respect to the MADM1, the proposed model modifies some of the kinetic equations listed in +Esposito et al. (2011a,b). Each kinetic constant (Ksbk, Kac and Kpro) is expressed as function of the TS +content in order to take into account the reduction of intermediate process kinetic on the following +processes: the initial substrate disintegration, the acetate and the propionate up-take. More precisely +assuming CSTR conditions and a constant reactor Volume (V), for each state variable (Ci), the mass +balance has the following form: + dCi qC= i−in qC− i−outdt V V +∑ ν ρ (8) j=i−23 ij j +w   here:   6   2           +CHAPTER 5 - ADM1 FOR DRY AND SEMI-DRY ANAEROBIC DIGESTION OF SOLID +ORGANIC WASTE +the term qCi−in qC− i−outV V = 0 in batch conditions, where the flow rate (q) is assumed to be zero, and +the term∑ ν ijρ j is the overall reaction term expressed as a sum of specific kinetic rate for the j=i−23 +process j (ρj) multiplied by the stoichiometric coefficients (νij) that describe the influence of the +specific process j on the individual component i. +The specific kinetic rates and the stoichiometric coefficients used in the present model are strictly +equivalent to those present in the MADM1. +The main difference of the proposed model compared to the MADM1 is the capability to consider the +variation of the kinetic constants Ksbk, Kac and Kpro with the TS content. These constants are involved +in the following specific kinetic rates: + ρi,1 = Ksbk ⋅C ⋅a* (9) + Sρ = K ⋅ proi,13 pro K S ⋅Xpro ⋅ I+ 2 (10) s bu + Sρ aci,14 = Kac ⋅ K S ⋅Xac ⋅ I3 (11) s + ac +These equations have been reformulated by substituting the kinetic constants Ksbk, Kac and Kpro with +the following functions: + Ksbk (TS) = a ⋅TS + b (12) + Kac,pro(TS) = c ⋅TS + d (13) +where the new parameters a, b, c and d need to be calibrated depending on the substrate type (in this +study rice straw and food waste) and the specific experimental conditions such as temperature, +pressure, pH, retention time and mixing conditions (Liotta et al. 2014). + +5.3 Model calibration +The proposed model was calibrated using the experimental data obtained during anaerobic digestion +of food waste and rice straw. The experimental tests were conducted in batch, at 32°C, using two liter +r  eactors. The following TS concentrations were t  ested 4.2%, 12.8% and 19.2% for the food wast6e   3,           +CHAPTER 5 - ADM1 FOR DRY AND SEMI-DRY ANAEROBIC DIGESTION OF SOLID +ORGANIC WASTE +and 4.85%, 14.86% and 23.40% for the rice straw. The experimental procedures and the obtained +results are reported in Chapters 3-4. +The calibration was performed in two steps. In the first step, the simulated curves were plotted for +each value of K ac, Kpro and Ksbk, and the simulated results were compared with experimental data by +applying the RMSE method, as usually done for the model calibration process (Janssen and +Heuberger 1995; Esposito et al. 2011a, b). In the second step, the values of each K ac, Kpro, Ksbk +associated to the lower RMSE that better fit the proposed equations (12, 13), were introduced in the +model to perform a second set of simulations. These modelling results were again compared with +experimental data by individuating the final RMSE values for each K ac, Kpro and Ksbk value. The final +results of calibration procedure are summarized in Figures 29-31 and Table 18. In particular the +experimental data were used for both substrates to calibrate the disintegration kinetic constants Kdis of +the ADM1, assuming it coincides with the constant Ksbk of the MADM1, as the specific surface did +not varied in the different tests. Acetic and propionic acid productions were used to calibrate the +constants Kac and Kpro. All the other constants and parameters were set from literature data (Batstone +et al. 2002; Esposito et al. 2008, 2011a, b). + + + + + + + + + + +     6   4           +CHAPTER 5 - ADM1 FOR DRY AND SEMI-DRY ANAEROBIC DIGESTION OF SOLID +ORGANIC WASTE +(A) (B) +0.16 0.16 +0.14 0.14 +0.12 0.12 +0.1 0.1 +0.08 0.08 +0.06 0.06 +0.04 0.04 +0.02 0.02 +0 0 +0 10 20 30 40 50 0 0.04 0.08 0.12 0.16 +Time [d] Measured CH4 [mol]   +(C) (D) +0.4 0.4 +0.35 0.35 +0.3 0.3 +0.25 0.25 +0.2 0.2 +0.15 0.15 +0.1 0.1 +0.05 0.05 +0 0 +0 10 20 30 40 0 0.1 0.2 0.3 0.4 +Time [d] Measured CH4 [mol]                                                                                                         +(E) (F) +0.6 0.6 +0.5 0.5 +0.4 0.4 +0.3 0.3 +0.2 0.2 +0.1 0.1 +0 0 +0 10 20 30 40 0 0.1 0.2 0.3 0.4 0.5 0.6 +Time [d] Measured CH4 [mol] +Figure 29. Comparison of measured (points) and simulated (continuous line) data of cumulative +methane production for experiments with food waste at A, B) TS = 4.52%; C, D) TS = 12.87%; E, F) +TS = 19.02%. +     6   5           +CH4 [mol] CHCH [mol] 4 + [mol] +4 +Simulated CH [mol] Simulated CH [mol] +Simulated CH4 [mol] +4 4 +CHAPTER 5 - ADM1 FOR DRY AND SEMI-DRY ANAEROBIC DIGESTION OF SOLID +ORGANIC WASTE +(A) (B) x 10-3 (C) x 10-3 (D) +0.018 0.035 6 1 +0.016 0.9 +0.03 +5 +0.014 0.8 +0.025 0.7 +0.012 4 +0.6 +0.01 0.02 +3 0.5 +0.008 0.015 +0.4 +0.006 2 +0.01 0.3 +0.004 0.2 +1 +0.005 +0.002 0.1 +             0 0 0 00 20 40 60 0 20 40 60 0 20 40 60 0 20 40 60Time [d] Time [d] Time [d] Time [d]   +(E) (F) (G) x 10-3 (H) +0.045 0.07 0.025 6 +0.04 +0.06 +5 +0.035 0.02 +0.05 +0.03 4 +0.015 +0.025 0.04 +3 +0.02 0.03 +0.01 +0.015 2 +0.02 +0.01 0.005 +1 +0.01 +0.005 +           0 0 0 00 20 40 60 0 20 40 60 0 20 40 60 0 20 40 60Time [d] Time [d] Time [d] Time [d]   +(I) (L) +0.05 0.07 (J) (K)0.07 0.01 +0.045 0.009 +0.06 0.06 +0.04 0.008 +0.035 0.05 0.05 0.007 +0.03 +0.04 0.0060.04 +0.025 0.005 +0.03 +0.02 0.03 0.004 +0.015 0.02 0.02 0.003 +0.01 0.002 +0.01 0.01 +     0.005 0.00100 20 40 60 00 20 40 60 0 00 20 40 60 0 20 40 60Time [d] Time [d] Time [d] Time [d]   +Figure 30. Comparison of measured (points) and simulated (continuous line)   data for experiments with food waste: A-D) TS = 4.52%; E-H) TS = 12.92% and I-K) TS = 19.02%. + +     6   6           +propionate [mol] propionate [mol] propionate [mol] +acetate [mol] acetate [mol] acetate [mol] +butirate [mol] butirate [mol] butirate [mol] +valerate [mol] valerate [mol] +valerate [mol] +CHAPTER 5 - ADM1 FOR DRY AND SEMI-DRY ANAEROBIC DIGESTION OF SOLID +ORGANIC WASTE +(A) (B) x 10-3 (C) +1.8 x 10 +-3 (D) +0.14 0.14 3 +1.6 +0.12 0.12 2.5 +1.4 +0.1 0.1 +1.2 2 +0.08 0.08 1 +1.5 +0.06 0.06 0.8 +0.6 1 +0.04 0.04 +0.4 +0.02 0.02 0.5 +0.2 +0 0 0 0 +0 20 40 60 0 0.05 0.1 0.15 0.2 0 20 40 60 0 20 40 60 +Time [d] Measured CH4 [mol] Time [d] Time [d]   +(E) (F) x 10-3 (G) x 10-3 (H) +0.12 0.12 7 6 +6 +0.1 0.1 5 +5 +0.08 0.08 4 +4 +0.06 0.06 3 +3 +0.04 0.04 2 +2 +0.02 0.02 1 +1 +0 0 0 0 +0 20 40 60 0 0.05 0.1 0.15 0.2 0 20 40 60 0 20 40 60 +Time [d] Measured CH4 [mol] Time [d] Time [d]   +(I) (L) (J) x 10-3 (K) +0.25 0.25 0.02 9 +0.018 8 +0.2 0.2 0.016 7 +0.014 +6 +0.15 0.15 0.012 +5 +0.01 +4 +0.1 0.1 0.008 +3 +0.006 +0.05 0.05 0.004 2 +0.002 1 +0 0 0 0 +0 20 40 60 0 0.1 0.2 0.3 0.4 0 20 40 60 0 20 40 60 +Time [d] Measured CH4 [mol] Time [d] Time [d]   +Figure 31. Comparison of measured (points) and simulated (continuous line) data for experiments +  with rice straw: A-D) TS = 4.85%; E-H) TS = 14.86%; I-K) TS = 23.4%. +     +     6   7           +CH4 [mol] CH4 [mol] CH4 [mol] +Simulated CH4 [mol] Simulated CH4 [mol] Simulated CH4 [mol] +propionate [mol] +propionate [mol] propionate [mol] +acetate [mol] acetate [mol] acetate [mol] +CHAPTER 5 - ADM1 FOR DRY AND SEMI-DRY ANAEROBIC DIGESTION OF SOLID +ORGANIC WASTE + +Table 18. Kinetic constant for disintegration and VFA at different TS concentrations for food waste +and rice straw. +   +TS Kdis RMSE Kac RMSE Kpro RMSE +Substrate +[%] [d-1] [d-1] [d-1] +4.52 6.5 0.0072 8.47 0.0076 8.47 0.0052 +Food Waste 12.8 4 0.01 5.08 0.019 5.08 0.019 +19.02 2 0.0065 2.46 0.011 2.46 0.021 + 4.85 2.5 0.01 8.79 0.005 8.79 0.005   +Rice Straw 14.86 1.25 0.009 5.94 0.001 5.94 0.0019   + 23.40 0.65 0.0073 3.51 0.001 3.51 0.0055 + +5.4. Results and discussion +Table 18 and Figure 32 show that for both substrates the calibrated disintegration rate constant +linearly decreased with increasing TS concentration for both substrates. The linear function (12) can +be expressed in this case as follow: +For food waste: Kdis = −0.31⋅TS + 7.9 with r2 = 0.99 (14) +For rice straw: Kdis = −0.1⋅TS + 2.9 with r2 = 0.97 (15) +Where Kdis is assumed to be coincident with Ksbk. +The values of parameters a, b are different for the two tested substrates because of the specific +characteristic of the initial substrate to be hydrolysed. In fact food waste is a more easily +biodegradable substrate compared to rice straw that is a complex lignocellulosic structure more +difficult to be disintegrated. In fact, the structure of rice straw consists of different types of polymers +that are difficult to degrade such as: cellulose (37.4%), hemi-cellulose (44.9%), lignin (4.9%) and +silicon ash (13%) (Hills and Robert 1981; Mussoline et al. 2013). Thus for each TS the rice straw +disintegration rate constant (and the values a, b) are lower than the one of food waste. These results +are consistent with results previously presented by Liotta et al. (2014), where a linear correlation with +r2 = 0.99 was found between the carrot waste disintegration rate constant and TS in the range of wet +conditions. +     6   8           +CHAPTER 5 - ADM1 FOR DRY AND SEMI-DRY ANAEROBIC DIGESTION OF SOLID +ORGANIC WASTE +The linear correlations (14, 15) describe the slowing-down of the disintegration process with higher +values of the TS content caused by the lack of water and the limited transfer of hydrolysis products +(and other intermediates) to bacterial sites (Lay et al. 1997a, 1997b; Mora-Naranjo et al. 2004; +Pommier et al. 2007). This is in agreement with results presented by Abbassi Guendouz et al. (2012), +Pommier et al. (2007) and Liotta et al. (2014), who observed a strong impact of the TS content on +biodegradation kinetic rates and maximum methane production in anaerobic digestion of different +substrates. +Figure 33 shows that for both substrates, a linear and inverse correlation exist between the values of +the propionate and acetate kinetic constants and the TS content. In this case, a unique linear function, +as reported in (13), can be expressed for acetate and propionate as follows: +For food waste: Kac/pro = −0.41⋅TS +10.35 with r2 > 0.99 (16) +For rice straw: K = −0.28 ⋅TS +10.71 with r2 ac/pro > 0.97 (17) +The values of parameters b, c in equation (16, 17) are the same for acetate and propionate. This +means that the kinetic rate constants for acetate and propionate are equal for each TS content. Thus, it +can be concluded that the effect of the water content on propionate and acetate up-take is equal. +Also in this case the parameters c, d differ on the base initial substrate type because of different +experimental conditions and biomass involved in the anaerobic degradation of food waste and rice +straw. Additionally there are larger differences between the values of Kac/pro for rice straw and food +waste with higher TS. Thus, the intrinsic characteristics of the substrate type are more influent on the +process development and biomass selection with a lack of water. +This study show that with a higher TS content lower values of Kac/pro are obtained, that determine +higher concentrations of acetate and propionate during the whole process (Figures 30-31). This means +that a higher TS content can lead to process inhibition due to VFA accumulation, implying lower +process efficiency in terms of VS degradation, final methane yield and specific methane production +rate. Indeed, Figures 30-31 show a lower level of inhibition for the experiments under wet digestion +conditions (TS = 4.52% for the food waste and TS = 4.85% for the rice straw), compared to the +experiments under semi-dry (TS = 12.87% and TS = 14.86%) or dry (TS = 19.2% and TS = 23.4%) +anaerobic conditions. This is probably due to a reduction of the water content that implies a lower +nutrient content in the media and TVFAs accumulation. +Despite the good fitting between simulated and experimental concentrations, showing the capability +of the model to simulate the AD process of the two substrates with different initial TS, it is wor6th9                 +CHAPTER 5 - ADM1 FOR DRY AND SEMI-DRY ANAEROBIC DIGESTION OF SOLID +ORGANIC WASTE +noting that the model fitting is of higher quality for the data obtained during rice straw digestion. For +food waste, Figures 31,e and 31, i show that some points could not be fitted by the simulated curves. +This means that an inhibition phenomenon, related to the difficult degradation of propionic acid and +consequent formation of propionate isomers during the process not taken into account in the +simulation, should be considered in the further development of the kinetic equations of the model. +This different behaviour can be related to the nature of the substrate type. Food waste is of complex +nature and contains many different compounds that have different degradation kinetics. In contrast, a +unique substrate like rice straw, presents a kinetic behaviour easier to be modelled. +   +Figure 32. Linear correlation between disintegration kinetic constant and TS for rice straw and food +waste. + + + + + + + + +Figure 33. Linear correlation between propionate and acetate kinetic constants and TS content for rice +straw and food waste. + + + +     7   0           +CHAPTER 5 - ADM1 FOR DRY AND SEMI-DRY ANAEROBIC DIGESTION OF SOLID +ORGANIC WASTE +5.5 Conclusion +• A mathematical model capable to simulate dry anaerobic digestion of selected complex +organic substrates such as rice straw and food waste is proposed. +• Model calibration resulted in the determination of the disintegration and VFA kinetic +constants for different TS contents in the range of 4.5%-23%. +• The good fitting of the bio-methanation tests data with the model simulation results for both +methane production and VFA concentrations confirms the suitability of the model. +• A linear equation that correlate the TS content with the disintegration kinetic constant was +proposed and included in the model MADM1. +• A linear equation that correlate the TS content with the acetate and propionate kinetic +   constants was proposed and included in the model MADM1.   +     +     7   1           +CHAPTER 6 – LITERATURE REVIEW +         +       +       +CHAPTER 6 +Literature Review +   +       +     +The paragraph 6.1 is the modified version of the article: +Flavia Liotta, Patrice Chatellier, Giovanni Esposito, Massimiliano Fabbricino, Eric D. van Hullebusch +& Piet N. L. Lens. (2014). Hydrodynamic mathematical modeling of aerobic plug flow and non-ideal +flow reactors: a review, Crit. Rev. Env. Technol. DOI:10.1080/10643389.2013.829768 + +The paragraph 6.2 is the modified version of the article: +Flavia Liotta, Patrice Chatellier, Giovanni Esposito, Massimiliano Fabbricino, Eric D. van Hullebusch +& Piet N. L. Lens. Current views on hydrodynamic +submitted to Crit. Rev. Env. Technol. (under review).   models of non-ideal flow anaerobic reactors, +     7   2           +CHAPTER 6 – LITERATURE REVIEW +6.1 Mathematical modelling of aerobic plug flow reactor and non-ideal flow reactor +6.1.1 Introduction +Mathematical modelling and dynamic simulation have become important tools for design and +operation of wastewater and solid waste treatment plants. However, semi-empiric methods and +mathematical models based on ideal assumptions are still used for routine reactor design and +operation. For instance, biochemical models for the evaluation of the bioconversion processes +prevailing in CSTR, such as the IAWPRC Activated Sludge Model (ASM1) (Henze et al. 1987) and +modelling tools to evaluate system design and upgrade options, such as the ATV models (ATV 1991; +Benedetti et al. 2008) are widely applied. However, these models do not include the hydrodynamics of +the bioreactor. This is a limitation for the model suitability as many authors claim that the efficiency of +the pollution removal process depends also on the reactor hydrodynamics (Levin and Gealt 1993; Le +Moullec et al. 2008; Makinia and Wells 1999). +Several authors in the presented models couple the hydrodynamic processes with biochemical +processes and consider in the model the effect of one process on another. In particular the biochemical +process can be affected by the reactor flow conditions because the biomass, substrates and inhibiting +compounds can be distributed in different reactor zones. This implies that the biochemical process can +occur with different kinetics depending on hydrodynamic condition. Inhibition could also happen due +to the accumulation of some inhibitory compounds in specific reactor zones. In parallel, the biomass +type developing in the reactor influences the viscosity of the mixed liquor and thus the hydrodynamics +of the reactor. The objective of this literature review is, therefore, to review mathematical models of +aerobic reactors going beyond the hypothesis of complete mixing conditions and focusing only on +hydrodynamic aspects and on the role of reactor configuration on the process performances. The +present research also analyses and compares performance-prediction models referring to the most +common aerobic bioreactors configurations, i.e. Activated Sludge Reactors (AS), Fluidized Bed +Reactors (FBR), Biofilters (BF) and Trickling Filters (TF), and addresses both plug flow reactors and +non-ideal flow reactors. Finally, the chapter illustrates more in details the differences among the +proposed approaches, indicates the adopted solving algorithms and discusses the capacity of the +models to fit the experimental data. + +     7   3           +CHAPTER 6 – LITERATURE REVIEW +6.1.2. Design models and performance-prediction models +A design model is a model capable of predicting the reactor volume when the desired treatment +efficiency and the operational conditions are set. It is typically based on simplified assumptions +aiming to make the model easy to apply. For instance, steady-state instead of dynamic conditions are +assumed. In the literature, there are few attempts to use steady-state mathematical models to design +PFR and non-ideal flow reactors (San 1994) (Table 19). They are often simply modelled in terms of +design graph or charts (San 1994). These steady-state models are however beyond the scope of this +chapter. In contrast, a performance-prediction model is typically a dynamic model that simulates most +of the physical, chemical and biological processes taking place in the reactor. It is aiming to predict +the effluent concentrations once the bioreactor volume is known and the operational conditions are +set. Table 20 gives some performance-prediction models published in the literature. They are +reviewed in details in this chapter, after a short description of the fundamentals of the adopted +approaches. The attempts made by the authors to calibrate or validate these models are described as +well. + +Table 19. Design model of Activated Sludge and Fluidized Bed Reactor + + R e a c tor References +Activated Sludge San (1994); + Muslu (2000) + Fluidized Bed Reactor Shieh et al. (1982) + + + + + + + + + + + +     7   4           +CHAPTER 6 – LITERATURE REVIEW + +Table 20. Performance prediction mathematical models + San (1989); San (1992); + Activated Sludge L   awrence and McCarty (1980); Olsson and Andrews (1978); + PFR Fluidized Bed Shieh et al. (1982);   +Biofilter and Meunier and Williamson (1981); +Trickling Filters Baquerizo et al. (2005); Jacob et al. (1996);   + Milbury et al. (1965); + TIS/TIS derived Activated Sludge Braha and Hafner (1985); +Muslu (2000a,b). +Fluidized Bed Y u e t a l . ( 1 9 9 9 )   +Biofilter and Fdz-Polanco et al. (1994);   +Trickling Filters + Martinov et al. (2010); Mezaoui + (1979); Nyadziehe (1980); + Activated Sludge Sant'Anna (1985); De Clercq et al. + (1999); Turian et al. (1975); Lee et + al. (1999a,b); + Olsson and Andrews (1978); Makinia and Wells (2000); + El-Temtamy et al. (1979a,b); + Muroyama and Fan (1985); + Dispersion Fluidized Bed D a v i d s o n e t a l . ( 1 9 8 5 ) ; + Lin (1991); +Kim and Kang (1997); +Michelsen and Østergaard (1970).   +Froment and Bischoff 1990; +Biofilter and Trickling Séguret and Racault (1998); Muslu +Filters (1990); Muslu (1984); +Muslu  and San 1990; Séguret et al. (2000) + Activated Sludge Le Moullec et al. (2010a,b); Glover + (2006) + CFD Fluidized Bed   +Biofilter and Iliuta and Larachi (2005)   +Trickling Filters + + +       +     7   5           +CHAPTER 6 – LITERATURE REVIEW +6.1.3 Modeling approaches +Hydrodynamic models can be generally divided into two different groups: ideal models, referring to +CSTR and PFR conditions, and non ideal models, taking into account the effect of longitudinal +mixing neglected by ideal models (Table 21). In the CSTR model, the inlet reactant is assumed to be +completely mixed in the reactor so that concentrations are homogeneous in the vessel. +The mass-balance equation for a non-reactive tracer in a CSTR is: + dCex V =Q ⋅Cin −Q ⋅Cex (18) dt +where: +t = time [T]; +V = reactor control volume [L3]; +Q = volumetric flow rate [L3T-1]; +C = reactant concentration [ML-3]; +in = subscript denoting influent; +ex = subscript denoting effluent; +In the PFR, it is assumed that no longitudinal mixing occurs between adjacent elements of the fluid +and each element of the influent reactant remains in the reactor for a time equal to the hydraulic +retention time (HRT). +The mass-balance for a non-reactive tracer is: + ∂C dV =Q C Q ⎛C ∂C⋅ − ⋅⎜ + dx ⎞⎟ (19) +∂t ⎝ ∂x ⎠ +where: +x = spatial variable in the flow direction [L]. +Under un-steady state conditions, equation (11) may be written as: + ∂C v ∂C= − ⋅ (20) +∂t ∂x +where: +v = flow velocity [LT-1]. +Among non-ideal models, a prominent role is played by the tank-in-series (TIS) model. This model is +used to describe the dispersion in PFR. The TIS model describes the flow in a reactor system +  considering it can be discretized into a series o   f equal-sized hypothetical CSTRs. This model7i  n6g           +CHAPTER 6 – LITERATURE REVIEW +approach was introduced for tracer analyses and one of the earliest descriptions of this theory was +given by MacMullin and Weber (1935). +If a tracer is distributed uniformly throughout all the compartments of the vessel and then diluted out +at a constant rate, the effluent tracer concentration Cex as a function of time is given by (Martin, 2000): +C NN t N−1 N⎛ ⎞ − tex = ⎜ ⎟ e τ (21) +Cin (N −1) !⎝τ ⎠ +where: +N = number of reactor in series. +Levenspiel (1972) related the number of reactors in series to the variance number with the following +expression: + 2 1σ = (22) +N +where: +σ2 = variance of Residence Time Distribution (RTD) curve from a pulse tracer input. +Generally, N = 1 represents a CSTR, whereas N = ∞ means a PFR. +With respect to the previous approach, the extended tank-in series model (ETIS) (Murphy and +Timpany 1967) presents a small difference, as it introduces the concept of non-integer number of +hypothetical tanks in series to remove the quantization problem which occurs as N tends to 1. The +ETIS model defines the exit age distribution function, E(t), through the following equations: +C NN t N −1 N⎛ ⎞ − t E(t)= ex = ⎜ ⎟ e τ (23) +Cin Γ(N )⎝τ ⎠ +∞ +Γ(N )= ∫ e−v ⋅v(N −1)dv (24) +0 +Consequently, the N parameter loses its physical meaning as a number (positive) of tanks in the ETIS +model, but the model acquires a continuous distribution of flow-rate. The ETIS model coincides with +the TIS model when the parameter N is an integer number. This model is particularly useful when N is +small and a large number of discontinuities occurs in the TIS model due to the discrete nature of the +parameter N. A further variation of the TIS model consists in fractionating the reactor in different +sections, e.g. a CSTR section, a PFR section and a dead section with by-pass flows or back-mixing +flows between the zones. With tracer tests and considering different liquid and gas flow rates, it is +possible to define the values of bypass flows and dead sections. +     7   7           +CHAPTER 6 – LITERATURE REVIEW +Apart from the TIS and TIS-derived models, other approaches have been followed to describe the +dispersion effect. One of the pioneering and most complete studies on longitudinal mixing in aeration +tanks was published by Thomas and McKee (1944). They demonstrated that longitudinal mixing is +the effect of various factors as the degree of turbulence, the flow rate, the length of the tank and the +number of baffles. The authors set up the dispersion model introducing the differential equation for a +tubular reactor with longitudinal diffusion as well as flow (changes in volume were assumed not to +occur, so that the mean longitudinal velocity is the same at all cross-sections). The resulting equation +is: +∂C D ∂ +2C ∂C += 2 − v (25) ∂t ∂x ∂x +where: +D = dispersion number [L2T-1]. +Equation (17) was solved considering as initial boundary conditions that the concentration gradient +was equal to the initial concentration and by assuming that the exit gradient was equal to zero at the +end of the reactor. +The authors calculated the dispersion coefficient as: + D = L2 1802 (26) π ⋅ t90 +where: +L = reactor length [L]; +t90 = time required for the effluent concentration to attain 90% of its ultimate value [T]. +The dispersion number, D is defined as: + D D= (27) +v ⋅ L +D has an important role to indicate which of the ideal flow models is approached. When D is higher +than 0.5-4, completely mixing can be assumed (Khudenko and Shpirt 1986; U.S. EPA 1993; Makinia +and Wells 1999). Long and narrow tanks, with a dispersion number lower than 0.05-0.2 (Khudenko +and Shpirt 1986; U.S. EPA 1993; Eckenfelder et al. 1985; Makinia and Wells 1999) are considered an +approximation of plug flow. Typical dispersion numbers in wastewater treatment units are in the range +between 0.1 and 4, which suggests that the existing deviations from ideal flow have to be taken into +consideration (Makinia and Wells 2005; Makinia and Wells 1999). +     7   8           +CHAPTER 6 – LITERATURE REVIEW +With regard to the integration of the equations an algebraic solution is possible for simple models +based on CSTR or CSTR in series configurations, whereas finite difference techniques or +Computational Fluid Dynamics (CFD). + +Table 21 Modelling approach: PFR, CSTR, TIS, Dispersion model, CFD basic concept and equation + + + Modelling approach Basic concept Equation + + No longitudinal mixing +Ideal PFR occurs between adjacent ∂C v ∂C = − ⋅ elements of fluid. ∂t ∂x + + The concentration is C t− + Ideal CSTR assumed to be +ex = e τ +homogeneous in the Cin + reactor. +TIS The flow is discretized Cex N N +N −1 N +⎛ t ⎞ − t +into a series of = e τ + C (N −1) +⎜ ⎟ + !⎝τ ⎠ +hypothetical CSTRs. in +Dispersion model The Differential ∂C 2D ∂ C ∂C equation that include = − v ∂t ∂x2 ∂x + longitudinal diffusion +   and advection term. CFD Is a techniques applied Discretizes the reactor using a   to solve fluid dynamics computational grid and include   models on digital fundamental mass, momentum computers. and energy conservation +     +equation. +6.1.4.Mathematical modeling of Activated Sludge plug flow reactors +6.1.4.1 Process description +The activated sludge process is used for the biological treatment of municipal and industrial +wastewaters. The basic activated sludge treatment process (Fig. 34A) consists of the following three +  components: i) a flocculant slurry of mixed liquo  r suspended solids (MLSS) utilized in the bioreac7  to9r           +CHAPTER 6 – LITERATURE REVIEW +to remove soluble and particulate organic matter from the influent waste stream; ii) a sedimentation +tank to separate the MLSS from the treated water and iii) a recycle system to return solids removed +from the liquid-solids separation unit back to the bioreactor. +The MLSS containing bioreactor is commonly called an aeration basin. It is an open tank equipped +with a system to transfer oxygen into solution to provide mixing energy to guarantee suspension of the +MLSS. Models taking into account the hydrodynamics of the plug flow aeration basin, that could +affect key parameters of the process such as treatment efficiency or settling properties of the activated +sludge, are described below. + +6.1.5. Model development +6.1.5.1 Ideal PFR and CSTR in series +The ideal plug-flow model has been frequently applied to plug flow activated sludge systems (Fig. +34B). Lawrence and McCarty (1970), assuming steady-state conditions, proposed the following +equation for processes that occur in the aeration basin based on the hypothesis of constant biomass +concentration in the reactor, valid as long as the SRT/HRT ratio is higher than 5: +dC C ⋅ X += −µ ⋅ (28) +dt ks +C +X = time averaged biomass concentration [ML-3]; +ks = saturation coefficient [ML-3]; +µ = maximum specific growth rate [T-1]. +San (1989, 1992) considered the same mass balance equation proposed by Lawrence and McCarty +(1970) for the reactant at steady-state conditions. Taking also into account the time variation of the +biomass concentration in the reactor and introducing the settler in the process configuration, they +obtained the following differential equations: + dC 1 C ⋅ X ⎛ 1 ⎞= −µ ⋅ ⋅ ⎜ ⎟ (29) +dt Y ks +C ⎝1+ R ⎠ +dX dC k ⋅ X +− =Y ⋅ + d (30) +dt dt 1+ R +where: +  X = biomass concentration [ML-3];   8   0           +CHAPTER 6 – LITERATURE REVIEW +ks = saturation coefficient [ML-3]; +R = sludge recycle ratio; +µ = maximum specific growth rate [T-1]; +Y= yield coefficient; +k = decay coefficient [T-1d ]. +Equations (21) and (22) were solved by San (1989, 1992) using the following boundaries conditions, +obtained from the mass balances of substrate and biomass concentration at the mixing point of fresh +feed and recycled flow (Fig. 34B), also proposed by Tuček et al. (1971): +Cin + R ⋅CCmix = (31) 1+ R +X X= in + R ⋅ Xrmix (32) 1+ R +where: +r = subscript denoting the return flow; +mix = subscript denoting the combined flow entering in aeration basin; +in = subscript denoting the inlet flow in the activated sludge system constituted of aeration basin and +settler. +Another attempt to use the ideal plug flow approach for activated sludge plug flow reactors, was done +by Olsson and Andrews (1978) who proposed a model that simulates the substrate, biomass and +oxygen concentrations as a function of time and the spatial variable. +To the best of our knowledge, one of the first attempts to model a plug flow reactor with a tank in +series configuration was done by Milbury et al. (1965). Following this work also Murphy and +Timpany (1967); Braha and Hafner (1985) and Muslu (2000a,b) modeled the plug flow reactor as a +multiple tanks in series configuration. In particular Muslu (2000a,b) applied the old work of Milbury +et al. (1965), removing some hypotheses of their proposed model. In particular they changed the +biochemical model and proposed a new modeling approach where the axial change in biomass +concentration is considered by writing two mass balance equations for biomass and reactant and +considering a series of equal-sized, completely mixed reactors (Fig. 34 C) to represent the PFR +reactor. +A steady state mass balance is considered for the biomass and substrate. The resulting equations that +represent the effluent concentration of substrate and biomass from each reactor in dimensionless form +are: +     8   1           +CHAPTER 6 – LITERATURE REVIEW +1 kd ⋅τ X inC + −C = ex = N X exex (33) +kS (µ − kd )⋅τ X in−1+ +N X ex +X Xex X in +Cin −Cexex = = (34) +Y ⋅ kS ⎛⎜1 +kd ⋅τ+ ⎞⎟ +⎝ N ⎠ +These equations have to be solved using trial and error procedures. +(1+R)Q C C+ΔC (1+R)Q + X X+ΔX +influent effluent Q C + o Ci Q1, C1 Q-Qww +Q C Q0 Cex Xo Xi0 in Plug X1 +flow Aeration +Tank +Qr+Qw Qw,C +sludge Qr,C Xw +recycle + Xr Xr,C +A. Schematic configuration of an activated sludge system B. Representation of plug flow model for activated sludge system + Q C Ci Ce C Q0-Q4Q C 1 i 20 in + X Xi Xe X C2 X5X iin 2 +Q3+Q4 +Q3,C3 C2 X3 + X3 Q4 +C. Reactor in series with sludge return + Figure 34. Schematic representation of activated sludge reactor. + + +6.1.5.2 Non ideal flow reactor models +In the plug flow aeration basin of activated sludge process can cause high transverse axial mixing and +high aeration rate, high traverse velocities and irregular air distribution. Therefore, it is not possible to +describe the process with ideal plug flow equations. Thus several authors (San 1989; Lee et al. 1999a; +Wehner and Wilhelm 1956) described non-ideal conditions, caused by axial mixing, with the +following advective-diffusive equation including a reaction term: + ∂C ∂(v ⋅ C) ∂ ⎛D ∂C+ = ⎞⎜ ⎟+ RC (34) +   ∂t ∂x ∂x ⎝ ∂x ⎠   8   2           +CHAPTER 6 – LITERATURE REVIEW +where: +R = reaction term [ML-3T-1C ]. +In particular, Khudenko and Shpirt (1986) did not introduce the reaction term in the equation (34), but +coupled this equation to the oxygen mass transfer equation to find the optimal sizes to the aeration +tank and aeration system. +San (1992) developed an analytical solution for the differential equations of dispersed plug flow +systems in steady-state conditions, including a reaction term based on Monod kinetics. Lately the +same author (San 1994) introduced the following differential equations to simulate the effect of feed +and outlet channels: +2 + 1 d C dC− = 0 x∉[0, 1] (35) +Pe dx2 dx +1 d 2C dC τ ⋅µ ⋅ X 1 +− − = 0 x∈[0, 1] (36) +Pe dx2 dx Y ⋅ kS 1+C +where: +Pe = Peclet number. +Equations (35) and (36) were solved using boundary conditions introduced by Wehner and Wilhelm +(1956), resulting from the conservation of reactants at the exit and entrance of the reactor, taking into +account flow and diffusion, and from the intuitive argument that the concentrations should be +continuous between the reactor entrance and exit sections in steady-state conditions. +Turian et al. (1975), Lee et al. (1999a, 1999b) and Makinia and Wells (2000a,b) incorporated a more +comprehensive chain of biological reactions into the dispersion flow reactor model in unsteady state +conditions. Olivet et al. (2005) proposed tanks in series model to simulate the hydrodynamic +behaviour of a full scale plant. In particular a four tank in series model was developed. The authors +also included a dead zone to simulate the reactor zone with diffusers. Furthermore, the hydraulic +model includes the external recycle from the secondary settler. RTD tests were done to find the model +that better describes the reactor hydraulic behaviour. Also Potier et al. (2005) simulated full scale +aerated channels treating wastewater by applying a tanks in series model with back-mixing. The +authors considered in the model the variations of the wastewater characteristics (concentration and +composition of polluted influent, flow-rate, etc.). They also demonstrated that it is possible to simulate +easily the variations of the axial dispersion coefficient with the flow-rate through this model with a +maximal fixed number of mixing cells and a variable backflow rate. The authors also found several +     8   3           +CHAPTER 6 – LITERATURE REVIEW +correlations of the dispersion coefficient with reactor width, reactor length and gas flow-rate as +reported below: +0.5 +D =0.2032 "Q %⋅H ⋅$ GL ' (37) # & +where: +Q = gas flow-rate [ML-3G ]. +In another paper, Fall and Loaiza-Navia (2007) modelled with AQUASIM Software a full-scale +activated sludge reactor by applying the CSTR in series model. The authors also validated the model +by operating tracer tests. Lately, Ramin et al. (2011) modelled the activated sludge reactor also +including a settling tank. The authors also performed a sensitivity analysis with the Monte Carlo +method and uncertainty method and applied the convection-dispersion model. +6.1.5.3 Computational fluid dynamics model development +All the models described above are called “systemic models”, because they emphasize the functional +aspects of the reactor, without detailing the localization of the phenomena inside the reactor. Thus, +they give quite rapidly and with moderate efforts a first approximation of the reactor behavior. These +models have a good robustness in the range of experimental and size conditions for which they have +been developed (Le Moullec 2010b). However, they could remain unsatisfactory to consider local +phenomena and to model the influence of the reactor geometry (length/width ratio, presence of +baffles, effluent inlet device), the aeration process (sparging device, gas fraction field) and the +resulting local mixing (Le Moullec 2010a). +In the last few years some attempts were made to model the activated sludge reactor using a new +approach: a Computational Fluid Dynamics (CFD) model. It is a powerful tool which allows studying +the influences of the operating parameters and the hydrodynamic phenomena at local scale (Le +Moullec 2010b). With a structural approach a CFD model discretizes the reactor using a +computational grid, formulates and solves the fundamental mass, momentum, and energy +conservation equations in space (Huang et al. 2005). CFD simulations can define the flow patterns and +the retention time distribution to characterize the reactor hydraulic behavior. This information +provides a hint to the role of possible hydraulic problems related to the bad plant performance. +     8   4           +CHAPTER 6 – LITERATURE REVIEW +Alex et al. (2002) were among the first authors in the literature to use the CFD approach to generate +an appropriate model structure to simulate the biological processes in CSTR activated sludge +compartments. The first authors who implemented the ASM1 into the CFD code through the use of +classical convective scalar transport equations were Glover et al. (2006). The obtained model, +subsequently called CFD-ASM1, was then analysed at different levels and was validated with an +experimental study and two numerical studies of an SBR-oxidation ditch (Vermande 2005). Glover et +al. (2006) demonstrated that the classical biological modeling can take advantages of CFD results in +order to obtain the local oxygen concentration and transfer and the hydraulic structure (recycling rate +and number of perfect mixed reactors) of the system. +However, despite numerous developments and improvements, this approach still remains difficult to +handle for reactors involving complex and coupled local hydrodynamics, heat and mass transfer and +chemical reactions because of the high computational requirements. +Le Moullec et al. (2011) coupled CFD with the ASM model and compartmental approach. The +authors considered also the dispersion model and found a correlation between the axial dispersion +coefficient, the gas and liquid flow-rates and the reactor geometry. Such studies should allow to +improve the detailed design of aerated reactors in wastewater treatment plants (gas distribution +system, baffles location). In another study, Zima et al. (2009) proposed CFD for predicting the +behaviour of reactive pollutants in the aerobic zone of a full scale bioreactor. The one-dimensional +advection-dispersion equation was combined with simple biokinetic models incorporating the Monod- +type expressions. +Even in single-phase reactors, chemical reactions are described by non-linear terms that often cause +numerical instabilities. The high data quantity required is often prohibitive, while the complexity of +the problems that arises from coupling the fluid dynamics with the bio-chemical phenomena means +that the systems has be treated with attention for case (Rigopoulos and Jones 2003). In fact a lot of +parameters are involved in both the biochemical (kinetic and stoechiometric) and hydrodynamic +(dispersion) models. Furthermore is difficult to solve together two systems of linear and non-linear +equations represented by Navier-Stocks equations and differential equations. These models also +assume that the bio-chemical model does not impact on the hydrodynamic model and vice versa. This +assumption is possible by neglecting the effect of biochemical processes on hydrodynamics but it is a +big assumption for the effect of hydrodynamic conditions on biochemical processes. In fact the +biochemical process can be affected by the reactor flow conditions because, the biomass, substra8te5s                 +CHAPTER 6 – LITERATURE REVIEW +and inhibiting compounds can be distributed in different reactor zones. This implies that the +biochemical process can occur at a different kinetic in function of the hydrodynamic condition. +Recently, “hybrid” approaches have emerged as an alternative. In these cases CFD is employed only +for the hydrodynamic simulations, while the bio-chemical phenomena are resolved with +compartmental modeling (Rigopoulos and Jones 2003). The latter describes the reactor as a network +of functional compartments spatially localized. It is based on CFD and on the determination of +volumes in which physico-chemical processes occur. +6.1.5.4 Models comparisons +The model proposed by Lawrence and McCarty (1970), San (1989, 1992) and Milbury (1965) are old +and simple to apply but the results can present a big degree of uncertainty. More complete models +taking into account the dispersion related to reactor configuration and aeration are the ones proposed +by Khudenko and Shpirt (1986) and San (1992). But the best models are those proposed by Turian et +al. (1975), Lee et al. (1999a, 1999b), Olivet et al. (2005), Potier et al. (2005) and Makinia and Wells +(2000a,b) who considered biochemical reactions and dispersion flow are the ones. Finally it is also +useful to apply CFD models that are more complex than the previous models but describe the +hydrodynamic phenomena more in detail, considering the local process that happens in the reactor. +6.1.6. Mathematical modeling of fluidized bed reactors +6.1.6.1 Process description +In biological Fluidized Bed Reactors (FBR), the liquid to be treated is pumped through a bed of inert +particles (sand, pumice, activated coal) at a velocity sufficient to cause fluidization. Particles in a +fluidized state provide a large specific area for attached biomass growth; this feature enables long +solids residence times and low suspended solid concentrations. Usually aeration occurs through the +liquid recirculation from the reactor to an oxygenator in which air or oxygen is bubbled (Fig. 35). It is +also possible to have a three-phase fluidized bed reactor, by insufflating the oxygen directly into the +reactor (Wisecaver and Fan 1989; Hirata et al. 1986; Trinet et al. 1991; Fan et al. 1987). +     8   6           +CHAPTER 6 – LITERATURE REVIEW +                                                                                                                                        Figure 35. Schematic representation of fluidized bed reactor. + +6.1.6.2 Model development +6.1.6.2.1 Ideal flow reactor models +The liquid phase transport of a reactant through an FBR encompasses molecular diffusion, turbulent +diffusion, and convective diffusion caused by a non-uniform velocity distribution; the axial dispersion +is insignificant under normal operating conditions. Thus, FBRs have usually been modeled using ideal +flow patterns, such as CSTR or PFR (Shieh et al. 1982; Mulcahy et al. 1980; Mulcahy et al. 1981; +Rittmann 1982; Park et al. 1984) conditions. Due to the high recirculation rates many mathematical +models that were developed, as CSTRs did not consider the spatial gradients of the substrates and +products along the height of the reactor. +Rittmann (1982) stated that FBR can achieve a better performance compared to complete-mix because +the biofilm is evenly distributed throughout the reactor while the liquid regime is still “plug flow”. +Adding an effluent recycle, making the liquid phase more homogeneous, can change this +hydrodynamic behaviour. That dilutes the feed and makes the performance approaching a complete +mixing unit, which implies a lower removal efficiency than under plug-flow conditions (Rittmann +1982). Shieh et al. (1982) tried to apply the PFR model to an FBR assuming that macroscopic radial +     8   7           +CHAPTER 6 – LITERATURE REVIEW +gradients do not occur inside the reactor and pseudo-steady-state conditions prevail. The adopted +continuity plug flow equation is: +u dC + Rv = 0 (38) dx +where: +u = superficial velocity [ML-1]; +Rv = reactant conversion rate per unit fluidized bed volume [ML-3T-1]. +The authors included the following elements in their model: i) external and internal biofilm mass +transfer; ii) reactant consumption within the biofilm; and iii) a degree of bed expansion and an +expanded bed height under a given set of operating conditions such as flow rate, biofilm thickness, +media size, and density. As a result, a general model of an FBR reactor was obtained by combining +equation (38) with the reactant conversion rate expression and integrating the resulting equation +subject to boundary conditions that considers a bulk-liquid reactant concentration equal to the inlet +reactant concentration. The resulting equation describing the reactant concentration profile through +the FBR is: +0.9 +0.55 x ⎡0.55 3⋅r +2 ⎤ +C =C − ⋅0.6162 p 0.55 0.45⎢ ⎥ k ⋅D ⋅ x Φ ≥1.15 (39) in v 0 0,m⎣⎢ρ ⋅ (r 3 − r 3p m )⋅0.5⎦⎥ +where: +k0 = intrinsic zero order rate constant [T-1]; +rm = media radius [L]; +rp = bioparticle radius [L]; +r = biofilm dry density [ML- 3 ]; +Φ0,m = Thiele modulus. + +6.1.6.2.2 Non ideal flow reactor models +A three-phase fluidized bed reactor cannot always be described using simple models such as ideal +plug flow, because appreciable back-mixing may occur in the liquid phase (Muroyama and Fan 1985). +This back-mixing is caused by the rising of coalesced gas bubbles, in particular for beds of fine +particles (Muroyama and Fan 1985). Thus, Yu et al. (1999) proposed a tank-in-series model, applying +  equation (13), to describe the flow pattern of an F  BR that considers the reactor to be a combination8   o8f           +CHAPTER 6 – LITERATURE REVIEW +two ideal CSTR reactors. Many other investigations on the flow pattern in an FBR suggest that an +axial dispersed plug flow model can also be used to simulate the hydrodynamics of the process +(Østergaard 1968; El-Temtamy et al. 1979a; Muroyama and Fan 1985; Davidson et al. 1985; Lin +1991; Kim and Kang 1997; Michelsen and Østergaard 1970; El-Temtamy 1979b). +Additionally, many authors studied the effect of gas production on the hydrodynamics for the design +and scale-up of three-phase fluidized bed reactors. El-Temtamy et al. (1979a,b) described the flow of +the gaseous and liquid phases in a three-phase FBR by introducing a radial dispersion coefficient +inside the following axially dispersed plug flow equation: +∂C u ∂C ∂2C ⎛ ∂2C 1 ∂C ⎞ ++ ⋅ = D +Dr⎜⎜ + ⋅ ⎟⎟+ RC (40) ∂t ε ∂t ∂x2 ⎝ ∂r +2 r ∂r ⎠ +where: +ε = fluidized bed porosity; +r = relative radial position [L]; +Dr = radial dispersion coefficient [L2T-1]. +The authors solved equation (33) using boundary equations proposed by Danckwert (1953). +The authors also identified an indirect correlation between the Peclet number based on the particle +diameter and the gas flow rate and a correlation between axial mixing in the liquid phase, the presence +and motion of bubbles and the radial velocity profile (El-Temtamy et al. 1979a; Mulcahy and La +Motta 1978). +Lin (1991) applied an axial dispersion model for the bulk phase considering reactant diffusion and +consumption inside the biofilm and imposing Danckwerts (1953) boundary conditions to solve the +proposed equations. Additionally, the author compared the experimental data obtained by Mulcahy +and La Motta (1978) and Jeris (1977) with the model results and a high value of the Peclet number +was also found that enables a simplification based on plug flow conditions. Thus, neglecting the +dispersion term, the substrate in the bulk phase was modelled using the axial dispersion equation: +C C +∂ ∂ + Cin Cin Ab ⋅kS ⋅H +⎛ C C f ⎞= − − ⋅⎜⎜ − ⎟⎟ (41) ∂t ∂x ε ⋅u ⎝Cin Cin ⎠ +where: +Cf = reactant concentration in the biofilm phase [ML-3]; +Ab = specific surface area of coated particle [L2]; +  H = height of fluidized bed [L].   8   9           +CHAPTER 6 – LITERATURE REVIEW +In this case, the authors imposed an initial boundary condition for the value of the initial reactant +concentration in the bulk phase. + +6.1.6.2.3 Models comparisons +The models proposed by Ritmann (1982) and Schieh et al. (1982) are plug flow and steady-state +models, that are easy to apply but their results not are accurate. Instead more accurate models consider +  also the effect of gas production on hydrodynamic behaviour (Lin et al. 1991; El-Temtamy 1979a,b). +6.1.7 Mathematical modeling of biofilter reactors +6.1.7.1 Process description +Aerobic biofilters (Fig. 36) are rectangular or circular packed beds used for the bio-oxidation of +domestic or industrial wastewater. It is possible to schematize the reactors as a three-phase system +where the liquid phase passes through the bed in contact with both the microbial film and a counter- +current air stream rising by natural convection. Trickling filters have characteristics similar to +biological aerated filters, except they are not submerged. +EFFLUENT +LIQUID +RECIRCULATION +PFR OXYGENETOR +FBR +INFLUENT +   +Figure 36. Schematic representation of up-flow biofilter reactor design. +     +   +   9   0           +CHAPTER 6 – LITERATURE REVIEW +6.1.7.2 Model development +6.1.7.2.1 Ideal flow reactor model +Many models assume ideal plug flow conditions in biofilter; however, non-ideal conditions may occur +with increased mixing and dispersion at a high flow rate. Rittmann (1982), Chang and Rittmann +(1987), Oleszkiewicz (1981), Costa Reis and Sant’Anna (1985) proposed a complete bioreactor model +that includes the biofilm and CSTR flow for the liquid phase. +In particular, Rittmann (1982) stated that the biofilter hydrodynamics are related to the recycle ratio, +in fact the reactor can achieve complete mixing conditions when the recycle ratio exceeds 10. +Although some researchers have found that aerobic biofilters act as plug flow systems due to either +channelling or backmixing (Särner 1978; Gray and Learner 1984; Vandevenne 1986; Muslu 1986; +Meunier and Williamson 1981). In particular, Meunier and Williamson (1981) modelled the reactor +considering a plug flow regime but neglected the back-mixing effect from rising bubbles of biogas. +Baquerizo et al. (2005) proposed a mathematical model for the biofilter based on the mass balance +equations, and considering four phases in the system: gas, liquid, biofilm, and solid. A plug flow +pattern is considered for both the liquid and gas phases, resulting in the proposed equations: +∂Cg ∂C a= −vg ⋅ g − b ⋅Fg−l (42) ∂t ∂x ε +∂Cl v ∂C a a= b bl ⋅ + ⋅Fg−l − Fl−b (43) ∂t ∂x h h +where: +g = subscript referred to the gas phase; +l = subscript referred to the liquid phase; +v = interstitial velocity [LT−1]; +ab = biofilm surface area per unit volume of biofilter bed [L2L−3]; +Fg − l = mass flux from the gas phase to the liquid phase [ML +−2T−1]; +F = mass flux from the liquid phase to the biofilm phase [ML−2 −1l−b T ]; +h = dynamic hold-up coefficient [ad.]. +In addition to the presented equations, the authors proposed a mass balance for the biofilm and the +  solid phase. Jacob et al. (1996) developed a com   plete dynamic model and applied it to an aero9b   1ic           +CHAPTER 6 – LITERATURE REVIEW +biofilter assuming ideal plug flow conditions. The authors accounted for filter clogging and described +a progressive reduction of the liquid space caused by biomass growth and suspended particle +retention. + + 6.1.7.2.2 Non-ideal flow reactor model +Fdz-Polanco et al. (1994) performed a tracer test at a pilot scale plant and obtained different hydraulic +reactor models by fitting experimental data with the theoretical model. These authors achieved a +Standard Relative Deviation (SRD) value below of 20% only applying a CSTR reactor and a dead +zone model. They also performed tracer tests for several design parameters (the length/particle +diameter ratio and the porosity) and operational parameters (liquid and gas superficial velocity). These +tests approached the plug flow for porous bed reactors, low bed porosity, low liquid and/or gas +velocity. However, different authors demonstrated that back-mixing could occur in such reactors +depending on the bed length, size of the packing particles and liquid phase velocity (Martinov et al. +2010; Froment and Bischoff 1990). Martinov et al. (2010) modelled a fibrous fixed bed reactor using +recycle with a tank-in-series model, which is advantageous since it can model the large void fraction +of the fixed bed and it is independent of the boundary conditions. Furthermore to account for a +deviation from ideal flow, they proposed a schematic model with recirculation. +Sanchez et al. (2005) proposed a model based on two-mixed reactors of different sizes and included in +the model the biofilm and gas liquid transfer. The proposed equations that describe the two mixed +reactors of different size are reported below in dimensionless form: +exp( θ ! exp) $ θ ! '− a − ⋅& )E!(θ !) = %1− a (2 a 1 (44) ⋅ − +a V= R2V V (45) R1 + R2 +where: + VR1 = volume of the first reactor [L3]; +VR1 = volume of the first reactor [L3]; +E’ = dimensionless residence time distribution function [ad.]; +θ’ = dimensionless time [ad.]. +     9   2           +CHAPTER 6 – LITERATURE REVIEW + +Also Perez et al. (2005) proposed a model based on the tanks in series model for nitrifying fixed bed +bioreators. This model was used to provide a detailed description of the biomass, ammonium, nitrite +and nitrate concentrations along the reactor vertical axis. This flow model is useful to describe in a +simple way the biofilm thickness gradient along the bed as experimentally observed. +The tanks in series description were complemented with a back-mixing flow-rate to describe the effect +of the aeration flow-rate on the liquid phase mixing. Physically, raising gas bubbles generate a liquid +down-flow, which is taken into account in the mathematical description of the flow model. +The reactor was then divided into three parts: the bottom represented by one stirred tank, the fixed bed +represented by 5 identical stirred tanks in series, and the top represented by one stirred tank. To +complete the hydrodynamic equations, a gas–liquid mass transfer term and a liquid-biofilm transfer +term were added. +Froment and Bischoff (1990) focused on packed bed axial dispersion, using a low Reynolds number +range (between 1 and 10) and the axial dispersion model. They demonstrated that the Peclet number +of non-aerated granular beds varies within the range 1.4-2. Similar studies in a 0.2 m diameter packed +bed bubble column with high porosity packing and a vertical co-current up-flow of gas and liquid +have been reported by Bhatia et al. (2004). Séguret and Racault (1998) applied the residence time +distribution method to define the effect of the mixing pattern on the process performance in a full- +scale nitrifying biofilter. They demonstrated that the floating filter bed itself behaves as a dispersed +plug flow reactor. Additionally, they identified a direct correlation between the dispersion and the +flow rate, and a variation of the dispersion coefficient and the residence time distribution along the +reactor height. They also applied a theoretical nitrifying model that accounts for the observed +hydrodynamic behavior. One limit of the mechanistic models is the large number of variables +requiring experimental confirmation. Thus, empirical models that are simpler to implement and solve +are of interest, such as the model proposed by Mann and Stephenson (1997). +With regard to Trickling filters (TF), many authors studied residence time distribution in TFs (Sinkoff +et al. 1959; Kshirsagar et al. 1972; Tariq 1975; Särner 1978; Gray and Learner 1984; Vandevenne +1986). In most works on the hydrodynamic behavior of TF, the RTD profile is a function of the media +used, the hydraulic loading, and the amount of biomass. TF are modeled in most studies as a series of +perfect mixers with a dead zone (Mezaoui 1979; Nyadziehe 1980; Sant' Anna 1980). While in the +  model proposed by De Clercq et al. (1999) the   influence of the heterogeneous film structure w9  a3s           +CHAPTER 6 – LITERATURE REVIEW +considered, which consisted of a biofilm, a free flowing and a captured liquid film. The authors +modelled the diffusion effect with the tanks in a parallel configuration and the free flowing liquid with +CSTR series configuration linked to the diffusion block (De Clercq et al. 1999). Other model +approaches are also described in the literature, such as the axial dispersed plug flow model proposed +by Séguret and Racault (1998). The authors proposed a bio-diffusion model which considers the TF as +a vertical tube that includes the reactor filling, an immobile phase, and a liquid film. The flow in the +liquid is postulated to be an axially dispersed plug flow, and the governing equation is: +∂C ∂2D C ∂C 1= ⋅ −u ⋅ + ae ⋅ JE (x) (46) ∂t ∂x2 ∂x εβm +where: +ae = specific surface area available for exchange per volume of filter [L2L-3]; +bm = mobile volume fraction; +JE(X) = flux of reactant at the interface between the main flow and the immobile phase [ML-2T-1]. + +To solve this equation, the authors applied Danckwerts boundary conditions for the dispersion of flow +at the flow entrance, and the cessation of dispersion at the output (Séguret et al. 2000). In the +immobile zone it is assumed that the tracer is subject to diffusion. One particular case of equation (46) +is when a slice dz is consider to be perpendicular to the flow direction, in this case the mass balance +becomes: +∂C ∂2 += D Cm ⋅ 2 (47) ∂t ∂x +where: +Dm= molecular diffusion coefficient of reactant inside the biomass in the immobile phase [L2T-1]. +Additionally the following boundary conditions at the liquid/biomass interface are also defined: + C(z = 0) = C(X ) (48) + ⎛ ∂C ⎞⎜ ⎟ = 0 (49) +⎝ ∂z ⎠z=e +where: +e = thickness of biomass [L]. +Muslu (1990, 1984), Muslu and San (1990) conducted a tracer test on inclined plane trickling filters. +The result was used to determine the following expression that correlates the dispersion coefficient for +  conserved tracer substances in flow over porous m   edia and the flow rate: 9   4           +CHAPTER 6 – LITERATURE REVIEW +D φ= q4 / 3 (50) +L +where: +φ = coefficient function of viscosity, molecular diffusion, localization of the flow path [ad.]; +q = flow rate per unit of width [ML-2]; +L = length of axial travel in the reactor [L]. +The authors identified the hydraulic reactor model considering different flow patterns that could occur +inside the reactor. With high hydraulic loadings the flow pattern is a dispersed plug flow, thus the +authors applied the axial dispersion equation. While with lower hydraulic loading rates the authors +assumed a complete mix flow pattern. A transition zone in the flow regime indicates other mixing +conditions. +Iliuta and Larachi (2005) modelled TF reactors using a two-dimensional two-fluid dynamic model. +The complete model describes two-phase flow and the space-time evolution of biological clogging +and physical plugging. It is based on the macroscopic volume-averaged mass and momentum balance +equations, the continuity equation for the solid phase, the species balance equation for the fine +particles and the volume-averaged species balance equations at the reactor level. The model is coupled +with the simultaneous transport and consumption of phenol and oxygen within the biofilm and the +simultaneous diffusion of both phenol and oxygen and the adsorption of phenol within the activated +carbon particles. Using equations that account for the reactor hydrodynamics, the authors applied the +axial dispersion model to describe the species balance in the fluid phase for oxygen and the substrate, +  while plug flow was assumed in the gas phase. +6.1.7.2.3 Models comparisons +Meunier and Williamson (1981), Baquerizo et al. (2005) and Jacob et al. (1996) proposed a plug flow +model neglecting the back-mixing effect. Others models proposed by Fdz-Polanco et al. (1994), +Martinov et al. (2010), Pérez et al. (2005) and Sanchez et al. (2005) included also the back-mixing +conditions with tank in series configurations. Also Séguret and Racault (1998), Froment and Bischoff +(1990), Muslu (1984, 1990), Muslu and San (1990) considered in the model the effect of dispersion +by applying dispersion equation obtaining a more detailed model. Lately, CFD model was proposed +by Iliuta and Larachi (2005). This is the most complete model because it describes a two-phase flow +  and the space-time evolution of physical and biolo  gical phenomena 9   5           +CHAPTER 6 – LITERATURE REVIEW +6.1.8 Model comparisons and validation and calibration +6.1.8.1 Models comparisons +The models presented above for activated sludge reactor, fluidized bed reactor and biofilter reactor +have different advantages and disadvantages. Furthermore there are some models which can be useful +in some situation and not in others. Table 22 lists all the models reported indicating for each one the +advantages and disadvantages and when can be utilize. + + + + + + + + + + + + + + + + + + + + + + + +     9   6           +CHAPTER 6 – LITERATURE REVIEW +Table 22. Models comparisons + +Author Advantages Disadvantages When can be +used +Van der Meer and Heertjes, 1983; Bolle et Introduce the model of CSTR Without calibration and For initial simulation +al., 1986a,b; Costello et al.,1991a,b, Ojha in series model for UASB validation, simple to understand the +and Singh (2002) and Singh (2005). UASB reactor model with a lot of general reactor +assumption behaviour +Wu and Hickey (1997), Singhal (1998) Consider dispersion in the Without calibration and For initial simulation +and Zang et al. (2005). But the best models reactor validation, simple to understand the +are those proposed by Kalyuzhnyi et al., model with a lot of general reactor +(2006), Batstone et al. (2005), Mu et al. assumption behaviour +(2008) and Penã et al. (2006). UASB +Ren et al. (2009). Use the CFD model, describe Without calibration and To study the process +UASB the process with validation in detail and focalize +local phenomena also on local +phenomena in the +reactor +Young and McCarty (1968), Young and Apply the simple model of Do not model the gas For initial simulation +Young (1988). AFBR CSTR in series in AFBR phase in the reactor to understand the +reactor general reactor +behaviour +Escudié et al. (2005), Huang and Jih Consider the presence of Without calibration and For initial simulation +(1997) and Smith (1996). AFBR biofilm validation and to understand the +biofilm growth +Bonnet et al. (1997) Introduce the model of plug Without calibration and For initial simulation +BAF flow. validation, simple to understand the +model with a lot of general reactor +assumption behaviour +Seok and Komisar (2003), Otton et Consider dispersion in the Without calibration and For initial simulation +al.(2000), Buffière et al. (1998a,b), reactor validation, simple to understand the +Schwarz et al.(1996-1997) and Diez and model with a lot of general reactor +Blanco (1995). BAF assumption behaviour +Buffière et al. (1998a,b). Apply the dispersion model Without model For initial simulation +BAF and consider also the gas- calibration and to understand the +phase behaviour validation general reactor +behaviour +Monteith and Stephenson (1981), Apply the simple model of Do not model the gas For initial simulation +Mendoza and Sharratt (1998, 1999), Smith CSTR in series in AFBR phase in the reactor to understand the +et al. (1993) and Keshtkar et al. (2003). reactor general reactor +CSTR behaviour +Vavilin et al. (2001, 2003). CSTR Consider dispersion in the Without calibration and For initial simulation +reactor validation, simple to understand the +   model with a lot of general reactor assumption behaviour +     9   7           +CHAPTER 6 – LITERATURE REVIEW +6.1.8.2 Activated sludge reactor +6.1.8.2.1 Ideal PFR and CSTR in series +Lawrence and McCarty (1970) first solved the proposed differential equations and obtained an +algebraic solution. This solution was approximate because they assumed that the biomass +concentration in the reactor remains nearly constant at least as long as the ratio of the solid retention +time to the hydraulic retention time (SRT/HRT) exceeded 5. With this assumption, they demonstrated +that the difference between PFR and CSTR is not too significant with regard to the evaluation of the +biomass concentration. San (1989) solved the same equations with a finite difference method, +avoiding any assumptions that could become restrictive in the case of wastewater with high solids +concentrations. The author described a numerical method to determine the mean residence time and +the effect of the kinetic coefficients on the mean solids residence times, but did not calibrate and +validate the model with experimental data for the field conditions. +As a first attempt to model a plug flow reactor with a CSTR in series model, Milbury et al. (1965) +defined the effective number of compartments for different detention times. Therefore they compared +the effluent tracer concentration of a rectangular laboratory aeration vessel with the model results. +Another model was developed by Muslu (2000a) and compared to the CSTR model results obtained +with the approximate model developed by Lawrence and McCarty (1970). Experimental data reported +by Lovett et al. (1984) were used to validate the model. The author obtained larger differences +between the real and simulated data when the mean solids residence times were small. In particular for +some industrial wastewater applications, there may be a considerable difference between the results of +the Muslu model and the approximate analytical solution of Lawrence and McCarty that neglects the +existence of a longitudinal biomass concentration gradient. +Among the models cited above only San (1989, 1992) solved the proposed equations using finite +difference technique, the other authors (Lawrence and McCarty 1990; Milbury et al. 1965) proposed +algebraic solutions of the equations introducing some simplifications. +Many authors performed tracer experiments that estimate the hydraulic parameters and characterize +the hydraulic reactor model. These parameters include the real HRT value, the dispersion coefficient +(for a dispersion model), the number of reactors in series (for a tank-in-series model), and back- +mixing flows or dead zone volume. It is possible to obtain these parameters from the RTD curve that +  describes the exit concentration with time. The  AWWA guide (Teefy 1996) gives several advi9c  e8s           +CHAPTER 6 – LITERATURE REVIEW +regarding the achievement of tracer tests in water and wastewater treatment plants particularly with +respect to the selection of suitable tracer. Murphy and Timpany (1967) made a comparison between +reactor model and lab-scale reactor hydrodynamics using experimental points obtained from a tracer +test conducted with a laboratory tank. The authors showed that the two extremes of PFR and CSTR +are inadequate and that the dispersion model fits the experimental data significantly better than equal +size CSTRs in series or the unequal size CSTR in series model. +6.1.8.2.2 Non ideal flow reactor models +San (1994) compared his method with a method using the same boundary conditions (Wehner and +Wilhelm 1956) but with a first order reaction instead of a Monod type reaction. The author +implemented the proposed equation and obtained a graph that can be used to design a plug flow +reactor, in particular it gives a correlation between reaction rate, Peclet number and biological +efficiency. Makinia and Wells (2000b) verified the flow pattern effects of their model on the one- +dimensional unsteady advection-dispersion equation using data from a full-scale plant and introducing +the model parameters developed from previous experiments (Makinia and Wells (2000a) and data +from the literature. With dynamic conditions, the authors compared the predicted concentration of +ammonia nitrogen and dissolved oxygen with the experimental data, and showed that, in all cases, the +errors between the model predictions and the data were lower for the advection-dispersion model than +for the tank-in-series model. In fact, even in the case of five mixed zones of equal size that was found +as the best fitting tank-in-series model, the predicted peak concentrations were lower by +approximately 12–17% and delayed by approximately 30–60 min compared with the actual peaks. +The dispersion model was solved in unsteady conditions with a computational algorithm proposed by +Lee et al. (1999a, 1999b). The results were compared with results obtained by the proposed model- +collocation with a tank-in-series model using experimental data (Lee et al. 1999b). The authors +applied the model to pilot-scale activated sludge process data presented in a previous study (Nogita et +al. 1983), and showed that with simulated dynamics of the reactant at the outlet of the pilot plant, the +proposed algorithm provides a superior prediction than the tank-in-series model. They demonstrated +the feasibility of improving the accuracy of the results by optimizing the Peclet number. +Lee at al. (1999a) also validated the model using different numerical techniques - the orthogonal +collocation method (MOC), the line method (ML), and the internal collocation and four elements +     9   9           +CHAPTER 6 – LITERATURE REVIEW +method (OCFE) and experimental data related to the hydraulics of a Surface Flow System (SSF) +constructed wetland process presented by King and Forster (1990). +For all of these methods there is a good agreement between the experimental data and the model +results, but these validations suggest that the OCFE technique is superior to ML and MOC in terms of +numerical stability and the accuracy of the solution. Furthermore, all simulated RTD curves show a +slower rise time and a faster tail than the experimental data, which indicates a plant-model mismatch. +It is important to note that the experimental tracer curves at various points across the gravel bed of the +SSF describe different peak concentrations and response times, which implies that there is a +channelling phenomenon to a certain extent which is not accounted for in the axial dispersion model. +The authors also calibrated the model with simulations using different values of the Peclet number, +and they demonstrated that with an appropriate value it is possible to predict the process time delay +using either technique (preferably OCFE or ML). +Glover et al. (2006) calibrated and validated a CFD-ASM1 model using experimental data from a +laboratory scale reactor. Le Moullec et al. (2010b) applied a CFD model to an activated sludge reactor +and compared systemic, CFD, and compartmental models for a biological reactor used in wastewater +treatment in a theoretical case, without reference to experiments. In this model, the author considered +a gas-liquid reactor with oxygen transfer and complex kinetics and showed that all three models +follow the same main trends; in particular, the compartmental model provided results very similar to +the CFD model. A discrepancy was observed between the CFD and compartmental models due to the +more realistic introduction of effluent in the CFD model. In the case of a particulate biodegradable +substrate, significant differences are noted between a systemic model and a CFD-based model (Le +Moullec et al. 2010b) this is due to the calculated hydrolysis process, which is affected by the in- +homogeneity of the particulate compounds concentration on a section of the reactor (Le Moullec et al. +2010b). This in-homogeneity is not taken into account in systemic models. + +6.1.8.3 Fluidized Bed Reactors +Shieh et al. (1982) performed a sensitivity analysis of the proposed model parameters using reported +numerical values. These authors studied the effects of media size and biofilm thickness on FBR +performance in terms of the reactant conversion rate and biomass concentration. They found that these +  are two most important parameters that affect t  he FBR performance, but they did not include 1t  h0e0           +CHAPTER 6 – LITERATURE REVIEW +effects of the hydrodynamic parameters on the process. The authors additionally proposed an iterative +procedure that is applied to the model for design purposes. +Yu et al. (1999) performed tracer experiments using a laboratory scale fluidized bed reactor to study +the mixing and flow patterns of tap water. The author introduced a pulse input of a dye solution and +demonstrated that the flow pattern can be described with a model of two CSTRs in series. This result +was obtained by calculating, from the tracer concentration, the residence time distribution curves and +their variance correlated to the number of CSTR reactors. The author also demonstrated that this +approach improved the fit to the experimental data at low gas velocities and was equivalent to the +axially dispersed plug flow model at higher gas velocities. Lin (1991) presented graphs that compared +experimental data from the literature for biological fluidized bed de-nitrification and predicted values +of the model. The graphs only enable qualitative agreement to be observed between experimental data +and model predictions. El-Temtamy et al. (1979b) performed tracer tests on a laboratory scale reactor +and correlated the radial concentration profile to the radius by varying the superficial gas velocity. +The authors obtained different values of the radial dispersion coefficient and found that this parameter +does not change with particle size as the fluid flow rates vary. + +6.1.8.4 Biofilter reactors +Considering the ideal reactor model previously proposed, Jacob et al. (1996) solved the proposed +system of eight differential equations, using two methods to reduce the distributed parameter model to +a differential algebraic equation (DAE) system: the method of lines and orthogonal collocation. The +experiments were performed on synthetic wastewater to simulate the nitrification and denitrification +process. In the nitrification process, the experimental data was compared for nitrites and carbon +concentrations, and a very good agreement was found between the experimental and the model +results. In the denitrification process, the nitrate, nitrite, and carbon concentration were compared to +the experimental data and found to be in good agreement. It should be emphasized that the simulations +were performed without a real estimation of all parameters involved; in fact most of the parameters +were taken from the literature or measured experimentally. Thus, this model lacks a rigorous +parameters estimation procedure. De Clercq et al. (1999) performed a tracer test using a full-scale +reactor and obtained improved fitting of the model performance to the measured lithium effluent +  concentration with a two-tank-in-series configura  tion. This did not include the diffusion effect as th1  e0y1           +CHAPTER 6 – LITERATURE REVIEW +stated that this phenomenon does not influence the residence time distribution. Séguret and Racault +(1998) performed a tracer test in order to obtain an experimental RTD curve and to estimate the +immobile and mobile volume and the first moment of the proposed bio-diffusion model. The mobile +volume from the bio-diffusion model and the first order moment were compared to the free draining +volume and the mean retention time obtained experimentally. The authors determined that the mean +residence time is overestimated compared with the first order of the bio-diffusion model. The reason +may be an inaccurate fit of a decreasing exponential used to extend the RTD towards the infinite. It +should be noted that the authors proposed to implement the hydrodynamic model using a kinetic +biofilm model but did not demonstrate its applicability. To determine the range of validity of their +models, Muslu (1990) performed some experiments using a data collected by Lamb and Owen (1970). +In particular, the predicted and measured reactant removal efficiency, defined using the measured inlet +and outlet COD concentrations, were compared to flow rate values. Good agreement was found +between the experimental data and model results, with a determination coefficient equal to 0.98. +Baquerizo et al. (2005) performed a sensitivity analysis of the model parameters and a model +validation that compared the model results and experimental data referring only to the ammonia +concentration along the reactor height. They only reported graphs to describe the gas concentration +profiles along the biofilter bed for a low and a high ammonia inlet concentration, without giving a +correlation index. Iliuta and Larachi (2005) performed a parameter estimation and model validation +using experimental data, but they did not estimate the dispersion number because the extent of back- +mixing in the liquid phase was quantified by a comprehensive Bodenstein number correlation (Piché +et al. 2002). Additionally, the authors found good correspondence between the model results and the +experimental data reported in the literature (Wisecaver and Fan 1989; Hirata et al. 1986). This +agreement reflects the validity of the model over a wide range of biofilm thicknesses and ascertains +the contribution of biological clogging in the hydrodynamic model. In Table 23 are listed all models +previously described and are compared the calibration and validation procedures adopted for each. + + + + + + +     1   02           +CHAPTER 6 – LITERATURE REVIEW +Table 23. Model Calibration (C) and Validation (V): AS, FBR, BF, AF estimated parameters +Reactor C V Estimated Parameters Authors +- - - Lawrence and McCarty (1980); +- - - San (1989); +X X Kinetic parameters Muslu (2000a); +- - - San (1992); +- - - +AS X X Dispersion + coefficient, kinetic + and stoichiometric Makinia and Wells (2000a,b) + parameters + +X X Peclet number Lee et al. (1999a,b) +X X Kinetic parameters (m, Y) Glover et al. (2006) + - - - Le Moullec et al. (2010a,b) +FBR - - - Shieh et al. (1982) +- - - El-Temtamy et al. (1979a,b) +Kinetic parameters, + X X external mass transfer coefficient, dispersion Lin (1991) +number + - X - Jacob (1996) + +X - Number of reactor in series Fdz-Polanco (1994) +BF/TF X X Kinetic parameters Muslu (1990) +Kinetic and +X X stoichiometric Baquerizo et al. (2005) +parameters +- X Iliuta and Larachi (2005) + + +     +     1   03           +CHAPTER 6 – LITERATURE REVIEW + 6.2 Mathematical modelling of anaerobic plug flow reactor and non-ideal flow reactor +6.2.1 Introduction +Anaerobic biological processes are widely applied for wastewater and organic waste treatment. +Pioneering applications, not yet abandoned, were mainly based on low rate reactors using non- +attached growth (McCarty and Smith; 1986). More recently, high rate anaerobic reactors using +biofilms and bioflocs to increase the mean cell residence time, have been also proposed and +successfully applied (Annachhatre, 1996). The growing interest towards anaerobic treatments can be +explained considering the advantages of these processes, which can be summarized as: i) positive +energy balance due to methane production; ii) no energy spending for aeration; iii) low biomass yield, +leading to reduced sludge production; iv) reduced requirement of nutrients, which allows the +treatment of many different substrates; v) low maintenance costs and little or no odour problems. Of +course the process has also some disadvantages such as the long start-up time, the sensitivity to toxic +compounds, the need to control alkalinity conditions and higher investments costs (Tchobanoglous et +al. 2003; Gavrilescu 2000). To study the sensitivity of anaerobic processes to various operational +conditions and to optimize the design of anaerobic reactors, several performance-prediction models +have been proposed, dealing with kinetic expressions that describe the degradation and the production +of organic and inorganic substrates inside the reactor. In some cases, these models have been coupled +with the hydrodynamic description of the process to take into account the variability existing among +the various configurations that certainly affect the overall performances of the treatment (Levin and +Gealt 1993; Le Moullec et al. 2008). +6.2.2 Mathematical modelling of UASB Reactors +UASB reactors were developed in the late 1970s in the Netherlands by Lettinga et al. (1980) and are +still widely used for wastewater treatment. The process is based on the development of a sludge bed, +localized at the bottom of the reactor, formed by the natural self-immobilization of anaerobic bacteria. +Above that bed a zone of finely suspended particles called sludge blanket is formed. A clear zone over +the sludge blanket constitutes the settling zone. The influent wastewater is distributed at the bottom of +the reactor and flows upward (Fig. 37a). +     1   04           +CHAPTER 6 – LITERATURE REVIEW +   +               +                                                                                                                           +   + a) UASB reactor +                                                                                                                      b) Anaerobic biofilter reactor +     1   05           +CHAPTER 6 – LITERATURE REVIEW +                                                                                                                                         +   c) Anaerobic Fluidized Bed Reactor +Figure 37. Schematic representation of a) UASB reactor, b) Anaerobic Biofilter, c) Anaerobic +Fluidized Bed Reactor + +6.2.2.1 Hydrodynamic based models +Mathematical models of UASB reactors generally distinguish the three over mentioned zones and the +reactor is described by Tank in Series derived models, usually named multi-compartment models +(Van der Meer and Heertjes, 1983; Bolle et al. 1986a,b; Costello et al.1991a,b; Wu and Hickey, 1997; +Narnoli and Indu, 1997). +Both Heertjes et al. (1978, 1982) and Bolle et al. (1986a,b) divided the reactor into three +compartments simulating the hydrodynamic conditions in the sludge bed and in the sludge blanket +using a CSTR model, and the hydrodynamic conditions in the settling zone using a PFR model. +Particularly Heertjes et al. (1978) assumed a by-pass flow between the inlet section and the second +reactor, a dead zone in the first reactor, and a return flow between the second and the first reactor (Fig. +38a), obtaining the following equation set: +V dC11 =Q C +Q ⋅C −Q ⋅C + dt +0 0 2 2 1 1 + (51) +V dC22 =Q1C1 +Qk ⋅C0 −Qdt 2 +⋅C2 −Q ⋅C2 + (52) +with: +     1   06           +CHAPTER 6 – LITERATURE REVIEW +Q =Qk +Q0 (53) +Q1 =Q0 +Q2 (54) +V=V1 +V2 +V3 +Vd (55) +where: +Q = influent flow [L3T-1]; +Q = by-pass flow [L3 -1k T ]; +Q0 = flow entering the sludge bed [L3T-1]; +Q1 = flow entering the sludge blanket [L3T-1]; +Q2 = return flow [L3T-1]; +V1 = ideally mixed region in the sludge bed volume [L3]; +Vd = dead space volume [L3]; +V2 = sludge blanket volume [L3]; +V3 = plug-flow region volume [L3]; +C = substrate concentration in the sludge bed [ML-31 ]; +C2 = substrate concentration in the sludge blanket [ML-3]. + +Bolle et al. (1986 a, b) introduced two main variations to the configuration assumed by the multi- +compartment model proposed by Heertjes et al. (1978). He neglected the return flow between the first +and the second reactor, and added a by-pass between the inlet section and the third reactor (Fig. 38b). +The resulting equation set obtained by Bolle et al. (1986a) is therefore: +V dC11 = (1− SF1 ) ⋅Q ⋅C0 − (1− SF1 ) ⋅Q ⋅C dt 1 (56) +V dC22 = (1− SF1 ) ⋅Q ⋅C1 − (SF1 − SF2 ) ⋅Q ⋅C0 − (1− SF2 ) ⋅Q ⋅C dt 2 (57) +where: +SF1 = fraction of flow by-passing the sludge bed; +SF2 = fraction of flow by-passing the sludge blanket. + +     +     1   07           +CHAPTER 6 – LITERATURE REVIEW + +Vd +Q1 +0 +Q C0 Q0 Q Q0 +0 0 Q2 V3C3 0 +0 V2 C2 +V1C1 +Qk +0 + +a. Block diagram proposed by Heertjes et b. Block diagram proposed by Bolle et al.1986a,b +al. 1978a, b. + +Figure 38. Block diagram proposed by Heertjes et al. (1978 a,b) and Bolle et al. (1986a,b). + +Ojha and Singh (2002) completed the previous models by developing and testing a theory based on +the flow resistance. They found that increasing the flow resistance in the reactor increases the +magnitude of short-circuiting flows in the sludge bed. Successively, assuming the same +schematization proposed by the previous authors, Singh et al. (2006) calculated the by-pass flow and +the dead-zone in steady-state conditions, using the following mass-balance equation: + (58) +where: +Ce = the exit concentration [ML-3]; +re = the effective fraction of flow expressed as re=1-(Qb /Qi); +Qb = the by-pass flow [L3T-1]; +Qi = the influent flow [L3T-1]; +fe = the active space for flow expressed as fe = (1-Vd )/(Vd +Vr). + +Wu and Hickey (1997), instead, modeled the sludge bed and the sludge blanket as a CSTR with a +dead volume, and the settling zone as a PFR with lateral dispersion (Fig. 39a), developing the +following equations: + V dC   =V ⋅C0 (t) −Q ⋅C(t) + (59) +dt   1   08           +EFFLUENT +INFLUENT +CHAPTER 6 – LITERATURE REVIEW +∂C D ∂2C u ∂C += − + ∂t L ∂z 2 L ∂z (60) +where: +V = CSTR working volume [L3]; +C0(t) = influent concentration [ML-3]; +Q = flow entering the working volume [L3T-1]; +z = axial coordinate [L]; +u = flow velocity within the PFR [LT-1]; +L = reactor length [L]. +Assumed initial and boundary conditions were: +C(0,t) = C(t) (61.a) +C(z,0) = C0 (61.b) +To avoid the need to evaluate too many parameters, Singhal et al. (1998) developed a simpler block +diagram to simulate the reactor, composed by two reactors in series, each characterized by an axial +dispersion (D1, D2), assuming that part of the liquid flow by-passes the first zone and enters directly +into the second one (Fig. 39b). The authors applied the following dispersion equation in dimensionless +form to both model's compartments. +2 + ∂G ∂ G 1 ∂G= − (62) +∂θ ∂η 2 Pe ∂η +where: +q = t/t, dimensionless time; +h = z/L, dimensionless axial coordinate; +Pe = Peclet number; +G = C/C0, dimensionless concentration. +     1   09           +CHAPTER 6 – LITERATURE REVIEW +Assumed initial condition for the first reactor was: + C = 0 for h>0 (62) + +For the first zone of the model the equation (62) was solved analytically following the procedure +proposed by Smith (1981). The response of the second zone was evaluated by using the Crank- +Nicholson method and applying the following boundary conditions: +1 ⎛ ∂C ⎞ S +QC +− ⎜ ⎟ + (C) = 1(θ )⎜ ⎟ η>0 η = 0,θ ≥ 0 + Pe ⎝ ∂η ⎠η 0 (S +Q)> (63.a) +⎛ ∂C ⎞ +⎜⎜ ⎟ = 0 η =1,θ ≥ 0 + ⎝ ∂η +⎟ +⎠ (63.b) + +The model proposed by Wu and Hickey (1997) was later reconsidered by Zeng et al. (2005). The +authors added to the previous equations the following expression of the dispersion coefficient, +obtained from a non reactive tracer test: + +D = D +ua +bη0 (64) +where: +a, b and Do = empirical parameters; +u = flow velocity [LT-1].   +Vd + +Q CSTR Dispersed +flow V1 D1 V2D2 +Zone 2 +Zone 1 +Qr + +a) Wu and Hickey (1997) b) Singhal et al. (1998) + +Figure 39. Block diagrams of UASB reactor proposed by Wu and Hickey +(1997), b) Singhal et al. (1998). +   +     1   10           +CHAPTER 6 – LITERATURE REVIEW + + 6.2.2.2 Models coupling hydrodynamic with anaerobic digestion conversions +In the literature there are also several attempts to model these reactors considering both the hydraulic +and biochemical behavior. One attempt was done by Batstone et al. (2005) and Mu et al. (2008), who +introduced reaction terms into dispersion equation using the biochemical model ADM1 proposed by +Anaerobic digestion I.W.A. working group (Batstone et al. 2002). Similarly Kalyuzhnyi et al. (1997, +1998) introduced the following equation to simulate the biochemical process, that was solved under +steady-state conditions, using the Danckwert boundary conditions: +∂C(z, t) ∂ ⎡D(z, t) ∂C(z, t)⎤ ∂= ⎢ ⋅ ⎥ − [u(z, t) ⋅C(z, t)]+ r(z, t) −M (z, t) (65) ∂t ∂z ⎣ ∂z ⎦ ∂z +where: +r(z,t) = reaction term; +M(z,t) = gas transfer coefficient. +Later the authors developed a more complete model combining the granular sludge dynamics, the +solid-liquid-gas interactions, hydrodynamics with the biological conversions and the liquid phase +equilibrium chemistry (Kalyuzhnyi et al., 2006). They introduced the following expression for the +vertical velocity of sludge aggregates: + u(z, t) V= R −WS (66) T ⋅CS +where: +VR = the reactor liquid volume [L3]; +T = the retention time [T]; +CS = the reactor cross section [L]; +WS = the settling velocity for sludge solids [LT-1]. + +They also used the dispersion coefficient expression for sludge aggregates, developed by Narnoli and +Indu (1997): +2 +⎡ ⎛ ⎞⎤ +D(z t ⎛ ⎞, ) − A= A2 ⋅ ⎢q(z, t) ⋅⎜⎜1−exp⎜ +3 +⎜ ⎟⎟ +⎢⎣ ⎝ ⎝ q(z, t) +⎟ ⎥ +⎠⎟⎠⎥⎦ (67) +where: +  A2, A3 = empirical parameters [ad.];   1   11           +CHAPTER 6 – LITERATURE REVIEW +q(z, t) = surface gas production [L3T-1]. +The resulting equation system was solved under unsteady-state conditions. Danckwert boundary +conditions were used only for the soluble substrates while, for the biomass, the authors took into +account the wash-out in the last compartment, assumed to be equal to the upward liquid velocity: +u(0) ⋅ Xi (0, t) = D(0, t) +dXi (0, t) z = 0 + dz (68.a) +u(H ) ⋅ Xi (H , t) = D(H , t) +dXi (H , t) z = H +dz (68.b) +where: +Xi (0, t) = biomass concentration at reactor inlet [ML-3]; +X (H, t) = biomass concentration at reactor outlet [ML-3i ]. + +Batstone et al. (2005) and Penã et al. (2006) used only one advective-diffusive equation to describe +the entire reactor. Particularly the model proposed by Batstone et al. (2005) combines the internal +recycle proposed by Bolle et al. (1986a,b) with the internal bypass proposed by Singhal et al. (1998). +The authors considered the internal flow bidirectional, assuming either a recycle flow from the +beginning of the second half of the reactor length to the influent section, or a by-pass from the influent +section to the second half of the reactor length. Finally, Ren et al. (2009) developed the first 3-D +transient CFD model to elucidate the hydrodynamics of the three-phase (gas-liquid-solid) UASB +reactor. In the CFD simulation, a multiphase control volume, composed of one continuous +(wastewater) and two dispersed (gas bubbles and microbial granules) phases, were analysed with the +Eulerian-model (Dìez et al. 2007). + +6.2.2.3 Models comparisons +The models proposed by Van der Meer and Heertjes, 1983, Bolle et al. 1986a, b, Costello et al. 1991a, +b, Ojha and Singh (2002) and Singh (2005) are CSTR in series models and present a lot of +assumptions but are simple to apply; the results can present a big degree of uncertainty. More +complete models taking into account the dispersion related to reactor configuration are the ones +proposed by Wu and Hickey (1997), Singhal (1998) and Zang et al. (2005). But the best models are +  those proposed by Kalyuzhnyi et al. (2006), Bats   tone et al. (2005), Mu et al. (2008) and Penã et1  a1l.2           +CHAPTER 6 – LITERATURE REVIEW +(2006), who considered biochemical reactions and dispersion flow integrating in dispersion model +also ADM1 model. Finally it is also useful to apply CFD models that are more complex than the +previous models but describe the hydrodynamic phenomena more in detail, considering the local +process that happens in the reactor, one attempt was done by Ren et al. (2009). +6.2.3. Mathematical modelling of Anaerobic Biofilters +ABFs are anaerobic packed-bed reactors, characterized by the formation of a biofilm responsible for +the development of the anaerobic degradation of the influent substrate (Fig. 37 b). The influent flow +can travel along the reactor both in the upflow mode (UAF configuration) or in the downflow mode +(DAF configuration), although the first configuration is most widely applied (Fig. 37 b). The +advantages of ABFs are the operational simplicity, elimination of mixing devices, better capability to +withstand large toxic shock loads and the absence of a secondary clarifier. The major disadvantage are +related to the cost of the packing material and to the possibility of packing clogging caused by the +solids and biomass accumulation in the packing media (Gavrilescu, 2000; Rajeshwari et al., 2000). +To define the hydraulic behavior of ABFs it is important to take into account: i) the nature of the +anaerobic processes occurring within the reactor; ii) the production of biogas and iii) the accumulation +of biological solids. +One of the earliest attempts to model hydraulic behavior of such reactors was done by Young and +McCarty (1968) who proposed one of the first models for ABFs, based on reactors in series. They +developed a model of the process based on the premises of an ideal plug flow condition, making some +adjustments to take into account the effect of solids accumulation, the consequence of mixing due to +gas production and the existence of a diffusion gradient between the bulk liquid and the biological +solids surfaces. Young and Young (1988) proposed a new model as a combination of ideal systems, +composed by: a first CSTR, representing the inlet zone; an ideal plug-flow reactor with a dead zone, +representing the central part of the reactor and a second CSTR representing the outlet zone (Fig. 40a). +The dead-space region was introduced to take into account the physical configuration of the vessel, +the formation of stagnant eddies near the discontinuities such as corners, baffles and contact points of +the packing material, and the formation of stagnant areas adjacent to the surface. +Escudié et al. (2005) modeled the reactor considering two interconnected regions: a completely mixed +one representing the mixed liquid and a dead zone representing the biofilm (Fig. 40b). The resulting +  mass balances were:   1   13           +CHAPTER 6 – LITERATURE REVIEW +V1C1 = (Q1 ⋅Cin +Q2 ⋅C2 )− (Q1 ⋅C1 +Q2 ⋅C1) (69) +V C = (Q ⋅C −Q ⋅C ) (70) 2 2 2 1 2 2 +where: + +V1 = ideal Continuous Stirred Tank Reactor (‘‘CSTR1’’), which represents the easily mixed liquid in +the reactor [L3];V2 = ideal Continuous Stirred Tank Reactor (‘‘CSTR2’’), which represents the biofilm +zone [L3];C2 = the tracer concentration within the biofilm [ML-3];C1 = the tracer concentration within +the CSTR -31 [ML ];Cin = inlet tracer concentration [ML-3];Q1 = inlet liquid flow rate [L3T-1]; Q2 = +liquid flow rate between the two theoretical CSTRs [L3T-1]. +Assuming: +C1(0) +M += +V (71) +C2 (0) = 0 (72) +A different configuration, composed by a CSTR with a dead zone, followed by a plug flow reactor, +and including a by-pass of the first reactor (Fig. 40c) was proposed by Smith et al. (1996). The authors +assumed that the flow through the mixed zone and the plug flow zones was sequential and localized in +correspondence of the biofilter bed, while the dead zone (Vd) was assumed to be parallel to the mixed +zone with a transfer flow between them, characterized by a transfer rate proportional to the difference +in concentration between the two zones. + + + + + + + + + + +     1   14           +CHAPTER 6 – LITERATURE REVIEW + + + Q1 + + V1 V2S1 S2 + + +a. b. + + +c. + +Figure 40. Modelling schemes of anaerobic biofilters proposed by a)Young and Young (1988), b) +Escudié et al. (2005) and c) Smith et al. (1996). + +Finally Huang and Jih (1997) coupled a dispersion model with a deep-biofilm kinetic neglecting the +radial dispersion and the substrate removed by dispersed cells. They obtained the following equation: +∂S ∂S ⎛ ∂ 2S ⎞ +ε + u = D⎜⎜ ⎟∂t ∂Y ∂Y 2 ⎟ +− aJ (73) +⎝ ⎠ +where: +S = the substrate concentration in the bulk liquid [ML-3]; +Y = the spatial distance [L]; +a = the specific biofilm surface area [L]; +ε = the fraction of reactor volume; +  J = the substrate flux at biofilm surface [ML +-2T-1],   assumed equal to: 1   15           +CHAPTER 6 – LITERATURE REVIEW +J ∂S= β +∂t (74) +where: +β = partition coefficient. +Equation (74) was solved considering steady-state conditions and applying the Dirichlet boundary +conditions. The authors additionally manipulated the equation normalizing it with reactor height and +obtaining the following expression: +∂S ∂S 1 ⎛ ∂ 2S ⎞ +θ + = ⎜⎜ ⎟t Y Pe 2 ⎟ ∂ ∂ * ⎝ ∂Y * ⎠ (75) +where: +Y* Y= ; +H +H (ε + β ⋅ε ) +θ = = estimated HRT +u . +6.2.3.2 Models comparisons + +The models proposed by Young and McCarty (1968), Young and Young (1988) are CSTR in series +models old, simple to apply and the results can present a big degree of uncertainty. More complete +models taking into account the dispersion related to reactor configuration are the ones proposed by +Escudié et al. (2005), Huang and Jih (1997) and Smith (1996), who introduced a more complete model +considering also the effect of biofilm growth. +6.2.4 Mathematical modeling of Anaerobic Biological Fluidized Bed Reactors +An AFBR is a vertical bed of inert particles (sand, pumice, activated coal) that serve as carrier +material for the biofilm development. The liquid to be treated is pumped through the bed at a +sufficient velocity to cause fluidization (Fig. 37c). In the fluidized state the carrier material provide a +large specific surface for attached biomass growth. This feature permits to attain a long solids +residence time for the development of the biological reactions and a low concentration of suspended +solids. Mathematical reactor models for AFBRs have been developed as CSTR (Worden and +Donaldson 1987) or PFR (Bonnet et al. 1997). Models for AFBRs generally consist of three pa1r1ts6                 +CHAPTER 6 – LITERATURE REVIEW +(Saravanan and Sreekrishnan, 2006): i) a bed fluidization model which describes the effect and the +feature of inert particles; ii) a biofilm model which describes the rate of substrate conversion per +individual granule and iii) a reactor flow model, which links the biofilm and the bed fluidization +models to yield the substrate concentration as a function of the axial position within the AFBR. +Many investigations suggested also that an axial dispersed plug flow model can be successfully used +to simulate the hydrodynamic process is occurring in AFBRs (Seok and Komisar 2003; Otton et al. +2000; Buffière et al. 1998 a, b; Schwarz et al. 1996-1997; Diez and Blanco 1995). +Bonnet et al. (1997) assumed that no dispersion occurs in AFBR reactors. The authors extended the +PFR model considering un-steady state conditions and taking into account many components involved +in the process such as: organic matter, VFA, methane, carbon dioxide, acidogenic and methanogenic +bacteria. The dynamic model was developed considering the liquid and solid phase separately to +compute the mass balance for all the process components and the momentum equation to link the +solid and the liquid velocities. The authors used the model to study the effect of different parameters, +including hydraulic and biological variables. +Buffière et al. (1998a, b) stated that the liquid mixing is well represented by an axially dispersed PFR +model. Studying the effect of gas production on the hydrodynamic behavior of an AFBR, the authors +demonstrated that this production is able to modify the axial mixing degree, which is responsible for +the establishment of a concentration gradient in the reactor. In contrast Diez and Blanco (1995) stated +that it is possible to study the AFBR as a solid-liquid fluidized bed neglecting the effect of biogas on +the hydrodynamic behavior. The authors also described the important role of the biofilm growth on +the hydrodynamic behavior showing that the biofilm produces significant effects on the relationship +between the up-flow velocity and the bed expansion. +Turan and Ozturk (1996) studied the effect of the anaerobic biomass concentration on the hydraulic +retention time and the dispersion coefficient. The authors applied the axial dispersion equation and +defined the values of the Peclet number using the equation proposed by Van der Laan et al. (1957): +σ 2 (θ ) = 2Pe−1 − 2Pe−2[1− exp(−Pe)] (76) +where: +σ2 (θ) = the variance of the theoretical response curve for closed reactor. +Similarly, Seok and Komisar (2003) developed an axial-dispersion model to simulate the behaviour of +AFBRs, neglecting the effect of the gas formation on the hydrodynamic behaviour. They applied their +  model to quasi-steady state conditions, consideri  ng no external mass transfer resistance due to go1  o1d7           +CHAPTER 6 – LITERATURE REVIEW +local mixing and small external boundary layers (Buffière et al. 1998c; Schwarz et al. 1996), +obtaining the following mass balance equation: +∂Ci (z, t) u ∂C (z, t) ∂ +2C (z, t) += − i +D i 2 +Πi (z, t)+M C (z, t)∂t ε ∂z ∂z w,i i (77) +∂C j (z, t) u ∂C (z, t) ∂ +2C (z, t) += − j +D j 2 +Π j (z, t)+ rw, j (z, t)+Tj (z, t) ∂t ε ∂z ∂z (78) +where: +Ci = concentration of the suspended microbial species i in the bulk liquid [ML-3]; +Cj = concentration of substrate j in the bulk liquid [ML-3]; +u = superficial liquid velocity [LT-1]; +ε = bed porosity; +D = axial dispersion coefficient [L2T-1]; +Π j = exchange rate of microbial species i between bulk liquid and bio-particle [ML-3T-1]; +Mw,i = net growth rate of microbial species i in the bulk liquid [T-1]; +Πj = transport rate of substrate j from the bulk liquid into the biofilm [ML-3T-1]; +rw,j = net formation rate of substrate j in the bulk liquid [ML-3T-1]. + +The authors rearranged equations (77-78) introducing moving boundaries conditions and a system of +normalized time-dependent spatial coordinates to simulate the bed expansion, the segregation along +the reactor height and the microbial population distribution both along the reactor height and inside the +biofilm. They paid particular attention to the bio-particle segregation phenomena associated with the +biofilm exchange processes observed in the experimental study, but they partly neglected the +theoretical interpretation of the hydrodynamics. + +6.2.4.1 Models comparisons +The model proposed by Bonnet et al. (1997) is plug-flow model, simple to apply but the results can +present a big degree of uncertainty. More complete models taking into account the dispersion related +to reactor configuration are the ones proposed by Seok and Komisar (2003), Otton et al. (2000), +Buffière et al. (1998 a, b), Schwarz et al. (1996-1997) and Diez and Blanco (1995). More complete +models are the ones where also the gas production is taken into account, such as the models proposed +  by Buffière et al. (1998a, b).   1   18           +CHAPTER 6 – LITERATURE REVIEW +6.2.5. Mathematical modeling of wet and dry digesters treating bio-solids +The term digester is usually referred as anaerobic reactors used for the treatment of OFMSW or +sewage sludge. The process is termed low-solids, or wet, whenever the TS in the feed below 10%, and +high-solids, or dry, whenever the TS is higher than 20%. Wet processes take place in closed reactors +equipped with mixing systems aimed at minimizing the in-homogeneities in the treated fluid. +Nonetheless RTD studies carried out on full-scale digesters have shown that actively mixed volumes +are generally as low as 23% of the total volume Monteith and Stephenson (1981), and therefore, +together with traditional models assuming CSTR conditions, different approaches able to take into +account the effect of non-ideal mixing conditions have also been proposed. Dry processes, instead, +take place in different reactors working in batch or continuous conditions. They have been rarely +modelled in terms of hydrodynamic conditions. One attempt was done by Zaher and Chen (2006) who +built mathematical models for industrial scale plug flow reactors (Dranco, Kompogas and Valorga +designs). The authors used both ADM1 and Aquasim® software (Reichert, 1998) as a simulation +platform. All different designs were modelled imposing CSTR in series configuration and introducing +bifurcations to take into account recycling effects. One of the earliest attempts to model non-ideal +mixing conditions of wet digesters was done by Smith et al. (1993). The authors proposed the same +approach used to model the ABFs, considering three zones: a small initial mixed zone, a large main +mixed zone and a dead zone. A dispersion coefficient was also used to describe the cross boundary +movement of the substrate from the mixed zones into the dead zone. Mendoza and Sharratt (1999) +proposed a compartment model with a confined-gas mixing (Fig. 41). The authors assumed that the +circulation around the uptake tube can be represented by an ideally mixed compartment. Moreover +they assumed that the fluid circulation, down the tank and back to the draft tube inlet, can be +represented by a number of equally sized tanks-in-series (Fig. 41). The mass balances resulted in the +following set of linear first-order ordinary differential equations: +dCm ⎛C1,1 −Cm ⎞ Cb −C= ⎜ ⎟+ m +dt ⎜⎝ αt ⎟r ⎠ αtc (79) +dC1,1 N (C0 −C1,1) N (Cm −C= + 1,1 +) +dt (1−α)tr 2(1−α)tc (80) +dC1,3 N(C= 1,1 +−C1,2 ) (81) +dt 2(1−α)tc +     1   19           +CHAPTER 6 – LITERATURE REVIEW + dCb N(C −C ) N(C −C )= 1,3 b + 2,3 b (82) +dt 2(1−α)tr 2(1−α)tc +where: +C = non-reactive substrate concentration [ML3]; +m = index of components inside mixed volume Vm; +b = index of components inside mixed volume Vb; +1, 2, 3 = index of components inside mixed volumes V1, V2, V3 respectively; +tr = the mean retention time in the vessel [T]; +tc = the circulation time [T]; +N = the number of reactors in series; +  α = the ratio of ideally mixed volume to the total liquid volume. +       +Figure 41. Flow reactor scheme of anaerobic digester proposed by Mendoza and Sharratt (1999), +where m = index of components inside mixed volume Vm , n = the number of reactors in series, Q = +flow-rate. + +Another simple two region model was proposed by Mendoza and Sharratt (1998) (Fig.42). This model +assumes that the whole volume can be divided into two sections, called, respectively, flow-through +region and retention region. Both regions are assumed to be perfectly mixed but the transfer of +material between them is limited, as the retention region behaves like a stagnant zone. Different levels +of mixing are accomplished by adjusting the relative volume of the flow-through region and the +e   xchange rate between regions expressed as the   turnover time of material in the vessel. The m1a   s2s0           +CHAPTER 6 – LITERATURE REVIEW +balance for a generic component j (Fig. 42) yields to a set of ordinary differential equations which can +be summarized: + dC1, j C0, j −C1, j C= + 2, j −C1, j ± R(C ) (83) +dt ατ αθ 1, j +dC2, j C2, j −C= 2, j ± R(C ) (84) +dt (1−α)θ 1, j +where: +j = index of different components involved in mass balance: degradable portion of viable activated +sludge microorganism, particulate solids requiring hydrolysis, soluble substrates for acid formers, +degradable portion of acidogenic biomass, VFA for methanogens, methanogenic biomass, methane; +t = V/Qexch, is the turnover time [T]; +Qexch = flow exchange between zones [L3T-1]; +α = ratio of the volume in flow-through region to the total reactor volume [ad.]; +(1-α) = relative volume of the retention region [ad.]. + +In the set of the presented equations, equation (83) with odd numbers, applies to the flow-through +zone whereas equation (84), with even numbers, applies to the retention zone. + +Figure 42. Reactor flow model of anaerobic digesters proposed by Mendoza and Sharratt (1998), +where the subscript: 1= flow-through region; 2 = retention region; exch = exchange between zones; α += ratio of the volume in flow-through region to the total reactor volume; S1, S2 = soluble substrate +COD concentration; P1, P2 = degradable particulate COD concentration; X1, X2 = biomass +concentration. +Later, Keshtkar et al. (2003) proposed the same mathematical model as Mendoza and Sharratt (1998) +  combining the two-region mixing model with a pr  oper structured kinetic model. 1   21           +CHAPTER 6 – LITERATURE REVIEW +Vavilin et al. (2001, 2003) introduced a system of parabolic partial differential equations in a 2D +reactor imposing cylindrical symmetry. The proposed system describes the VFA and methanogenic +biomass concentration profiles along the rector height at different times. More in detail, the authors +tried to simulate anaerobic reactor which treat solid waste by applying distributed model that includes +diffusion and advection of VFA and methanogenic biomass. +Vesvikar and Al-Dahhan (2005) carried out 3-D steady-state Computational Fluid Dynamics (CFD) +simulations of anaerobic digesters to visualize the flow patterns, obtaining the hydrodynamic +parameters of the reactors. Another attempt to develop a mathematical model with CFD simulations +was done by Wu and Chen (2008) who conducted a numerical simulation of the flow field to +qualitatively and quantitatively characterize the mixing and dead zones. The CFD model developed +was based on continuity and momentum equations and on the standard semi-empirical turbulence +model proposed by Launder and Spalding (1974). +Terashima et al. (2009) proposed a homogeneous single-phase, laminar flow CFD model and selected +a momentum equation for simulating the flow patterns in the digester. The authors introduced the +following Uniformity Index (UI), using as statistical parameter Relative Mean Deviation (RMD), that +characterizes the mixing inside the anaerobic reactor: +m +V =∑Vi + i=1 (85) +m +∑Ci ⋅Vi +C = i=1 + V (86) +m +∑[Ci −C ' ⋅Vi ] +UI = i=1 (87) +V ⋅C +where: +V = the volume of digester [L3]; +Vi = the partial volume for numerical calculation [L3]; +Ci = the local tracer substrate concentration [ML-3]; +C’ = the average tracer concentration in the digester [ML-3]. + +     1   22           +CHAPTER 6 – LITERATURE REVIEW +6.2.5.1 Models comparisons +The model proposed by Monteith and Stephenson (1981), Mendoza and Sharratt (1998, 1999), Smith +et al. (1993) and Keshtkar et al. (2003) are CSTR in series models, simple to apply but the results can +present a big degree of uncertainty. More complete models taking into account the dispersion related +to reactor configuration are the ones proposed by Vavilin et al. (2001, 2003). Finally it is also useful +to apply CFD models that are more complex than the previous models but describe the hydrodynamic +phenomena more in detail, considering the local process that happens in the reactor, these attempts +were done by Terashima et al. (2009), Wu and Chen (2008) and Vesvikar and Al-Dahhan (2005). +6.2.6. Model comparisons and validation and calibration +6.2.6.1 Models comparisons +The models presented above for UASB, fluidized bed reactor, biofilter reactor and anaerobic digester +treating bio-solids have different advantages and disadvantages. Furthermore there are some models +which can be useful in some situation and not in others. + +6.2.6.2 UASB reactor model validation and calibration +Tracer experiments (performed with non reactive substrate) were carried out to validate the multi- +compartment models proposed for UASB reactors (Ojha and Singh, 2002; Bolle et al. 1986a,b; Wu +and Hickey, 1997). Some of them were used to calibrate the model’s parameters. Ojha and Singh +(2002) estimated each of the hydraulic parameters of the models proposed by Bolle et al. (1986a,b) +and Wu and Hickey (1997), obtaining always good values of the determination coefficient, defined as: +n +∑(xi − x)2 +R2 = i=1 +n . +Batstone et al. (2005) compared the multi-compartment models with the axial-dispersion model and +obtained the best fitting between the experimental data of tracer tests operated at laboratory scale and +the model's results in case of a multi-compartment model with eight tanks. The authors also, used lab- +scale experimental data to calibrate their model, estimating the dispersion number as well as 1th2e3                 +CHAPTER 6 – LITERATURE REVIEW +governing biochemical kinetic parameters such as the maximum uptake rate and the half-saturation +concentration. +The CSTR model proposed by Singh et al. (2006) was tested at different temperatures, fixing the HRT += 10 hours. Data fitting resulted to be satisfying for temperature values higher than 22°C, with a +determination coefficient varying between 0.98 and 0.94, supporting the assumption that a complete +mix flow pattern exists inside the reactor at elevated temperatures. At lower temperatures, instead, the +model was proven to be inadequate to describe the data sets, probably because of the reduced biogas +production. +Because of the important role of biogas production on the reactor hydrodynamic behavior Wu and +Hickey (1997) carried out a calibration of their model at bench scale, varying the gas production rate. +Lately Singhal et al. (1998) demonstrated that a simple two-compartment axial-dispersion model was +adequate to explain the fluid flow characteristics without sacrifying the accuracy of the predictions. +They found a good fitting between the model predictions and the response of an UASB reactor to an +impulsive input of a non-reactive tracer. Zeng et al. (2005) developed a parameter estimation +procedure to yield acceptable agreement between measured and calculated tracer trajectories and +obtained a correlation between the dispersion number and the up-flow velocity for different reactor +heights. Wu and Hickey (1997) observed the responses of an UASB reactor to an influent step +increase, predicting the working volume, the dead volume and the plug-flow reactor volume which +resulted in a close agreement with the total reactor volume. The authors performed also a sensitivity +analysis on the major factors influencing the reactor performances and found that the distribution of +the tracer within the reactor was largely dependent on diffusion processes. Kalyuzhnyi et al. +(1997,1998) made a comparison between the experimental data of Alphenaar et al. (1993) and the +model predictions, obtaining a determination coefficient >0.99. The authors demonstrated that the +dispersed plug-flow model was able to describe adequately a sufficiently big pool of experimental +data but revealed also the same deficiencies in its conceptual structure. In particular they showed that +the model overestimates the effluent substrate concentration and the amount of volatile suspended +solids in the reactor. Lately Kalyuzhnyi et al. (2006) compared model's predictions and experimental +data recorded by Yan et al. (1989, 1993). Although they did not report the obtained values of the +determination coefficient or any other statistical index, it is possible from represented the diagrams to +appreciate a close trend between the experimental data and the simulated ones, especially in terms of +COD reduction. +     1   24           +CHAPTER 6 – LITERATURE REVIEW +Mu et al. (2008) used the ADM1 as a basis for the development of a comprehensive distributed +parameter model, named ADM1d, that used a hyperbolic tangent function to describe the biomass +distribution within a one compartment model. The authors made a comparison of ADM1 and ADMld +outputs and showed that ADMld was better suited for modeling anaerobic reactors with limited +mixing and high organic load, such as UASB reactors. The model was also validated by Tartakovsky +et al. (2008), using the experimental results obtained at laboratory scale. They found that ADM1d +gives a good description of biogas flow rates, methane concentration, COD effluent concentrations +and VFA under different organic loads and recirculation rates. Additionally the authors demonstrated +that the model was able to simulate COD and VFA gradients along the reactor height. Batstone et al. +(2005) performed also tracer tests at full scale and demonstrated that the best fitting of experimental +tracer tests was achieved with the two-CSTR model. Penã et al. (2006) and Penã (2002)  demonstrated +that the ideal flow pattern occurs only when the operational conditions are close to the design +scenario, with a particular reference to the HRT design value. They showed that when the reactor is +under-loaded, there is a hydrodynamically dispersed flow pattern with the coexistence of a well-mixed +fraction, stagnant zones and short-circuiting flows. The authors obtained a correlation between the +dispersion number, the effluent concentrations of COD and the effluent concentration of total +suspended solids revealing that the optimal hydrodynamic condition occurs somewhere in between the +two ideal flow extremes (i.e., plug flow and complete mixing). Ren et al. (2009) performed a 3-D +unsteady CFD model to visualize the phase holdup and obtained their flow patterns in a UASB +reactor. The simulation results further confirmed the discontinuity in the mixing behavior throughout +the UASB reactor and the key role of the dispersion coefficient, that decreases along the axis of the +reactor. In order to better describe the hydrodynamic behavior of the reactor they successfully +introduced the Increasing-sized CSTRs (ISC) model and made a comparison with a CSTR in series +model demonstrating that the results of the first one match the measured non-reactive substrate +trajectories better than the results of the second one. + +6.2.6.3 Anaerobic Biofilters model validation and calibration +Young and Young (1988) performed tracer experiments in order to define the dead space volume and +the mixing ratio as a function of Reynolds number for the model proposed to simulate ABFs hydraulic +behavior. The authors demonstrated that the plug flow and the dead space increase with the specific +     1   25           +CHAPTER 6 – LITERATURE REVIEW +surface area of the media. Although the authors recognized the interference between the hydrodynamic +and the biological process they did not presented a complete model to simulate both. +Escudié et al. (2005) validated the proposed model and estimated the following key parameters from a +tracer curve analysis: the volume of the first theoretical CSTR, the volume of the dead zone and the +value of the exchange flow between the two reactors. The values were obtained by minimizing the +difference between the experimental data and the model results. +Smith et al. (1993) carried out hydrodynamic studies to define scale-up strategies, obtaining a +correlation between laboratory scale reactor tracer tests and the volume of plug flow and mixed zone +of full-scale reactors. Varying the impeller power, the authors defined with tracer tests and +computational methods, the values of the dispersion coefficients, the volumes of the dead zone, the +initial mixed zone and the large main zone. The authors also investigated through tracer studies the +effect of liquid up-flow velocity and biogas production on the degree of rector mixing. Thus they +obtained different values of hydrodynamic parameters with different operating conditions and media +types inside the reactor. +Tay et al. (1996) performed tracer tests to define the hydraulic characteristics of ABFs. The study +revealed that the behavior of ABF reactors reflects more closely a plug-flow system with a certain +degree of dispersion: this is clearly shown by the obtained values of the dispersion number, ranging +from 0.0022 to 0.0045 for an HRT varying from 24 h to 6 h. Additionally the study demonstrated that +the hydrodynamics and the extent of mixing can regulate the mass transfer and can have an important +influence on the degree of contacts between the substrate and the bacteria, therefore affecting the +whole ABF efficiency. In a second study, Tay and Show (1998) performed tracer tests considering +dirty-bed and clean-bed conditions. They observed with clean bed conditions hydraulic flow patterns +closer to a plug-flow system with a relatively large amount of dispersion, while in the case of dirty- +bed conditions the flow pattern was found to be more similar to completely mixed flow conditions +with high value of the dead-space (from 43-51%). +Huang and Jih (1997) made tracer experiments with a laboratory scale reactor to study the diffusion +inside the reactor and thus defining the value of the Peclet number. Estimated values ranged from 0.01 +to 1.5, reflecting that back-mixing occurs in biofilters due to the rising bubbles of biogas. Additionally +the authors compared the experimental data and simulation results with reference to COD removal +efficiency, obtaining a standard deviation of +/- 5%. The calculated COD removal efficiency using the +CSTR model was found to be close to or lower than that using the axial dispersion model. They a1ls2o6                 +CHAPTER 6 – LITERATURE REVIEW +studied the VFA profile along the reactor and claimed that the flow pattern in the liquid phase was +completely mixed. +6.2.6.4 Anaerobic Fluidized Bed Reactor model validation and calibration +Buffière et al. (1996) performed tracer experiments on an AFBR at very low gas flow rates and +observed that the axially dispersed plug-flow model was not accurate enough to simulate the +experimental data. In fact the tracer response curves were characterized by secondary peaks, +suggesting the presence of an internal recycle current. The tank in series model led to a better fitting +of the experimental data at low gas velocities. However, the model performance was equivalent to the +performance of the axially dispersed plug flow model at higher gas velocities. The authors Buffière et +al. (1998a,b) correlated the degree of mixing in the bioreactor to the Peclet number, showing that the +mixing conditions of the liquid phase have a slight influence on the reactor performances. +Buffière et al. (1998a,b) stated that for modeling purpose of AFBRs it is necessary to know the +variations of the Peclet number and of the axial dispersion coefficient. The authors tested several +correlations to fit the experimental determination of the dispersion number, and found that the most +appropriate one was the expression proposed by Muroyama and Fan (1985), which corresponds to the +expression of a modified Peclet number, calculated with the column diameter as space length +parameter: +DcU1 =1.01U 0.7381 U +−0.167D−0.583 +ε ⋅ z g c (88) +where: +U1 = liquid velocities [LT-1]; +Ug = gas velocities [LT-1]; +Dc = column diameter [L2]; +z = column length [L]. + +Turan and Ozturk (1996) obtained a correlation between the biological growth concentration and the +ratio between Peclet and Reynolds numbers with a determination coefficient equal to 0.569. Assuming +clean media, they also obtained a correlation between the HRT, Peclet and Reynolds numbers ratio: +Pe 0.312t = 26.6⎛ ⎞⎜ ⎟ r 2 = 0.54 + ⎝Re ⎠ (89) +     1   27           +CHAPTER 6 – LITERATURE REVIEW + +Otton et al. (2000) performed tracer tests using a simple tubular reactor to calibrate and validate the +proposed hydrodynamic model. They quantified the recycling effect as a plug flow with a variable +delay and the fluidization effect as an axial dispersion phenomenon. The authors only qualitatively +discussed the validation; the presented graphs indicate a satisfactory agreement between all +experimental data and the model simulation, but the model could not describe small variations of the +operating parameters that occurred inside the reactor. + +6.2.6.5 Wet and dry digesters model validation and calibration +Mendoza and Sharratt (1999) carried out tracer experiments at different flow rates to define the +number of tanks-in series able to better simulate non-ideal flow in wet digesters. The authors obtained +experimental results making tracer tests and demonstrated a good fitting between compartment model +results and experimental tests. In the previous work, Mendoza and Sharratt (1998) did not performed +any model calibration and validation but made an evaluation of the impact of the mixing parameters +and showed that the relative volume of the flow-through region has a more significant effect than the +turnover time (θ). The authors demonstrated that the degree of the liquid mixing affects the residence +time distribution and the distribution of the components inside the reactor, influencing the kinetic rates +of the anaerobic process. +Keshtkar et al. (2003) compared preliminary simulations with sequencing batch experimental runs, +measuring methane yield at various organic loading rates for an HRT = 3 days, to determine the most +appropriate set of mixing model parameters. +In the context of CFD models, Wu and Chen (2008) operated model's validation by comparing the +predicted velocities with the experimental data proposed by Pinho and Whitelaw (1990). Finally, +Terashima et al. (2009) made a comparison between experimental and CFD tracer response curve, +finding a reasonably good fitting and analyzed the progress of mixing in the digester by defining a +new parameter of uniformity index (UI). The developed model could be a usefull tool to define the +required time for complete mixing in a full-scale digester at different solid concentrations and +different mixing rate. Also Vesvikar and Al-Dahhan (2005) carried out 3D steady-state CFD +simulations considering different digester configurations. The authors performed CFD simulation in +  terms of overall flow pattern, location of circu  lation cells and stagnant regions, trends of liq1u   i2d8           +CHAPTER 6 – LITERATURE REVIEW +velocity profiles, and volume of dead zones. The results showed good qualitative comparison with the +experimental data in terms of flow pattern, location of dead zones and trends in velocity profile. +6.2.7. Conclusion +Development of high-rate reactors has made anaerobic treatment an attractive option to treat +wastewaters and bio-solids. In this chapter, mathematical models to simulate plug flow and dispersed +plug flow of four specific anaerobic bioreactor configurations, i.e. Upflow Anaerobic Sludge Blanket +Reactors, Anaerobic Fluidized Bed Reactors, Anaerobic Biofilters, wet and dry Digesters are +reviewed. This review details the effect of hydrodynamics/flow pattern on the reactor performance. +Most models are based on CSTR in series and axial dispersion equations to simulate the +hydrodynamics of plug flow reactors. They mainly differ by the numerical techniques and the +boundary conditions used to solve the mathematical equations. Model calibration is often aimed at +assessing the key hydrodynamic parameters, i.e. the dispersion number or the Peclet number, by +operating tracer test. When the model includes both a hydrodynamic module of the reactor and a +biochemical module to simulate the biochemical reactions, model calibration is also aimed at +assessing the kinetic constants. The research also describes the attempts to validate the proposed +models, illustrating the models capability to fit the experimental data. In all reported models +reasonably good fitting was found between model results and experimental data. +Most of the models described in this chapter are useful tools for operational optimization of waste and +wastewater treatment plants but there are still only few attempts to apply the proposed models for +optimum design and scale-up of these bioreactors. This indicates that further research efforts should +be focused on such design models to provide a mathematical tool for bioreactor sizing purposes + + + + +     1   29           +CHAPTER 7– DISCUSSION AND CONCLUSIONS + + + + + + + + +CHAPTER 7 +Discussion and Conclusions + +     + +     +     +   +     +     +     1   30           +CHAPTER 7– DISCUSSION AND CONCLUSIONS +7.1 Discussion and Conclusions + +In the present research, the effect of TS content on dry and wet AD of different complex organic +substrates was studied. The results indicate that water plays in both conditions an essential role on the +specific methane production rate and VS degradation. In terms of final methane production yield, a +different behaviour between wet and dry AD conditions was found. In particular in wet AD of carrot +waste the same value of the final methane production yield, i.e. 450 mL/gVS with a standard deviation +of 14.23 was found. This is not in agreement with the results obtained in both dry and semidry +conditions with both rice straw and food waste. In these cases a higher final methane production yield +was found with lower TS values. This last finding is in agreement with previous tests performed by +Abbassi-Guendouz et al. (2012), Fernández et al. (2008) and Dong et al. (2010). +It is worth mentioning the existence of a linear relationship obtained in the case of carrot waste and +food waste between TS content and initial methane production rate (Fig. 43). Such relationship was +also observed by Lay et al. (1997b) on AD of selected dry organic waste (e.g. sludge cake, meat, +carrot, rice, potato and cabbage), Le Hyaric et al. (2012) on AD of cellulose, Abbassi-Guendouz et al. +(2012) on AD of cardboard, Mora-Naranjo et al. (2004) for waste samples excavated from landfill and +Pommier et al. (2007) for paper waste. The presented results confirm that the TS content, also in wet +AD, has a strong effect on the kinetic rates. At lower TS, due to the increasing water content and +better transport and mass transfer conditions, it seems to be plausible that the microorganisms are +better sustained with soluble substrates (Mora-Naranjo et al. 2004). This was not confirmed by the +tests carried out on rice straw (Fig. 43). This can be due to the different substrate composition and to +the complex nature of lignocellulosic compounds and difficult bio-availability of cellulose (Sambusiti, +2013). Further tests have to be done to explain this behaviour in detail. In particular a larger range of +TS have to be investigated to understand in detail the correlation between TS content and initial +methane production rate. +     1   31           +CHAPTER 7– DISCUSSION AND CONCLUSIONS + +Figure 43. Linear correlation between initial methane production rate and TS for anaerobic digestion +of carrot waste, food waste and rice straw. + +Inhibition tests were carried out to investigate the specific inhibition processes that take place with +complex organic compounds. A different behaviour in terms of VFAs concentration was found. In wet +AD of carrot waste no VFAs accumulation was observed, and all the concentrations were lower than +the inhibition threshold values, while in dry and semidry digestion acid accumulation was found. This +means that inhibition occurs with lack of water and this inhibition is the cause of the lower final +methane production yield with higher TS contents. However, in the specific case of rice straw, it was +noticed a similar value of the final specific methane production yield in the case of dry and semi–dry +conditions but a significant difference in terms of VFAs concentrations between these two different +tests. This might be due to another inhibition mechanism that occurs beyond a threshold value of TS +content, that can explain the similar value of final methane production at different TS contents. Thus, +the soluble phenols was analysed to understand better the process inhibition with higher TS content. +An accumulation of free phenolic compounds in the liquid bulk of the digesting mixture was found +and can explain the inhibition problems observed over TS content of 15%. This can be related to the +effect of the hydrolysis of lignocellulosic material that is composing the rice straw. Thus, there is a +transfer of phenolic matter from the solid matrix of the digestate to the liquid matrix. In reactors with +TS content of 23.4 %, due the lack of water, at parity of phenolics release, the hydrolysis brings to +higher concentrations that are probably above the methanation inhibition limit. This could explain the +specific methane production kinetics as well as the VFA accumulation due to the inhibition of the +  methanogenesis step.   1   32           +CHAPTER 7– DISCUSSION AND CONCLUSIONS +Further studies were also done to compare the process performances also in terms of VS and COD +degradation. For both substrates, rice straw and food waste, the better performances were observed at a +lower TS content. This finding is in agreement with the measured final methane production yield. +It has to be stressed that the higher TS content in the batch reactor without mixing implies +heterogeneous conditions inside the reactor and possible accumulations of inhibitory compounds +inside specific reactor zones are likely to occur. In full-scale reactor the accumulation of inhibitory +compound in a specific reactor zone could imply operating problems and reactor acidification. Thus it +is important for each specific reactor configuration to monitor the process and identify specific +conditions that could determine such inhibition problems.   +In particular, further studies have to be done to individuate the highest TS content that can be accepted +in an anaerobic reactor over that acidification phenomena occur, i.e. the maximum TS value before a +complete process inhibition. On this topic, only one work has been already done by Abbassi-Guendoz +et al. (2012), who found a threshold concentration of 30% TS that determine an inhibitory effect in +high solids anaerobic digestion. This threshold could correspond to an inhibition of anaerobic +digestion at high solids content due to accumulation of metabolic by-products, such as volatile fatty +acids. +Moreover further research is needed to define the optimal TS of anaerobic digestion of food waste and +rice straw. In the present work the wet digestion was individuated as the best option to maximize the +specific final methane yield, but there is a need to make also an economical balance taking into +account different process costs. In particular for a specific full-scale reactor, it has to be done a +balance between the economical return related to higher specific methane production and the +additional costs of water use, digestate production and pre-treatments needed. However this study is +beyond the scope of this research and it has to be treated case by case considering a specific reactor +configuration and waste type to be treated. +Another instrument useful for full-scale reactor operation can be a complete mathematical model of +the anaerobic digestion process considering dry and wet conditions. This model can simulate the +effect of TS content on the process performances. In this thesis a mathematical model was proposed +and the model calibration was done only using the data obtained from batch experiments. The +proposed model can be applied to simulate full-scale application, and also can be calibrated by using +the data of full-scale plant considering the nature and quantity of the substrate to be treated and the +specific reactor configuration. +     1   33           +CHAPTER 7– DISCUSSION AND CONCLUSIONS +Considering all the results obtained in the present work, still a lot of efforts have to be done yet to +understand in deep the dry anaerobic digestion process, in particular the following research gaps and +needs should be considered: +• increase the understanding of the effect of the reactor configuration, optimizing the operating +conditions; +• increase the understanding of the dry anaerobic digestion processes through the comprehensive +analysis of the roles of phase separation, microbial community distribution patterns, hydrogen ion +partial pressure and accumulation of toxic compounds; +• understand the different effect of specific process inhibitors such as (Heavy Metals) HMs on +different TS anaerobic digestion processes; +• define optimized reactor configurations in terms of mixing conditions for different TS contents in +the reactor. This can be addressed performing hydrodynamic tests aimed at assessing the mixing effect +and the degree of dispersion in the reactor in order to define a configuration capable to reduce the +dispersion and short-circuiting problems. +Hydrodynamic experiments on plug flow laboratory scale reactor can be conducted with water and +tracer, to understand how the hydrodynamic is influenced by flow-rate variations and reactor +configurations (length, diameter, presence of impellers) and individuate the degree of dispersion with +different flow-rate values. Hydrodynamic experiments should be conducted also in anaerobic +conditions with inoculum and substrate to assess the effect of the substrate amount in the reactor and +TS content on the degree of dispersion. 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Valor., 3, 89-98. +     1   62           diff --git a/examples/theses/These_Nathalie_Mitton.pdf b/examples/theses/These_Nathalie_Mitton.pdf new file mode 100644 index 00000000..e7a491d7 Binary files /dev/null and b/examples/theses/These_Nathalie_Mitton.pdf differ diff --git a/examples/theses/These_Nathalie_Mitton/fulltext.pdf b/examples/theses/These_Nathalie_Mitton/fulltext.pdf new file mode 100644 index 00000000..e7a491d7 Binary files /dev/null and b/examples/theses/These_Nathalie_Mitton/fulltext.pdf differ diff --git a/examples/theses/These_Nathalie_Mitton/fulltext.pdf.txt b/examples/theses/These_Nathalie_Mitton/fulltext.pdf.txt new file mode 100644 index 00000000..0408604d --- /dev/null +++ b/examples/theses/These_Nathalie_Mitton/fulltext.pdf.txt @@ -0,0 +1,5069 @@ +AUTO-ORGANISATION DES RESEAUX SANS FIL +MULTI-SAUTS A GRANDE ECHELLE. +Nathalie Mitton +To cite this version: +Nathalie Mitton. AUTO-ORGANISATION DES RESEAUX SANS FIL MULTI-SAUTS A +GRANDE ECHELLE.. Computer Science. INSA de Lyon, 2006. French. +HAL Id: tel-00599147 +https://tel.archives-ouvertes.fr/tel-00599147 +Submitted on 8 Jun 2011 +HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est +archive for the deposit and dissemination of sci- destine´e au de´poˆt et a` la diffusion de documents +entific research documents, whether they are pub- scientifiques de niveau recherche, publie´s ou non, +lished or not. The documents may come from e´manant des e´tablissements d’enseignement et de +teaching and research institutions in France or recherche franc¸ais ou e´trangers, des laboratoires +abroad, or from public or private research centers. publics ou prive´s. +Me´moire +pre´sente´ par +Nathalie MITTON +en vue de l’obtention du diploˆme +DOCTORAT EN INFORMATIQUE ET +RESEAUX +de l’INSA de Lyon +AUTO-ORGANISATION DES RE´ SEAUX +SANS FIL MULTI-SAUTS A` GRANDE +E´ CHELLE. +Soutenue le 27/03/2006. +Nume´ro d’ordre : 2006-ISAL-0023. +Apre`s avis de : Franc¸ois BACCELLI +Catherine ROSENBERG +David SIMPLOT-RYL +Devant la commission d’examen forme´e de : +Bartlomiej (Bartek) BLASZCZYSZYN +Charge´ de recherche a` l’INRIA - TREC +Serge FDIDA +Professeur a` l’Universite´ Pierre et Marie Curie – Paris VI +E´ ric FLEURY (Directeur de the`se) +Professeur a` l’INSA de LYON +Isabelle GUE´ RIN LASSOUS (Directrice de the`se) +Charge´e de recherche habilite´e a` l’INRIA - ARES +David SIMPLOT-RYL (Rapporteur) +Professeur a` l’Universite´ de Lille +pour les travaux effectue´s au Centre d’Innovations en Te´le´communications & Inte´gration +de services de l’INSA de Lyon (CITI) sous la direction du Pr. E´ ric Fleury et du Dr. Isabelle +Gue´rin-Lassous. +Table des matie`res +1 Introduction 7 +1.1 Me´thodologies et notations . . . . . . . . . . . . . . . . . . . . . . . 10 +1.1.1 Mode`le utilise´ dans les analyses stochastiques . . . . . . . . . 10 +1.1.2 Mode`le de simulation . . . . . . . . . . . . . . . . . . . . . . 11 +2 E´ tat de l’art 13 +2.1 Clusters a` 1 saut . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 +2.2 Clusters a` k sauts . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 +2.3 Clusters hie´rarchiques . . . . . . . . . . . . . . . . . . . . . . . . . . 21 +2.4 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 +3 Algorithme de clustering 23 +3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 +3.2 La me´trique de densite´ . . . . . . . . . . . . . . . . . . . . . . . . . 24 +3.3 La formation des clusters . . . . . . . . . . . . . . . . . . . . . . . . 24 +3.4 Maintenance de la structure . . . . . . . . . . . . . . . . . . . . . . . 28 +3.5 Analyse de la me´trique . . . . . . . . . . . . . . . . . . . . . . . . . 28 +3.5.1 Recherche de la meilleure k-densite´ . . . . . . . . . . . . . . 28 +3.5.2 Densite´ moyenne . . . . . . . . . . . . . . . . . . . . . . . . 29 +3.5.3 Re´partition des valeurs de densite´ . . . . . . . . . . . . . . . 31 +3.6 Analyse de la structure . . . . . . . . . . . . . . . . . . . . . . . . . 31 +3.6.1 Analyse the´orique du nombre de clusters . . . . . . . . . . . 31 +3.6.2 Caracte´ristiques des clusters . . . . . . . . . . . . . . . . . . 33 +3 +4 TABLE DES MATIE`RES +3.7 Comparaison a` d’autres heuristiques . . . . . . . . . . . . . . . . . . 36 +3.7.1 Comparaison avec DDR . . . . . . . . . . . . . . . . . . . . 36 +3.7.2 Comparaison avec l’heuristique Max-Min d-cluster . . . . . . 39 +3.8 Analyse de l’auto-stabilisation . . . . . . . . . . . . . . . . . . . . . 42 +3.8.1 Pre´-requis . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 +3.8.2 Construction d’un DAG de hauteur constante . . . . . . . . . 44 +3.8.3 Analyse de la construction du DAG de couleurs . . . . . . . . 45 +3.8.4 Utilisation des couleurs pour le clustering . . . . . . . . . . . 48 +3.8.5 Validation des proprie´te´s auto-stabilisantes . . . . . . . . . . 50 +3.9 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52 +3.10 Publications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 +3.11 Annexes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54 +3.11.1 Analyse de la densite´ moyenne . . . . . . . . . . . . . . . . . 54 +3.11.2 Calcul analytique du nombre de clusters . . . . . . . . . . . . 56 +3.11.3 Temps de transmission borne´ . . . . . . . . . . . . . . . . . . 58 +4 Diffusion 61 +4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61 +4.2 E´ tat de l’art . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62 +4.3 Analyse the´orique . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64 +4.4 Notre contribution a` la diffusion . . . . . . . . . . . . . . . . . . . . 66 +4.4.1 Se´lection des passerelles . . . . . . . . . . . . . . . . . . . . 66 +4.4.2 L’algorithme de diffusion . . . . . . . . . . . . . . . . . . . . 71 +4.5 Analyses et re´sultats de simulations . . . . . . . . . . . . . . . . . . 72 +4.5.1 E´ lection et utilisation des passerelles . . . . . . . . . . . . . . 72 +4.5.2 Performances de la diffusion . . . . . . . . . . . . . . . . . . 74 +4.5.3 Robustesse de la diffusion . . . . . . . . . . . . . . . . . . . 79 +4.6 Analyse de la se´lection des MPR dans OLSR . . . . . . . . . . . . . 82 +4.6.1 La se´lection des MPR . . . . . . . . . . . . . . . . . . . . . 82 +4.6.2 Analyse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84 +4.6.3 Re´sultats nume´riques et simulations . . . . . . . . . . . . . . 88 +4.6.4 Conse´quences . . . . . . . . . . . . . . . . . . . . . . . . . . 90 +4.7 Conclusion et perspectives . . . . . . . . . . . . . . . . . . . . . . . 91 +4.8 Publications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92 +4.9 Annexes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93 +TABLE DES MATIE`RES 5 +5 Localisation et routage 97 +5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97 +5.2 Localisation et routage . . . . . . . . . . . . . . . . . . . . . . . . . 100 +5.2.1 Re´sume´ et analyse de complexite´ . . . . . . . . . . . . . . . 101 +5.3 Notre proposition . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102 +5.3.1 Pre´liminaires . . . . . . . . . . . . . . . . . . . . . . . . . . 102 +5.3.2 Distribution des partitions de l’espace virtuel - ILS . . . . . . 103 +5.3.3 Enregistrement . . . . . . . . . . . . . . . . . . . . . . . . . 104 +5.3.4 De´parts et arrive´es . . . . . . . . . . . . . . . . . . . . . . . 104 +5.3.5 Ajouter de la redondance et de la robustesse . . . . . . . . . . 106 +5.3.6 Ope´ration de look-up . . . . . . . . . . . . . . . . . . . . . . 106 +5.3.7 Routage sur le re´seau physique . . . . . . . . . . . . . . . . . 112 +5.4 Simulations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114 +5.4.1 SAFARI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114 +5.4.2 Comparaison des structures . . . . . . . . . . . . . . . . . . 116 +5.4.3 Look-up et routage . . . . . . . . . . . . . . . . . . . . . . . 118 +5.5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122 +5.6 Publications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124 +6 Conclusion et perspectives 125 +6.1 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125 +6.2 Perspectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126 +6 TABLE DES MATIE`RES +Chapitre 1 +Introduction +De nos jours, les gens se de´placent et communiquent de plus en plus. Ils ont de´sormais +besoin de nouvelles technologies leur permettant de fac¸on simple et rapide de re´cupe´rer +diverses informations et de communiquer avec des personnes distantes pouvant eˆtre +n’importe ou` dans le monde. Ces dernie`res anne´es ont vu le de´veloppement technolo- +gique de nombreux composants et appareils e´lectroniques de toute sorte pour re´pondre +a` ces nouveaux besoins. Ces appareils communicants sont de plus en plus petits, ont +des capacite´s de calcul de plus en plus performantes et sont de plus en plus re´pandus. +On les rencontre partout dans notre quotidien : a` la maison, au bureau, dans les voi- +tures, etc. Les acce`s a` l’information deviennent omnipre´sents a` travers les te´le´phones +portables, ordinateurs portables, PDA et les technologies de communications sans fil. +Cependant, l’apparition et l’expansion de ces phe´nome`nes ont e´galement conduit a` +une explosion de la complexite´ a` tout niveau, a` un point de´passant les capacite´s hu- +maines a` controˆler et se´curiser. L’intervention humaine doit eˆtre remplace´e par une +auto-gestion du syste`me par les machines. C’est ce qu’on appelle l’autonomic compu- +ting. Afin d’assurer l’ubiquite´ des informations, les entite´s technologiques doivent eˆtre +mises en re´seau et eˆtre capables de re´pondre aux de´fis suivants : +Auto-configuration et auto-organisation. Chaque entite´ doit eˆtre capable de se +configurer elle-meˆme a` partir d’interactions locales avec les autres entite´s afin +de faire e´merger un comportement global qui assure le bon fonctionnement +du re´seau. Elle doit s’adapter aux modifications de la topologie du re´seau. Par +exemple, les entite´s doivent eˆtre capables d’e´tablir des routes pour joindre les +personnes souhaite´es ou acce´der a` une information donne´e. +Auto-gue´rison. Lorsqu’une panne se produit, le re´seau doit eˆtre capable de la loca- +liser, de l’identifier et de l’isoler afin qu’elle ne contamine pas l’ensemble du +re´seau, et si possible de la corriger. +Auto-optimisation. Chaque entite´ doit pre´server les ressources globales du re´seau afin +de lui assurer une dure´e de vie aussi longue que possible, tout en effectuant +correctement les taˆches qui lui sont alloue´es. +7 +8 CHAPITRE 1. INTRODUCTION +Auto-protection. Le re´seau doit eˆtre capable d’apprendre de ses fautes et des at- +taques exte´rieures qui surviennent. Il doit pouvoir les identifier rapidement et +se prote´ger contre elles. +Tous ces de´fis doivent pouvoir eˆtre adresse´s en tenant compte des contraintes +intrinse`ques des entite´s technologiques et des technologies de communication. +L’autonomic computing couvre ainsi un tre`s large domaine des re´seaux informatiques, +tous pre´sentant des contraintes supple´mentaires spe´cifiques. Au sein de ce large spectre +que repre´sente l’autonomic computing et qui repre´sente un re´el de´fi scientifique pour +les anne´es a` venir, je me suis oriente´e lors de ma the`se vers le domaine des re´seaux +sans fil tels que les re´seaux ad hoc ou les re´seaux de capteurs, qui offre l’avantage +d’eˆtre plus cible´ en termes d’applications, tout en englobant un grand nombre des de´fis +scientifiques pre´sente´s ci dessus. +Les re´seaux sans fil multi-sauts sont des re´seaux radio mobiles sans aucune infrastruc- +ture, ce qui leur permet une implantation rapide. Ils peuvent aussi eˆtre couple´s a` un +LAN pour e´tendre la couverture d’une infrastructure existante. Les entite´s peuvent +apparaıˆtre, disparaıˆtre, se de´placer inde´pendamment les unes des autres. La topolo- +gie du re´seau est e´volutive. Les terminaux peuvent communiquer dans la limite de +la porte´e de leur communication radio. Un sche´ma de communication multi-sauts est +ne´cessaire pour permettre a` deux correspondants distants de communiquer. Dans ce +sche´ma de communication, chaque terminal peut eˆtre utilise´ comme routeur pour re- +layer les communications d’autres terminaux. La configuration de ces routes multi- +sauts est re´alise´e par un protocole de routage. Afin d’eˆtre efficaces, ces protocoles +de routage doivent conside´rer les caracte´ristiques intrinse`ques du re´seau (topologie en +constante e´volution), des terminaux (taille me´moire et capacite´s de calcul limite´es...) +et du me´dium de communication (bande passante limite´e, interfe´rences...). +Il existe aujourd’hui de nombreux protocoles de routage pour de tels re´seaux. Cepen- +dant, bien qu’efficaces sur des re´seaux peu denses ou de petite ou moyenne taille, aucun +d’eux ne peut eˆtre utilise´ sur de grandes e´chelles car ils ge´ne´reraient trop de trafic de +controˆle ou ne´cessiteraient des tables de routage trop importantes. L’une des solutions +commune´ment propose´es pour le routage sur de grandes e´chelles est d’introduire un +routage hie´rarchique en regroupant ge´ographiquement des entite´s proches en clusters +et en utilisant des sche´mas de routage diffe´rents au sein des clusters et entre les clus- +ters. Une telle approche permet a` chaque entite´ de stocker la totalite´ des informations +de son cluster et seulement une partie des informations concernant les autres clusters +et de cette fac¸on, permet une extensibilite´ du re´seau. +Dans ce document, je pre´sente une solution d’utilisation de re´seau sans fil multi-sauts +dense. Ce document est organise´ suivant les diffe´rentes e´tapes de cette solution : or- +ganisation du re´seau, diffusion, localisation et routage. A` chaque e´tape, les re´sultats +obtenus ont e´te´ analyse´s par simulation, par des e´tudes comparatives avec des solu- +tions existantes et, lorsque cela e´tait possible par une analyse the´orique. Le premier +chapitre est la pre´sente introduction, dans laquelle je pre´sente les notations utilise´es au +cours du document et les mode`les utilise´s pour les e´tudes analytiques et les simula- +tions. Dans le chapitre 2, les diffe´rentes approches propose´es dans la litte´rature pour +organiser un re´seau en clusters sont pre´sente´es. Seules les me´thodes qui proposent une +9organisation du re´seau sont mentionne´es. Il existe e´galement de nombreuses e´tudes sur +l’apport de cette organisation sur la capacite´ du re´seau comme c’est le cas de [37] mais +cet aspect n’est pas l’objet de cette the`se et ces e´tudes ne sont donc pas pre´sente´es dans +ce chapitre. +Le chapitre 3 de´crit notre solution de clustering et en e´tudie les diffe´rentes ca- +racte´ristiques. L’algorithme de clustering se base sur une nouvelle me´trique qui permet +de lisser des petits changements de topologie. Les clusters sont construits en s’adap- +tant a` la topologie sous-jacente, sans contrainte ni parame`tre fixe´ a priori. Une analyse +the´orique permet de de´gager certaines proprie´te´s comme une borne supe´rieure sur le +nombre de clusters obtenus sur une surface donne´e. Des simulations de´gagent des ca- +racte´ristiques de la structure obtenue et comparent ses performances aux structures +obtenues a` partir d’autres protocoles de clustering existants. Il en ressort que notre +algorithme construit des clusters qui offrent le meilleur comportement face a` la dy- +namicite´ des entite´s du re´seau. Dans ce chapitre, nous montrons e´galement que notre +algorithme est auto-stabilisant localement, ce qui lui confe`re de bonnes proprie´te´s pour +le passage a` l’e´chelle et la re´sistance aux fautes. +A` partir des caracte´ristiques de´gage´es de la structure de clusters, nous proposons deux +grandes applications indispensables a` tout re´seau : une diffusion efficace d’information +et un processus de routage. Nous construisons donc une seule structure pour diverses +applications. Le processus de diffusion est pre´sente´ et e´tudie´ dans le chapitre 4. Ce +protocole de diffusion a pour avantage d’avoir deux de´clinaisons : il peut permettre une +diffusion globale a` l’ensemble du re´seau et/ou une diffusion limite´e au sein d’un cluster. +Il ne demande que peu d’e´changes et de calculs. La diffusion ainsi ge´ne´re´e s’ave`re +solliciter moins d’entite´s que les protocoles de diffusion existants et donc consomme +moins d’e´nergie, tout en e´tant plus robuste face a` des cassures de liens. +Le chapitre 5 aborde le processus de routage hie´rarchique applique´ a` la structure. Il +s’agit d’un protocole de routage indirect (c.a`.d. effectue´ en deux temps) qui pre´sente +une approche originale, en conside´rant le sche´ma inverse de celui ge´ne´ralement utilise´ +dans la litte´rature. En effet, les caracte´ristiques des clusters ont montre´ qu’un sche´ma +classique pre´senterait les meˆmes proble`mes d’extensibilite´ rencontre´s dans un re´seau a` +plat, comme nous le verrons. Ce processus de routage inte`gre un processus de locali- +sation base´ sur les tables de hachage distribue´es et sur la mise en œuvre d’un routage +adapte´ aux re´seaux sans fil, comme le routage par intervalle. Le protocole de rou- +tage fournit des routes proches de l’optimal tout en maintenant O(1) informations sur +chaque entite´. +Le dernier chapitre conclut ce document et donne plusieurs perspectives a` l’ensemble +des travaux mene´s au cours de cette the`se. Ce travail a e´te´ re´alise´ dans le cadre de ma +the`se effectue´e au sein du laboratoire CITI de l’INSA de Lyon et de l’e´quipe INRIA +ARES, sous la direction d’E´ ric FLEURY et d’Isabelle GUE´RIN LASSOUS. +10 CHAPITRE 1. INTRODUCTION +1.1 Me´thodologies et notations adopte´es au cours de la +the`se +Un re´seau sans fil multi-sauts peut eˆtre mode´lise´ par un graphe G = (V,E) ou` V +repre´sente l’ensemble des terminaux mobiles etE repre´sente les liaisons radios existant +entre ces stations. Dans notre approche, nous n’avons conside´re´ que des liens radios bi- +directionnels, c.a`.d qu’un lien e = (u, v) existe si les stations u et v sont a` porte´e de +communication radio l’une de l’autre. +Nous notons dist(u, v) la distance euclidienne de u a` v et d(u, v) la distance dans +le graphe (en nombre de sauts) entre les nœuds u et v. Cette distance correspond au +nombre de sauts minimum que l’on doit faire pour rejoindre v depuis u. Nous notons +Γk(u) le k-voisinage (ou le voisinage a` k sauts) du nœud u. Le k-voisinage d’un nœud +est l’ensemble des nœuds a` k sauts de lui : Γk(u) = {v 6= u | d(u, v) ≤ k}. Nous +notons δk(u) = |Γk(u)| la cardinalite´ de cet ensemble. On note ge´ne´ralement Γ(u) +pour Γ1(u). On remarquera que u n’appartient pas Γk(u) (∀k > 0, u ∈/ Γk(u)). Par +de´finition, δ1(u) = δ(u) = |Γ1(u)| est le degre´ du nœud u. +Nous de´signons par C(u) le cluster auquel appartient le nœud u et H(u) son cluster- +head. +Nous utilisons e(u/C) pour de´noter l’excentricite´ du nœud u dans un cluster C. L’ex- +centricite´ d’un nœud est la plus grande distance entre u et tout autre nœud du meˆme +cluster C : e(u/C) = maxv∈C(u)(d(u, v)). Le diame`tre d’un cluster C, note´ D(C), est +la plus grande excentricite´ dans ce cluster : D(C) = maxu∈C(e(u/C)). +1.1.1 Mode`le utilise´ dans les analyses stochastiques +Lors des diffe´rentes analyses the´oriques que nous avons mene´es, nous repre´sentons un +re´seau sans fil multi-sauts par un processus ponctuel de Poisson d’intensite´ constante +λ. +Un processus de Poisson est un processus ponctuel pour lequel la disposition des points +est comple`tement ale´atoire a` chaque re´alisation. L’une des proprie´te´s caracte´risant le +processus de Poisson est que le nombre de points dans une zone donne´e est inde´pendant +des autres points du processus. Le processus de Poisson est le processus repre´sentant +le mieux la distribution des nœuds du re´seau dans l’espace. Dans cette the`se, nous +n’avons conside´re´ que des processus de Poisson homoge`ne (intensite´ constante dans le +plan) et isotrope (proprie´te´s invariantes par rotation). +Pour simuler une re´alisation d’un processus de Poisson homoge`ne d’intensite´ λ dans +un carre´ de surface S, on de´finit d’abord le nombre de points N du semis en tirant un +nombre pseudo-ale´atoire dans une loi de Poisson de parame`tre λ × S. Le nombre de +λkpoints N prend les valeurs k avec la probabilite´ suivante : P(N = k) = k! exp(−λS). +λ repre´sente alors le nombre moyen de nœuds par unite´ de surface. Pour chaque point +i, l’abscisse xi et l’ordonne´e yi sont ensuite de´finies par un nombre pseudo-ale´atoire +tire´ dans une loi uniforme. +1.1. ME´THODOLOGIES ET NOTATIONS 11 +Si Φ est le processus de Poisson conside´re´, on de´signe par Φ(S) l’ensemble des points +du processus Φ distribue´s dans la surface S. Nous conside´rons qu’il existe un lien entre +deux points du processus u et v si dist(u, v) ≤ R ou` R est la porte´e de communication +radio des nœuds (u et v sont voisins). +1.1.2 Mode`le de simulation +1+2R +1 + + + + + +w + + + + W + + + +FIG. 1.1 – Seuls les nœuds de w sont conside´re´s pour les mesures simule´es mais le +processus de point est distribue´ dans W afin d’e´liminer les effets de bord. +Toutes les simulations mene´es lors de cette the`se suivent le meˆme mode`le. Nous avons +utilise´ un simulateur que nous avons de´veloppe´. Ce simulateur suppose une couche +MAC ide´ale, c.a`.d qui ne ge´ne`re aucune collision. Utiliser ce simulateur plutoˆt qu’un +simulateur re´seau qui prend en compte les collisions et caracte´ristiques des protocoles +de niveaux infe´rieurs nous permet de focaliser notre e´tude sur le comportement des +protocoles de niveau 3 uniquement, sans tenir compte des ale´as des protocoles utilise´s +au niveau des autres couches. +Les nœuds sont de´ploye´s ale´atoirement suivant un processus de Poisson dans une +feneˆtre carre´e de (1 + 2R) × (1 + 2R) avec diffe´rentes intensite´s λ. On conside`re +que deux nœuds u et v sont voisins si dist(u, v) ≤ R ou` R est la porte´e de communi- +cation radio des nœuds. Dans chaque cas, chaque statistique est la moyenne sur plus de +1000 simulations. Les mesures ne sont prises en compte que si l’ensemble des nœuds +forment une composante connexe (aucune entite´ n’est isole´e dans le re´seau). +De fac¸on a` e´liminer les effets de bords de cette feneˆtre, les diffe´rentes mesures ne sont +calcule´es que sur les nœuds se trouvant dans une feneˆtre centralew de taille 1×1 (voir +Figure 1.1), l’ensemble des points du processus e´tant distribue´s dans la feneˆtreW et les +points de w restant impacte´s par les points en dehors de w. Cette technique est appele´e +”minus-sampling”. Pour une description plus de´taille´e, se re´fe´rer a` [76] page 132. +12 CHAPITRE 1. INTRODUCTION +Chapitre 2 +E´ tat de l’art +Un re´seau ad hoc ne repose sur aucune infrastructure fixe. Les entite´s sont +inde´pendantes les unes des autres et communiquent entre elles par radio, sans utiliser +de station de base. Afin de permettre des communications entre deux stations n’e´tant +pas a` porte´e radio l’une de l’autre, les nœuds interme´diaires doivent relayer le message. +Afin que le relais des messages soit efficace, il faut e´tablir des routes entre les nœuds, +de fac¸on a` ce que chaque entite´ sache vers quelle autre station envoyer le message pour +qu’il puisse atteindre sa destination. C’est le roˆle principal des protocoles de routage. +Les protocoles de routage classiques standardise´s au sein du groupe de travail MANET +(Mobile Ad hoc NETwork) de l IETF1’ se montrent efficaces sur des re´seaux de petite +ou moyenne taille mais passent difficilement a` l’e´chelle [46, 71]. +Il existe classiquement deux grandes familles de protocoles de routage dans la +litte´rature et au sein du groupe MANET : +– pro-actif : les routes sont e´tablies et maintenues en permanence sur chaque nœud. +L’avantage d’un tel processus est qu’une route est disponible imme´diatement quelle +que soit la destination. Les inconve´nients sont la taille des tables de routage a` main- +tenir sur chaque nœud (taille en O(n) si n est le nombre de nœuds dans le re´seau) et +le nombre de messages de controˆle a` envoyer pe´riodiquement pour maintenir a` jour +les routes qui ne sont pas toujours employe´es. +– re´actif : les routes sont cherche´es a` la demande. L’avantage d’un tel protocole +est qu’il permet d’alle´ger en moyenne les tables de routage et de ne pas envoyer +pe´riodiquement des messages de recherche de route. L’inconve´nient est que lors- +qu’une route est ne´cessaire, la recherche de route vers le nœud destination peut eˆtre +tre`s longue, incluant une forte latence et ne´cessitant une inondation du re´seau. +Ainsi, avec de tels protocoles ”a` plat”, lorsque la taille re´seau grandit, le trafic de +controˆle a tendance a` devenir pre´-dominant laissant une part congrue aux communi- +cations re´elles. Cela se traduit e´galement par une augmentation de la latence et/ou +une explosion de la table de routage. Pour palier ce proble`me, une des solutions com- +1http ://www.ietf.org/html.charters/manet-charter.html +13 +14 CHAPITRE 2. E´TAT DE L’ART +mune´ment propose´es est d’introduire un routage hie´rarchique et d’organiser des nœuds +en groupes aussi nomme´s clusters. +Le clustering consiste en un de´coupage virtuel du re´seau en groupes de nœuds proches +ge´ographiquement. Ces groupes sont appele´s clusters. Ils sont ge´ne´ralement identifie´s +par un nœud particulier, un chef de groupe aussi nomme´ cluster-head. Dans la plupart +des algorithmes de clustering, les clusters sont construits a` partir d’une me´trique par- +ticulie`re qui permet d’assigner un chef a` chaque nœud ; le cluster e´tant alors constitue´ +du cluster-head et de tous les nœuds qui lui sont rattache´s. L’ide´e initiale du routage +hie´rarchique est de permettre a` chaque entite´ de stocker la totalite´ des informations de +son cluster et seulement une partie des informations concernant les autres clusters. Cela +minimise la taille des tables de routage et la quantite´ de trafic ge´ne´re´. +Outre le fait de rendre le routage plus efficace, le clustering pre´sente e´galement d’autres +avantages. Il peut faciliter le partage des ressources et/ou la synchronisation au sein +d’un cluster et permettre une re´-utilisation spatiale des fre´quences radio pour minimiser +les interfe´rences [50]. Plus important encore, l’organisation d’un re´seau apporte aussi +plus de stabilite´ [61]. +De nombreuses solutions de clustering ont e´te´ propose´es. La majorite´ d’entre elles pro- +posent l’utilisation d’une me´trique qui permet aux nœuds de se choisir un chef. Cette +me´trique peut eˆtre par exemple l’identifiant ou le degre´ des nœuds, une valeur de mobi- +lite´ des nœuds ou encore une somme ponde´re´e de tous ces e´le´ments. D’autres solutions +cherchent dans un premier temps a` de´terminer un ensemble dominant connecte´ sur le- +quel les clusters sont baˆtis. Une grande partie des solutions de clustering construisent +des clusters a` 1 saut (dits 1-clusters), c.a`.d des clusters ou` chaque nœud est a` un saut +de son chef de cluster. Les protocoles donnant naissance a` des k-clusters (clusters ou` +chaque nœud est a` au plus k sauts de son cluster-head) sont plus re´cents et plus rares. +Dans ce chapitre, nous dressons un e´tat de l’art qui permet de passer en revue les +principaux types de solutions propose´es dans la litte´rature pour organiser un re´seau ad +hoc en clusters. +2.1 Clusters a` 1 saut +De nombreux algorithmes de clustering produisent des clusters a` 1 saut. L’un des al- +gorithmes les plus anciens est ”l’algorithme du plus petit ID” ou LCA, propose´ initia- +lement par Ephremides, Wieselthier et Baker dans [28]. Chaque nœud se de´signe ou +non cluster-head en se basant sur son identifiant et celui de ses voisins. Un nœud peut +avoir trois statuts diffe´rents : cluster-head, passerelle ou nœud ordinaire. A` l’origine, +tous ont un statut de nœud ordinaire. Si un nœud u a le plus petit identifiant parmi les +nœuds de son voisinage, il se de´clare cluster-head. Sinon, il attend que tous ses voisins +ayant un identifiant plus petit que le sien ait de´clare´ leur statut. Si au moins l’un d’eux +s’est de´clare´ chef, u de´clare a` son voisinage son statut de nœud ordinaire. u appartient +alors a` chacun des clusters de ses voisins s’e´tant de´clare´ chef. Si tous les voisins de u +ayant un identifiant plus petit que celui de u se sont de´clare´s nœuds ordinaires (car ils +2.1. CLUSTERS A` 1 SAUT 15 +se sont attache´s a` un autre de leur voisin de plus petit ID), u se de´clare cluster-head. +Une fois que chaque nœud a de´clare´ son statut de nœud ordinaire ou de cluster-head, +si un nœud entend parmi ses voisins plus d’un cluster-head, il se de´clare passerelle. +Le protocole LCA est notamment utilise´ par le routage CBRP (Cluster Based Routing +Protocol) [42], pour la formation des clusters. +Par la suite, avec le protocole HCC (High Connectivity Clustering), Gerla et Tsai [36] +ont cherche´ a` apporter plus de stabilite´ a` la structure de clusters forme´s par le LCA, en +utilisant le degre´ des nœuds plutoˆt que leur identifiant. Le nœud ayant le plus fort degre´ +dans son voisinage se de´clare cluster-head. Si deux voisins ont le meˆme degre´, c’est ce- +lui de plus petit identifiant qui prend sa de´cision le premier. L’ide´e est que des nœuds +de fort degre´ sont de bons candidats pour eˆtre cluster-heads car ils couvrent un grand +nombre de nœuds et le nombre de clusters re´sultant en sera re´duit. Par ailleurs, l’identi- +fiant d’un nœud e´tant unique, un nœud de faible ID aura tendance a` rester cluster-head +longtemps, malgre´ la mobilite´ des nœuds. Ne´anmoins, si ce nœud est tre`s mobile, il +de´truira constamment la structure. +Ainsi, ces protocoles construisent des clusters a` 1 saut qui se recouvrent (les passerelles +appartiennent a` plusieurs clusters). Cette structure a e´te´ propose´e pour acheminer les +messages de controˆle et de routage ou` seuls les cluster-heads et les passerelles agissent. +Leur maintenance s’ave`re couˆteuse car le mouvement d’un nœud peut engendrer des +re´actions en chaıˆne et ne´cessiter une reconstruction totale de la structure. C’est pour- +quoi les auteurs de [24] ont propose´ ”Least Cluster Change” (LCC). LCC ajoute une +e´tape de maintenance des clusters forme´s avec le LCA ou le HCC. Les clusters ne +sont reconstruits que si deux cluster-heads se retrouvent voisins (le nœud de plus faible +degre´ et/ou de plus fort ID suivant le cas abandonne le roˆle de cluster-head) ou si un +nœud ordinaire n’a plus aucun cluster-head dans son voisinage (il relance le processus +de clustering). De cette fac¸on, LCC ame´liore la stabilite´ de la structure. Cependant, les +re´actions en chaıˆne de re-construction ne sont que limite´es et ne sont pas comple`tement +supprime´es du fait qu’un seul nœud peut re-lancer la proce´dure de clustering s’il n’a +plus aucun cluster-head dans son voisinage. +Le protocole MOBIC [13], autre protocole de clustering a` 1 saut, applique le meˆme +algorithme que LCA et HCC mais utilise une me´trique base´e sur la mobilite´ plutoˆt que +le degre´ ou l’identifiant des nœuds. Cette me´trique cherche a` caracte´riser la mobilite´ +relative d’un nœud. L’ide´e est qu’un nœud peu mobile est un bon candidat pour eˆtre +cluster-head car stable. Pour calculer sa mobilite´ relative, un nœud mesure le niveau +de signal qui l’unit a` chacun de ses voisins. La mobilite´ d’un nœud u est calcule´e a` +partir des rapports entre ce niveau de signal et celui mesure´ a` l’e´tape pre´ce´dente pour +chaque voisin de u, l’atte´nuation du signal e´tant de´pendante de la distance se´parant les +nœuds. Le nœud dont la mobilite´ est la plus faible dans son voisinage devient cluster- +head. Les auteurs de MOBIC utilise l’algorithme LCC pour la maintenance de leur +structure en ajoutant une re`gle supple´mentaire : si deux cluster-heads u et v arrivent +dans le voisinage l’un de l’autre, le cluster-head v de plus fort identifiant n’abandonne +son roˆle de cluster-head que si u fait toujours partie de ses voisins apre`s une certaine +pe´riode de temps. Cela permet de ne pas reconstruire la structure si deux cluster-heads +ne se retrouvent voisins que pour une courte pe´riode. La mobilite´ des nœuds n’est plus +reconside´re´e par la suite a` moins d’avoir a` reconstruire toute la structure. Cependant, les +16 CHAPITRE 2. E´TAT DE L’ART +inconve´nients du LCC ne sont pas e´limine´s. Bien que la prise en compte de la mobilite´ +des nœuds semble inte´ressante pour de´terminer les cluster-heads, cette me´thode est un +peu complexe et ne´cessite que les nœuds soient en mesure d’estimer les puissances de +signal. De plus, elle ne conside`re pas certains phe´nome`nes physiques qui provoquent +des atte´nuations he´te´roge`nes du signal. +Plutoˆt que d’utiliser l’identifiant ou le degre´ des nœuds, d’autres protocoles de clus- +tering utilisent une somme ponde´re´e de plusieurs me´triques. Cette cate´gorie d’algo- +rithmes vise a` e´lire le cluster-head le plus adapte´ a` une topologie pour une utilisation +donne´e. Par exemple, dans un re´seau de senseurs ou` l’e´nergie est un facteur impor- +tant, le parame`tre d’e´nergie re´siduelle peut obtenir un poids plus e´leve´ dans la somme +ponde´re´e de la me´trique re´sultante. WCA [20] est un protocole utilisant une somme +ponde´re´e de quatre crite`res : la diffe´rence de degre´ Dv , la somme des distances avec +les voisinsPv , la vitesse relative moyenneMv et le temps de service en tant que cluster- +head. Pour un nœud v, la diffe´rence de degre´ Dv est la diffe´rence entre le degre´ de v +et une constante M repre´sentant le nombre de nœuds qu’un cluster-head peut servir. +Cependant, les auteurs n’explicitent pas le moyen de de´terminer M . La mobilite´ rela- +tive Mv est obtenue comme dans MOBIC. Les distances Pv entre v et ses voisins sont +calcule´es a` l’aide d’un GPS. L’e´lection se fait en se basant la` encore sur l’algorithme +de LCA, le nœud dont la somme ponde´re´e de ces crite`res est la plus petite devenant +cluster-head. Les clusters sont ensuite maintenus sans plus reconside´rer la me´trique +ponde´re´e. Le processus de clustering est relance´ quand un nœud arrive dans une zone +couverte par aucun cluster-head, ceci pouvant entraıˆner des re´actions de reconstruction +en chaıˆne comme dans les algorithmes pre´ce´dents. +Ainsi, plusieurs me´thodes de clustering a` 1 saut se basent sur l’algorithme du LCA +et changent juste le crite`re de de´cision. C’est pourquoi Basagni, dans [12] reprend +l’algorithme de LCA en donnant comme crite`re un poids ge´ne´rique que chacun de´finit +comme il le souhaite. Il en e´tudie alors the´oriquement les diffe´rentes proprie´te´s. +Toutes les me´thodes de clustering mentionne´es jusqu’a` maintenant produisent des clus- +ters recouvrants, c.a`.d. une structure dans laquelle un nœud peut appartenir a` plusieurs +clusters. Leur inconve´nient majeur est que le mouvement d’un nœud peut provoquer +la re-construction d’un cluster, qui, par re´action en chaıˆne, provoque le re-construction +de la structure entie`re. Afin d’e´viter cela, d’autres protocoles de clustering ont e´te´ pro- +pose´s, produisant des clusters non re-couvrants : un nœud appartient a` exactement un +cluster. +Dans 3HBAC [82], les auteurs proposent un protocole qui impose trois sauts entre deux +cluster-heads. Le nœud ayant le plus fort degre´ dans son voisinage se de´clare cluster- +head. Ses voisins s’attachent a` lui et se de´clarent ”nœuds membres”. Les nœuds voisins +de ces nœuds membres et non voisins d’un cluster-head se de´clarent ”unspecified” et ne +peuvent plus eˆtre cluster-head. Lorsque deux cluster-heads se retrouvent dans le voisi- +nage l’un de l’autre, celui de plus grand identifiant abandonne son roˆle de cluster-head +et devient un nœud membre. Ses voisins deviennent soit membres (s’ils sont voisins du +cluster-head) soit non spe´cifie´s. Les re´actions en chaıˆne de re-construction sont ainsi +e´vite´es. +Dans ”Adaptive Clustering” [50], les auteurs n’utilisent le statut de cluster-head que +2.1. CLUSTERS A` 1 SAUT 17 +pour la formation des clusters. Une fois les clusters forme´s, la notion de cluster-head +disparaıˆt, chaque nœud du cluster tenant alors le meˆme roˆle. La motivation des au- +teurs est que les cluster-heads peuvent devenir des goulots d’e´tranglement par la suite, +sources de perte de trafic et saturation de bande passante. De plus, les cluster-heads +seraient appele´s a` de´penser leur e´nergie plus vite que les autres nœuds. Pour construire +de tels clusters, chaque nœud maintient un ensemble Γ qui initialement contient les +identifiants de tous ses 1-voisins. Un nœud n’est autorise´ a` diffuser son statut (cluster- +head, membre, non spe´cifie´) que s’il posse`de un identifiant plus petit que les nœuds de +Γ. Il ne se de´clare cluster-head que s’il a un identifiant plus petit que tous les nœuds +de son ensemble Γ. Sur re´ception du statut d’un nœud u, les voisins de u suppriment +u de leur ensemble Γ. Si u a annonce´ qu’il e´tait cluster-head, ses voisins s’attachent +a` lui s’ils n’e´taient encore membres d’aucun cluster ou si le cluster-head auquel ils +s’e´taient attache´s avait un identifiant plus grand que u. Le processus s’arreˆte lorsque +l’ensemble Γ de chaque nœud est vide. Comme le roˆle de cluster-head disparaıˆt une +fois les clusters forme´s, la maintenance de la structure est un peu diffe´rente que dans +les cas pre´ce´dents. Chaque nœud doit connaıˆtre son voisinage a` deux sauts. De cette +fac¸on, il sait si les membres de son cluster restent a` deux sauts de lui. Si deux nœuds +du meˆme cluster se retrouvent e´loigne´s de plus de deux sauts, seul celui encore voisin +du nœud de plus fort degre´ dans le cluster reste dans le cluster. L’autre doit se rattacher +a` un autre cluster. Bien que n’utilisant pas la notion de cluster-head, la maintenance de +cet algorithme maintient le nœud de plus fort degre´ au centre du cluster, ce qui peut +revenir au meˆme que de l’e´lire comme cluster-head. Le protocole de maintenance de +l’”Adaptive Clustering” a ensuite e´te´ repris par les auteurs de [44] qui se proposent de +l’appliquer au LCA. +Tous les algorithmes de´crits jusqu’a` pre´sent peuvent eˆtre qualifie´s de protocoles de +”clustering actif”, c.a`.d. que des messages de controˆle sont envoye´s dans le but de +construire et maintenir les clusters. A` l’oppose´, les auteurs de [47] proposent un proto- +cole de ”clustering passif”, c.a`.d. qu’ils n’utilisent aucun message de´die´ a` la construc- +tion des clusters. Les clusters ne sont cre´e´s que lorsque ne´cessaires, c.a`.d. lorsqu’un +nœud a une information a` diffuser. Le protocole de clustering passif utilise alors ces +messages d’information pour construire les clusters, en ajoutant des champs aux pa- +quets d’information. Un nœud a quatre statuts possibles : cluster-head, passerelle, nœud +ordinaire et non de´fini. Par de´faut, le statut des nœuds est non de´fini. Seul un nœud +ayant un statut non de´fini peut devenir cluster-head. Si un tel nœud a un message a` +envoyer, il se de´clare cluster-head et diffuse son statut en l’ajoutant a` l’information +qu’il devait envoyer. Les nœuds voisins d’un cluster-head deviennent des nœuds or- +dinaires, les nœuds voisins de plusieurs cluster-heads deviennent des passerelles. Les +nœuds ordinaires ne relaient pas les messages de diffusion. Aucun message n’e´tant +de´die´ a` la maintenance de la structure, les passerelles et les nœuds ordinaires activent +des compteurs lorsqu’ils rec¸oivent des nouvelles de leur(s) cluster-head(s). S’ils restent +sans nouvelle d’eux le temps que leur compteur expire, les nœuds ordinaires reprennent +un statut non de´fini et les passerelles prennent le statut de nœud ordinaire ou non de´fini +suivant le nombre de cluster-heads qu’elles entendent encore. +Comme nous venons de le voir, il existe de nombreux protocoles de clustering a` 1 +saut. Les solutions les plus anciennes proposaient des clusters recouvrants. Ce type de +18 CHAPITRE 2. E´TAT DE L’ART +clusters permet principalement de baˆtir un ensemble dominant connecte´ sur le re´seau +(constitue´ des cluster-heads et des passerelles) pour pouvoir diffuser une information +(principalement pour le routage) sur le re´seau sans solliciter tous les nœuds. Puis +d’autres e´tudes ont donne´ des clusters non-recouvrants, plus robustes face a` la mo- +bilite´ des nœuds. Ce type de clusters permet e´galement d’autres applications comme la +re´utilisation spatiale de fre´quences ou de codes (les nœuds de deux clusters non voisins +peuvent utiliser la meˆme fre´quence). Puis, des propositions plus re´centes sont apparues +permettant la construction de clusters a` k sauts, encore plus robustes et permettant de +nouvelles applications comme l’application de zones de services ou de protocole de +routage hie´rarchique. +2.2 Clusters a` k sauts +La me´thode la plus re´pandue pour la construction de clusters a` k sauts est une extension +des algorithmes de clustering a` 1 saut. Par exemple, les auteurs de [23] ge´ne´ralisent +l’algorithme de Lin et Gerla [50]. Leur algorithme suppose que chaque nœud connaıˆt +ses voisins situe´s jusqu’a` k sauts de lui. Le nœud ayant le plus petit identifiant parmi +les nœuds a` au plus k sauts de lui, diffuse son statut de cluster-head a` ses k-voisins. +Lorsque tous les nœuds de son k-voisinage ayant un plus identifiant que lui ont dif- +fuse´ leur de´cision d’eˆtre chef de cluster ou de s’attacher a` un autre chef, le nœud u +peut prendre sa propre de´cision de s’attacher au nœud de son k-voisinage de plus pe- +tit identifiant s’e´tant de´clare´ chef de cluster s’il existe, ou de cre´er son propre cluster +sinon. De la meˆme fac¸on que pour les clusters a` 1 sauts, ce meˆme algorithme est uti- +lise´ en utilisant diffe´rentes me´triques. Dans le meˆme papier [23], les auteurs proposent +e´galement d’utiliser le k-degre´ (δk) des nœuds (nombre de voisins a` au plus k sauts) +pour de´terminer le cluster-head : le nœud de plus fort k-degre´ et de plus petit identifiant +en cas d’e´galite´ est promu chef de cluster. Les clusters re´sultants sont des k-clusters +(chaque nœud est a` au plus k sauts de son chef) recouvrants (un nœud peut appartenir a` +plusieurs clusters). Deux chefs sont e´loigne´s d’au moins k + 1 sauts. Cependant, nous +retrouvons les meˆmes inconve´nients que pour les algorithmes de clusters a` 1 saut, a` +savoir qu’un petit changement de nœuds peut engendrer une reconstruction comple`te +de la structure. +Les auteurs de [67] introduisent une me´trique qu’ils appellent ”associativite´” qui se +veut repre´senter la stabilite´ relative des nœuds dans leur voisinage. Pour chaque nœud, +l’associativite´ comptabilise le temps que chacun des nœuds de son voisinage reste ef- +fectivement dans son voisinage et en fait la somme sur chaque voisin. A` chaque pe´riode +de temps, un nœud u conside`re quels sont ses voisins actuels de´ja` pre´sents lors de la +pe´riode pre´ce´dente et ajoute +1 a` la valeur associe´e a` chacun d’eux. Si un voisin a +disparu, la valeur qui lui e´tait associe´e passe a` 0, si un autre apparaıˆt, il prend la valeur +1. A` chaque pe´riode de temps, l’associativite´ de u est la somme des valeurs associe´es a` +chacun de ses voisins. Cette valeur prend donc en compte la stabilite´ de u (si u est rela- +tivement stable dans son voisinage, il aura une forte associativite´) et le degre´ des nœuds, +cette valeur n’e´tant pas normalise´e. L’algorithme de formation des clusters est le sui- +vant. Un nœud conside`re les nœuds de son k-voisinage ayant un degre´ supe´rieur a` une +2.2. CLUSTERS A` K SAUTS 19 +valeur seuil et e´lit parmi eux celui ayant la plus forte associativite´. Le plus fort degre´ +et le plus faible identifiant sont ensuite utilise´s pour rompre les e´galite´s. Les clusters +re´sultants sont e´galement des k-clusters recouvrants mais qui visent a` eˆtre plus stables +dans le temps et dans l’espace que ceux se basant sur le simple degre´ ou identifiant. +Dans [51], Lin et Chu proposent une approche base´e sur aucune me´trique particulie`re. +Lorsqu’un nœud u arrive dans le re´seau, il est en phase ”d’initialisation”. Il demande +alors a` ses voisins s’ils sont comme lui en phase d’initialisation ou s’ils ont un cluster- +head et dans ce cas, a` quelle distance ce cluster-head se situe-t-il. Si tous les voisins +de u sont en phase d’initialisation, u s’e´lit chef de cluster et diffuse cette information. +Tous les r-voisins de u qui n’ont aucun autre chef plus proche que u s’attache au cluster +de u. Sinon, u s’attache au cluster de son voisin dont le chef est le plus proche et a` au +plus r sauts de lui. Si tous les cluster-heads des clusters de ses voisins sont a` plus de r +sauts de u, u se de´clare chef de cluster et rallie a` son cluster tous ses voisins a` moins +de r sauts dont le chef est plus e´loigne´ que u. Si deux cluster-heads se retrouvent a` +moins deD sauts l’un de l’autre,D < r, le chef de cluster de plus faible identifiant doit +ce´der son roˆle et tous les membres de son cluster doivent se trouver un autre chef. Cette +me´thode de clustering est inte´ressante dans la mesure ou` elle produit des r-clusters non +recouvrants ou` les chefs sont e´loigne´s de au moins D sauts. Cela assure une certaine +stabilite´ a` la structure. Cependant, l’abandon du roˆle de cluster-head par un nœud peut +engendrer de fortes re´actions en chaıˆne. +Une approche plus originale est celle propose´e par Fernandess et Malkhi dans [32]. +Leur algorithme se de´compose en deux phases. La premie`re e´tape consiste a` trou- +ver un arbre couvrant du re´seau base´ sur un ensemble dominant connecte´ de cardi- +nalite´ minimale (MCDS). Les auteurs proposent d’utiliser l’algorithme de [2] pour +construire le MCDS mais pre´cisent que n’importe quelle me´thode peut eˆtre utilise´e. La +seconde phase de l’algorithme consiste en une partition de l’arbre couvrant en 2k-sous- +arbres, un 2k-sous-arbre e´tant un arbre de diame`tre au plus 2k sauts. Chaque sous-arbre +consiste en un k-cluster. Cependant, une telle approche a une complexite´ temporelle et +une complexite´ en messages en O(n) (n e´tant le nombre de nœuds dans le re´seau) +et est par conse´quent difficilement extensible. De plus, les auteurs n’abordent pas la +maintenance d’une telle construction, qui ne semble pas triviale. +Les auteurs de Max-Min d-cluster [4] utilisent l’identifiant des nœuds pour construire +des k-clusters non recouvrants. Cependant, leur algorithme est un peu plus complexe +que ceux vus jusqu’a` maintenant. Il se de´compose en trois phases. Lors de la premie`re +phase, chaque nœud collecte l’identifiant de ses voisins jusqu’a` d sauts et en garde le +plus grand qu’il diffuse de nouveau a` d sauts lors de la seconde phase. Chaque nœud +garde alors le plus petit des identifiants qu’il rec¸oit lors de cette deuxie`me phase (le +plus petit parmi les plus grands). La troisie`me e´tape consiste au choix du cluster-head +base´ sur les identifiants collecte´s lors des deux phases pre´ce´dentes. Si un nœud u a +vu passer son propre identifiant lors de la deuxie`me phase, il devient chef de cluster. +Sinon, si u a vu passer un identifiant durant chacune des phases 1 et 2, il e´lit le nœud +portant cet identifiant comme chef. Sinon, u e´lit comme chef le nœud de plus grand +identifiant dans son d voisinage. La structure re´sultante s’ave`re robuste, cependant la +latence induite par l’algorithme est non ne´gligeable. +20 CHAPITRE 2. E´TAT DE L’ART +Dans [3], les meˆmes auteurs introduisent une notion d’identifiant virtuel. Le but est +d’apporter une certaine e´quite´ entre les nœuds et d’e´viter qu’un meˆme nœud soit trop +longtemps cluster-head et e´puise ainsi ses ressources, tout en assurant qu’il le reste +suffisamment longtemps pour apporter une stabilite´ a` la structure. Les nœuds prennent +le roˆle de cluster-head tour a` tour. Initialement, l’identifiant virtuel d’un nœud est e´gal +a` son propre identifiant. A` chaque pe´riode de temps, chaque nœud non cluster-head +incre´mente de 1 son identifiant virtuel jusqu’a` atteindre un maximum MAXV ID. Le +nœud ayant l’identifiant virtuel le plus fort parmi ses k-voisins devient le cluster-head. +En cas de conflits, c’est le nœud qui a le moins ope´re´ en tant que chef qui devient +cluster-head (et de plus fort identifiant normal si toujours e´galite´). Un nœud qui de- +vient cluster-head prend ajoute a` son ancienne valeur d’identifiant virtuelle MAXV ID +de fac¸on a` assurer qu’il conserve le plus fort identifiant virtuel et reste cluster-head. +Un nœud reste cluster-head pendant une pe´riode de temps ∆(t) au bout de laquelle +il passe son identifiant virtuel a` 0 et abandonne son roˆle de chef. Lorsque deux chefs +entrent dans le voisinage l’un de l’autre, celui de plus faible identifiant virtuel aban- +donne son roˆle. Dans le meˆme papier, les auteurs proposent e´galement une construction +ou` l’identifiant virtuel de base serait le degre´ des nœuds. Cet algorithme permet donc +la formation de k-clusters en assurant une certaine stabilite´ de la structure. Ne´anmoins, +elle ne´cessite une synchronisation des nœuds afin que chacun se base sur la meˆme +pe´riode de temps pour incre´menter son identifiant virtuel et surtout pour comptabili- +ser la pe´riode durant laquelle il est cluster-head. Or, une synchronisation dans de tels +re´seaux est non triviale et ne´cessite beaucoup de messages. +Les auteurs de [45] proposent un autre type d’algorithme, formant cette fois des clusters +sans chef de cluster. Pour cela, chaque nœud ne´cessite e´galement la connaissance de +son k-voisinage. Un cluster est forme´ par un ensemble de nœuds tel qu’il existe entre +deux nœuds de cet ensemble un chemin d’au plus k-sauts. Si k = 1, chaque cluster +est une clique. Un nœud appartenant a` plusieurs clusters est dit nœud frontie`re. Les +clusters sont donc recouvrants. Malheureusement, cet algorithme implique beaucoup +de messages de controˆle, de maintenance et de donne´es a` ge´rer par les nœuds. +Les auteurs de DDR [59] proposent e´galement une structure sans cluster-head. Contrai- +rement a` la plupart des algorithmes de formation de k-clusters, les nœuds ne ne´cessitent +que de la connaissance de leur 1-voisinage. La formation des clusters se base sur la +construction d’un arbre. Chaque nœud choisit comme pe`re son voisin de plus faible +identifiant. Il existe alors exactement une areˆte sortante par nœud. Cela conduit a` la +formation d’un arbre. Tous les nœuds du meˆme arbre appartiennent au meˆme cluster. +Le diame`tre de tels clusters n’est pas fixe´ a priori et s’adapte automatiquement a` la to- +pologie sous-jacente. Cet algorithme a e´te´ ensuite repris par Baccelli [7] en y ajoutant +la notion de cluster-head et en controˆlant la taille des clusters. Pour cela, un nœud a +le droit de se choisir comme pe`re s’il a le plus fort identifiant dans son 1-voisinage. Il +existe alors des nœuds sans areˆte sortante qui deviennent des cluster-heads. Ces cluster- +heads ont alors la possibilite´ de borner la hauteur des arbres a` d sauts en diffusant l’in- +formation le long des branches de l’arbre. Si la branche est trop longue, le nœud se +trouvant a` d+1 sauts de son cluster-head doit s’attacher a` un autre pe`re (et donc casser +la branche). +D’autres algorithmes comme ceux propose´s dans [39, 60] ne proposent qu’une solution +2.3. CLUSTERS HIE´RARCHIQUES 21 +de maintenance. Par exemple, les auteurs de [60] proposent de maintenir un certain +nombre de nœuds dans un cluster, qui de´pendrait du nombre d’entite´s que le cluster- +head est en mesure de ge´rer. L’ide´e est de maintenir en permanence le nombre de nœuds +entre deux seuils. Si un cluster est trop petit, le chef de cluster doit e´lire parmi ses +clusters voisins celui le plus adapte´ pour une fusion, c’est-a`-dire celui dont le nombre +de nœuds permet la fusion des deux clusters. Si aucun ne correspond, le chef de cluster +doit de´terminer un cluster qui peut lui ce´der des entite´s pour un meilleur e´quilibrage du +nombre de nœuds. Si les clusters sont trop gros, le chef doit e´lire parmi ses membres +un autre cluster-head et scinder son cluster en deux. Il reste cluster-head d’un cluster +re´sultant tandis que le nœud qu’il a e´lu devient chef du second cluster. Cette me´thode +est cependant tre`s couˆteuse en calculs, latence et messages et supporte mal le passage +a` l’e´chelle du re´seau. +2.3 Clusters hie´rarchiques +Il existe e´galement des propositions de structures hie´rarchiques a` plusieurs niveaux, +c’est-a`-dire ou` les clusters sont ensuite regroupe´s en d’autres clusters de niveaux +supe´rieurs et ainsi de suite. Bien que la majorite´ des algorithmes vus jusqu’a` main- +tenant peuvent eˆtre applique´s re´cursivement sur les clusters pour former des clusters de +niveau supe´rieur, ils n’ont pas e´te´ e´crits dans ce but contrairement aux exemples que +nous e´nonc¸ons ici. +Dans [11], Banerjee et Khuller se basent sur un arbre couvrant, construit graˆce a` un +parcours en largeur, pour la construction de k-clusters. Les clusters sont forme´s par +branche, en fusionnant re´cursivement deux sous-arbres de l’arbre couvrant jusqu’a` +obtenir une taille correcte. Le processus est alors re´-ite´re´ jusqu’a` obtenir un certain +nombre de niveaux. +Dans [5], les auteurs cherchent a` combiner les partitions physiques et logiques des +nœuds ainsi que leur mobilite´. Pour cela, ils utilisent un GPS. Les auteurs supposent +que les nœuds re´pondent a` un mode`le de mobilite´ de groupe. L’algorithme consiste +ensuite a` regrouper en un meˆme cluster les nœuds proches ge´ographiquement et qui +se de´placent a` un vitesse semblable dans une meˆme direction. Le processus est ensuite +re´-ite´re´ jusqu’a` obtenir le nombre de niveaux voulu. +La structure de cellules hie´rarchiques de SAFARI [69] est base´e sur une auto-se´lection +des nœuds en tant que drums (cluster-heads). Le nombre de niveaux hie´rarchiques +s’e´tablit automatiquement en fonction de la topologie sous-jacente des nœuds. Les +clusters de niveau i sont groupe´s en clusters de niveau i+1 et ainsi de suite, les simples +nœuds e´tant conside´re´s comme des cellules de niveau 0. Chaque cluster-head de niveau +i se choisit un cluster-head de niveau i + 1. Tous les cluster-heads de niveau i ayant +choisi le meˆme cluster-head de niveau i+ 1 appartiennent au meˆme cluster de niveau +i + 1. Un cluster-head u de niveau i de´cide de monter ou descendre son niveau en +fonction du nombre de cluster-heads de niveau i + 1 et i − 1 qui existent a` une cer- +taine distance. S’il n’existe aucun cluster-head de niveau supe´rieur a` une distance plus +petite que Di (Di constante de´pendant du niveau i du cluster-head) de u, u de´cide +22 CHAPITRE 2. E´TAT DE L’ART +d’augmenter son niveau. Si deux cluster-heads de meˆme niveau sont a` moins de h×Di +(0 < h < 1, facteur d’hyste´resis) sauts, le cluster-head de plus grand identifiant des- +cend son niveau. Un cluster-head de niveau i est e´galement cluster-head de tout niveau +j tel 0 < j < i. Cet algorithme construit des k-clusters hie´rarchiques, ou` k de´pend du +niveau du nœud i : k = Di. D1 doit eˆtre fixe´. A` partir de la`, Di de´pendant de Di−1, le +rayon des clusters de chaque niveau est fixe´. Cette structure hie´rarchique peut cepen- +dant n’eˆtre utilise´e que dans un cadre pre´cis de routage, propose´ par les auteurs. Nous +verrons cette utilisation plus en de´tail dans le chapitre 5. +2.4 Conclusion +Ainsi, il existe de nombreux protocoles de clustering dans la litte´rature. Tous cependant +ne sont pas adapte´s a` une extension du re´seau comme nous avons pu le constater. En +effet, des clusters a` 1 saut ne peuvent pas eˆtre utilise´s dans ce cadre du fait du nombre +de clusters qu’ils ge´ne´reraient sur de la larges e´chelles et du fait que le moindre chan- +gement a` l’e´chelle d’un nœud provoquerait une reconstruction de la structure. En effet, +si le re´seau compte beaucoup d’entite´s, ces changements peuvent eˆtre fre´quents et mi- +nimes a` l’e´chelle du re´seau. Les clusters a` k sauts sont moins de´veloppe´s. Beaucoup +s’inspirent des protocoles de clustering a` 1 saut et en gardent les inconve´nients. Dans +ma the`se, j’ai propose´ un nouvel algorithme de clustering a` k sauts pouvant s’adap- +ter aux petites modifications du re´seau. Cet algorithme prend note des inconve´nients +des protocoles existants et tente de les e´viter, comme nous le verrons de`s le chapitre +suivant. +Chapitre 3 +Algorithme de clustering, stable +et robuste +3.1 Introduction +Notre principal objectif est de proposer un moyen d’utiliser des re´seaux sans fil tre`s +denses. Comme nous l’avons vu, l’une des solutions possibles est d’introduire une +hie´rarchie dans le re´seau en construisant des clusters. Afin de permettre une extensibi- +lite´ totale et ne pas avoir a` reconstruire les clusters apre`s chaque mouvement individuel +d’un nœud, nous avons cherche´ a` construire des clusters qui n’aient aucun parame`tre +fixe´ a` l’avance, qu’il s’agisse du rayon, du diame`tre ou de nombre de nœuds par clus- +ter. Ces parame`tres doivent s’adapter d’eux-meˆmes a` la topologie du re´seau, qui e´volue +au cours du temps. De plus, l’heuristique se doit d’eˆtre distribue´e et asynchrone tout +en minimisant le nombre d’informations a` e´changer. Notre algorithme n’utilise que +des messages de type ”PAQUET HELLO” comme ceux utilise´s dans OLSR [25] afin +de de´couvrir le 2-voisinage d’un nœud. Les clusters forme´s doivent eˆtre stables (les +cluster-heads doivent conserver ce statut suffisamment longtemps pour limiter le trafic +de controˆle ne´cessaire a` la reconstruction des clusters) tout en s’adaptant aux change- +ments de la topologie sous-jacente. Enfin, afin d’ame´liorer la stabilite´ de la structure, +e´tant donne´ que les nœuds trop mobiles pour initier une communication n’ont aucun +besoin de la structure, ils ne participent pas a` la phase de construction et restent des +nœuds inde´pendants. Dans le cas contraire, de par leur mobilite´, ils pourraient obliger +le re´seau a` re-construire inutilement les clusters. +Comme mentionne´ dans le chapitre 2, diffe´rentes me´triques ont e´te´ utilise´es pour le +choix des cluster-heads dans les algorithmes de clustering. L’identifiant des nœuds +e´tant immuable, il permet de conserver les chefs de cluster tre`s longtemps. Cependant +de tels clusters sont inde´pendants de la topologie sous-jacente et ne sont pas toujours +adapte´s. Le degre´ des nœuds s’ave`re l’une des me´triques les plus adapte´es, l’ide´e e´tant +23 +24 CHAPITRE 3. ALGORITHME DE CLUSTERING +qu’un chef de fort degre´ permet de couvrir un grand nombre de nœuds, ce qui per- +met d’en minimiser le nombre. Cependant, un mouvement individuel d’un nœud dans +des clusters base´s sur cette me´trique peut conduire a` une re´-organisation comple`te du +re´seau, alors que la structure globale du re´seau reste inchange´e. +Base´s sur cette constatation, nous avons introduit une nouvelle me´trique, que nous +avons appele´e densite´. L’ide´e est que, si un petit changement de topologie intervient +dans le voisinage d’un nœud, son degre´ δ peut changer alors que globalement son +voisinage est conserve´. Notre me´trique est une densite´ de liens et cherche a` lisser les +petits changements de topologie qui interviennent au niveau individuel d’un nœud, tout +en permettant aux clusters de s’adapter a` la topologie sous-jacente. +3.2 La me´trique de densite´ +La k-densite´ d’un nœud, note´e ρk(u), est le ratio du nombre de liens par le nombre de +nœuds dans le k-voisinage d’un nœud. +De´finition 1 (densite´) La k-densite´ d’un nœud u ∈ V est +|e = (v, w) ∈ E |w ∈ {u,Γk(u)} et v ∈ Γk(u)| +ρk(u) = +δk(u) +La 1-densite´ (e´galement note´e ρ(u)) est donc le rapport entre le nombre de liens entre +u et ses voisins plus le nombre de liens entre les voisins de u et le nombre de ses voisins +(par de´finition, son degre´). +Afin d’illustrer cette me´trique, prenons l’exemple repre´sente´ sur la Figure 3.1. +Conside´rons le nœud p et calculons sa 1-densite´ ρ(p). ρ(p) est le ratio entre le nombre +d’areˆtesL(p) et le nombre de nœuds (|Γ(p)|) dans le 1-voisinage Γ(p) de p. Les nœuds +de Γ(p) sont les nœuds gris fonce´ (Γ(p) = {a, b, c, d, e, f}). L(p) repre´sente alors le +nombre de liens entre p et ces nœuds (liens en pointille´s) et le nombre de liens entre ces +nœuds (liens tiret). Ainsi, L(p) = 4 + 6 = 10 et δ(p) = 6 d’ou` ρ(p) = 10/6 = 5/3. +On remarquera que pour calculer ρk(p), p doit connaıˆtre Γk+1(p) afin de connaıˆtre les +liens existant entre ses k-voisins. +3.3 La formation des clusters +Chaque nœud u surveille son voisinage et juge ainsi de sa mobilite´ relative. Si cette +dernie`re n’est pas trop importante, alors u participe a` l’algorithme de clustering, si- +non, il reste un nœud inde´pendant. L’ide´e est qu’un nœud trop mobile ne pourra pas +instancier de communications avec les autres entite´s du re´seau. Il n’a donc pas besoin +d’appartenir a` un cluster puisqu’il ne pourrait pas en tirer avantage. De meˆme, si un +3.3. LA FORMATION DES CLUSTERS 25 +b a +p f +c +d e +FIG. 3.1 – Illustration de la me´trique de densite´. +nœud trop mobile est pris en compte dans la construction des clusters, il risque de +casser la structure inutilement de par les nombreuses cassures de liens induites par sa +forte mobilite´ et obligera le re´seau a` reconstruire les clusters. Cette valeur de mobilite´ +relative d’un nœud u peut eˆtre calcule´e en ve´rifiant la constance du voisinage de u, en +conside´rant par exemple le nombre de nœuds restant dans le voisinage de u pendant un +certain temps. +Pe´riodiquement, chaque nœud suffisamment stable calcule sa densite´ et la diffuse lo- +calement a` son 1-voisinage. Chacun est alors en mesure de comparer sa propre densite´ +a` celle de ses voisins ”suffisamment stables”. A` partir de la`, un nœud de´cide soit de +s’e´lire comme cluster-head (s’il posse`de la plus forte densite´), soit de choisir comme +pe`re son voisin de plus forte densite´. En cas d’e´galite´, afin de privile´gier la stabilite´ +de la structure, le nœud choisi sera celui de´ja` e´lu au tour pre´ce´dent s’il est en course, +sinon celui de plus petit identifiant. De cette fac¸on, deux voisins ne peuvent pas eˆtre +tous deux cluster-heads. Cette me´thode d’e´lection construit implicitement une foreˆt +couvrante oriente´e. +Si un nœud u choisit le nœud w, on dit que w est le pe`re de u (note´ P(u) = w) +dans l’arbre de clustering et que u est un fils de w (note´ u ∈ Ch(w)). Si aucun nœud +n’a e´lu le nœud u comme pe`re (Ch(u) = ∅), u est une feuille d’un des arbres, sinon, +u est qualifie´ de nœud interne. Le pe`re d’un nœud peut s’eˆtre choisi comme pe`re un +autre nœud de son voisinage et ainsi de suite. Un arbre s’e´tend automatiquement, sans +contrainte sur sa hauteur, jusqu’a` atteindre les frontie`res d’un autre arbre. Tous les +nœuds appartenant au meˆme arbre appartiennent alors au meˆme cluster. Afin d’apporter +une stabilite´ plus importante, un chef de cluster ne doit pas eˆtre trop excentre´ dans son +propre cluster. En effet, si un chef de cluster se trouve a` la frontie`re de son cluster et +qu’il bouge, il a plus de chance d’entrer en compe´tition avec un autre chef et ainsi de +casser les deux clusters. C’est pourquoi, nous ajoutons une re`gle supple´mentaire qui +indique que tout nœud voisin d’un cluster-head doit s’attacher a` ce cluster-head. Si un +nœud est voisin de plusieurs cluster-heads, une fusion est instancie´e entre ces clusters +et le cluster re´sultant a pour chef le cluster-head en compe´tition de plus forte densite´. +De cette fac¸on, deux cluster-heads sont distants de 3 sauts minimum. Supposons un +nœud u voisin d’un chef de cluster H ( H ∈ Γ1(u)) mais qui ne l’a pas choisi comme +pe`re (P(u) 6= H), alors, deux cas sont possibles : +– soit le pe`re de u est e´galement cluster-head ; dans ce cas les deux clusters fusionnent. +26 CHAPITRE 3. ALGORITHME DE CLUSTERING +Le cluster-head final est le nœud le plus fort parmi ceux en compe´tition : P(u). +(Puisque u pouvait choisir entre H et P(u) et a choisi P(u)). H n’est plus cluster- +head, il choisit u comme son pe`re ; +– soit le pe`re de u s’est attache´ a` un autre de ses voisins et n’est pas cluster-head ; cela +signifie que u se situe a` au moins deux sauts de son chef. Il change alors de pe`re et +choisit H. +E´ tant donne´ un nœud v ∈ V , pour tout nœud u ∈ Γ1(v), on de´finit Age(u) +comme le nombre de pe´riodes successives ou` un nœud u a choisi v comme pe`re. On +de´finit e´galement ≺ comme un indicateur d ordre binaire tel que pour (u, v) ∈ V 2’ , , +u ≺ v si et seulement si {ρk(u) < ρk(v)} ou {ρk(u) = ρk(v) ∧Age(u) < Age(v)} +ou {ρk(u) = ρk(v) ∧Age(u) = Age(v) ∧ Id(v) < Id(u)}. +L’algorithme s’auto-stabilise quand chaque nœud connaıˆt l’identite´ de son cluster-head. +Algorithm 1 Formation des clusters +Pour tout nœud u ∈ V +⊲ Initialisation des variables. +H(u) = P(u) = −1 +∀v ∈ Γ1(u), Age(v) = 0 +while ((H(u) = −1) ou (H(u) 6= Hold(u))) +⊲ Boucle jusqu’a` stabilisation +Hold(u) = H(u) +Scrutation du voisinage +Calcul de la valeur de mobilite´ +if (Mobilite < SeuilMobilite) +Re´cupe`re Γk+1(u) +Calcule ρk(u) +Diffuse localement ρk(u) a` ses 1-voisins. +⊲ Cette diffusion locale peut s’effectuer par exemple en ajoutant la valeur de ρk(u) dans +un paquet HELLO. +⊲ A` ce moment, le nœud u connaıˆt la k-densite´ de tous ses voisins et peut choisir son pe`re. +if (∀v ∈ Γ1(u), v ≺ u) then H(u) = u ⊲ u devient cluster-head. +else +⊲ ∃w ∈ Γ1(u) t.q.∀v ∈ {u} ∪ Γ1(u), v ≺ w +P(u) = w +H(u) = H(w) +⊲ Soit P(w) = H(w) = w donc u est directement lie´ a` son chef de cluster, soit w +a choisi un autre nœud x comme pe`re (∃ x ∈ Γ1(w) | P(w) = x) et re´cursivement +H(u) = H(w) = H(x). +end +if ((H(u) = u) et (∃v ∈ Γ1(u) | P(v) 6= u)) then +⊲ u est cluster-head, mais tous ses voisins ne l’ont pas choisi comme pe`re. +if (P(v) = H(v)) then +⊲ Au moins deux cluster-heads (H(u) et H(v)) ont un voisin commun v. Si P(v) = +H(v) alors u ≺ H(v). u s’e´crase et choisit v comme pe`re (les clusters C(u) et C(v) +fusionnent). +P(u) = v et H(u) = H(v) +Age(v)++ et ∀w ∈ Γ1(u), Age(w) = 0. +end +3.3. LA FORMATION DES CLUSTERS 27 +end +if (∃v ∈ Γ1(u) t.q. {(H(v) = v) et (H(P(u)) 6= H((u))}) +⊲ u n’est pas chef et est a` plus de 2 sauts de son chef (son pe`re n’est pas chef) alors qu’il +compte un chef parmi ses voisins. Il change de pe`re. +P(u) = v et H(u) = v +Age(v)++ et ∀w ∈ Γ1(u)Age(w) = 0. +end +Diffuse localement P(u) et H(u) +end +Exemple +Afin d’illustrer cette heuristique, exe´cutons l’Algorithme 1 sur le graphe de la figure 3.2 +en conside´rant la 1-densite´. Dans le 1-voisinage du nœud a, on a deux voisins (Γ1(a) = +{d, i}) et deux liens ({(a, d), (a, i)}), d’ou` ρ(a) = 1 ; le voisinage du nœud b compte +4 voisins (Γ1(b) = {c, d, h, i}) et cinq liens ({(b, c), (b, d), (b, h), (b, i), (h, i)}), d’ou` +ρ(b) = 54 . La table 3.1 montre les valeurs finales des densite´s des nœuds. +c b h e +j +l +d +g +i +a k +f m +FIG. 3.2 – Exemple. +Nœuds a b c d e f g h i j k l m +Degre´ 2 4 1 4 2 2 2 3 4 2 4 2 2 +Nb Liens 2 5 1 5 2 3 2 4 5 3 5 3 3 +Densite´ 1 1.25 1 1.25 1 1.5 1 1.33 1.25 1.5 1.25 1.5 1.5 +TAB. 3.1 – Densite´ des nœuds du graphe de la figure 3.2. +Dans cet exemple, le nœud c e´lit son voisin b (P(c) = b) dont la densite´ est la plus +forte dans Γ1(c) ∪ {c} (∀v ∈ Γ1(c) ∪ {c} , v ≺ b). Le nœud de plus forte densite´ +dans le voisinage de b est h, d’ou` P(b) = h. Comme h a la plus forte densite´ dans +son voisinage, il devient son propre pe`re et donc cluster-head : H(h) = h. Le nœud +c choisit b qui choisit h et tous trois appartiennent au meˆme cluster de cluster-head +h et donc : H(c) = H(b) = H(h) = h. ρ(j) = ρ(f) : ni j ni f n’e´taient choisis +auparavant, c’est donc le plus petit identifiant qui tranche. Supposons j ≺ f , alors +P(j) = f et P(f) = f d’ou`H(f) = H(j) = f . Aucun nœud n’ayant choisi a, j, c, e, +i, g et m comme pe`re, ils deviennent des feuilles. Finalement, nous obtenons une foreˆt +couvrante du re´seau, compose´e de trois arbres de racines h, l et f (figure 3.3(a)), qui +donnent naissance a` trois clusters (figure 3.3(b)). +28 CHAPITRE 3. ALGORITHME DE CLUSTERING +c b h e c b h e +j j +l l +d d +g g +i i +a k a k +f m f m +(a) Arbres de clustering. (b) Clusters. +FIG. 3.3 – Arbres (a) et clusters (b) construits avec l’Algorithme 1 sur le graphe de la +figure 3.2 (Les cluster-heads/racines apparaissent en blanc). +3.4 Maintenance de la structure +La maintenance de cette structure construite a` partir de l’heuristique de la k-densite´ +est simple, e´tant donne´ que chaque nœud n’a besoin que de son k + 1-voisinage pour +la construire. En effet, d’apre`s la taxonomie e´tablie par [81], un algorithme peut eˆtre +qualifie´ de local si chaque nœud n’a besoin que de la connaissance de son 1 et 2 voi- +sinage pour l’exe´cuter, ou de quasi-local, si les nœuds ne´cessitent une information +dans un voisinage borne´. Cela implique une maintenance rapide. Chaque nœud calcule +pe´riodiquement ses valeurs de mobilite´ et de densite´. S’il est suffisamment stable, il +compare sa densite´ a` celle de ses voisins et choisit pe´riodiquement son pe`re. Un nœud +non stable a` l’origine et dont le voisinage se stabilise peut ainsi s’attacher a` la structure +sans la de´truire. +3.5 Analyse de la me´trique +Dans cette section, nous nous sommes inte´resse´s aux diffe´rentes caracte´ristiques de +notre me´trique de densite´. +Dans un premier temps, nous avons calcule´ sa valeur the´orique moyenne a` l’aide de la +ge´ome´trie stochastique et des calculs de Palm. Puis, nous avons compare´ les diffe´rentes +k-densite´s. Nous verrons ainsi que la 1-densite´ est non seulement la densite´ la moins +couˆteuse mais e´galement la plus stable face a` la mobilite´ des nœuds et que les cluster- +heads se´lectionne´s agissent comme des bassins d’attraction. Nous terminerons cette +partie par une analyse de la re´partition des valeurs de densite´ parmi les nœuds du +re´seau. +3.5.1 Recherche de la meilleure k-densite´ +Nous nous sommes interroge´s sur les diffe´rentes k-densite´s : laquelle est la plus +ade´quate ? En effet, nous avons vu que pour calculer une k-densite´, chaque nœud doit +connaıˆtre son k+1 voisinage. Ainsi, plus k augmente, plus la k-densite´ est couˆteuse en +3.5. ANALYSE DE LA ME´TRIQUE 29 +messages, utilisation de bande passante et latence. C’est pourquoi, nous avons compare´ +par simulation les structures forme´es par la 1-densite´ et la 2-densite´. +Comme le montre la table 3.2, la 2-densite´ construit moins de clusters que la 1-densite´. +Un nœud est plus excentre´ dans son cluster avec k = 2. Ne´anmoins, ces caracte´ristiques +tre`s similaires ne nous permettent pas de trancher entre les diffe´rentes densite´s. C’est +pourquoi, nous avons e´galement compare´ le comportement des structures obtenues +avec les densite´s 1 et 2 face a` la mobilite´ des nœuds. En effet, la densite´ la plus +inte´ressante sera celle qui offre la meilleure stabilite´, c.a`.d qui reconstruit moins sou- +vent les clusters lorsque les nœuds se de´placent, limitant ainsi les e´changes de messages +de controˆle et de mise a` jour des tables de routage. Un nœud peut quitter son cluster et +migrer dans un autre sans que cela ne casse la structure de clusters. +750 nœuds 3000 nœuds 5000 nœuds +k-densite´ 1 2 1 2 1 2 +Nb clusters 4.67 3.01 4.23 2.53 4.42 2.43 +D(C) 7.1 9.72 9.25 11.67 9.4 12.15 +e˜(u/C) 4.86 6.45 6.21 7.03 6.02 8.42 +TAB. 3.2 – Comparaison des k-densite´s. +Pour cela, nous avons simule´ un re´seau ou` les nœuds peuvent choisir ale´atoirement +de bouger a` diffe´rentes vitesses allant de 0 a` 1.6m/s (pie´tons) dans des directions +ale´atoires (Mode`le de mobilite´ Random Way Point) pendant 500s . La table 3.3 donne +le nombre moyen de reconstructions de clusters durant la simulation. +Moy Min Max +1-densite´ 7.5 2 13 +2-densite´ 9.4 4 14 +TAB. 3.3 – Nombre de clusters re-contruits apre`s mobilite´ des nœuds. +La 2-densite´ reconstruit plus souvent la structure que la 1-densite´. La 1-densite´ s’ave`re +donc la densite´ la plus robuste et la moins couˆteuse puisqu’elle ne ne´cessite la connais- +sance que du 2-voisinage d’un nœud, tout comme dans OLSR. De plus, utiliser une +k-densite´ avec k > 2 serait trop couˆteux et impliquerait une maintenance moins effi- +cace. C’est pourquoi, par la suite, on ne conside´rera que la 1-densite´. +3.5.2 Densite´ moyenne +Nous analysons ici la 1-densite´ moyenne ρ˜(u) d’un nœud u. On conside`re un re´seau +sans fil multi-sauts ou` les nœuds sont distribue´s suivant un processus de Points de Pois- +son d’intensite´ constante λ. Nous calculons alors la 1-densite´ moyenne en conside´rant +une distribution de Palm. Dans une telle distribution, un nœud 0 est artificiellement +30 CHAPITRE 3. ALGORITHME DE CLUSTERING +ajoute´ a` la distribution poissonienne. Ce nœud 0, place´ a` l’origine du plan, sert de base +d’observation pour les calculs. Sous la probabilite´ de Palm, ce nœud existe presque +suˆrement. Puisque le processus est stationnaire, la densite´ moyenne de 0 est valide +pour tout autre point du processus. +Soit ρ(0) la densite´ moyenne du nœud 0. Φ de´signe le processus ponctuel : Φ(S) +repre´sente le nombre de points du processus se trouvant sur une surface S donne´e. +S i l b l d d y ′o t B(u,R) a ou e e centre u et e ra on R et Bu la boule centre´e en u de rayon +R prive´e du singleton {u} ′: B = B(u,R)\ {u} o et o, u . E P de´signent respectivement +l’espe´rance et la probabilite´ sous la distribution de Palm. +Nous cherchons donc a` calculer la densite´ moyenne ρ˜(u) = oE [ρ(0)] d’un nœud quel- +conque u. +Lemme 1 La 1-densite´ moyenne d(e tout nœud)u s’e´crit :√ ( − {− })o 1 3 3 1 exp λpiR2ρ˜(u) = E [ρ(0)] = 1 + pi − λR2 − +2 4 pi +La preuve de ce lemme est donne´e en annexes 3.11.1. L’ide´e est de compter le nombre +de liens dans le voisinage d’un nœud. Un lien existe entre deux nœuds s’ils sont a` +une distance infe´rieure ou e´gale a` R. Si v est un voisin de u, alors, il existe autant +de liens entre v et un autre voisin de u que de voisins communs a` u et v (nœuds a` +distance infe´rieure a` R a` la fois de u et de v). Le nombre de voisins communs a` u et v +correspond au nombre de points se trouvant a` l’intersection des zones de transmission +de u et v. Cette surface est la zone repre´sente´e en bleu sur la figure 3.4. Par la suite, +nous de´noterons par A(r) cette surface. Le calcul de ρ˜ consiste a` sommer le nombre +de points se trouvant en moyenne dans cette zone pour chacun des voisins v de u en +fonction de la distance euclidienne r de u a` v. Les liens e´tant ainsi compte´s deux fois, +la somme finale est divise´e par deux. +R u v R +r +FIG. 3.4 – Intersection du voisinage de deux nœuds voisins u et v. Les nœuds se trou- +vant dans la zone bleue sont des voisins communs a` u et v. +3.6. ANALYSE DE LA STRUCTURE 31 +Afin de ve´rifier la validite´ de nos re´sultats analytiques, nous avons compare´ les valeurs +de densite´ moyenne obtenues par analyses et par simulation. Le mode`le de simulation +utilise´ est celui de´crit dans le Chapitre 1.1. La table 3.4 donne les re´sultats pour une +valeur de R = 0.1 et diffe´rentes valeurs d’intensite´ λ du processus de Poisson. Notons +que la the´orie et la simulation s’accordent parfaitement. +500 nœuds 600 nœuds 700 nœuds +The´orie Simulation The´orie Simulation The´orie Simulation +δ˜ 15.7 15.3 18.8 18.3 22.0 21.2 +ρ˜ 4.7 5.0 5.6 5.9 6.5 6.8 +800 nœuds 900 nœuds 1000 nœuds +The´orie Simulation The´orie Simulation The´orie Simulation +δ˜ 25.1 25.0 28.3 27.9 31.4 31.0 +ρ˜ 7.5 7.1 8.4 8.6 9.3 9.4 +TAB. 3.4 – Degre´ et densite´ moyens des nœuds. +3.5.3 Re´partition des valeurs de densite´ +La figure 3.5 montre comment les valeurs de densite´ sont re´parties. La figure 3.5(a) +donne le nombre de nœuds ayant une valeur de densite´ donne´e. Les barres verticales +indiquent les valeurs prises par les cluster-heads. La figure 3.5(b) donne un exemple +de distribution des densite´s dans le plan. Les cluster-heads apparaissent en bleu. Plus +la couleur des nœuds est jaune, plus leur densite´ est forte. Nous pouvons constater que +dans chaque cluster, les densite´s les plus fortes se situent autour des chefs de cluster. +Plus un nœud est loin d’un cluster-head, plus sa densite´ est faible. Les cluster-heads +forment des sortes de bassin d’attraction, ce qui apporte une stabilite´ a` la structure. +3.6 Analyse de la structure +Afin de pouvoir au mieux utiliser la structure de clusters forme´e par notre heuristique, +nous en avons e´tudie´ certaines caracte´ristiques par simulation et quand nous le pou- +vions, par analyse the´orique en utilisant la ge´ome´trie stochastique. +3.6.1 Analyse the´orique du nombre de clusters +Dans cette section, nous avons cherche´ a` calculer analytiquement le nombre de clus- +ters (ou de cluster-heads) produit par l’algorithme de clustering (algorithme 1). Comme +pour le calcul de la densite´ moyenne (section 3.5.2), nous utilisons la ge´ome´trie sto- +chastique suivant le mode`le de´fini dans la section 1.1. +32 CHAPITRE 3. ALGORITHME DE CLUSTERING +(a) Histogramme. Nombre de nœuds du re´seau ayant une (b) Plus la couleur est rouge, plus la +densite´ donne´e. densite´ est grande. Cluster-heads en +bleu. +FIG. 3.5 – Distribution des valeurs de densite´ parmi les nœuds. Les cluster-heads ap- +paraissent en bleu. Plus la couleur des nœuds est jaune, plus leur densite´ est forte. +Nous utilisons les meˆmes notations et la meˆme mode´lisation que pre´ce´demment, a` +savoir que l’on conside`re un re´seau sans fil multi-sauts ou` les nœuds sont distribue´s +suivant un processus ponctuel de Poisson Φ d’intensite´ constante λ. +On cherche dans un premier temps a` calculer le nombre de clusters (ou cluster-heads) +dans un espace C. +Lemme 2 Le nombre moyen de cluster-heads appartenant a` un domaine C est : +[Nombre de cluster heads dans C] = λν(C) oE - PΦ (0 est chef ) +ou` ν(C) repre´sente la mesure de Lebesgue1 dans IR2. +Pour de´terminer le nombre moyen de cluster-heads, il nous faut donc dans un premier +temps calculer oPΦ (0 est chef ), probabilite´ qu’un nœud soit chef. Les nœuds e´tant dis- +tribue´s uniforme´ment et inde´pendamment, cette probabilite´ est la meˆme pour tous les +nœuds. Cela revient a` calculer la probabilite´ qu’un nœud ait la plus forte densite´ dans +son voisinage. +Lemme 3 La probabilite´ qu’un point 0 so(it chef sous la probabilite´ d)e Palm est : +o o +PΦ (0 est chef) = PΦ ρ(0) > max ρ(Yk) +k=1,..,Φ(B0) +Nous avons cherche´ a` calculer cette quantite´ mais n’avons pu obtenir qu’une borne +supe´rieure. +1La mesure de Lebesgue sur IR d’un intervalle coı¨ncide avec sa longueur, la mesure de Lebesgue d’une +re´gion de l espace sur IR2’ coı¨ncide avec la surface de cet espace. Pour une de´finition plus formelle, se re´fe´rer +a` [76], chapitre 1. +3.6. ANALYSE DE LA STRUCTURE 33 +Conjectu(re 1 Une borne supe´rieure)pou(r la probabili∑+∞ ( +te´ qu’u)n n)œud soit chef est : +1 λpiR2 +n +o 2 +PΦ ρ(0) > max ρ(Yk) ≤ 1 + exp {−λpiR } +k=1,..,Φ(B0) n n! +n=1 +Les de´tails du calcul sont donne´s en annexes 3.11.2. L’ide´e est dans un premier temps +de conditionner la probabilite´ que 0 soit chef par le fait qu’il ait ou non des voisins. Si +0 n’a pas de voisin, 0 est chef avec la probabilite´ 1. Dans le cas contraire, on majore +cette probabilite´ par la probabilite´ qu’un voisin v de 0 ait la plus forte densite´ parmi +Γ(0), les voisins de 0, probabilite´ que l’on peut calculer sous Palm. +La figure 3.6 repre´sente la borne supe´rieure du nombre de clusters pour diffe´rentes +valeurs de R et de λ (avec R diminuant de bas en haut). On peut voir que lorsque +que l’intensite´ des nœuds augmente, la borne supe´rieure du nombre de clusters tend +asymptotiquement vers une constante, ce qui permet a` notre structure de supporter le +passage a` l’e´chelle du re´seau. +Upper bound of the number of clusters in function of the process intensity +160 +140 +120 +100 +80 +60 +40 +500 1000 1500 2000 2500 3000 +lambda +FIG. 3.6 – Borne supe´rieure du nombre de clusters en fonction de λ (en abscisse) et de +R (diffe´rentes courbes : de bas en haut R = 0.1, 0.09, 0.08, 0.07, 0.06, 0.05 m). +3.6.2 Caracte´ristiques des clusters +Les re´sultats donne´s dans cette section ont e´te´ obtenus par simulation, en utilisant le +mode`le de´crit dans la section 1.1. La table 3.5 re´sume les caracte´ristiques principales +des clusters pour R = 0.1 et diffe´rentes valeurs de λ. +On remarquera que malgre´ l’augmentation de l’intensite´ des nœuds, l’excentricite´ +moyenne e˜(u/C) d’un nœud dans son cluster et la hauteur moyenne des arbres de +clustering restent constante, du fait du nombre constant de clusters. Ceci va s’ave´rer +eˆtre un atout lors de l’utilisation de notre structure pour effectuer une diffusion (cf. +chapitre 4) ou pour router sur cette structure (cf. chapitre 5). Nous pouvons e´galement +noter qu’une grande partie des nœuds sont des feuilles dans l’arbre de clustering (en- +viron 75%). Comme nous le verrons dans le chapitre 4, cette proprie´te´ va elle aussi +s’ave´rer fort utile lors d’une diffusion d’un message sur une telle structure. +34 CHAPITRE 3. ALGORITHME DE CLUSTERING +500 nœuds 600 nœuds 700 nœuds +# clusters/arbres 11.76 11.51 11.45 +e˜(u/C) 3.70 3.75 3.84 +e˜(H(u)/C(u)) 3.01 3.09 3.37 +Hauteur des arbres 3.27 3.34 3.33 +% feuilles 73,48% 74,96% 76,14% +Degre´ dans l’arbre des nœuds non feuilles 3.82 3.99 4.19 +Voronoı¨ : distance euclidienne 84.17% 84.52% 84.00% +Voronoı¨ : nombre de sauts 85.43% 84.55% 84.15% +800 nœuds 900 nœuds 1000 nœuds +# clusters/arbres 11.32 11.02 10.80 +e˜(u/C) 3.84 3.84 3.84 +e˜(H(u)/C(u)) 3.17 3.19 3.23 +Hauteur des arbres 3.34 3.43 3.51 +% feuilles 76,81% 77,71% 78,23% +Degre´ dans l’arbre des nœuds non feuilles 4.36 4.51 4.62 +Voronoı¨ : distance euclidienne 83.97% 83.82% 83.70% +Voronoı¨ : nombre de sauts 83.80% 83.75% 83.34% +TAB. 3.5 – Caracte´ristiques des clusters. +Forme des clusters. +Comme le montre la figure 3.7, les clusters ressemblent a` un diagramme de Vo- +ronoı¨ construit autour des chefs de clusters. Si S est un ensemble de n sites de l’espace +euclidien, pour chaque site p de S, la cellule de Voronoı¨ V (p) de p est l’ensemble des +points de l’espace qui sont ge´ographiquement plus proches de p que de tous les autres +sites de S. Le diagramme de Voronoı¨ de V (S) est la de´composition de l’espace en +cellules de Voronoı¨ des sites de l’espace. +Ainsi, cela signifierait qu’e´tant donne´s les cluster-heads, un nœud s’est attache´ a` celui +le proche de lui en distance euclidienne. Afin d’e´valuer cette caracte´ristique, nous avons +mene´ des simulations pour connaıˆtre le pourcentage de nœuds se situant dans la cellule +de Voronoı¨ de leur chef et e´tant donc plus pre`s de lui que de tout autre chef en distance +euclidienne. De plus, comme dans un re´seau sans fil, on ne conside`re pas la distance +euclidienne mais la distance en nombre de sauts, nous avons e´galement regarde´ quelle +proportion de nœuds e´taient plus proches en nombre de sauts de leur propre chef plutoˆt +que de tout autre. Les re´sultats nume´riques sont donne´s dans la table 3.5. La figure 3.8 +donne pour une topologie de clusters (figure 3.8(a)) la proportion des nœuds se situant +dans la ”bonne” cellule de Voronoı¨ en distance euclidienne (figure 3.8(b)) et en nombre +de sauts (figure 3.8(c)). On remarquera que plus de 80% sont plus proches de leur +cluster-head que d’un autre aussi bien en distance euclidienne qu’en nombre de sauts. +Ceci pre´sente un avantage e´galement pour la diffusion d’un message dans un cluster, +comme nous le verrons plus tard dans le chapitre 4. +3.6. ANALYSE DE LA STRUCTURE 35 +1 +0.9 +0.8 +0.7 +0.6 +0.5 +0.4 +0.3 +0.2 +0.1 +0 +0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 +1 +0.9 +0.8 +0.7 +0.6 +0.5 +0.4 +0.3 +0.2 +0.1 +0 +0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 +FIG. 3.7 – Structure de clusters (sche´mas de gauche) et diagramme de Voronoı¨ corres- +pondants (sche´mas de droite) pour λ = 1000 et λ = 500. +(a) Topologie (b) Voronoı¨ euclidien (c) Voronoı¨ sauts +FIG. 3.8 – Pour une structure de clusters (a), les nœuds dans la ”bonne” cellule de +Voronoı¨ en distance euclidienne (b) ou en nombre de sauts (c) apparaissent en noir. +36 CHAPITRE 3. ALGORITHME DE CLUSTERING +3.7 Comparaison a` d’autres heuristiques +Dans le but d’e´valuer notre heuristique et d’eˆtre en mesure de la situer parmi les +heuristiques existantes, nous la comparons a` d’autres heuristiques de la litte´rature : +DDR [59] et Max-Min d-cluster [4]. Ces heuristiques, de´crites dans le chapitre 2 +construisent des clusters dont le rayon est supe´rieur a` 1 saut comme notre heuristique. +Max-Min d-cluster utilise l’identifiant des nœuds mais cherche a` ne pas toujours fa- +voriser l’identifiant le plus fort et ainsi e´viter que les plus grands identifiants soient +toujours cluster-heads. DDR, quant a` lui, est tre`s semblable a` notre algorithme mais +se base sur le degre´ des nœuds. +3.7.1 Comparaison avec DDR +L’heuristique de DDR [59] construit des clusters de fac¸on assez similaire a` la noˆtre +mais utilise le degre´ des nœuds comme me´trique au lieu de la densite´. Tout comme dans +notre cas, le rayon des clusters n’est pas fixe´ a` l’avance et s’adapte automatiquement a` +la topologie sous-jacente. Le degre´ est moins couˆteux que la densite´ puisqu’il ne´cessite +la connaissance du 1-voisinage seulement. C’est pourquoi, nous avons voulu comparer +les structures de clusters obtenues pour chacune des heuristiques. +(a) Clusters DDR (b) Clusters Densite´ +FIG. 3.9 – Exemple de structure obtenue pour λ = 1000 et R = 0.1 avec DDR (a) et +avec la 1-densite´ (b). +Nb clusters Nb nœuds par cluster D˜(C) e˜(u/C) +DDR 10.0 100 5.8 4.2 +densite´ 11.1 90.9 5.0 3.8 +TAB. 3.6 – Comparaison des clusters de DDR et de ceux obtenus par notre heuristique. +3.7. COMPARAISON A` D’AUTRES HEURISTIQUES 37 +Les re´sultats sont donne´s par la figure 3.9 et la table 3.6. On remarquera que les struc- +tures sont tre`s semblables. Nous avons alors compare´ la robustesse des structures face +a` la mobilite´ des nœuds. Afin de permettre le passage a` l’e´chelle de la structure et de +limiter les e´changes entre les nœuds, les chefs de cluster doivent rester chefs aussi long- +temps que possible tout en maintenant des clusters adapte´s a` la topologie sous-jacente. +Les auteurs de [66] donnent la de´finition suivante de la robustesse : ”one measure of ro- +bustness of the topology is given by the maximum number of nodes that need to change +their topology information as a result of a movement of a node 2” . C’est pourquoi, +nous avons mene´ des simulations en appliquant une mobilite´ sur les nœuds et releve´ +la proportion de chefs e´tant re´-e´lus. Plus ce ratio est grand, moins importants sont les +changements des informations des tables de routage des nœuds. +Dans nos simulations, chaque nœud peut bouger ale´atoirement dans une direction +ale´atoire a` une vitesse ale´atoire allant de 0 a` 10m/s (mode`le voiture) et de 0 a` 1.6m/s +(mode`le pie´ton) durant 15 minutes (Mode`le Random Way Point). La table 3.7 donne le +pourcentage de cluster-heads re´-e´lus toutes les 2 secondes par chacune des heuristiques. +Les re´sultats montrent qu’en moyenne, notre heuristique reconstruit moins souvent les +clusters que DDR. Elle s’ave`re donc eˆtre plus robuste. +500 nœuds 600 nœuds 800 nœuds 1000 nœuds +ρ DDR ρ DDR ρ DDR ρ DDR +1.6m/s 68.7% 65% 67.2% 63.5% 64.5% 62.4% 62.2% 56.8% +10m/s 30.1% 27.5% 27% 25.3% 26.2% 23.1% 24.8% 20.35% +TAB. 3.7 – % de cluster-heads re´-e´lus. +De par la mobilite´ des nœuds, un nouveau nœud peut apparaıˆtre dans le voisinage +d’un autre. De fac¸on a` comprendre pourquoi la me´trique de densite´ est plus stable que +le degre´ utilise´ par DDR, nous avons analyse´ comment le voisinage d’un nœud est +perturbe´ par l’apparition de ce nouveau nœud. La structure de clusters se re-construit si +le nœud qui avait le plus fort degre´ ou la plus forte densite´ dans son voisinage se trouve +un voisin dont le degre´ ou la densite´ est devenu(e) plus fort(e) que le/la sien(ne), donc +si l’ordre des degre´s ou densite´s entre les nœuds a change´. +Nous conside´rons un processus ponctuel de Poisson d’intensite´ λ, distribue´ dans une +boule de rayon 2R centre´e en un point 0 : B(0, 2R). Nous conside´rons alors le degre´ et +la densite´ de ce point 0 ainsi que ceux d’un de ses voisins y choisi arbitrairement. Nous +ajoutons alors le nœud mobile u dans le voisinage de 0. u est un nœud uniforme´ment +distribue´ dans B(0, R). Nous pouvons alors calculer la probabilite´ que l’ordre des +degre´s de 0 et y change a` cause de la pre´sence de u. Cela ne peut se faire que si u +n’est pas voisin de y et si δ(0) = δ(y) ou δ(0) = δ(y)− 1. En effet, si u est voisin a` la +fois de 0 et de y, l’ordre ne changera pas. Si u n’est voisin que de 0 et si δ(0) > δ(y), +seul le degre´ de 0 augmente, ce qui ne change pas l’ordre. De meˆme si δ(0) < δ(y)−1, +meˆme si le degre´ de 0 augmente de 1, il reste infe´rieur a` δ(y). +2Une mesure de la robustesse de la topologie est donne´e par le nombre maximum de nœuds qui doivent +changer leur information sur la topologie pour le mouvement d’un nœud. +38 CHAPITRE 3. ALGORITHME DE CLUSTERING +Soit C une variable de´signant la re´gion du plan B(0, R)\B(y,R). C correspond a` la +zone de voisinage du nœud 0 dans laquelle les nœuds ne sont pas voisins de y (Voisi- +nage de 0 non colore´ sur la figure 3.4 ou` on prend u = 0 et v = y). ν(C) est la mesure +de Lebesgue de C = B(0, R)\B(y,R). +La probabilite´ P1 que u ne soit voisin que du nœud 0 revient a` la probabilite´ que u se +t d l d C D P = ν(C)rouve ans a zone e . ’ou` : 1 piR2 . +La probabilite´ P2 que δ(0) = δ(y) est la probabilite´ que 0 et y aient autant de voisins +non communs avant l’arrive´e de u. D’ou` : +∑∞ +P2 = P(Φ(B(0, R)\B(y,R)) = k)× P(B(y,R)\B(0, R) = k) +k∑=0∞ λ2kν(C)2k += exp−2λν(C) +k!k! +k=0 +La probabilite´P3 que δ(0) = δ(y)−1 est la probabilite´ que y ait un voisin non commun +avec 0 en plus de 0. D’ou` : +∑∞ +P3 = P(Φ(B(0, R)\B(y,R)) = k)× P(Φ(B(y,R)\B(0, R)) = k + 1) +k∑=0∞ λ2k+1ν(C)2k+1 += exp−2λν(C) +k!(k + 1)! +k=0 +A` partir de la`, pour obtenir la probabilite´ Pp que l’ordre change, il nous faut faire la +moyenne sur tous les points y, en multipliant par la probabilite´ que y existe, c.a`.d. par +la probabilite´ P(Φ(B(0, R)) > 0) que le nœud 0 ait au moins un voisin. Sachant que +y est uniforme´ment distribue´ dans B(0, 2R), la probabilite´ Pp que l’ordre change peut +alors s’e´crire : +Pp = E [P1(P2 + P3)]P( (Φ(B(0, R)) > 0)− {− })= E [[P1(P2 + P )] 1 exp λpiR2∑ 3 ]+∞ 2nν(C) (λν(C)) λν(C) ( − {− })= E (1 + ) 1 exp λpiR2 +piR2 n!n! n+ 1 +n=0 +Malheureusement, nous n’avons pas e´te´ en mesure de donner un re´sultat analytique +donnant la probabilite´ que l’ordre des densite´s des nœuds 0 et y soit perturbe´ par l’ar- +rive´e du nœud u. Ne´anmoins, nous avons obtenu une approximation par simulation. La +figure 3.10 donne les probabilite´s que l’ordre change pour les deux me´triques (obtenues +par simulation) et la probabilite´ Pp obtenue analytiquement pour le degre´. +Ces re´sultats correspondent a` ceux obtenus pre´ce´demment dans la table 3.7. La pro- +babilite´ que l’ordre des me´triques change avec l’apparition d’un nœud mobile dans un +voisinage est plus importante pour le degre´ que pour la densite´. Cela tend a` prouver +que la structure base´e sur la densite´ est plus stable que celle base´e sur le degre´. +3.7. COMPARAISON A` D’AUTRES HEURISTIQUES 39 + 0.1 +degree +density +theoritical probability for the degree as metric + 0.09 + 0.08 + 0.07 + 0.06 + 0.05 + 0.04 + 0.03 + 15 20 25 30 35 40 45 50 55 +mean number of neighbors +FIG. 3.10 – Probabilite´ que l’ordre des me´triques change entre deux voisins. +3.7.2 Comparaison avec l’heuristique Max-Min d-cluster +L’heuristique Max-Min d-cluster [4] produit e´galement des clusters dont le rayon est +supe´rieur a` 1. La structure de Max-Min a obtenu de tre`s bons re´sultats de stabilite´. Elle +utilise l’identifiant des nœuds mais tente de contrebalancer le fait qu’un cluster-head +e´lu sur cette me´trique garde son roˆle quasi-inde´finiment, en e´lisant non pas le plus +grand ou plus petit identifiant mais le nœud posse´dant le plus petit identifiant parmi les +plus grands identifiants des nœuds se trouvant a` au plus d sauts de lui. Le parame`tre d +est le rayon des clusters et doit eˆtre fixe´ a priori. +Structure. +Nb clusters Nb de nœuds par cluster D˜(C) e˜(u/C) +densite´ 11.1 90.9 5.0 3.8 +Max-Min 2-cluster 28.6 34.9 3.6 3.1 +Max-Min 3-cluster 13.3 75.2 4.9 3.4 +Max-Min 4-cluster 8.2 122.0 6.5 4.9 +TAB. 3.8 – Caracte´ristiques des clusters de la densite´ et de Max-Min d-cluster. +Dans un premier temps, nous avons simule´ Max-Min d-cluster pour plusieurs valeurs +du rayon d. Les re´sultats donne´s dans la table 3.8 nous montrent que l’heuristique Max- +Min pour d = 3 est la plus proche de notre heuristique. Par la suite, c’est celle que nous +conside´rerons. +La figure 3.11 donne le nombre de clusters produits par notre heuristique et par Max- +Min 3-cluster pour λ = 1000 et diffe´rentes valeurs de R. +On remarquera que le nombre de clusters obtenu est similaire pour les deux me´triques +mais Max-Min 3-cluster construit des clusters plus petits lorsque le re´seau est peu +probabilities +40 CHAPITRE 3. ALGORITHME DE CLUSTERING +55 +MaxMin +Density +50 +45 +40 +35 +30 +25 +20 +15 +10 +5 +60 70 80 90 100 110 120 130 140 150 +Radius (meters) +FIG. 3.11 – Nombre de clusters forme´s pour diffe´rentes valeurs de R avec la densite´ +(−×−) et Max-Min 3-cluster (−+−). +dense. Notre heuristique s’adapte mieux aux re´seaux peu denses puisqu’il produit des +clusters plus adapte´s et en plus petit nombre. De plus, contrairement a` l’heuristique de +Max-Min, notre algorithme n’autorise pas la formation de clusters a` un seul nœud qui +sont inutiles. +Les figures 3.12 (a) et (b) donnent un exemple de structure de clusters obtenue par +simulation par chacune des heuristiques sur une meˆme distribution des nœuds. Dans +les deux cas, les clusters semblent homoge`nes. Les chefs de clusters sont bien re´partis +dans l’espace. +(a) Clusters obtenus par Max-Min 3- (b) Clusters obtenus par notre heuris- +cluster tique +FIG. 3.12 – Exemple d’une structure de clusters pour une topologie a` 1000 nœuds de +rayon de transmission R = 0.1 obtenue avec Max-Min 3-cluster (a) et avec l’heuris- +tique utilisant la densite´ (b). +# of clusters +3.7. COMPARAISON A` D’AUTRES HEURISTIQUES 41 +Comparaison face a` la mobilite´ des nœuds. +De la meˆme fac¸on que pour DDR, nous avons compare´ l’heuristique de Max-Min +et la noˆtre face a` la mobilite´ des nœuds, en effectuant des simulations ou` les nœuds +bougeaient a` diffe´rentes vitesses ale´atoires. Nous avons pu constater que Max-Min d- +cluster re´-e´lit les meˆmes cluster-heads dans plus de 90% des cas. Cela e´tait pre´visible +e´tant donne´ que l’e´lection conside`re l’identite´ des nœuds qui ne change pas lorsque les +nœuds bougent. En se basant seulement sur ces re´sultats, on pourrait donc pre´tendre +que Max-Min est plus stable que notre heuristique. Seulement, l’identifiant des nœuds +e´tant inde´pendant de la topologie sous-jacente, les clusters nouvellement reforme´s ne +sont pas toujours adapte´s a` la topologie. Afin d’e´valuer cela, nous avons conside´re´ plus +en de´tail l’apparition des nœuds. +Dans les re´sultats suivants, pre´sente´s dans la table 3.9, nous conside´rons une topologie +initiale de 500 nœuds dans laquelle apparaissent progressivement de fac¸on ale´atoire, +dix vagues de 100 nouveaux nœuds, avec des identifiants ale´atoires. Ces re´sultats +donnent le pourcentage de cluster-heads re´-e´lus et le pourcentage d’augmentation du +nombre de clusters dans le re´seau. +% cluster-heads re´-e´lus Evolution du nombre de clusters +densite´ 94.3% +0% +Max-Min 3-cluster 100% +46% +TAB. 3.9 – Comparaison de Max-Min 3-cluster et de l’heuristique de densite´ face a` +l’arrive´e des nœuds. +On remarque que meˆme si Max-Min re´-e´lit toujours les meˆmes chefs de cluster, l’heu- +ristique en e´lit e´galement d’autres. L’heuristique de densite´ quant a` elle incorpore les +nouveaux nœuds dans les clusters existants. Le comportement de Max-Min est duˆ au +fait que si un nouveau nœud a un identifiant supe´rieur au chef de´ja` en place, il cre´e´ son +propre cluster en ne modifiant les clusters existants que s’il est dans le voisinage d’un +ancien chef. Dans le cas contraire, les anciens clusters restent inchange´s. Le nouveau +nœud e´tant souvent le seul nœud de son cluster nouvellement forme´. +Comparaison des structures sur des topologies non uniformes. +Enfin, nous avons compare´ les structures obtenues par notre heuristique et Max-Min sur +des topologies de nœuds non uniformes. Les nœuds sont distribue´s autour de quelques +points choisis ale´atoirement qui pourraient repre´senter des villes. Les figures 3.13 (a) +et (b) illustrent une telle topologie. On peut remarquer que notre heuristique ge´ne`re +moins de clusters avec des cluster-heads mieux centre´s. Max-Min ge´ne`re la` aussi des +clusters a` 1 nœud ou des clusters-heads voisins. Par exemple, sur une meˆme topologie +de 1000 nœuds, notre heuristique ge´ne`re 8.7 clusters en moyenne contre 15.25 clusters +pour Max-Min. +42 CHAPITRE 3. ALGORITHME DE CLUSTERING +(a) Clusters obtenus par Max-Min 3- (b) Clusters obtenus par notre heuris- +cluster tique +FIG. 3.13 – Distribution non uniforme de nœuds : clusters obtenus avec Max-Min 3- +cluster (a) et avec la me´trique de densite´ (b). +Complexite´. +L’heuristique de Max -Min d-cluster se compose de 3 phases de diffusion de messages +a` d sauts : une phase re´cupe´rant le plus grand identifiant a` d sauts, une phase re´cupe´rant +le plus petit identifiant parmi les plus grands a` d sauts et enfin une phase pour diffuser +l’identite´ du chef de cluster. Notre heuristique, quant a` elle, est purement locale et +ne ne´cessite qu’une information sur le 2-voisinage obtenue par des messages diffuse´s +uniquement dans le 1-voisinage. Max-Min d-cluster s’ave`re donc plus couˆteux en terme +de messages et de latence que notre algorithme. +3.8 Analyse de l’auto-stabilisation +Comme nous avons pu le constater dans le chapitre 2, il existe de nombreux proto- +coles de clustering pour les re´seaux sans fil. Cependant, seulement tre`s peu ve´rifient +la robustesse de leur algorithme et, meˆme quand c’est le cas, l’e´valuation est mene´e +par simulation et jamais via une analyse the´orique. Dans cette section, nous appliquons +les principes d’auto-stabilisation a` notre algorithme de clustering. L’auto-stabilisation +est la proprie´te´ d’un syste`me a` atteindre seul une configuration dans laquelle il a un +comportement correct, en partant de n’importe quelle configuration arbitraire. A` l’aide +d’une approche the´orique, nous montrons que, sous certaines hypothe`ses, l’algorithme +est auto-stabilisant localement et que le temps de convergence est faible et borne´. Nous +validons ensuite cette proprie´te´ par simulation. +3.8. ANALYSE DE L’AUTO-STABILISATION 43 +3.8.1 Pre´-requis +Nous pre´sentons dans un premier temps les diffe´rentes hypothe`ses. Nous conside´rons +que l’algorithme se stabilise lorsque chaque nœud connaıˆt l’identite´ de son cluster- +head. Le temps de stabilisation est donc lie´ a` la hauteur des arbres de clustering, l’iden- +tite´ du chef devant eˆtre transmise jusqu’aux feuilles de l’arbre. Nous suivons les meˆmes +principes et hypothe`ses que dans [38] : +Hypothe`ses. Nous supposons qu’il existe une constante τ > 0 telle que la probabilite´ +qu’un paquet soit transmis sans collision entre deux nœuds voisins est au moins τ . Cela +implique que nous supposons que tous les nœuds parviennent a` e´mettre avec succe`s +un message en une e´tape de temps de´pendant de τ . Cela correspond aux hypothe`ses +classiques concernant les canaux multi-acce`s [14]. Cette hypothe`se est justifie´e en an- +nexes 3.11.3. Nous supposons e´galement qu’il existe une constante∆ connue, telle que +pour tout nœud u, δ(u) ≤ ∆. Ceci peut eˆtre ve´rifie´ par un controˆle de topologie qui est +en mesure d’ajuster la porte´e de communication ou la puissance de transmission des +nœuds lorsque le re´seau est trop dense. +Notation. Nous de´crivons les algorithmes sous la forme de re`gles garde´es. G → S +repre´sente une telle re`gle, ou` G est un pre´dicat sur les variables locales d’un nœud, +S une affectation de ces meˆmes variables locales. Si le pre´dicat G (la garde) est +vrai, l’affectation S est exe´cute´e, sinon elle est ignore´e. Certaines gardes peuvent eˆtre +de´clenche´es sur e´ve´nement, par exemple lors de la re´ception d’un message. Nous sup- +posons que ces e´ve´nements s’exe´cutent de manie`re atomique lors de la re´ception d’un +message. Pour toute configuration du syste`me, quand une garde G est vraie, G est +dite activable dans cette configuration. L’ope´rateur [] correspond a` la composition non- +de´terministe des re`gles garde´es ; ([]q : q ∈ Mp : Gq → Sq) est une formula- +tion re´duite de l’expression Gq1 → Sq [] Gq → Sq [] · · · [] Gq → Sq , ou`1 2 2 k k +Mp = {q1, q2, . . . , qk}. +Se´mantique de l’exe´cution. L’exe´cution du syste`me consiste pour chaque nœud a` +e´valuer pe´riodiquement ses re`gles garde´es. Nous supposons que chaque re`gle acti- +vable est exe´cute´e en un temps constant (ou ignore´e si la re`gle n’est pas activable). +De manie`re ge´ne´rale, nous conside´rons que lorsqu’un nœud exe´cute son programme, +toutes ses re`gles activables sont effectivement exe´cute´es en un temps constant (par +exemple en suivant le mode`le du tourniquet). +Propagation des variables partage´es. Certaines variables des nœuds sont dites par- +tage´es. Suivant le sche´ma pre´sente´ en [38], les nœuds diffusent pe´riodiquement les +valeurs de leurs variables partage´es. Cela signifie que lorsqu’un nœud affecte une va- +leur a` une variable partage´e, nous supposons que cette instruction est transforme´e de +telle sorte que, d’une part la variable partage´e est re´gulie`rement transmise au voisinage +du nœud, et que d’autre part cette retransmission s’effectue de manie`re probabiliste +pour e´viter les collisions. Une implantation possible peut eˆtre trouve´e dans [38]. Dans +la suite, nous supposons e´galement que le sche´ma de [38] est utilise´ pour obtenir Γ(u) +et Γ2(u) pour chaque nœud u. +44 CHAPITRE 3. ALGORITHME DE CLUSTERING +3.8.2 Construction d’un DAG de hauteur constante +Un DAG ou Directed Acyclic Graph est un graphe simple oriente´ et sans boucle. Dans +notre algorithme, comme dans tout algorithme utilisant l’identifiant des nœuds comme +crite`re de de´cision finale sans contrainte sur le rayon du cluster (comme dans DDR), +le pire cas en terme de stabilisation et de formation de clusters se rencontre quand +tous les nœuds ont la meˆme valeur de de´cision (comme le degre´ ou la densite´) et que +les identifiants des nœuds sont uniques et mal distribue´s. L’algorithme peut alors ne +construire qu’un seul cluster dont le diame`tre est aussi grand que celui du re´seau, le +temps de stabilisation de´pendant de ce diame`tre. De plus, il est e´vident que construire +un tel cluster est inutile puisque nous pourrions tout aussi bien utiliser directement +le re´seau. Pour pallier cet inconve´nient, il peut s’ave´rer utile d’allouer une couleur aux +nœuds, couleur choisie dans un espaceΩ constant et plus petit que celui des identifiants, +de fac¸on a` ce que les couleurs soient localement uniques (dans notre cas, les couleurs +doivent eˆtre uniques a` distance 2 pour qu’un nœud puisse choisir entre deux voisins en +compe´tition) et d’utiliser ces couleurs comme crite`re de de´cision finale. Un DAG peut +alors eˆtre construit a` partir de ces couleurs en orientant les areˆtes entre les voisins de la +couleur la plus grande vers la plus petite. +Notre construction de DAG a` hauteur constante est base´e sur la technique ale´atoire +de´crite dans [38], mais utilise un espace de couleur beaucoup plus petit Ω (|Ω| = +∆6 dans [38] tandis que ∆2, ou meˆme ∆ est suffisant dans notre cas avec ∆ = +maxu∈V δ(u)). +Soit Coloru ∈ Ω une variable partage´e de´signant la couleur du nœud u. Soit +ColorΓ(u) = {)Color v | v ∈ Γ(u)}, ou` )Colorv re´fe`re a` la copie en cache de +la variable partage´e Colorv au nœud u. En d’autres termes, Color v correspond a` la +couleur que u pense que v a. +Supposons que random(S) choisit avec une probabilite´ uniforme un e´le´ment dans un +ensemble S. Le nœud u{utilise la fonction suivante pour calculer Coloru : +)Coloru si )Color ∈6 Color( ) = u Γ(u)newColor Coloru +random(Ω \ ColorΓ(u)) sinon +L’algorithme de construction d’un DAG a` hauteur constante est le suivant : +N1 : VRAI → Coloru := newColor(Coloru) +The´ore`me 1 L’algorithme N1 stabilise avec probabilite´ 1 en un temps constant vers +un DAG de hauteur infe´rieure ou e´gale a` |Ω|+ 1. +Preuve 1 La preuve de ce the´ore`me est similaire a` celle de [38]. Supposons que la +hauteur du DAG soit supe´rieure a` |Ω| + 1. Cela signifie qu’il existe au moins deux +nœuds de meˆme couleur sur une branche du DAG (sur un chemin reliant la racine a` +une feuille). Or, les areˆtes du DAG sont oriente´es en fonction des couleurs des nœuds +qui sont ordonne´es. Si sur la meˆme branche, il existe deux nœuds u et v de meˆme +couleur, cela implique que Coloru < Colorv , ce qui contredit l’hypothe`se d’ordre total +des couleurs.  +3.8. ANALYSE DE L’AUTO-STABILISATION 45 +3.8.3 Analyse de la construction du DAG de couleurs +Nous avons cherche´ a` caracte´riser le DAG que nous construisons et son couˆt. Pour +cela, nous avons analyse´ analytiquement et par simulation le temps de construction +du DAG qui correspond au temps de stabilisation de l’algorithme de coloriage. Nous +avons e´galement mesure´ par simulation l’influence de la taille du domaine des couleurs +Ω sur ce temps de stabilisation et sur la taille du DAG re´sultant. Comme nous allons +le voir, il en ressort qu’un compromis est a` faire pour de´terminer le parame`tre Ω : plus +la valeur de |Ω| est grande, plus le temps de convergence de N1 est faible mais plus la +hauteur du DAG est importante. Une hauteur de DAG importante augmente le temps +de stabilisation des algorithmes qui se basent sur ces DAG. +Analyse the´orique du temps de convergence. +Le temps de convergence de l’algorithme de coloriage N1 correspond au nombre +d’e´tapes ne´cessaires avant que chaque nœud ait une couleur unique dans son voisinage. +Pour mener cette e´tude the´orique, nous nous sommes inspire´s du protocole NAP [21]. +Nous mode´lisons l’algorithme de coloriage par des lance´s successifs de boules dans des +urnes. L’ensemble des couleurs est repre´sente´ par M urnes dans lesquelles L boules +repre´sentant les nœuds sont distribue´es. +L’algorithme de coloriage peut eˆtre mode´lise´ de la fac¸on suivante en termes d’urnes et +de boules : +Algorithm 2 COLORIAGE(L, M ) +⊲ Entre´es : M urnes et L boules +⊲ Pre´-condition : M ≥ L +if (L 6= 0) then +Lance ale´atoirement L boules dans les M urnes ; +Met de coˆte´ toutes les urnes contenant exactement une boule avec leur boule ; +Soit c ≤M le nombre d’urnes isole´es ; +Appelle COLORIAGE(L− c, M − c) ; +end +On remarque qu’une telle analyse ne conside`re que des graphes complets. Dans un +re´seau sans fil qui n’est pas ne´cessairement un graphe complet, deux nœuds voisins (A +et B) n’e´tant pas en conflit mutuel peuvent tout de meˆme tirer une nouvelle couleur +simultane´ment s’ils sont chacun en conflit avec un autre de leur voisin non visible par +A ou B, ce qui n’est pas conside´re´ dans cette analyse. Ainsi, l’e´tude suivante nous +fournit une borne infe´rieure sur le temps de stabilisation de l’algorithme. Cet aspect est +plus de´taille´ dans [55]. +Dans chaque voisinage, le but est alors de n’avoir qu’une seule boule (un nœud) as- +socie´e a` une seule urne donne´e (une couleur). Soit la variable ale´atoire N repre´sentant +le nombre d’ite´rations ne´cessaires pour obtenir une telle configuration. Le temps de +convergence moyen de l’algorithme est l’espe´rance de N : E[N ]. Pour de´terminer +46 CHAPITRE 3. ALGORITHME DE CLUSTERING +E[N ], nous conside´rons une chaıˆne de Markov a` temps discret X = {Xn, n ∈ N} +sur l’espace I = 0, 1, ..., L. Xn = i repre´sente le fait qu’apre`s n transitions, exacte- +ment i boules et urnes ont e´te´ mises de coˆte´. +Nous notonsP(L,M) = (pi,j(L,M))(i,j)∈I2 la matrice de probabilite´ de transition de +la chaıˆne de Markov X . L’espe´rance E[N ] peut eˆtre de´duite du calcul des pi,j(L,M). +pi,j(L,M) repre´sente la probabilite´ d’avoir exactement j urnes de coˆte´ au temps n+1 +sachant que i urnes e´taient de coˆte´ au temps n. pi,j(L,M) peut aussi eˆtre vu comme +la probabilite´ d’obtenir exactement j − i urnes avec exactement une boule en lanc¸ant +L− i boules dans M − i urnes. Nous obtenons donc, pour tout i ≤ j : +pi,j(L,M) = pi,j = p0,j−i(L− i,M − i). (3.1) +X est acyclique et l’e´tatL est un e´tat absorbant. Cela signifie que pour tout i ∈ I−{L} +et tout j ∈ I, pi,j(L,M) = 0 si i > j et pL,L(L,M) = 1. +Graˆce a` la relation 3.1, nous pouvons ne calculer que les valeurs des p0,j−i(L−i,M−i) +pour i ≤ j pour obtenir toutes les valeurs de la matrice P(L,M). +p0,j(L,M) est la probabilite´ d’obtenir exactement j urnes avec exactement une boule +lors du lancer de L boules dans M urnes. Le cas j = L conduit au proble`me des +anniversaires, d’ou` : +M ! +p0,L(L,M) = +(M − L)!ML +Pour j < L, nous proce´dons de la sorte. L boules sont lance´es dans M urnes. On note +K0(L,M) le nombre d’urnes vides et K1(L,M) le nombre d’urnes contenant exacte- +ment une boule. Soit aL,M (k, j) la distribution jointe des deux variables ale´atoires K0 +et K1 : +aL,M (k, j) = P[K0(L,M) = k, K1(L,M) = j] +Les p0,j(L,M) peuvent alors s’e´crire : +∑M +p0,j(L,M) = P[K1(L,M) = j] = aL,M (k, j) +k=0 +Ainsi, afin de calculer la matrice de transition P(L,M), il ne nous reste qu’a` +de´terminer les aL,M (k, j). Pour cela, nous raisonnons par re´currence en conditionnant +le re´sultat du dernier lancer : pour obtenir k urnes vides et j urnes avec exactement une +boule en lanc¸ant L boules dans M urnes il faut qu a` la fin du lancer de la L − 1ieme, ’ +balle : +1. soit avoir k + 1 urnes vides et j − 1 urnes avec exactement une boule et lancer +la dernie`re boule dans une urne vide ; +2. soit avoir k urnes vides et j + 1 urnes avec exactement une boule et lancer la +dernie`re boule dans une urne qui contenait exactement une boule ; +3. soit avoir k urnes vides et j urnes avec exactement une boule et lancer la dernie`re +boule dans une urne qui contenait au moins deux boules. +3.8. ANALYSE DE L’AUTO-STABILISATION 47 +Pour L ≥ 2, on obtient : +k + 1 j + 1 M − (j + k) +aL,M (k, j) = aL−1,M (k+1, j−1)1{j≥1}+ aL−1,M (k, j+1)+ aL−1,M (k, j) +M M M +ou` 1{c} = 1 si la condition c est remplie et 0 sinon. +Les aL,M (k, j) peuvent eˆtre calcule´s par re´cursion en conside´rant que si L = 1 : +a1,M (k, j) = 1{k=M−1, j=1} +On remarque aussi que aL,M (k, j) = 0 si j > L, si k = M ou si j+k > M . De meˆme, +si j = L, on a aL,M (k, L) = 0 pour k 6= M − L et aL,M (M − L,L) = p0,L(L,M). +Une fois la matrice de probabilite´s de transition obtenue, on peut de´terminer la dis- +tribution de N (P [N = n] pour n = 0, . . . ,∞) et sa valeur moyenne E [N ]. Les cal- +culs sont les meˆmes que ceux mene´s dans l’e´tude du protocole NAP. Ils de´rivent des +re´sultats classiques des chaıˆnes de Markov. Nous les utilisons directement ici. +Nous de´finissonsQ la sous-matrice obtenue a` partir deP(L,M), en retirant la dernie`re +ligne et la dernie`re colonne qui correspondent a` l’e´tat absorbant L. +Soit α le vecteur ligne contenant la distribution initiale des probabilite´s des e´tats tran- +sitoires de X . α est tel que α = (P [X0 = i])i=0,...,L−1. La chaıˆne de Markov X +commence en l’e´tat 0 avec la probabilite´ 1, d’ou` α = (1, 0, . . . , 0). +De par les re´sultats classiques des chaıˆnes de Markov, on obtient : +[N = n] = αQn−1P (I −Q)1, pour n ≥ 1, +∑∞ +P [N > n] = αQk−1(I −Q)1 = αQn1, pour n ≥ 0, +k=n+1 +∑∞ +−1 +E [N ] = P [N > n] = α (I −Q) 1 +n=0 +ou` I est la matrice identite´ et 1 le vecteur colonne unite´, tous deux de dimension L. +On note V = (Vi)0≤i≤L−1 le vecteur d’espe´rance conditionnelle de´fini par Vi = +| O − −1E [N X0 = i]. n a V = (I Q) 1. D’ou` E [N ] = αV = V0. Le vecteur V est +solution du syste`me line´aire (I−Q)V = 1. Cela peut s’e´crire e´galement V = 1+QV . +Ainsi, comme la matrice P(L,M) est acyclique, on obtient, pour i = L− 2 . . . , 0 : +L +1 ∑−1 +V = 1 + p V i − i,j j1 pi,i j=i+1 +Comme VL−1,L−1 = 1/(1 − pL−1,L−1), on peut obtenir V0 re´cursivement, et ainsi, +obtenir le temps de convergence moyen E [N ]. +48 CHAPITRE 3. ALGORITHME DE CLUSTERING +Simulations. +Afin de valider nos re´sultats the´oriques et de mesurer l’impact de la taille du domaine +des couleurs Ω sur le temps de convergence et sur la hauteur du DAG, nous avons mene´ +des simulations utilisant plusieurs valeurs de |Ω|. Nous avons simule´ l’Algorithme N1 +tili t | | | | 2en u san Ω = (maxp∈V Γ(p) ) , cette valeur e´tant celle conside´re´e par certains +algorithmes auto-stabilisants base´s sur le coloriage [38]. Nous avons e´galement e´tudie´ +l’Algorithme N1 en utilisant |Ω| = 2 × (maxp∈V |Γ(p)|). De plus, comme dans les +re´seaux sans fil, les nœuds n’ont aucune connaissance globale du re´seau et donc, aucun +moyen a priori de connaıˆtre le plus fort degre´ du graphe, nous avons e´galement mene´ +des simulations en utilisant une taille de domaine de couleur propre a` chaque nœud, +t ll q ∀ ∈ | | | | 2e e ue : p V, Ωp = ( Γ(p) ) . +Nous avons alors conside´re´ le temps de convergence et la taille du DAG induit. +Dans un premier temps, nous avons compare´ les re´sultats the´oriques et de simulation +afin de valider chaque approche. La table 3.10 montre les temps de convergence de +l’algorithme de coloriage a` distance 1 sur une topologie grille ou` chaque nœud interne +a respectivement 4 ou 8 voisins. On remarque que les re´sultats s’accordent. +4 voisins 8 voisins +2 ∗Max Max2 2 ∗Max Max2 +The´orie Simulation The´orie Simulation The´orie Simulation The´orie Simulation +2.14 2.14 1.56 1.61 1.56 1.67 1.15 1.21 +TAB. 3.10 – Temps de stabilisation the´orique et obtenu par simulation avec |Ω| = +(max |N |)2p∈V p ) et |Ω| = 2× (maxp∈V |Np|) dans une grille a` 4 et 8 voisins. +La figure 3.14 montre l’influence de la taille du domaine sur le temps de convergence +et la hauteur du DAG dans le cas d’un coloriage a` distance 1. Les re´sultats montrent +clairement que plus la valeur de |Ω| est grande, plus le temps de convergence de N1 est +faible mais plus la hauteur du DAG est importante. Il y a donc un compromis a` faire +pour de´terminer le parame`tre Ω. +3.8.4 Utilisation des couleurs pour le clustering +Dans cette section, nous re´-e´crivons l’algorithme de clustering avec les re`gles d’auto- +stabilisation. Chaque nœud u maintient deux variables partage´es : ρ(u) et H(u) ou` +ρ(u) est la densite´ du nœud u et H(u) son cluster-head. +Afin d’utiliser le DAG des couleurs dans l’algorithme de clustering, +nous rede´finissons l’ope´rateur d’ordre binaire ≺ de´fini dans la sec- +tion 3 2 de la fac¸on suivante : pour (u, v) ∈ V 2. , u ≺ v si et +seulement si {ρ(u) < ρ(v)} ou {ρ(u) = ρ(v) ∧Age(u) < Age(v)} ou +{ρ(u) = ρ(v) ∧Age(u) = Age(v) ∧ Colorv < Coloru}. Soit max≺ la fonction +de maximum associe´e a` l’ope´rateur d’ordre binaire ≺. Quand un nœud u calcule le +3.8. ANALYSE DE L’AUTO-STABILISATION 49 +3 2 +2.8 +1.95 +2.6 +2.4 +1.9 +2.2 +2 1.85 +1.8 +1.8 |Omega| = 2 * Degre Max +1.6 |Omega| = Degre Noeud au carre +|Omega| = 2 * Degre Max |Omega|= Degre Max au carre +1.4 |O|mOemgeag| a=| D= eDgereg rneo Meuadx aauu ccaarrrree 1.75 +1.2 +1 1.7 +500 600 700 800 900 1000 1100 500 600 700 800 900 1000 1100 +Intensite du processus lambda Intensite du processus lambda +(a) Temps de stabilisation (b) Hauteur du DAG +FIG. 3.14 – Influence de Ω. +re´sultat de ≺ ou de max≺, il utilise les valeurs cache de son voisinage en supposant +)Coloru = Coloru et )ρ(u) = ρ(u). +Nous de´finisson{s maintenant la fonction clusterHead d’e´lection de cluster-head : +u si ∀v ∈ Γ(u), v ≺ u, +clusterHead = H(max≺{v ∈ Γ(u)}) sinon. +L’algorithme s’exe´cute comme suit : +R1 : VRAI → ρ(u) := densite +R2 : VRAI → H(u) := clusterHead +Lemme 4 Partant de n’importe quelle configuration initiale, chaque nœud u a une +valeur de densite´ correcte ρ(u) en un temps borne´ constant. +Preuve 2 Apre`s un temps constant, chaque nœud u a une vue correcte de son 2- +voisinage. Puis, apre`s l’exe´cution de la re`gle R1, la densite´ ρ(u) du nœud u est cor- +recte.  +Lemme 5 Partant de n’importe quelle configuration initiale, chaque nœud u a une +valeur correcte pour H(u) en un temps borne´ constant. +Preuve 3 Supposons que tout nœud a une valeur correcte de sa densite´ (vrai apre`s +un temps constant d’apre`s le Lemme 4). Apre`s que la variable partage´e ρ(u) ait e´te´ +communique´e sans collision a` tout nœud de Γ(u) (cela arrive apre`s un temps constant), +chaque nœud a une valeur cache correcte pour la densite´ de chacun de ses voisins. +Nous conside´rons maintenant le DAG induit par la relation ≺ (note´ DAG≺ par la +suite). En un temps constant, les racines de DAG≺ ont une valeur correcte de l’identite´ +de leur cluster-head (puisqu’il s’agit de leur propre identifiant). Supposons que tout +nœud a` distance infe´rieure ou e´gale a` n des racines de DAG≺ a une valeur correcte de +l’identite´ de leur cluster-head. Sur exe´cution de la re`gle R2 sur les nœuds a` distance +Temps de stabilisation +Hauteur du DAG induit +50 CHAPITRE 3. ALGORITHME DE CLUSTERING +n+1 des racines de DAG≺, ces nœuds obtiennent alors une valeur correcte de l’identite´ +de leur cluster-head (puisque le cluster-head est de´termine´ de fac¸on de´terministe (i) +par la densite´ et la topologie locale – qui est fixe – et (ii) par l’identite´ des cluster-heads +des nœuds a` distance infe´rieure ou e´gale a` n des racines de DAG≺). Par induction, le +temps ne´cessaire a` la stabilisation de l’algorithme est proportionnel a` la hauteur du +DAG≺. +Nous prouvons maintenant que la hauteur du DAG≺ est borne´e par une constante. Les +couleurs des nœuds sont borne´es par une constante |Ω|. Le nombre d’areˆtes dans le +1 voisinage d un nœud est borne´e par ∆2- ’ , le nombre de 1-voisins est borne´ par ∆, +d ou` le nombre de valeurs possibles pour la densite´ est au plus de ∆3’ , . Le nombre de +couples (densite´ couleur) possibles pour un nœud est |Ω|∆3, , lui-meˆme borne´ par une +constante. Ainsi, la hauteur du DAG≺ est lui-aussi borne´ par une constante. +L’algorithme stabilise en un temps proportionnel a` la hauteur du DAG≺, celle-ci e´tant +constante. Donc le temps de stabilisation est lui aussi borne´ par une constante.  +3.8.5 Validation des proprie´te´s auto-stabilisantes +Comme mentionne´ dans la section 3.8.1, nous supposons l’existence d’une constante +τ > 0 telle que chaque nœud est en mesure de diffuser localement une trame et d’en +recevoir une de chacun de ses voisins en un temps borne´, appele´ une e´tape de temps. +Apre`s une e´tape, chaque nœud connaıˆt ses 1-voisins. Apre`s deux e´tapes, il connaıˆt ses +2-voisins et peut calculer sa valeur de densite´ et apre`s trois e´tapes, il connaıˆt son pe`re. +Le nombre d’e´tapes ne´cessaires a` un nœud pour connaıˆtre l’identite´ de son cluster-head +de´pend directement de la distance qui l’en se´pare et est borne´ par la hauteur de l’arbre +auquel il appartient. +Les simulations mene´es ici nous ont permis d’e´valuer l’importance de l’introduction +des couleurs. Le mode`le de simulation est toujours celui de´crit dans le chapitre 1.1. +Les nœuds sont de´ploye´s suivant un Processus de Points de Poisson avec diffe´rentes +valeurs de λ et de R. +L’allocation des couleurs se fait suivant l’Algorithme N1. Chaque nœud se choisit +ale´atoirement une couleur entre 0 et |Ω| = ∆2 (avec ∆ = maxv∈V δ(u)). Il com- +pare alors sa couleur a` celle de ses voisins. Si deux voisins ont la meˆme couleur, le +nœud dont la couleur est la plus petite se choisit une autre couleur et ainsi de suite jus- +qu’a` ce qu’il n’existe aucune paire de nœuds voisins portant la meˆme couleur. A` partir +de la`, les clusters sont construits suivant l’algorithme 1 en utilisant les couleurs comme +crite`re de de´cision finale. +Les caracte´ristiques des clusters obtenus sont donne´es dans la table 3.11 pour λ = 1000 +et diffe´rentes valeurs deR. Bien que donne´s pourλ = 1000, les re´sultats sont similaires +quelle que soit la valeur de λ. +On remarque que quel que soit R (et donc le degre´ δ des nœuds), l’excentricite´ +moyenne des cluster-heads et la hauteur des arbres varient peu. Cela confirme notre +hypothe`se stipulant que la transmission de l’identite´ du chef de cluster se fait en un +3.8. ANALYSE DE L’AUTO-STABILISATION 51 +temps constant. On notera e´galement que dans un tel cas ou` les densite´s et identifiants +des nœuds sont uniforme´ment distribue´s, l’utilisation des couleurs n’apporte pas grand +chose. Cela est duˆ au fait que dans une telle distribution, les nœuds utilisent uniquement +les densite´s pour de´terminer leur pe`re puisqu’elles sont rarement e´gales. +R = 0.05 (δ = 7.85) R = 0.08 (δ = 20.11) R = 0.1 (δ = 31.42) +Couleurs avec sans avec sans avec sans +Nb clusters 61.0 61.4 19.2 19.5 11.7 11.7 +e˜(H(u)/C(u)) 2.6 2.6 3.1 3.1 3.2 3.2 +Hauteur arbre-cluster 2.7 2.7 3.3 3.3 3.5 3.5 +TAB. 3.11 – Caracte´ristiques des clusters pour une topologie ge´ome´trique ale´atoire +avec λ = 1000. +Conside´rons maintenant un sce´nario ou` les nœuds sont distribue´s dans une grille avec +des identifiants allant croissant de la gauche vers la droite et du bas vers le haut. Dans +ce cas, tous les nœuds inte´rieurs de la grille ont la meˆme valeur de densite´ et le meˆme +degre´. Le seul moyen de choisir leur pe`re est d’utiliser les identifiants. Comme ceux- +ci sont mal re´partis, tous les nœuds vont finalement s’attacher au meˆme cluster-head, +comme le montre le tableau 3.12. Dans un pareil cas, on remarquera que l’introduction +des couleurs est utile car elle permet de re´duire de fac¸on drastique le nombre d’e´tapes +ne´cessaires avant la stabilisation (puisqu’elle re´duit fortement la hauteur des arbres de +clustering) et de construire des clusters plus adapte´s. La figure 3.15 montre un exemple +de clusters obtenus pourR = 0.05. Les cluster-heads apparaissent en bleu, une couleur +par cluster. Sur la figure 3.15(a), les couleurs ne sont pas utilise´es et seulement un +cluster est cre´e´. Sur la figure 3.15(b), les couleurs sont conside´re´es et plusieurs clusters +homoge`nes sont cre´e´s. +Grille 32× 32 Grille 18× 18 Grille 15× 15 +Couleurs avec sans avec sans avec sans +Nb clusters 52.8 1.0 29.3 1.0 18.5 1.0 +e˜(H(u)/C(u)) 3.4 29.1 4.1 19.1 3.6 6.5 +Hauteur arbres-cluster 3.7 83.4 4.7 100.5 4.5 32.1 +TAB. 3.12 – Caracte´ristiques des clusters forme´s sur une grille a` 8 voisins. +Dans cette partie, nous avons introduit un me´canisme supple´mentaire dans la construc- +tion des clusters qui permet a` notre algorithme de se stabiliser en un temps rapide +et borne´ et ce, quelle que soit la topologie sous-jacente. Ce caracte`re local d’auto- +stabilisation apporte une stabilite´ a` notre algorithme et une robustesse face aux pannes +et attaques. En effet, lorsqu’un tel phe´nome`ne survient, l’auto-stabilisation permet au +re´seau de ne pas eˆtre impacte´ dans son ensemble par la cassure de liens. Les nœuds +sont capables d’isoler la faute et de la re´parer. +52 CHAPITRE 3. ALGORITHME DE CLUSTERING +(a) sans utiliser les couleurs (b) en conside´rant les couleurs +FIG. 3.15 – Exemple de constructions obtenues pour des grilles a` 8 voisins. +3.9 Conclusion +Dans ce chapitre, nous avons introduit une nouvelle me´trique qui permet d’organiser +un re´seau sans fil multi-sauts en clusters. Nous avons ensuite analyse´ cette me´trique +analytiquement et par simulation, ainsi que la structure de clusters qu’elle permet de +construire. L’algorithme de clustering et le calcul de cette me´trique sont locaux, dis- +tribue´s et ne ne´cessitent la connaissance que du voisinage a` deux sauts pour chaque +nœud. Ils sont donc peu couˆteux et permettent une maintenance locale donc rapide. +L’algorithme de clustering ne repose sur aucun parame`tre fixe´ a priori et a e´te´ prouve´ +auto-stabilisant en un temps borne´ et constant. La structure de clusters forme´e pre´sente +d’inte´ressantes caracte´ristiques. Compare´e a` d’autres algorithmes de la litte´rature, elle +s’ave`re plus robuste face a` la mobilite´ des nœuds et s’adapte mieux a` la topologie sous- +jacente. +Tout re´seau doit permettre aux entite´s de communiquer et ne´cessite pour cela un pro- +tocole de routage/localisation et un processus de diffusion de messages. Graˆce aux +caracte´ristiques de notre structure de clusters que nous avons de´gage´es au travers de +nos e´tudes et analyses, nous avons pu proposer deux utilisations de la structure qui +tirent avantage de ces proprie´te´s : un processus de diffusion (chapitre 4) et un proces- +sus de localisation et de routage (chapitre 5) pour permettre aux entite´s du re´seau de +communiquer. +3.10. PUBLICATIONS 53 +3.10 Publications +1. Colloques et confe´rences internationaux avec comite´ de lecture : +(a) Self-stabilization in self-organized Multihop Wireless Networks. Nathalie +Mitton, E´ ric Fleury, Isabelle Gue´rin-Lassous and Se´bastien Tixeuil. Work- +shop on Wireless Ad Hoc Networking (WWAN’05), Juin 2005, Columbus, +Ohio, USA. +(b) Self-organization in large scale ad hoc networks. Nathalie Mitton, Anthony +Busson and E´ ric Fleury. Mediterranean Ad Hoc Networking Workshop +(MED-HOC-NET’04), Juin 2004, Bodrum, Turquie. +2. Colloques et confe´rences nationaux : +(a) Auto-stabilisation dans les re´seaux ad hoc. Nathalie Mitton, E´ ric Fleury, +Isabelle Gue´rin-Lassous et Se´bastien Tixeuil. ALGOTEL’05, Mai 2005, +Presqu’ıˆle de Giens, France. +(b) Auto-organisation dans les re´seaux ad-hoc a` grandes e´chelles. Nathalie +Mitton, Anthony Busson et E´ ric Fleury. ALGOTEL’04, Mai 2004, Batz- +sur-mer, France. +(c) Auto-organisation dans les re´seaux ad-hoc a` grandes e´chelles. Natha- +lie Mitton et E´ ric Fleury. Journe´es Graphes Re´seaux et Mode´lisation, +GRM’03, De´cembre 2003, Paris, France. +3. Rapports de recherche : +(a) On Fast Randomized Colorings in Sensor Networks. Nathalie Mitton, E´ ric +Fleury, Isabelle Gue´rin-Lassous and Bruno Se´ricola and Se´bastien Tixeuil. +LRI-1416. Juin 2005. +(b) Self-stabilization in self-organized Multihop Wireless Networks. Nathalie +Mitton, E´ ric Fleury, Isabelle Gue´rin-Lassous and Se´bastien Tixeuil. RR- +5426. De´cembre 2004. +(c) Analysis of the Self - organization in Multi-hops wireless networks. Natha- +lie Mitton, Anthony Busson and E´ ric Fleury. RR-5328. Octobre 2004. +(d) Self-organization in large scale ad hoc networks. Nathalie Mitton and E´ ric +Fleury. RR-5042. De´cembre 2003. +4. Se´minaires, pre´sentations, expose´s : +(a) Auto-organisation dans les re´seaux ad hoc grandes e´chelles. Nathalie Mit- +ton, E´ ric Fleury. Se´minaire ACI Pair a` Pair - Arcachon - France - 6-7 Mai +2004. +54 CHAPITRE 3. ALGORITHME DE CLUSTERING +3.11 Annexes +3.11.1 Analyse de la densite´ moyenne +Nous donnons ici la preuve du lemme 1 qui donne la valeur moyenne de la 1-densite´ +d’un nœud : +Lemme 1 La 1-densite´ moyenne d(e tout nœud)u est :√ ( − {− })o 1 3 3 1 exp λpiR2ρ˜(u) = E [ρ(0)] = 1 + pi − λR2 − +2 4 pi +Preuve 4 Soit (Yi)i=1,..,Φ(B′ ), chacun des points de Φ se trouvant dans B′0. Par0 +de´finition de la densite´, on a :   +1 Φ∑(B′0) Φ(B′ ∩B′o [ρ(0)] = 1 + o 0 Y )iE E  +2 Φ(B′ ) +i=1 0 +′ l b l d i d i l { } ′Bu est a ou e centre´e en u e rayon R, pr ve´e u s ng eton u : Bu = +B(u,R)\ {u} Φ(B′ ∩B′. 0 Y ) correspond au nombre de voisins communs aux nœuds 0i +et Yi. En faisant ainsi la somme des voisins communs a` 0 et Yi pour tous les Yi, on ob- +tient le nombre de liens entre les voisins de 0. Cependant, chaque lien est ainsi compte´ +deux fois (un lien entre Yi et Yj est compte´ quand on conside`re Yi voisin commun de +Yj et 0 et quand on conside`re Yj voisin commun de 0 et Yi). C’est pourquoi on se doit +de diviser cette somme par 2. +Nous supposons que ρ(0) = 1 si le nœud 0 n a aucun voisin (Φ(B′’ 0) = 0). Nous +di i l l d d d d ′con t onnons par a va eur u egre´ u nœu 0 : δ(0) = Φ(B0). Nous obtenons +alors : +∑+∞ +o [ρ(0)] = o [ρ |δ = 0] o(δ = 0) + oE E 0 0 P 0 E [ρ0|δ0 = k] oP (δ0 = k) +k=1 +∑  ∑ ∣∣ ′+∞ Φ(B 0)1 Φ(B′ ′0 ∩B Y ) += 1 + o  iE ∣Φ(B′0) = k o ′P (Φ(B 0) = k) +2 Φ(B′0) +k=1 i=1 +∑+∞∑k1 1 [ ∣∣ ] += 1 + o Φ(B′ ∩B′ )∣Φ(B′ ) = k × oE 0 Y 0 P (Φ(B′0) = k) +2 k i +k=1 i=1 +(3.2) +Les nœuds (Yi)[i=1,..,k e´tant in +l p o ′ ∩ ′ ∣∣ +de´pendants ]et uniforme´ment distribue´s dans B′0, +es e´rance Φ(B B )∣Φ(B′’ E 0 Y 0) = k est la meˆme pour tout i, i = 1, .., ki +3.11. ANNEXES 55 +(et donc pour tout voisin Yi de 0). On note ν(S) la mesure de Lebesgue de la +re´gion du plan S dans IR2 Connaissant ν(B′ ∩ B′ ) et sachant que Φ(B′. ) = k, +a(lors le nombre de) 0 Yi 0nœuds dans B′ ′0 ∩ B Y suit une loi binomiale de parame`trei +ν(B′ ∩B′ ) +k − 1, 0 Yiν(B ) .′0 +′ ′ +L b y d p i d i − ν(B 0∩B Y )e nom re mo en e o nts ev ent : (k 1) iν(B ) .′0 +D’ou`, pour tout i = 1, .., k : +[ ∣∣∣ ] (k − 1) [ ∣∣∣ ]o Φ(B′ ∩B′E 0 Y ) Φ(B′0) = k = o ′ ′ ′E ν(B 0 ∩Bi 2 Y ) Φ(B 0) = kpiR i +− (3.3)(k 1) += o ′ ′E [ν(B 0 ∩B2 Y )]piR i +Cette e´galite´ 3 3 vient du fait que la surface ν(B′ ∩ B′. 0 Y ) ne de´pend pas du nombrei +de Yi, puisque les nœuds Yi sont inde´pendants. +Si on pose que le nœud Yi est a` une distance r du nœud 0, l’ai√re de l’intersection +B′ ′ ′ ′ 2 r 20 ∩ B Y devient ν(B 0 ∩ B Y ) = A(r) = 2R arccos 2R − r R − r +2 +4 , commei i +illustre´ sur la figure 3.4. +Puisque les Y sont uniforme´ment distribue´s dans B′i 0, la valeur moyenne de l’aire +intersection est : +o [ν(B′ ∩B′E 0 Y )] =i ∫oE [A(r)]2pi ∫ R A(r) += +0 ( 20 piR√ ) +r dr dθ +3 3 += R2 pi − +4 +Soit p la probabilite´ que deux voisins de 0 soient eux-meˆmes voisins. p est la valeur +moyenne de l’aire d’intersection divise´e par la surface totale ou` peuvent se trouver les +voisins de 0 (piR2). On a : +∫ ( √ ) √ +∈ ∩ 2 +1 u 2− − u − 3 3p = P (Y2 B0 BY ) = 2 arccos u 1 udu = 11 pi u=0 2 4 4pi +≈ 0.5865 +56 CHAPITRE 3. ALGORITHME DE CLUSTERING +Ce re´sultat combine´ a` celui de l’e´quation 3.2 nous donne : +∑∑ ( √ )+∞ k +o 1 1 k − 1 3 3 +E [ρ(0)] =1 + pi − o (Φ(B′P 0) = k) +2 k +∑k=1 i=1 ( +pi ) 4 ++∞ − √1 k 1 3 3 +=1 + pi − oP (Φ(B′0) = k) +2 +k=( pi 41 √ ) (∑ )+∞ ∑+∞1 − 3 3=1 + pi × k o (Φ(B′P 0) = k)− o ′P (Φ(B 0) = k) +2pi ( 4√ ) k=1 +1 − 3 3 ( − ( − { })) +k=1 +=1 + pi λpiR2 1 exp λpiR2 +2pi 4 +(3.4) +L’e´galite´ 3.4 de´coule du the´ore`me de Slyvniack dont l’une des conse´quences est que +l b d ′e nom re e voisins Φ(B0) de 0, sous la probabilite´ de Palm, suit une loi de Poisson +discre`te de parame`tre λpiR2.  +3.11.2 Calcul analytique du nombre de clusters +Nous donnons ici les calculs de´taille´s de la borne du nombre de clusters donne´ dans le +the´ore`me 1. Nous bornons la probabilite´ qu’un nœud soit chef. +Conjecture 1 Une borne supe´rieure pour la probabilite´ qu’un nœud soit chef est : +( ) ( ∑+∞ ( ) )n +o 1 λpiR +2 +PΦ ρ(0) > max ρ(Yk) ≤ 1 + exp {−λpiR2} +k=1,..,Φ(B0) n n! +n=1 +Preuve 5 Calculer la probabilite´ pour un nœud d’eˆtre chef revient a` calculer la pro- +babilite´ pour un nœud d’avoir la plus forte densite´ dans son voisinage. +Nous conside´rons le point 0. Soient B0 = B(0, R) la boule de rayon R centre´e en 0 +′ +et B0 la boule de rayon R centre´e en 0 prive´e du singleton {0}. Soit (Yi)i=1,..,Φ(B′ ),0 +chacun des points de Φ se trouvant dans B′0. +La densite´ des points de B0 est e´qui-distribue´e puisque les positions de ces points sont +uniforme´ment et in(de´pendamment distribue´es dans B0. D’ou` :∣ ) +o ∣∣ ′ ≤ 1P ρ(Yi) > max ρ(Yk) Φ(B0) = n +k=1,..,n;k 6=i n +Si l i i i ( ′e po nt 0 n’a aucun vo s n Φ(B0) = 0), 0 est un cluster-head. +3.11. ANNEXES 57 +Nous(avons : ) +o +P ρ(0) > max ρ(Yk) +( ′k=1,..,Φ(B )0 ∣∣ )∣ ( ) ( )o ′ ′ ′=P ρ(0) > max ρ(Yk) Φ(B0) > 0 oP Φ(B0) > 0 + oP Φ(B0) = 0 +′ +k=1,..,Φ(B ) +0 +On note : ( ∣∣ )∣ ( )p = o ′ ′0 P ρ(0) > max ρ(Yk) Φ(B0) > 0 × oP Φ(B0) > 0 +′ +k=1,..,Φ(B ) +0 +Si nous su(pposons que les densite´s sont e´qui-distribue´es, nous a)vons :∣∣∣ ( )p < o ′ ′0 P ρ(Y1) > max(ρ(0), max ρ(Yk)) Φ(B0) > 0 × oP Φ(B0) > 0 +k=2,..,Φ(B′ ) +0 +Il s’agit d’une conjecture, en effet nous n’avons pas re´ussi a` de´montrer ce re´sultat. +Cependant d’apre`s nos simulations, quelle que soit la densite´ des nœuds, la quantite´ +p0 est deux a` trois fois plus petite que le terme de droite de cette ine´galite´. +De plus, comme l’e´ve`nement +E1 = {ρ(Y1) > max(ρ(0), max ρ(Yk))} +k=2,..,Φ(B′ ) +0 +est inclus dans l’e´ve`nement +E2 = {ρ(Y1) > max ρ(Yk))} +k=2,..,Φ(B′ ) +0 +nous pouvons majorer la probabilite´ que E1 se produise par la probabilite´ que E2 se +re´alise. Nous obtenons : +( ) ( ) +p0 ≤ o o +′ o o ′ +P [(E1]× P Φ(B0) > 0 ≤ P [E2]× P∣∣ ) +Φ(B0) > 0( ) +o ′ ′p0 ≤ P ρ(Y1) > max ρ(Yk)∣Φ(B0) > 0 × oP Φ(B ) > 0 +′ +k=2,..,Φ(B ) +∑ ( 0 ∣ ) +0 ++∞ +o ∣ ′= oP ρ(Y1) > max ρ(Yk)∣Φ(B0) = n × P (Φ(B′0) = n) +n∑=1+∞ ( ) +′ +k=2,..,Φ(B ) +0 +1 λpiR2 +n +≤ exp {−λpiR2} +n n! +n=1 +58 CHAPITRE 3. ALGORITHME DE CLUSTERING +De plus, d’apre`s le the´ore`me de Slivnyak [76], le nombre de points sous la distribution +de Palm dans un espace Bore´lien de IR2 qui ne contient pas le point 0, suit une loi de +Poisson discre`te. Nous en de´duisons : +( ) ∑+∞ ( )2 n +o 1 λpiR +P ρ(0) > max ρ(Yk) ≤ exp {−λpiR2}+ exp {−λpiR2} +k=1,..,Φ(B0) n n! +n=1 + +Comme, d’apre`s le lemme 3, le nombre de clusters est tel que +[Nb de clusters dans C] = λν(C) oE PΦ (0 est chef ), on obtient une borne supe´rieure +pour le nombre de clusters forme´s par notre algorithme dans une surface C : +∑+∞ ( )1 λpiR2 n +E [Nb de clusters dans C] ≤ λν(C) exp {−λpiR2}+ exp {−λpiR2} +n n! +n=1 +3.11.3 Temps de transmission borne´ +Dans cette partie, nous justifions l’hypothe`se suivante : ”il existe une constante τ > 0 +telle que chaque nœud est en mesure de diffuser localement une trame et d’en recevoir +une de chacun de ses voisins en un temps borne´ ∆(τ)” faite dans la section 3.8.5 pour +prouver le caracte`re d’auto-stabilisation de notre algorithme. +Dans [83], les auteurs fournissent une analyse des performances du protocole IEEE +802.11 pour la couche MAC des re´seaux sans fil. En conside´rant un graphe a` n stations, +toutes a` porte´e de transmission les unes des autres (c.a`.d. que le graphe de communica- +tion est complet), les auteurs mode´lisent l’activation de la pe´riode de contention par les +nœuds avant l’e´mission d’une trame. La dure´e de cette pe´riode de´pend des collisions +qui ont pu se produire pour cette trame auparavant. On trouve en particulier dans ce +papier la probabilite´ Psuc qu’il y ait une transmission re´ussie parmi les n stations en un +slot de temps donne´. Une transmission est conside´re´e comme re´ussie si exactement une +station e´met pendant cette pe´riode de temps. Si pc est la probabilite´ qu’il y ait au moins +un paquet transmis sur le me´dium parmi les n stations (pc est aussi donne´ dans [83]), +nous avons : +P = (n− 1)((1 − p )(n−2)/(n−1)suc c + pc − 1) +Nous montrons maintenant que le temps moyen au bout duquel tous les voisins d’un +nœud ont e´mis avec succe`s, est borne´ par une constante. Soit X la variable ale´atoire +de´signant le nombre de slots de temps ne´cessaire pour que n stations arrivent a` e´mettre +avec succe`s. Dans le meilleur cas, chaque station parle a` tour de roˆle. Ceci donne : +[X < n] = 0 et [X = n] = PnP P suc. +P [X = k, k > n] est la probabilite´ qu’a` la fin des (k−1) premiers slots, (n−1) stations +ont e´mis avec succe`s et que la nieme station re´ussit a` transmettre sa trame durant le slot +k. Nous avons : +3.11. ANNEXES 59 +( − )( )k 1 n +[X = k, k > n] = (1 − P )(k−n+1)PnP − − suck n+ 1 n 1 suc +Les n − 1 premie`res stations ont e´mis pendant les k − 1 premiers slots. On conside`re +donc la probabilite´ de choisir k − (n− 1) slots parmi les k − 1 premiers slots pendant +lesquels aucune transmission n’a eu lieu ou une collision est apparue, multiplie´ par le +nombre de possibilite´s de choisir la nieme station qui e´met durant le kieme slot. +On en de´duit le nombre moyen de slots ne´cessaire E [X ] pour que chacune des n sta- +tions parvienne a` e´mettre avec succe`s. +∑∞ +E [X ] = kP [X = k] +k=0 ∑∞ += nP [X = n] + kP [X = k] +( k∑=n+1 ( )( ) )∞ += Pnsuc × +k − 1 n +n+ k (1− P )(k−n+1) +k − n+ 1 n− suc1 +k=n+1 +Ceci peut eˆtre de´rive´ en : ( ) +n 1 +E [X ] = Psuc (n+ n(n+ 1)( − (n+ 1) + nP )Pn sucsuc ) +1 += nPnsuc 1 + (n+ 1)( − (n+ 1) + nPsuc)Pnsuc +Ainsi, comme Psuc de´pend uniquement de n et que nous supposons n borne´ par une +constante, E [X ] est aussi constant. D’ou` notre hypothe`se stipulant ”une constante τ > +0 telle que chaque nœud est en mesure de diffuser localement une trame et d’en recevoir +une de chacun de ses voisins en un temps borne´ ∆(τ)”. +60 CHAPITRE 3. ALGORITHME DE CLUSTERING +Chapitre 4 +Diffusion +4.1 Introduction +Comme nous avons pu le constater, auto-organiser un re´seau sans fil tel un re´seau +ad hoc ou de capteurs, pre´sente de nombreux avantages. Cependant, de tels re´seaux +ne´cessitent e´galement un me´canisme efficace de diffusion d’information. La diffusion +(ou broadcast) consiste a` transmettre un message depuis un nœud source vers l’en- +semble des entite´s du re´seau. Une telle ope´ration est employe´e par la grande majorite´ +des protocoles de routage (pour la de´couverte des routes entre les entite´s du re´seau). +Cette ope´ration s’ave`re aussi utile a` une station de base dans un re´seau de capteurs lors +de la diffusion d’une requeˆte ou de mise a` jour logicielle sur tous les capteurs. Cette +ope´ration, indispensable donc a` tout re´seau sans fil, a fait l’objet de nombreux travaux +avec, comme but premier, la re´duction du nombre de nœuds retransmettant le message +lors de sa diffusion a` l’ensemble du re´seau. +Les bonnes proprie´te´s d’un protocole de diffusion efficace sont les suivantes : +– extensibilite´ : il supporte le passage a` l’e´chelle ; +– accessibilite´ : une grande majorite´ des nœuds du re´seau joignables par la source +(appartenant a` la meˆme composante connexe) rec¸oit le message (plus de 90%) ; +– e´conome : l’e´nergie et la bande passante consomme´es sont minimise´es (le nombre +de messages retransmis et de re´ceptions redondantes est re´duit). +E´ tant donne´ qu’un re´seau sans fil ne´cessite a` la fois une auto-organisation et un pro- +tocole de diffusion, nous proposons d’utiliser la structure d’arbres forme´e par l’algo- +rithme 1, non seulement pour organiser le re´seau en clusters, mais e´galement pour +e´tablir une base propice a` une diffusion efficace, tirant avantage de certaines de ses +caracte´ristiques. Ainsi, une seule structure est cre´e´e pour deux ope´rations : l’organi- +sation et la diffusion. Notre algorithme de diffusion n’autorise que les nœuds internes +des arbres a` retransmettre le message. Comme nous l’avons constate´ dans le chapitre 3, +une grande proportion des nœuds sont des feuilles (environ 75%). Par conse´quent, une +diffusion base´e sur un tel ensemble n’autorise que peu de nœuds a` e´mettre. L’ensemble +61 +62 CHAPITRE 4. DIFFUSION +des arbres de clustering forme une foreˆt couvrante, donc un ensemble ou` tout nœud +est soit un nœud interne, soit directement voisin d’un nœud interne. Ne´anmoins, cet +ensemble n’est pas connecte´ puisque les arbres sont inde´pendants. Pour que la diffu- +sion touche toutes les entite´s du re´seau, il faut tout d’abord connecter ces arbres en +e´tablissant des passerelles entre eux. Lors de la diffusion, seuls les nœuds internes et +ceux constituant les passerelles seront autorise´s a` retransmettre le message. Notre algo- +rithme permet deux types de diffusion : une diffusion ge´ne´rale d’un message a` tous les +nœuds du re´seau mais e´galement une diffusion d’un message limite´e a` l’inte´rieur d’un +cluster. Pour ce dernier cas de figure, comme la hauteur des arbres est petite et proche +de l’optimal (excentricite´ du chef de cluster) et que les clusters sont proches de cellules +de Voronoı¨ (chapitre 3), un nœud recevra rapidement une information provenant de son +chef. +Dans ce chapitre, nous de´crivons dans un premier temps notre algorithme de diffu- +sion reposant sur la structure d’arbres ainsi que les algorithmes de se´lection des passe- +relles. Nous donnons ensuite une analyse the´orique d’une diffusion dans tout le re´seau, +montrant que le nombre de re´ceptions par nœud peut s’exprimer comme le produit +des degre´s des relais par la probabilite´ pour un nœud d’eˆtre un relais. Les simulations +viennent illustrer notre analyse the´orique, comparer sur divers aspects plusieurs proto- +coles existant et en e´valuer la robustesse. E´ tonnamment, il apparaıˆt que les protocoles +les plus fiables ne sont pas ceux produisant le plus de relais mais ceux dont les relais +ont le plus fort degre´. Les comparaisons entre ces diffe´rents algorithmes montrent aussi +que notre heuristique de diffusion pre´sente le meilleur compromis entre la consomma- +tion d’e´nergie (nombre d’e´missions et re´ceptions) et la robustesse. Au cours de ces +simulations, nous avons pu remarquer que l’heuristique de diffusion base´e sur les MPR +(multi-points relais) de OLSR (voir section 4.2) pre´sentait tre`s peu de robustesse face +a` la mobilite´ des nœuds. Afin de mieux comprendre le comportement des MPR, nous +avons analyse´ cette heuristique plus en de´tail. +La section 4.2 pre´sente quelques-unes des solutions de diffusion existant pour les +re´seaux sans fil. La section 4.3 donne l’analyse the´orique de la diffusion, utilisant la +ge´ome´trie stochastique et la distribution de Palm. La section 4.4 pre´sente la fac¸on dont +nous utilisons la structure d’arbres sous-jacente afin de re´aliser une diffusion efficace. +Nos comparaisons et e´valuations des diffe´rents algorithmes sont mene´es au travers des +simulations de la section 4.5. La section 4.6 pre´sente l’analyse de la se´lection des MPR +dans OLSR. Enfin, quelques remarques concluront ce chapitre (section 4.7). +4.2 Les algorithmes de diffusion pour les re´seaux ad +hoc dans la litte´rature +Afin de pouvoir supporter une extension du re´seau, un protocole de diffusion dans +les re´seaux sans fil se doit de limiter l’utilisation de la bande passante et la de´pense +en e´nergie ; il doit donc minimiser le nombre de messages ge´ne´re´s tout en assurant +qu’un maximum de nœuds connecte´s a` la source rec¸oivent le message (plus de 90%). +Beaucoup de solutions ont e´te´ propose´es avec des hypothe`ses plus ou moins similaires +4.2. E´TAT DE L’ART 63 +a` notre mode`le. Dans cette section, nous ne mentionnerons que ceux supposant les +meˆmes hypothe`ses que nous, c’est a` dire qui supposent un mode`le a` antennes omni- +directionnelles, sans controˆle de puissance. De plus, en supposant une couche MAC +ide´ale (qui ne ge´ne`re aucune collision), on conside`re la diffusion efficace si tous les +nœuds connecte´s a` la source rec¸oivent le message. Un e´tat de l’art plus complet concer- +nant des solutions probabilistes, utilisant des antennes directionnelles ou conside´rant +une couche MAC non ide´ale est donne´ dans [18]. +La me´thode de diffusion la plus triviale pour diffuser un message est l’inondation +aveugle ou blind flooding : lorsqu’un nœud rec¸oit le message diffuse´ pour la premie`re +fois, il le re´-e´met pour ses voisins. Ce me´canisme impose une charge e´norme au +re´seau, engendrant un grand nombre de messages et de collisions, de´pensant beaucoup +d’e´nergie et de bande passante. C’est pourquoi un tel me´canisme ne peut eˆtre envisage´ +pour un re´seau dense ou e´tendu. Ceci donna motive la mise au point de protocoles de +diffusion plus intelligents qui minimisent le nombre de re-transmissions ne´cessaires +en n’autorisant qu’un sous-ensemble de nœuds a` transmettre. Pour cela, on cherche a` +trouver un ensemble ”dominant”. En effet, afin que tous les nœuds du re´seau rec¸oivent +le message, chacun des nœuds doit eˆtre soit un dominant, soit voisin d’un dominant. La +difficulte´ est alors de trouver un tel ensemble dominant connexe de taille minimum qui +minimise e´galement le nombre de re´ceptions redondantes d’un message retransmis par +cet ensemble. Ce proble`me est montre´ NP-difficile [34]. I. Stojmenovic et J. Wu [75] +ont propose´ une classification des protocoles de diffusion en fonction du type d’en- +semble dominant qu’ils utilisent : cluster-based ou base´ sur la formation de clusters, +ensemble dominant de´pendant de la source et ensemble dominant inde´pendant de la +source. +Les solutions cluster-based [28, 36] sont les plus anciennes. Ces protocoles sont plus +de´taille´s dans le Chapitre 2. L’ide´e est que chaque nœud ayant le plus petit identifiant +(protocole Linked Cluster Architecture - LCA) ou le plus fort degre´ (High Connec- +tivity Clustering - HCC) dans son 1-voisinage se de´clare teˆte de cluster. Ses voisins +s’attachent a` lui. Si un nœud s’attache a` plus d’un cluster-head, il devient une passe- +relle. L’ensemble dominant connexe re´sultant comprend les cluster-heads et les passe- +relles. Par la suite, des optimisations ont e´te´ propose´es afin de minimiser la mainte- +nance pour e´viter des re´actions en chaıˆne e´tendues a` tout le re´seau lors de mouvements +de nœuds [24] ou afin de limiter le nombre de passerelles et donc la taille de l’ensemble +dominant [81]. +Dans les propositions base´es sur des ensembles dominants de´pendant de la source [49, +65], les e´metteurs se´lectionnent parmi leurs voisins les nœuds qui relaieront le message. +L’ensemble des relais ainsi choisis par un nœud u est aussi petit que possible et tel +que, chaque nœud a` 2 sauts de u est voisin d’au moins un de ces relais. Pour e´tablir +cette se´lection, u ne´cessite une connaissance de son 2-voisinage uniquement. Lors de la +diffusion, u fera suivre le message diffuse´ qu’il rec¸oit de v, seulement s’il le rec¸oit pour +la premie`re fois et a e´te´ choisi comme relais de v. Les diffe´rents algorithmes diffe`rent +ensuite sur la se´lection des relais, le plus connu e´tant celui base´ sur les Multi-Points +Relais (MPR) de OLSR [65]. Dans OLSR, les MPR sont e´galement utilise´s pour e´tablir +les tables de routage. La structure de diffusion a donc un usage double. Nous de´taillons +plus la se´lection des MPR dans la section 4.6. +64 CHAPITRE 4. DIFFUSION +Les protocoles de diffusion utilisant des ensembles dominants inde´pendants de la +source se´lectionnent cet ensemble inde´pendamment du nœud initiateur de la diffusion. +C’est le cas de notre algorithme. Les nœuds de´cident d’eux-meˆmes s’ils sont ou non +dans cet ensemble, contrairement aux solutions base´es sur des ensembles dominants +de´pendant de la source, ou la de´cision est prise par un autre nœud. Beaucoup de solu- +tions de ce type ont e´te´ propose´es. Dans chacune d’elles, les nœuds ne ne´cessitent que +la connaissance de leur 2-voisinage pour prendre leur de´cision. Un protocole simple +et efficace est le NES (Neighbor Elimination-Based Scheme) de Wu et Li [80], qui se +base sur l’e´limination de voisins. Dans ce sche´ma, un nœud u est dit interme´diaire +si au moins deux de ses voisins v et w ne sont pas eux-meˆmes voisins (u est l’in- +terme´diaire entre v et w). A` partir de la`, deux re`gles de se´lection sont applique´es sur les +interme´diaires afin de re´duire leur nombre. Les nœuds restants deviennent les membres +de l’ensemble dominant et donc les relais lors d’une diffusion. Les re`gles de se´lection +se basent sur une valeur de priorite´. Dans la version originale du NES, cette valeur est +l’identifiant des nœuds. Puis, plusieurs variantes ont e´te´ propose´es utilisant pour cette +valeur le degre´ du nœud ou l’e´nergie restante [26, 74]. Les auteurs de [74] proposent +un autre type d’algorithme base´ sur l’e´limination des voisins que l’on peut re´sumer +par ”Wait and See”. Sur re´ception d’un message de diffusion, un nœud attend pendant +un temps ale´atoire. Durant cette pe´riode, il observe si un de ces voisins retransmet le +message et dans ce cas, quels sont ses voisins recevant ainsi l’information. Si a` la fin de +la pe´riode d’attente, il reste parmi ses voisins des nœuds n’ayant pas rec¸u le message, +il l’e´met. Les auteurs de [19] ont ensuite propose´ une ame´lioration a` cet algorithme +en conside´rant le RNG - Relative Neighborhood Graph (graphe de voisinage relatif) +plutoˆt que le graphe re´el. Ces derniers sche´mas base´s sur l’e´limination de voisins (Wait +& See et Wait & See base´ sur RNG) obtiennent d’excellentes performances en terme +de nombre d’e´missions et de re´ceptions mais induisent une latence importante dans le +processus de diffusion du fait de la pe´riode d’attente ale´atoire de chaque nœud. +4.3 Analyse the´orique d’une diffusion dans un re´seau +sans fil +Comme nous avons pu le constater dans la section 4.2, la plupart des protocoles de +diffusion visent a` re´duire le nombre de nœuds qui relaient le message, l’objectif princi- +pal e´tant de minimiser l’e´nergie globale consomme´e pour diffuser le message. Comme +les nœuds consomment de l’e´nergie non seulement pour transmettre mais aussi pour +recevoir un message, un protocole de diffusion efficace en terme d’e´conomie d’e´nergie +doit chercher a` minimiser E, avec E = Ctx × nbtx + Cry × nbry ou` Ctx (resp. Cry) +est le couˆt e´nerge´tique d’une transmission (resp. re´ception) d’un paquet et nbtx (resp. +nbry) est le nombre de fois ou` le message est e´mis (resp. le nombre de re´ceptions). +Or, les nœuds des re´seaux ad hoc utilisant la technologie 802.11 [31], tout comme les +capteurs [63], ne´cessitent approximativement autant d’e´nergie pour recevoir que pour +e´mettre (Cry ≈ Ctx) et donc, ni les re´ceptions ni les transmissions ne peuvent eˆtre +ne´glige´es lors du bilan e´nerge´tique. +4.3. ANALYSE THE´ORIQUE 65 +Dans cette analyse, nous nous sommes inte´resse´s au nombre moyen de fois ou` un +nœud donne´ rec¸oit un meˆme message lors d’une diffusion. Comme dans les ana- +lyses the´oriques pre´ce´dentes, nous utilisons les proprie´te´s des processus ponctuels +et les meˆmes notations, a` savoir : Φ(S) repre´sente le nombre de points du proces- +sus Φ distribue´s sur la surface S, B(x,R) est la boule de rayon R centre´e en x et +′ +Bx = B(x,R) \ {x}. +Nous notons r le nombre moyen de re´ceptions d’un meˆme message par un nœud (qu’il +soit un relais ou non). Nous donnons deux re´sultats pour r dans les Propositions 1 et 2, +que nous utiliserons par la suite afin de comparer les diffe´rents algorithmes de diffusion +e´tudie´s. Les re´sultats de r donne´s par ces deux propositions sont semblables mais la +Proposition 1 conside`re le mode`le particulier que nous utilisons dans les simulations, +de´crit dans le Chapitre 1.1 alors que les re´sultats de la proposition 2 sont e´galement +applicables a` une classe plus large de graphes ale´atoires. Dans les deux cas, nous ne +donnons ici que l’ide´e ge´ne´rale de la preuve, les preuves et calculs de´taille´s se trouvant +en Annexes 4.9. +Pour la Proposition 1, nous conside´rons un processus ponctuel stationnaire Φ d’inten- +site´ λ > 0. Deux points (x, y) de Φ sont connecte´s (et donc voisins) si et seulement si +la distance Euclidienne les se´parant est infe´rieure ou e´gale a` R (d(x, y) ≤ R), R e´tant +le rayon de transmission radio des nœuds (mode`le de graphe ge´ome´trique ale´atoire). +Proposition 1 E´tant donne´ un processus ponctuel stationnaire Φ d’intensite´ λ (λ > +0), soit ΦRelay d’intensite´ λRelay un amincissement de Φ. Les points de ΦRelay +repre´sentent les relais. Nous supposons que ΦRelay est toujours un processus ponc- +tuel stationnaire. Le nombre moyen de re´ceptions d’un meˆme message par nœud r est : +λ [ ]Relay ′ +r = oE Φ(B ) +[ ] λ ΦRelay 0 +′ +ou` oEΦ ΦRelay(B0) est l’espe´rance sous Palm par rapport au processus Φ (et donc +l l ) d b d l d ′a va eur moyenne u nom re e re ais ans B0. +La preuve de cette proposition est donne´e en annexes 4.9. Le nombre de re´ceptions +d’un meˆme message rec¸u par un nœud de´pend du nombre de relais dans son voisinage. +Le re´sultat s’interpre`te de la fac¸on suivante. Le nombre moyen de re´ceptions par nœud +est le produit du degre´ moyen d’un relais par la probabilite´ pour un nœud donne´ d’eˆtre +un relais (ou de fac¸on e´quivalente par le ratio du nombre de relais sur le nombre total +de nœuds). +Nous conside´rons maintenant des mode`les de graphes ale´atoires plus ge´ne´raux. Nous +supposons que les degre´s des nœuds et le nombre de re´ceptions par nœud sont e´qui- +distribue´es. A noter que nous ne supposons pas ces quantite´s inde´pendamment dis- +tribue´es, ce qui fait que cette hypothe`se n’est pas restrictive. De plus, cette condition +est ve´rifie´e par la plupart des graphes ale´atoires. Par exemple, un graphe ale´atoire de +type Erdo¨s et Renyi [29] qui consiste en n sommets entre lesquels des areˆtes sont +66 CHAPITRE 4. DIFFUSION +place´es avec une probabilite´ uniforme p, inde´pendamment des autres areˆtes, ve´rifie nos +hypothe`ses. +Proposition 2 E´tant donne´ un graphe ale´atoire G(V,E) et un ensemble de relais +Relay ⊂ V ou` les degre´s des nœuds et des relais ainsi que le nombre de re´ceptions +par nœud sont e´qui-distribue´s.[Le no∣mbre moyen∣∣ ] +de re´ceptions par nœud r s’e´crit : +r = E δ(v1) v1 ∈ Relay P(v1 ∈ Relay) (4.1) +La preuve de cette proposition est donne´e en annexes 4.9. L’ide´e est de voir que le +nombre de re´ceptions d’un meˆme message rec¸ues par un nœud correspond au nombre +moyen de relais qu’il a dans son voisinage. On peut de´duire le re´sultat ci-dessus, pour +un graphe ge´ne´ral (proposition 2). Il est le meˆme que pour un graphe ge´ome´trique +ale´atoire (proposition 1) : le nombre moyen de re´ceptions par nœud est le produit du +degre´ des relais par la probabilite´ d’eˆtre un relais. Dans l’e´galite´ 4.1, v1 est un nœud +choisi ale´atoirement parmi l’ensemble des sommets V . Le choix de v1 n’a aucun im- +pact sur les re´sultats puisque la probabilite´ pour un nœud d’eˆtre un relais lors de la +diffusion est e´qui-distribue´e et est la meˆme pour v1 que pour tout autre nœud du graphe. +Dans cette analyse, nous avons montre´ que le nombre moyen de re´ceptions par nœud +est le produit du degre´ moyen des relais par la proportion des relais. Si n est le nombre +de nœuds dans le re´seau et proptx la proportion des relais (nbtx = n×proptx), l’e´nergie +globale consomme´e s’e´crit : +× × ( )E = nCry proptx p+ δRelay +ou` p de´pend du type de technologie utilise´e par les nœuds radio (p ≈ 1 pour les cap- +teurs [63], p ≈ 4 pour les nœuds utilisant la technologie 802.11 [31]). Il en ressort +clairement que pour diminuer E, il faut jouer sur les parame`tres δRelay et proptx. +4.4 Notre contribution a` la diffusion +Dans cette section, nous introduisons dans un premier temps un algorithme permet- +tant l’e´lection de nœuds passerelles entre nos clusters. Puis, dans un second temps, +nous donnons l’algorithme permettant d’appliquer deux types de diffusion sur notre +organisation en arbres : un algorithme de diffusion globale (dans tout le re´seau) et un +algorithme de diffusion dans un cluster. +4.4.1 Se´lection des passerelles +On appelle nœud frontie`re un nœud comptant parmi ses voisins au moins un +repre´sentant d’un ou plusieurs clusters autres que le sien. +Une passerelle Gateway(C(u), C(v)) = 〈x, y〉 entre deux clusters voisins C(u) et C(v) +est une paire de nœuds frontie`res 〈x, y〉 telle que x ∈ C(u), y ∈ C(v) et x ∈ Γ1(y). +4.4. NOTRE CONTRIBUTION A` LA DIFFUSION 67 +c b h e +j +l +d +g +i +a k +f m +FIG. 4.1 – Exemple d’arbres de clustering forme´s par la me´trique de densite´. +Dans une telle paire, on appelle le nœud x le nœud passerelle x = GW (C(u), C(v)) +et le nœud y le nœud miroir de la passerelle y = GWm(C(u), C(v)). Ces passe- +relles sont oriente´es dans le sens ou` il existe une passerelle permettant a` C(u) de +joindre C(v) ( Gateway(C(u), C(v))) et une autre qui permet a` C(v) de joindre C(u) +(Gateway(C(v), C(u))), ces deux passerelles pouvant eˆtre diffe´rentes. +Notre algorithme de se´lection des passerelles se de´roule en deux e´tapes. Dans un pre- +mier temps, chaque nœud frontie`re, choisit localement son miroir dans les clusters +voisins. Un nœud frontie`re et son miroir forment alors une paire de nœuds candidate +au titre de passerelle. Dans un second temps, l’algorithme se´lectionne parmi ces paires +candidates, la paire la plus ade´quate au roˆle de passerelle. Comme les nœuds de la +passerelle seront invite´s a` re-transmettre un message diffuse´ dans tout le re´seau, l’algo- +rithme de se´lection favorise l’e´lection des nœuds internes afin de minimiser le nombre +d’e´metteurs. En effet, les nœuds internes appartiennent de´ja` a` l’ensemble des nœuds +relais. Les se´lectionner en tant que passerelle n’ajoute aucun e´metteur et donc aucun +message superflu. +Cependant, il est clair que si une passerelle est le seul moyen de raccorder un ensemble +du re´seau a` la source du message diffuse´, cette passerelle devient un point sensible. +Afin d’ajouter de la robustesse au protocole envers une cassure de liens au niveau des +passerelles, chaque nœud passerelle e´lit parmi ses voisins une passerelle de secours +(ou de back-up). Cette dernie`re re´-e´mettra le message diffuse´ si et seulement si elle +n’entend pas la passerelle principale. Nous reprenons ici la philosophie Wait & See vue +dans la section 4.2. Dans la suite, nous de´taillons la se´lection des trois types de nœuds : +miroir, passerelle et passerelle de secours. +Se´lection des miroirs. +Comme mentionne´ dans le chapitre 3.8, tout nœud u sait en un temps borne´ s’il existe +parmi ses voisins un nœud v qui n’appartient pas au meˆme cluster que lui (C(u) 6= +C(v)) et donc s’il est un nœud frontie`re. Chaque nœud frontie`re u doit se´lectionner +son miroir parmi les nœuds de son voisinage appartenant a` un cluster diffe´rent du sien. +Pour cela, dans un premier temps, u conside`re parmi ces nœuds ceux qui ne sont pas +des feuilles et qui sont donc des transmetteurs dans tous les cas. u se´lectionne parmi eux +le nœud de plus forte densite´. Si tous les nœuds conside´re´s sont des feuilles, u choisit +68 CHAPITRE 4. DIFFUSION +le nœud de plus faible degre´, de fac¸on a` limiter le nombre de re´ceptions occasionne´es +lors de l’e´mission du message diffuse´ par le miroir. +Si u est un nœud frontie`re du cluster C(v) (C(v) 6= C(u)), on note m(u, C(v)) le nœud +miroir choisi par u dans C(v). Si u est voisin de plusieurs clusters diffe´rents du sien, +il doit e´lire plusieurs miroirs, un dans chacun des clusters voisins. Par exemple, sur la +figure 4.1, le nœud i doit se choisir deux miroirs, m(i, C(f)) dans C(f) et m(i, C(l)) +dans C(l). +Algorithm 1 Se´lection du nœud miroir - EXE´CUTE´ SUR CHAQUE NŒUD FRONTIE`RE u, +c.a.d., ∃v ∈ Γ1(u) s.t. C(v) 6= C(u) +Pour chaque cluster voisin C pour lequel u est un nœud frontie`re : C =6 C(u) et +∃v ∈ Γ1(u) ∩ C +Se´lectionne l’ensemble S des nœuds tels que S = C ∩ {v | Γ1(u) | Ch(v) 6= ∅}. +⊲ u conside`re dans un 1er temps l’ensemble des nœuds non feuilles, e´metteurs dans tous les cas. +if (S 6= ∅) then Se´lectionne l ensemble S′’ des nœuds tels que +S′ = {v | v = maxw∈Sρ(w)}. +⊲ u conside`re les candidats ayant la plus forte valeur de densite´ dans le but de favoriser la +stabilite´. +else ⊲ Tous les candidats miroirs de u sont des feuilles. +S = {C ∩ Γ1(u)}. +Se´lectionne l ensemble S′ des nœuds tels que S′’ = {v | v = minw∈Sδ(w)}. +⊲ u conside`re les feuilles de plus faible degre´ afin de minimiser le nombre de re´ceptions +ge´ne´re´es lors de l’ajout de cette feuille dans l’ensemble des relais. +end +if (S′ = {v}) then m(u, C) = v. +⊲ S′ ne contient qu’un nœud : le miroir de u. +else m(u, C) = v tel que Id(v) = minw∈S′Id(w). +⊲ Il existe des ex-aequo. u choisit le nœud de plus faible Id. +end +Se´lection des passerelles. +La seconde e´tape de l’algorithme de se´lection de passerelle e´lit les passerelles reliant +chaque cluster C a` chacun de ses clusters voisins C′, parmi les paires forme´es par un +nœud frontie`re et son miroir dans C′. Cette e´tape ne´cessite que des informations concer- +nant les nœuds frontie`res soient remonte´es a` la racine. Suivant la taxonomie de [81], +cette e´tape est qualifie´e de quasi-locale car chaque entite´ ne´cessite des informations +situe´es a` une distance borne´e (ici distance borne´e par la hauteur de l’arbre, elle-meˆme +borne´e par une constante). La premie`re e´tape de l’algorithme qui permet aux nœuds +frontie`res de se´lectionner leur miroir ne ne´cessite que des informations locales (de voi- +sinage) et est qualifie´e de locale. Le fait que ces e´tapes soient locales ou quasi-locales +sous-entend une maintenance rapide et une robustesse de l’algorithme envers la mobi- +lite´ des nœuds [81]. +4.4. NOTRE CONTRIBUTION A` LA DIFFUSION 69 +La se´lection des passerelles de notre algorithme est distribue´e puisqu’une se´lection est +ope´re´e a` chaque niveau de l’arbre. Tout comme la se´lection des miroirs, elle cherche +a` favoriser l’e´lection des nœuds internes en tant que passerelles de fac¸on a` limiter les +re´ceptions redondantes lors d’une diffusion d’un message. Les nœuds frontie`res en- +voient leur Id a` leur pe`re en leur indiquant si eux-meˆmes et leur miroirs sont ou non +des feuilles. Chaque pe`re choisit parmi tous ses fils frontie`res le meilleur candidat dont +il envoie les informations a` son propre pe`re et ainsi de suite, jusqu’a` atteindre le cluster- +head. La se´lection est donc semi-distribue´e puisque chaque nœud interne e´limine des +candidats et n’en renvoie qu’un seul a` son pe`re. De cette fac¸on, seuls des paquets de pe- +tites tailles sont envoye´s depuis les nœuds frontie`res jusqu’a` la teˆte de cluster. Comme +mentionne´ en section 3.6.2-table 3.5, le degre´ moyen des nœuds internes est faible et +constant quel que soit le nombre de nœuds, ce qui induit un nombre borne´ de messages +a` chaque niveau. De plus, comme la hauteur des arbres est e´galement borne´e par une +constante, le nombre de niveaux est lui aussi faible. +De´finition 2 (Sous-arbre) v appartient au sous-arbre de racine u (note´ sT (u)) si +l’une des trois conditions suivantes est remplie : +– u = v, +– u est le pe`re de v : u = P(v), +– le pe`re de v appartient au sous-arbre de racine u : P(v) ∈ sT (u). +C(x) est un cluster voisin du sous-arbre sT (u) si et seulement si C(x) 6= C(u) et il +existe dans sT (u) un nœud v frontie`re du cluster C(x) : ∃z ∈ C(x) et y ∈ sT (u) tels +que y ∈ Γ1(z). +La passerelle entre deux clusters voisins est alors se´lectionne´e de la fac¸on suivante. +L’algorithme est exe´cute´ par chaque nœud interne, apre`s re´ception des informations +concernant tous les nœuds frontie`res de son sous-arbre. Pour chaque cluster voisin de +son sous-arbre, un nœud interne u conside`re l’ensembleG des nœuds candidats (nœuds +frontie`res) (G = {v ∈ sT (u) | ∃w ∈ Γ1(v) | C(w) 6= C(u)}). Il se´lectionne parmi eux +le sous ensemble G′- ⊂ G des nœuds internes. Si G est seulement compose´ de nœuds +feuilles (et donc G′ = ∅), la se´lection se poursuit parmi les nœuds de G directement. +Le nœud u prend en priorite´ les nœuds dont le miroir est un nœud interne et il choisit +parmi eux le nœud de plus forte densite´ si les candidats sont des nœuds internes ou +de plus faible degre´ sinon. En cas d’e´galite´, le nœud de plus petit identifiant est e´lu. +On remarque qu’entre deux clusters voisins C(u) et C(v), il existe deux passerelles +Gateway(C(u), C(v)) et Gateway(C(v), C(u)) qui sont diffe´rentes dans la plupart des +cas. Du fait de leur orientation et comme un relais ne re-transmet que sur la premie`re +re´ception du message, dans la plupart des cas, seulement une de ces deux passerelles +sera utilise´e lors d’une diffusion. Ce phe´nome`ne sera mis en e´vidence par les simula- +tions de la section 4.5. +Algorithm 2 Se´lection des passerelles - EXE´CUTE´ PAR CHAQUE NŒUD INTERNE u +70 CHAPITRE 4. DIFFUSION +Pour chaque cluster C =6 C(u) pour lequel ∃v ∈ sT (u) nœud frontie`re +Conside`re l’ensemble G des candidats : G = {v ∈ sT (u) | ∃w ∈ Γ1(v) | C(w) = C}. +Se´lectionne l ensemble G′ ⊂ G des nœuds v tel que G′’ = G ∩ {v|Ch(v) 6= ∅}. +⊲ u conside`re en priorite´ les nœuds non feuilles. +if (G′ 6= ∅) then +⊲ u favorise les nœuds internes de plus forte densite´ ayant un nœud non feuille comme miroir. +Se´lectionne l ensemble G” ⊂ G′ tel que G” = G′’ ∩ {v|Ch(m(v,C)) 6= ∅}. +if (G” 6= ∅) then +Se´lectionne l’ensemble Finalist ⊂ G” tel que +Finalist = {v|ρ(v) = maxw∈G”ρ(w)} . +⊲ Passerelle Nœud Interne↔Nœud Interne. +else +Se´lectionne l’ensemble Finalist ⊂ G” tel que +Finalist = {v|ρ(v) = maxw∈G′ρ(w)} . +⊲ Passerelle Nœud Interne↔Feuille. +end +else +⊲ Tous les candidats sont des feuilles. u favorise ceux de plus faible degre´ ayant un nœud interne +comme miroir. +Se´lectionne l’ensemble G” ⊂ G tel que G” = G ∩ {v|Ch(m(v, C)) 6= ∅}. +if (G” 6= ∅) then +Se´lectionne Finalist ⊂ G” tel que Finalist = {v|δ(v) = minw∈G”δ(w)} . +⊲ Passerelle Feuille↔Nœud Interne. +else +Se´lectionne Finalist ⊂ G” tel que Finalist = {v|δ(v) = minw∈G′δ(w)} . +⊲ Passerelle Feuille↔Feuille. +end +end +if (Finalist = {v}) then +Winner = v. +else +Winner = {v|Id(v) = minw∈F inalistId(w)}. +⊲ Conflits. u choisit le nœud de plus petit Id. +end +if (u = H(u)) then +Winner est le nœud passerelle : +Gateway(C(u),C) = 〈Winner, m(Winner,C)〉. +else +Envoie l’identite´ de Winner a` son pe`re P(u). +end +Se´lection de la passerelle de secours. +Cette se´lection est purement locale et n’engendre aucun couˆt supple´mentaire. Elle tire +avantage du caracte`re de diffusion du me´dium radio qui fait que lorsqu’un nœud e´met, +tous les nœuds a` porte´e radio entendent le message, meˆme s’il ne leur est pas destine´. +Quand un nœud frontie`re u envoie une information a` son pe`re durant le processus de +4.4. NOTRE CONTRIBUTION A` LA DIFFUSION 71 +se´lection des passerelles (algorithme 2), chacun de ses voisins apprend la condition de u +(feuille, nœud interne, nœud frontie`re, etc.). De cette fac¸on, le nœud passerelle apprend +qui dans son voisinage e´tait e´galement candidat et ainsi peut servir potentiellement de +passerelle de secours. Il se´lectionne ce nœud en choisissant parmi ses voisins un nœud +frontie`re dont le miroir est diffe´rent du sien. Cette passerelle de secours agit de la fac¸on +suivante. Sur re´ception d’un message de diffusion, la passerelle de secours enclenche +un compte a` rebours. Si a` la fin de celui-ci, elle n’a pas entendu la passerelle principale +e´mettre, elle e´met le message. Ce me´canisme n’ajoute aucune re´ception redondante et +ajoute de la robustesse au processus de diffusion. +4.4.2 L’algorithme de diffusion +Dans un re´seau sans fil, un nœud peut avoir usage de trois sortes de broadcast : +– une diffusion de voisinage : envoi d’un message a` tous ses 1-voisins (comme les +paquets HELLO) ; +– une diffusion localise´e : diffusion dans un cluster uniquement ; +– une diffusion globale : diffusion d’un message dans tout le re´seau. +Les passerelles ne seront utilise´es que dans le cas d’une diffusion globale, afin de re- +layer le message diffuse´ d’un cluster a` l’autre. Afin de distinguer ces trois types de +diffusions a` la re´ception d’un message, un nœud ne´cessite une indication dans le pa- +quet rec¸u1. Quand une diffusion est effectue´e dans un cluster C(u), le message est +relaye´ par tous les nœuds internes appartenant a` ce cluster. Quand le message doit eˆtre +propage´ dans tout le re´seau, tous les nœuds internes du re´seau ainsi que les passerelles +re´-e´mettent le message pour leurs voisins. Les passerelles (principales et de secours) +e´tant oriente´es, elles ne re´-e´mettent que sous certaines conditions. Le nœud passe- +relle GW (C(u), C(w)) re-transmet un message seulement s’il arrive de son propre +cluster C(u). Un nœud passerelle miroir GWm(C(u), C(w)) ne re-transmet le mes- +sage que s’il arrive du cluster C(u) pour lequel il est miroir. Ainsi, un nœud passe- +relle miroir GWm(C(u), C(w)) re-transmet un message provenant de C(u) quel que +soit le nœud qui le lui envoie et qui n’est donc pas ne´cessairement le nœud passe- +relle GW (C(u), C(w)). Les passerelles de secours agissent comme de´crit dans la sec- +tion 4.4.1. +Algorithm 3 Algorithme de diffusion +Pour tout nœud u, sur re´ception d’un message M provenant d’un nœud v ∈ Γ1(u) +⊲ A noter que v est le nœud qui a transmis M a` u mais pas force´ment la source de la diffusion. +if (u rec¸oit M pour la premie`re fois) then +if Diffusion ge´ne´rale then +if (Ch(u) 6= ∅) then +Re´-e´met +⊲ u est un nœud interne. +else +if ((C(u) = C(v)) et (u = GW (C(u),C(w))∀w ∈ V )) then +⊲ u est un nœud passerelle et M provient de son propre cluster. +1Les adresses IPv6 utilisent de´ja` ce ”scope” d’indication d’adresse multicast : local, global. +72 CHAPITRE 4. DIFFUSION +Re´-e´met +end +if ((C(u) 6= C(v)) et (u = GWm(C(v),C(u)))) then +⊲M provient d’un cluster pour lequel u est une passerelle miroir. +Re´-e´met +end +end +else +⊲ Il s’agit d’une diffusion dans un cluster. +⊲M n’est re´-e´mis que par les nœuds internes dudit cluster. +if ((C(v) = C(u)) et (Ch(u) 6= ∅)) then Re´-e´met end +end +end +4.5 Analyses et re´sultats de simulations +Dans un premier temps, nous avons simule´ le processus de se´lection des passerelles +afin de l’e´valuer. Puis, nous avons simule´ des diffusions globales dans tout le re´seau et +restreintes a` des clusters uniquement, en utilisant notre algorithme ainsi que d’autres +protocoles existants afin de comparer les performances de chacun des protocoles de +diffusion et de valider les re´sultats analytiques obtenus dans la section 4.3. +4.5.1 E´ lection et utilisation des passerelles +E´ tant donne´s deux clusters voisins C(u) et C(v), quatre types de passerelles sont pos- +sibles : +– Passerelle Feuille↔Feuille : GW (C(u), C(v)) et GWm(C(u), C(v)) sont deux +nœuds feuilles. Ce type de passerelle est le plus couˆteux puisque son utilisation +ajoute deux relais dans le processus de diffusion et cause donc plus de re´ceptions +redondantes. +– Passerelle Feuille↔Nœud interne : GW (C(u), C(v)) est une feuille et +GWm(C(u), C(v)) est un nœud interne. Ce type de passerelle n’ajoute qu’un +seul relais. Comme nous le verrons, c’est le type de passerelle le plus e´lu. +– Passerelle Nœud Interne↔Feuille : GW (C(u), C(v)) est un nœud interne et +GWm(C(u), C(v)) est un nœud feuille. +– Passerelle Nœud Interne↔Nœud Interne : GW (C(u), C(v)) et GWm(C(u), C(v)) +sont deux nœuds internes. Ce type de passerelle est le moins couˆteux puisqu’il +n’ajoute aucun e´metteur et donc n’engendre aucune re´ception superflue. Bien que +cela soit le type de passerelle que l’algorithme cherche a` favoriser, il est le moins +courant. +La table 4.1 donne le nombre moyen de passerelles qu’un cluster doit e´lire et maintenir +en moyenne vers ses clusters voisins, ainsi que le nombre de passerelles qui sont effec- +tivement utilise´es lors de la diffusion d’un message dans tout le re´seau. On remarque +4.5. ANALYSES ET RE´SULTATS DE SIMULATIONS 73 +500 nœuds 600 nœuds 700 nœuds +#clusters 11.93 11.64 11.36 +#passerelles e´lues par cluster 5.86 6.02 6.16 +#passerelles utilise´es par cluster 1.76 1.74 1.73 +800 nœuds 900 nœuds 1000 nœuds +#clusters 11.30 11.14 10.72 +#passerelles e´lues par cluster 6.20 6.22 6.26 +#passerelles utilise´es par cluster 1.76 1.68 1.66 +TAB. 4.1 – Nombre de passerelles e´lues et utilise´es par cluster lors d’une diffusion +ge´ne´rale initie´e par une source choisie ale´atoirement. +que le nombre de passerelles a` e´lire est raisonnable et quasiment constant malgre´ l’aug- +mentation de l’intensite´ des nœuds. Ceci de´montre une bonne caracte´ristique pour l’ex- +tensibilite´ de notre heuristique. Ne´anmoins, cette proprie´te´ e´tait pre´visible puisque, +comme constate´ dans le chapitre 3.6.1, le nombre de clusters est constant a` partir d’une +certaine intensite´ du processus sous-jacent et que les clusters forme´s correspondent +grossie`rement a` des cellules de Voronoı¨ centre´es sur les cluster-heads. Comme, dans +un diagramme de Voronoı¨, une cellule a 6 cellules voisines en moyenne, il en est de +meˆme pour nos clusters et donc pour le nombre de passerelles qu’ils doivent e´lire. +La figure 4.2(a) donne la proportion de chaque type de passerelles e´lues. On remar- +quera que les deux types de passerelles qu’on retrouve le moins sont celles de type +Feuille↔Nœud Interne et Nœud Interne↔Nœud Interne. Cela s’explique par le fait +que, par construction, la majeure partie des nœuds frontie`res sont des feuilles et donc, +la majeure partie des miroirs e´galement. Comme l’algorithme de se´lection conside`re +en priorite´ les nœuds internes pour le nœud passerelle, aussitoˆt qu’un nœud non feuille +est candidat, il est se´lectionne´. Comme il y a une majorite´ de feuilles sur les frontie`res, +ce nœud interne a une forte probabilite´ d’avoir une feuille comme miroir. Ceci explique +la forte proportion des passerelles Nœud Interne↔Feuille et Feuille↔Feuille. Plus le +re´seau est dense, plus on a de chances de trouver des nœuds internes aux frontie`res. +C’est pourquoi la proportion de passerelles de type Nœud Interne↔Feuille augmente +avec le nombre de nœuds alors que la proportion de passerelles Feuille↔Feuille +de´croıˆt. +Quand une diffusion ge´ne´rale est effectue´e, toutes les passerelles ne sont pas +ne´cessairement utilise´es. Si deux clusters voisins C(u) et C(v) sont relie´s par deux pas- +serelles Gateway(C(u), C(v)) et Gateway(C(v), C(u)), dans la plupart des cas, seule- +ment une des deux sera utilise´e. Comme le montre la table 4.1, le nombre de passerelles +utilise´es est quasiment constant et reste faible, toujours compris entre 1 et 2. Cela si- +gnifie que de fac¸on ge´ne´rale, ou le message diffuse´ pe´ne`tre un cluster et y meurt (dans +ce cas, il n’utilise qu’une seule passerelle), ou il le traverse et dans ce cas utilise deux +passerelles (une pour entrer et une pour en sortir). Ce phe´nome`ne s’explique par le fait +que nous conside´rons une couche MAC ide´ale et que le message se propage a` la meˆme +vitesse dans toutes les directions. Un message ne va donc pas ”contourner” un cluster +74 CHAPITRE 4. DIFFUSION +avant de l’inonder. +La figure 4.2(b) illustre la proportion de chaque type de passerelle utilise´e lors d’une +diffusion globale. La majorite´ des passerelles utilise´es sont celles n’ajoutant qu’un seul +relais dans le processus de diffusions. Cela est vrai meˆme pour des petits nombres de +nœuds alors que les passerelles Feuille↔Feuille e´taient majoritairement e´lues. Cela +montre une nouvelle caracte´ristique d’extensibilite´ de notre algorithme de diffusion : il +favorise l’utilisation des nœuds internes. Ainsi, comme le nombre moyen de passerelles +utilise´es est faible et que chacune d’elles n’ajoute qu’un relais dans le processus de +diffusion, le couˆt introduit par ces passerelles est faible. +0.45 0.6 +0.55 +0.4 Feuille<->Feuille +Noeud Interne<->Feuille +Feuille<->Noeud Interne 0.5 Feuille<->Feuille +Noeud Interne<->Noeud Interne Noeud Interne<->Feuille +0.35 Feuille<->Noeud Interne0.45 Noeud Interne<->Noeud Interne +0.3 0.4 +0.35 +0.25 +0.3 +0.2 0.25 +0.15 0.2 +0.15 +0.1 +0.1 +0.05 0.05 +500 550 600 650 700 750 800 850 900 950 1000 500 550 600 650 700 750 800 850 900 950 1000 +Intensite du processus lambda Intensite du processus lambda +(a) Passerelles se´lectionne´es (b) Passerelles utilise´es +FIG. 4.2 – Proportion de chaque type de passerelles se´lectionne´es et utilise´es par +cluster.(+ : Feuille↔Feuille ; × : Nœud Interne↔Feuille ; ∗ : Feuille↔Nœud Interne ; +2 : Nœud Interne↔Nœud Interne) +4.5.2 Performances de la diffusion +De fac¸on a` e´valuer notre algorithme, nous avons choisi de le comparer a` des proto- +coles de diffusion existants les plus repre´sentatifs (cf. section 4.2) : blind flooding, +HCC [36] (sche´mas cluster-based), Multi-Point Relais (MPR) [65] (ensemble domi- +nant de´pendant de la source), le NES de Wu et Li [80] (ensemble dominant inde´pendant +de la source) et le sche´ma ”Wait & See” de I. Stojmenovic, M. Seddigh et J. Zunic [74] +(ensemble dominant base´ sur des valeurs ale´atoires). Comme mentionne´ lors des ana- +lyses the´oriques de la section 4.3, nous cherchons a` comparer ces algorithmes en terme +d’e´conomie d’e´nergie (nombre de messages envoye´s et rec¸us par nœud) et de bande +passante (nombre de messages envoye´s au total), en cherchant a` calculer l’impact du +degre´ des nœuds relais sur ces performances. C’est pourquoi nous avons releve´ la pro- +portion des nœuds qui re´-e´mettent le message diffuse´, le degre´ de ces nœuds relais ainsi +que l’impact de ces valeurs sur le nombre de copies redondantes d’un meˆme message +rec¸ues par nœud. +Dans la meˆme optique, nous avons simule´ deux variantes du protocole NES de Wu et +Li : la version originale [80] ou` la valeur de priorite´ utilise´e par les nœuds est l’identi- +Proportion de chaque type de passerelles elues +Proportion de chaque type de passerelles utilisees +4.5. ANALYSES ET RE´SULTATS DE SIMULATIONS 75 +fiant des nœuds, et une version ou` la valeur de priorite´ est le degre´ des nœuds (plus l’Id +pour re´soudre les conflits) [26]. +Nous avons e´galement mesure´ la latence2, excepte´ pour le protocole NES-”Wait & +See” ou` la latence de´pend de la taille de la feneˆtre dans laquelle les nœuds tirent un +temps d’attente ale´atoire. +A priori, un grand nombre de nœuds e´metteurs et de re´ceptions multiples ajoute de +la redondance au protocole et le rend the´oriquement plus re´sistant face a` la mobilite´ +des nœuds et aux cassures de lien. C’est pourquoi, nous nous sommes inte´resse´s a` +l’impact du nombre de re´ceptions redondantes et du degre´ des relais sur la robustesse +des diffe´rents protocoles de diffusion. +Diffusion d’un message dans tout le re´seau (diffusion ge´ne´rale) +Nous analysons ici une diffusion d’un message dans tout le re´seau, initie´e par une +source choisie ale´atoirement parmi les nœuds du re´seau. +36 1 +34 Blind Flooding +HCC 0.9 +MPR +32 NES-’Wu et Li’ +NES-’Wu et Li, degre’ 0.8 +NES-’Wait&See’ +30 Arbres de densite Blind Flooding +HCC +0.7 MPR +28 NES-’Wu et Li’ +NES-’Wu et Li, degre’ +26 0.6 NES-’Wait&See’Arbres de densite +24 0.5 +22 +0.4 +20 +0.3 +18 +16 0.2 +14 0.1 +500 550 600 650 700 750 800 850 900 950 1000 500 550 600 650 700 750 800 850 900 950 1000 +Intensite du processus lambda Intensite du processus lambda +(a) Degre´ des e´metteurs (b) Proportion d’e´metteurs +FIG. 4.3 – Degre´ (a) et proportion (b) des e´metteurs en fonction des diffe´rents algo- +rithmes de diffusion et du nombre de nœuds.(+ : Blind Flooding ; × : HCC ; ∗ : MPR ; +2 : NES - Wu Li ; NES - Degre´ - Wu Li ; ⊖ NES - Wait & See ; • Arbres de densite´) +La figure 4.3 montre le degre´ dans le graphe des nœuds relais ainsi que leur proportion +dans le re´seau pour les diffe´rents algorithmes de diffusion conside´re´s. +La figure 4.3(a) montre le degre´ des relais. Comme dans le Blind Flooding, tous les +nœuds relaient le message, le degre´ moyen des relais correspond exactement au degre´ +moyen des nœuds dans le graphe. Nous pouvons voir que notre algorithme maximise +le degre´ moyen des relais. En effet, notre algorithme e´lit les relais sur leur valeur de +densite´ qui est quasiment proportionnelle a` leur degre´. La version originale du NES +de Wu et Li et le NES-”Wait & See” e´lisent des relais de meˆme degre´, infe´rieur au +degre´ moyen. Ceci est duˆ au fait que plus un nœud a de voisins, plus il a de chances +2Temps au bout duquel tous les nœuds du re´seau ont rec¸u le message de diffusion. +Degre des relais +Proportion d’emetteurs +76 CHAPITRE 4. DIFFUSION +soit d’entendre l’un d’eux e´mettre avant la fin de son temps d’attente (dans le cas du +protocole ”Wait & See”) soit d’avoir e´te´ ”e´limine´” par les re`gles de se´lection de l’algo- +rithme de Wu et Li. On remarque e´galement que les courbes repre´sentant les degre´s des +MPR et des relais dans le Blind Flooding sont confondues. Ceci montre que les relais +utilise´s lors d’une diffusion avec les MPR sont choisis inde´pendamment de leur degre´. +Les protocoles HCC et le NES-degre´ Wu de Li choisissent des relais de fort degre´ par +construction, ce qui se retrouve dans les re´sultats. +La figure 4.3(b) montre la proportion de relais dans le re´seau. Comme dans le blind +flooding, tous les nœuds re-transmettent le message, cette proportion est e´gale a` 1. On +observe que le protocole ”Wait & See” est l’heuristique ne´cessitant le moins de relais, +ce qui implique que cette heuristique de´pense moins d’e´nergie en e´mission. Notre heu- +ristique obtient des re´sultats proches. On remarquera e´galement que les deux variantes +du protocole NES de Wu et Li ge´ne`rent approximativement le meˆme nombre de relais. +Cependant, comme vu lors des analyses the´oriques, le nombre de re´ceptions par nœud +ne peut eˆtre directement de´duit des re´sultats du degre´ des relais ou directement de la +proportion d’e´metteurs puisqu’il est en fait le produit des deux. Comme certaines des +heuristiques produisant le moins de relais sont e´galement celles dont les relais ont les +plus forts degre´s, nous ne pouvons en de´duire laquelle minimise le plus le nombre de +re´ceptions. Nous pouvons juste supposer que la variante du protocole NES utilisant +l’identifiant des nœuds induira moins de re´ceptions que la variante utilisant le degre´ +des nœuds puisque pour un nombre e´quivalent de re´-e´metteurs, le degre´ de ses relais +est plus faible. La figure 4.4 montre le nombre de re´ceptions par nœud d’un message +diffuse´ dans tout le re´seau. +35 +Blind Flooding +HCC +MPR +NES-’Wu et Li’ +30 NES-’Wu et Li, degre’ +NES-’Wait&See’ +Arbres de densite +25 +20 +15 +10 +5 +500 550 600 650 700 750 800 850 900 950 1000 +Intensite du processus lambda +FIG. 4.4 – Nombre de re´ceptions par nœud en fonction du nombre de nœuds et des +diffe´rents algorithmes de diffusion.(+ : Blind Flooding ; × : HCC ; ∗ : MPR ; 2 : NES +- Wu Li ; NES - Degre´ Wu Li ; ⊖ NES - Wait & See ; • Densite´) +Ainsi, lorqu’un message est diffuse´ a` tous les nœuds du re´seau, l’algorithme NES- +”Wait & See” est celui induisant le moins de re´ceptions redondantes sur les nœuds, +de´pensant ainsi moins d’e´nergie et de ressources. On remarque que notre algorithme +obtient des re´sultats tre`s proches puisqu’il ne ge´ne`re qu’une re´ception de plus en +moyenne par nœud que ”Wait & See”. De plus, le ”Wait & See” e´tant base´ sur des +valeurs ale´atoires, la latence qu’il introduit est ine´vitablement supe´rieure a` celle intro- +Nombre de receptions par noeud +4.5. ANALYSES ET RE´SULTATS DE SIMULATIONS 77 +duite par notre protocole. On remarque e´galement que la version originale du NES de +Wu et Li cause moins de re´ceptions que sa variante base´e sur le degre´ des nœuds. +Latence : Puisque dans l’algorithme de se´lection des MPR, les relais sont choisis de +fac¸on a` ce que le 2-voisinage d’un nœud soit atteint en 2 sauts, le k-voisinage de la +source est atteint en k sauts. Sous l’hypothe`se d’une couche MAC ide´ale, les MPR +donnent des re´sultats optimaux en terme de latence (ici e´quivalente aux nombres de +sauts). C’est pourquoi nous avons compare´ la latence produite par notre heuristique +a` celle produite par les MPR afin de mesurer l’e´cart entre notre solution et l’optimal. +Nous conside´rons une unite´ de temps comme une e´tape de transmission (c.a`.d. 1 saut). +Les re´sultats sont pre´sente´s dans la table 4.2. Meˆme si notre algorithme n’est pas op- +timal en terme de latence, il ne s’en e´loigne gue`re (2 sauts au plus). La figure 4.5 +repre´sente la propagation temporelle d’une diffusion ge´ne´rale d’un message, initie´e +au temps 0 par une source centrale (en vert sur les sche´mas). Les cluster-heads ap- +paraissent en bleu. La couleur des autres nœuds de´pend du temps au bout duquel ils +rec¸oivent le message. Plus la couleur est claire, plus le temps est long. +(a) Propagation avec MPR (b) Propagation avec les arbres de +densite´ +FIG. 4.5 – Temps de propagation d’un message diffuse´ dans tout le re´seau par une +source centrale en utilisant les MPR (a) et notre me´trique (b). +500 nœuds 700 nœuds 800 nœuds 900 nœuds 1000 nœuds +MOY MAX MOY MAX MOY MAX MOY MAX MOY MAX +MPR 5.13 8.97 4.88 8.40 4.88 8.40 4.81 8.23 4.78 8.07 +Densite´ 6.31 11.05 6.22 10.78 6.24 10.95 6.15 10.66 6.19 10.74 +TAB. 4.2 – Temps max et moyen pour recevoir le message. Les valeurs ”MAX” donnent +le temps au bout duquel tous les nœuds du re´seau ont rec¸u le message. Les valeurs +”MOY” donnent le temps moyen au bout duquel un nœud rec¸oit le message. +78 CHAPITRE 4. DIFFUSION +Diffusion dans un cluster. +On suppose maintenant qu’une diffusion est initie´e dans chaque cluster, par chaque +cluster-head. Nous avons donc autant de diffusions simultane´es que de clusters. Un +nœud applique le protocole de diffusion (quel qu’il soit) en ne conside´rant que les +nœuds appartenant au meˆme cluster que lui. +1 35 +Blind Flooding +Blind Flooding MPR +MPR NES-’Wu&Li’ +0.9 NES-’Wu&Li’ NES-’Wu&Li-degre’ +NES-’Wu&Li-degre’ 30 NES-’Wait&See’NES-’Wait&See’ Arbres de densite +Arbres de densite +0.8 +25 +0.7 +0.6 20 +0.5 +15 +0.4 +10 +0.3 +0.2 5 +500 550 600 650 700 750 800 850 900 950 1000 500 550 600 650 700 750 800 850 900 950 1000 +Intensite du processus lambda Intensite du processus lambda +(a) Proportion d’e´metteurs (b) Nombre de re´ceptions +FIG. 4.6 – Proportion de e´metteurs (a) et Nombre moyen de re´ceptions par nœud (b) +pour une diffusion dans un cluster en fonction de l’intensite´ du processus et du proto- +cole utilise´.(+ : Blind Flooding ; × : MPR ; ∗ : NES - Wu Li ; 2 : NES - Degre´ Wu Li ; +NES - Wait & See ; ⊖ Densite´ ). +On remarque sur la figure 4.6, que pour ce type de diffusion, notre algorithme est +celui qui minimise le plus le nombre de relais et de re´ceptions, obtenant meˆme des +performances e´gales ou supe´rieures a` celles du protocole NES ”Wait & See”. +Ces re´sultats confirment e´galement les re´sultats analytiques montrant que le nombre de +re´ceptions ne peut eˆtre de´duit directement de la proportion d’e´metteurs. Par exemple, +notre algorithme utilise moins de relais avec de plus forts degre´s que le ”Wait & See” +pour finalement induire autant de re´ceptions par nœud. +La table 4.3 et la figure 4.7 repre´sentent les re´sultats concernant la latence induite dans +de telle diffusion par notre heuristique. Comme pour une diffusion ge´ne´rale, la latence +obtenue est tre`s proche de l’optimale, s’en e´loignant seulement d’une demie unite´ de +temps pour le temps moyen. Cela montre e´galement que, meˆme si les routes dans les +arbres, du cluster-head vers les autres nœuds du cluster ne sont pas toujours les plus +courtes, elles en sont tre`s proches. +Remarque 3 A` l’exception de notre algorithme, base´ sur la densite´, une diffusion dans +un cluster est e´quivalente a` une diffusion dans un environnement fini pour les autres +algorithmes de diffusion, contrairement a` une diffusion ge´ne´rale qui correspond a` une +diffusion dans un environnement non borne´. On remarquera que tous les protocoles +sont plus robustes dans des environnements infinis. +Proportion de noeuds emetteurs +Nombre de receptions par noeud +4.5. ANALYSES ET RE´SULTATS DE SIMULATIONS 79 +500 nœuds 700 nœuds 800 nœuds 900 nœuds 1000 nœuds +MOY MAX MOY MAX MOY MAX MOY MAX MOY MAX +MPR 1.76 4.71 1.78 4.85 1.81 4.83 1.81 4.80 1.82 5.00 +Densite´ 1.80 5.08 1.83 5.38 1.87 5.29 1.87 5.50 1.88 5.30 +TAB. 4.3 – Temps max et moyen pour recevoir le message dans un cluster. Les valeurs +”MAX” donnent le temps au bout duquel tous les nœuds du re´seau ont rec¸u le message. +Les valeurs ”MOY” donnent le temps moyen au bout duquel un nœud rec¸oit le message. +(a) Clusters (b) Propagation avec MPR (c) Propagation avec les arbres +de densite´ +FIG. 4.7 – Temps de propagation d’un message diffuse´ dans chacun des clusters +repre´sente´s sur (a), en utilisant les MPR (b) et notre me´trique (c). +4.5.3 Robustesse de la diffusion +Apre`s avoir conside´re´ tous ces re´sultats, nous nous sommes interroge´s sur la robus- +tesse de ces protocoles (toujours en conside´rant la couche re´seau uniquement) envers +la cassure de liens. En effet, jusqu’a` maintenant, nous n’avons compare´ les diffe´rents +protocoles qu’en terme d’e´nergie e´pargne´e en limitant les re´ceptions redondantes et le +nombre de re´-e´metteurs. Cependant, la redondance apporte de la robustesse au proces- +sus de diffusion. Il est donc le´gitime de se demander si une limitation de la redondance +dans un environnement aux liens radios sensibles est bien une bonne approche ou si +la redondance en terme de nombre de re´ceptions a re´ellement un impact sur la robus- +tesse ? Nous nous sommes aussi interroge´s sur l’impact du degre´ des relais sur cette +robustesse : pour une redondance de messages e´quivalente, est-il pre´fe´rable d’avoir +peu de relais avec un fort degre´ ou un plus grand nombre de relais avec un plus petit +degre´ ? +Afin d’e´valuer cet aspect de la diffusion et de re´pondre a` ces diverses interrogations, +nous avons applique´ une probabilite´ de cassure sur les liens et mesure´ la proportion +de nœuds qui rec¸oivent encore le message diffuse´. Les simulations que nous avons +faites supposent que le message se propage avant qu’aucune information de routage ne +soit recalcule´e par les nœuds comme par exemple l’ensemble des MPR (pour l’heuris- +tique des MPR), l’ensemble des voisins a` e´liminer (pour les sche´mas NES) ou le pe`re +dans l’arbre de clustering (pour l’algorithme base´ sur la densite´). Comme dans le blind +80 CHAPITRE 4. DIFFUSION +flooding, tous les nœuds retransmettent le message, si des nœuds ne rec¸oivent pas le +message, cela implique que le re´seau n’est plus connexe. +La figure 4.8 donne la proportion des nœuds touche´s par la diffusion quand on applique +une probabilite´ de cassure sur les liens pour les deux types de diffusion (ge´ne´rale et +dans un cluster) et λ = 1000. Globalement, le comportement des diffe´rentes heuris- +tiques est le meˆme pour les deux types de diffusion, excepte´ pour notre algorithme. Par +exemple, le NES-”Wait & See” qui e´tait le meilleur protocole en terme de re´ceptions +et d’e´metteurs est le protocole le moins robuste, quel que soit le type de diffusion. +La figure 4.8(a) pre´sente les re´sultats pour une diffusion dans un cluster. E´ tonnamment, +il ne semble pas que le nombre de re´ceptions redondantes et la robustesse du protocole +soient lie´s. Par exemple, l’algorithme base´ sur les arbres de densite´ est l’un de ceux +induisant le moins de re´ceptions redondantes et pourtant l’un des plus robustes. +Il semble que les protocoles dont les relais ont un fort degre´ tendent a` eˆtre plus ro- +bustes. En effet, des protocoles avec des relais a` fort degre´ (NES-degre´ et Densite´) sont +tre`s robustes alors que ceux avec des relais a` plus faible degre´ comme les MPR ou +le NES-”Wait & See” pre´sentent les pires comportements. Le NES-Wu&Li est moins +robuste que sa variante NES-degre´ (qui augmente le degre´ des relais). La redondance +en terme de nombre de re´ceptions multiples est donc tre`s couˆteuse en terme d’e´nergie +consomme´e et de bande passante utilise´e, sans pour autant apporter plus de robustesse +au processus de diffusion. +Notre heuristique pre´sente une bonne robustesse envers les cassures de liens lors d’une +diffusion dans un cluster. Comme elle minimise e´galement a` la fois le nombre de re- +lais et le nombre de re´ceptions par nœud, elle constitue le meilleur compromis couˆt- +robustesse-latence. +1 1 +0.9 0.9 +0.8 0.8 +0.7 0.7 +0.6 0.6 +0.5 0.5 +0.4 0.4 +0.3 Blind Flooding 0.3 Blind Flooding +MPR MPR +NES-’Wu&Li’ NES-’Wu&Li’ +0.2 NES-’Wu&Li-degre’ 0.2 NES-’Wu&Li-degre’ +NES-’Wait&See’ NES-’Wait&See’ +Arbre de densite Arbres de densite +0.1 0.1 +0 0 +0 0.2 0.4 0.6 0.8 1 0 0.2 0.4 0.6 0.8 1 +Probabilite de cassure de liens Probabilite de cassure de liens +(a) Cassure de liens - diffusion dans un cluster (b) Cassure de liens - diffusion globale +FIG. 4.8 – Proportion de nœuds recevant toujours le message de diffusion apre`s appli- +cation d’une probabilite´ de cassure sur les liens lors d’une diffusion dans un cluster (a) +ou dans tout le re´seau (b). +Cependant, comme le montre la figure 4.8(b), notre algorithme est bien moins robuste +lorsqu’il s’agit d’une diffusion globale. Il reste plus robuste que le NES-”Wait & See” +Proportion de noeuds recevant le message +Proportion de noeuds recevant le message +4.5. ANALYSES ET RE´SULTATS DE SIMULATIONS 81 +mais bien moins que le protocole NES de Wu et Li. Ce re´sultat, couple´ au fait que +notre heuristique est tre`s robuste lorsque le message est propage´ dans un cluster seule- +ment, montre que les liens sensibles dans une diffusion ge´ne´rale sont les passerelles. +En effet, si un cluster A ne peut eˆtre atteint que par le cluster B et que les nœuds de la +passerelle de B vers A tombent, l’ensemble du cluster A est alors isole´ de la diffusion. +Afin d’ajouter de la robustesse a` ce niveau, il est donc souhaitable d’e´lire plusieurs +passerelles entre deux clusters voisins. E´ lire plus d’une passerelle n’ajoute aucun couˆt +lors de la phase d’e´lection (aucun message supple´mentaire n’est utile) mais l’utilisation +de passerelles supple´mentaires engendre plus d’e´metteurs et de re´ceptions redondantes +lors de la propagation d’un message. Il y a donc un compromis a` faire entre le nombre +de passerelles a` e´lire et le couˆt de leur utilisation. De fac¸on a` estimer ce compromis, +nous avons simule´ une diffusion d’un message dans le re´seau en augmentant le nombre +de passerelles utilise´es. Les re´sultats sont donne´s par la figure 4.9. L’ajout de passe- +relles apporte vite de la robustesse au protocole, ce qui confirme le fait qu’il s’agissait +bien des liens sensibles. Comme le montre la figure 4.9(a), e´lire trois passerelles entre +chaque paire de clusters voisins permet d’obtenir la meˆme robustesse que pour le pro- +tocole NES de Wu et Li, sans pour autant produire plus de re´ceptions et d’e´metteurs +que ces heuristiques (figures 4.9(b) et 4.9(c)). +1 1 +Blind Flooding +0.9 MPR0.9 NES-’Wu et Li’ +NES-’Wait&See’ +0.8 Arbres de densite-1 passerelle0.8 Arbres de densite-2 passerellesArbres de densite-3 passerelles +Arbres de densite-4 passerelles +0.7 +0.7 +0.6 +0.6 +0.5 +0.5 +0.4 Blind Flooding +MPR +NES-’Wu&Li’ 0.4 +0.3 NES-’Wait&See’ +Arbres de densite-1 passerelle +arbres de densite-2 passerelles 0.3 +0.2 Arbres de densite-3 passerellesArbres de densite-4 passerelles +0.2 +0.1 +0 0.1 +0 0.2 0.4 0.6 0.8 1 500 550 600 650 700 750 800 850 900 950 1000 +Probabilite de cassure de liens Intensite du processus lambda +(a) Robustesse (b) Proportion d’e´metteurs +14 +Blind Flooding +MPR +NES-’Wu et Li’ +NES-’Wait&See’ +12 Arbres de densite-1 passerelleArbres de densite-2 passerelles +Arbres de densite-3 passerelles +Arbres de densite-4 passerelles +10 ++ Blind Flooding +8 × MPR +∗ NES - Wu Li +6 2 NES - Wait & See +Densite´ - 1 passerelle +4 ⊖ Densite´ 2 passerelles +500 550 600 650 700 750 800 850 900 950 1000 • Densite´ 3 passerelles +Intensite du processus lambda △ Densite´ 4 passerelles +(c) Re´ceptions par nœud (d) Le´gende +FIG. 4.9 – Robustesse envers les cassures de liens (a), Proportion d’e´metteurs (b) et +nombre de re´ceptions par nœud (c). +Proportion de noeuds recevant le message +Nombre de receptions par noeud +Proportion d’emetteurs +82 CHAPITRE 4. DIFFUSION +4.6 Analyse de la se´lection des MPR dans OLSR +Comme nous l’avons de´ja` vu, OLSR est un protocole de routage pro-actif pour les +re´seaux ad hoc, re´cemment standardise´ a` l’IETF. Il utilise le concept des Multi-Points +Relais (MPR) pour minimiser le trafic de controˆle et calculer les plus courts chemins +entre toute paire de nœuds. Chaque nœud du re´seau choisit ses MPR dans son voisinage +a` un saut. Lorsqu’un nœud u rec¸oit un message M d’un voisin v, il ne le re-transmet +que si c’est la premie`re fois qu’il rec¸oit M et si v a de´signe´ u comme e´tant un de ses +MPR. La se´lection des MPR consiste pour un nœud u a` choisir un ensemble minimal +de nœuds parmi ses voisins de telle fac¸on que l’ensemble des 2-voisins de u soit ainsi +couvert (c.a`.d. que chaque 2-voisin de u rec¸oit une transmission d’au moins un MPR +de u). De cette fac¸on, meˆme si u ne conside`re que les MPR dans son voisinage, il peut +joindre tous ses 2-voisins en 2 sauts, et par extension son k-voisinage en k sauts. +Ce protocole est tre`s ce´le`bre et pourtant, il est loin d’obtenir les meilleurs re´sultats. +Nous nous sommes alors penche´s sur la se´lection des MPR afin de l’analyser plus en +de´tail et de comprendre pourquoi. +4.6.1 La se´lection des MPR +Comme la se´lection optimale d’un ensemble minimum de MPR est un proble`me NP- +complet [40], nous donnons ici l’heuristique gloutonne de se´lection des MPR qui est +celle actuellement utilise´e dans l’imple´mentation d’OLSR. +Pour un nœud v ∈ Γ(u) nous notons d+, u (v) le nombre de nœuds que u peut atteindre +en deux sauts via v : +d+u (v) = |Γ2(u) ∩ Γ(v)| +Pour un nœud v ∈ Γ (u) soit d−2 , u (v) le nombre de nœuds dans le voisinage de u qui +permettent de connecter u et v en deux sauts : +d−u (v) = |Γ(u) ∩ Γ(v)| +Le nœud u se´lectionne dansΓ(u) un ensemble de nœuds couvrant inte´gralementΓ2(u). +Cet ensemble est l’ensemble des MPR de u. Nous le notons MPR(u). Chaque nœud a +donc son propre ensemble de MPR qui est diffe´rent d’un nœud a` l’autre. Par de´finition, +MPR(u) est tel que : ⋃ +u ∪ Γ2(u) ⊂ Γ(v) +v∈MPR(u) +Conside´rant un nœud u, nous appelons ”nœud isole´” pour u, tout nœud v ∈ Γ2(u) pour +lequel il n’existe qu’un chemin a` deux sauts de u a` v. En d’autres termes, un nœud v +est dit isole´ pour u si d−u (v) = 1. +L’algorithme de se´lection des MPR est exe´cute´ sur chaque nœud et suppose que chaque +nœud connaıˆt ses voisins a` 1 et 2 sauts. Il se de´compose en deux e´tapes. Nous notons +4.6. ANALYSE DE LA SE´LECTION DES MPR DANS OLSR 83 +MPR1 l’ensemble des nœuds MPR se´lectionne´s lors de la premie`re e´tape de l’algo- +rithme. Les MPR1 permettent de couvrir les nœuds isole´s. L’algorithme de se´lection +des MPR est le suivant. +Algorithm 4 Algorithme glouton de se´lection des MPR - Exe´cute´ sur chaque nœud. +Γ′(u) = Γ(u) et Γ′2(u) = Γ2(u). +⊲ Premie`re e´tape +Pour tout nœud v ∈ Γ(u) +if (∃w ∈ Γ(v) ∩ Γ (u) | d−2 u (w) = 1) then +Se´lectionne v comme MPR(u). +⊲ Se´lectionne comme MPR(u), les nœuds de Γ(u) couvrant les nœuds ”isole´s”. +Retire v de Γ′(u) et retire Γ(v) ∩ Γ (u) de Γ′2 2(u). +end +⊲ Seconde e´tape +while (Γ′2(u) 6= ∅) +Pour tout nœud v ∈ Γ′(u) +if (d+(v) = max d+u w∈Γ′(u) u (w)) then +Se´lectionne v comme MPR(u). +⊲ Se´lectionne comme MPR(u) le nœud v permettant de rattacher le plus de nœuds de +Γ2(u) a` u en deux sauts. +Retire v de Γ′(u) et retire Γ(v) ∩ Γ (u) de Γ′2 2(u). +end +Afin de mieux comprendre cet algorithme, exe´cutons-le sur le nœud u en vert sur +l’exemple de la figure 4.10. Les nœuds isole´s apparaissent en rouge, hachure´s hori- +zontalement. Par exemple, le nœud t est un nœud isole´ pour u car le nœud h est le +seul de ses voisins dans Γ(u). Le nœud h sera donc e´lu lors de la premie`re e´tape de +l’algorithme : h ∈MPR1. De la meˆme fac¸on, u e´lira les nœuds bleus, hachure´s verti- +calement h, i, c, g comme MPR1. Les nœuds k, j, t, s, r, q, o,m, l de Γ2(u) sont ainsi +couverts. Le nœud u passe alors a` la seconde e´tape de l’algorithme et ne conside`re dans +Γ2(u) que les nœuds non encore couverts (p et n) et dans Γ1 les nœuds non MPR1 +(b, f , e et d). Il ne garde donc qu’une vue re´duite de la topologie comme illustre´ sur +la figure 4.10(b). Il se´lectionne alors son voisin de plus fort degre´ dans ce graphe. +Comme le nœud e couvre n et p alors que f et d ne couvrent chacun qu’un nœud +de Γ2(u) (resp. p et n), c’est e qui est e´lu. A partir de la`, tous les nœuds de Γ2(u) +sont couverts par les nœuds se´lectionne´s comme MPR, l’algorithme s’arreˆte. On a : +MPR(u) = {c, e, i, h, g}. +Plusieurs algorithmes [8, 41, 53] ont e´te´ propose´s afin d’ame´liorer cet algorithme +et re´duire le nombre de MPR se´lectionne´s. Cependant, aucun d’eux ne re´duit +conside´rablement le nombre de MPR. Comme on peut le constater, la premie`re e´tape +de l’algorithme glouton ne peut eˆtre supprime´e, quel que soit l’algorithme de se´lection, +puisqu’elle seule permet de couvrir tous les nœuds isole´s. De plus, si on veut minimi- +ser le nombre de MPR, cette e´tape doit eˆtre exe´cute´e en premier lieu. C’est pourquoi, +toutes les variantes de cet algorithme ne portent en fait que sur la deuxie`me e´tape, ce +qui laisse in fine une faible marge de manœuvre, comme nous allons le montrer. +84 CHAPITRE 4. DIFFUSION + + + +l b + + + + +k + + +m +b  + +j   c + +i  + n +n u d + +t  u + d + + h + +o + e e +s g + f f +p + +q + + p +r  + + +(a) Topologie globale - Les nœuds isole´s de u ap- (b) Topologie conside´re´e par u a` la fin +paraissent en rouge et hachure´s horizontalement, les de la premie`re e´tape +MPR1 de u apparaissent en bleu et hachure´s verti- +calement. +FIG. 4.10 – Illustration de l’algorithme de se´lection des MPR. +4.6.2 Analyse +Nous nous sommes inte´resse´s aux proprie´te´s d’un ensemble MPR se´lectionne´ par un +nœud donne´. C’est pourquoi, dans notre analyse, nous ne conside´rons pas l’ensemble +du re´seau mais un point particulier, ainsi que son voisinage a` 1 et 2 sauts. En effet, +l’algorithme de se´lection de MPR est distribue´ et exe´cute´ inde´pendamment par chaque +nœud a` partir de sa connaissance de son voisinage a` 1 et 2 sauts. +Soit B(x,R) la boule de rayonR centre´e en x. Nous distribuons un processus ponctuel +de Poisson d’intensite´ λ > 0 dans B(0, 2R) et ajoutons un point 0 au centre de la +boule. Le voisinage de 0 est donc, par de´finition, l’ensemble des points du processus +se trouvant dans B(0, R)\0. C’est pour ce point 0 que nous e´tudions l’algorithme de +se´lection des MPR. +Re´sultats ge´ne´raux. +Avant de donner les re´sultats concernant l’e´tude des MPR, nous donnons des re´sultats +plus ge´ne´raux qui nous serviront pour les calculs suivants. +Soit A(r) l’aire de l’intersection de deux boules de rayon R dont les centres sont dis- +tants de r (figure 4.11(a)) : +( √r ) r2 +A(r) = 2R2 arccos − r R2 − +2R 4 +et A1(u, r, R) l’aire de l’union de deux disques de rayons respectifs R et u et dont les +centres sont distants de r (figure 4.11(b)) : +s +  +R2 − u2 + r2 2 u2 − R2 − r2 R2 − u2 − r2 +A1(u, r,R) = rR 1− −R +2 arccos − u2 arccos +2Rr 2Rr 2ur +4.6. ANALYSE DE LA SE´LECTION DES MPR DANS OLSR 85 + + + + + + + + +R u RR  + + + + + + + + +r r +(a) A(r) est l’aire en bleu : aire (b) A1(u, r, R) est l’aire hachure´e : +de l’intersection de deux boules de union des aires de deux disques de rayons +rayon R. R et u. +FIG. 4.11 – Illustration des aires A(r) et A1(u, r, R). +Nous sommes alors en mesure d e´valuer les valeurs moyennes de d+ d−’ 0 , 0 , |Γ(0)| et +|Γ2(0)| pour une distribution poissonnienne. +Proposition 4 Soit u ∈ Γ(0) un point uniforme´ment distribue´ dans B(0, R). +La valeur moyenne de d+0 (u) est donne´e par : +[ ] ∫ √λ 2pi ∫ R+ 2 − 2 3 3E d0 (u) = (piR A(r))rdrdθ = λRpiR2 0 0 4 +Pour obtenir la valeur moyenne de d+0 (u), l’ide´e est de compter le nombre moyen de +points se trouvant dans l’aire de l’intersection de B(u,R) (1-voisinage de u) et de +B(0, 2R)\B(0, R) (2-voisinage de 0) et de sommer pour tout point u ∈ Γ(0). +Soit v ∈ Γ2(0) un point uniforme´ment distribue´ dans B(0, 2R)\B(0, R). La valeur +moyenne de d−0 (v) est donne´e par : +[ ] ∫ √2R +− 2 2 3 +E d0 (v) = λ A(r)rdr = λR3R2 R 4 +Pour obtenir la valeur moyenne de d−0 (v), on compte le nombre de points se trou- +vant dans l’intersection de B(v,R) (1-voisins de v) et de B(0, R) (1-voisins de 0) +et on somme pour tout point v ∈ Γ2(0). On remarquera que v peut se trouver dans +B(0, 2R)\B(0, R) sans pour autant eˆtre un 2-voisin de 0 dans le cas ou` 0 et v n’ont +aucun voisin commun (si Γ(v) ∩ Γ(0) = ∅). Ainsi, pour obtenir le nombre moyen de +2-voisins de 0, nous devons conditionner le nombre de points v dans B(R, 2R) par la +probabilite´ que v soit un 2-voisin de 0, c.a`.d par la probabili +Nous obtenons : [ ] [ ] +te´ que {Γ(v) ∩ Γ(0) 6= ∅}. +− +− E d0 (v) +E d0 (v)|v ∈ Γ2(0) = (d−P 0 (v) > 0) +86 CHAPITRE 4. DIFFUSION +ou` ( ) ∫2 2R +d−P 0 (v) > 0 = 1− exp{−λA(r)}rdr3R2 R +La taille moyenne du voisinage de 0 est donne´e par : +δ˜(0) = [|Γ(0)|] = λpiR2E +Le nombre moyen de voisins a` deux sauts de 0 (|Γ2(0)|) correspond au nombre de +points v du processus se trouvant dans B(0, 2R)\B(0, R), conditionne´ par la proba- +bilite´ qu’il existe un voisin commun a` chaque v et 0 +| | ( ) +. On obtient : +2 +E [ Γ2(0) ] = 3λpiR P( d−0 (v) >∫0 ) +2 2R += 3λpiR2 1− exp{−λA(r)}rdr +3R2 R +Analyse de la premie`re e´tape de l’algorithme de se´lection des MPR. +Nous nous inte´ressons maintenant plus particulie`rement a` la premie`re e´tape de l’al- +gorithme de se´lection. Dans un premier temps, nous de´terminons le nombre moyen +de points isole´s pour le point 0. Comme nous l’avons vu, l’unique voisin d’un point +isole´ appartenant aussi a` Γ(0) est obligatoirement un MPR1. Cependant, le nombre +de points isole´s ne nous donne pas directement le nombre de MPR1 mais une borne +supe´rieure car un meˆmeMPR1 peut couvrir plusieurs points isole´s. Par exemple, sur la +figure 4.10(a), nous avons quatre MPR1 mais sept nœuds isole´s. Le MPR1 i permet +de couvrir deux nœuds isole´s : les nœuds j et k. +Par de´finition les nœuds isole´s sont les nœuds v ∈ Γ (0)(u) tels que d−, 2 0 (v) = 1. +Proposition 5 Soit v un point uniforme´ment distribue´ dans B(0, 2R)\B(0, R) et D +l ensemble des points isole´s v (tels que d−’ 0 (v) = 1). On obtient : +( ) ∫2 2R +d−P 0 (v) = 1 = λA(r)exp{−λA(r)}rdr3R2 R +Tout comme dans la proposition 4, nous ne conside´rons que les nœuds v tels que v ∈ +Γ2(0) : ( ) (P +P d−0 (v) = 1|v ∈ Γ2(0) = (d−0 (v) = 1) +) +− +P d0 (v) > 0 +Nous pouvons alors de´duire de cette∫probabilite´ le nombre moyen de points isole´s :2R +E [|D|] = 2piλ2 A(r)exp{−λA(r)}rdr +R +qui constitue une borne supe´rieure pour le nombre de MPR1 : +E [|MPR1|] ≤ E [|D|] +4.6. ANALYSE DE LA SE´LECTION DES MPR DANS OLSR 87 +Dans la proposition suivante, nous donnons une borne infe´rieure du nombre moyen de +MPR1 : +Proposition 6 Soit u un point uniforme´ment distribue´ dans B(0, R). +Z Z +2   R R+r  +P (u ∈MPR1) ≥ d ++ +P 0 (u) > 0 f(x, r,R) exp {−λ 2πR +2−A1(R, x,R) }rdxdr +R2 0 R +ou` f(x, r, R) est la fonction densite´ de probabilite´ : +[ ] +∂ +− λ A1(x, r, R)− 2pix ( )f(x, r, R) = ∂x− {− − } exp {−λ A1(x, r, R)− pix2 }1 exp λ (A (R, r,R) piR21 ) +De cette probabilite´, nous pouvons de´duire une borne infe´rieure pour le nombre moyen +de MPR1 : +Z Z +  R R+r ++  +E [|MPR1|] ≥ 2λπP d0 (u) > 0 f(x, r,R) exp {−λ 2πR +2−A1(R, x,R) }rdxdr +0 R +Preuve 6 Pour e´tablir la borne infe´rieure de la probabilite´ qu’un point de Γ(0) soit un +MPR1, nous nous basons sur une condition suffisante. Une condition suffisante pour +que u ∈ MPR1 est que le point w de Γ(u) le plus e´loigne´ de 0 est un point isole´ +(d−0 (w) = 1). +Connaissant r, la distance entre 0 et u, on est capable de calculer la distribution de la +distance entre 0 et w (le point du voisinage de u qui est le plus e´loigne´ de 0). Sachant +alors la distance x entre 0 et w, on calcule la probabilite´ qu’il n’existe qu’un seul +point (le point u) dans l’intersection des voisinages de 0 et w. Cette dernie`re condition +garantit que w est un point isole´ et que u ∈ MPR1. On inte`gre alors cette dernie`re +probabilite´ par les distributions de r et de x pour obtenir le re´sultat final. Cette borne +est tre`s fine puisque, dans la plupart des cas, les points isole´s sont les nœuds les plus +e´loigne´s de 0.  +Nous nous sommes aussi inte´resse´s a` la distribution spatiale des MPR1. Nous avons +pour cela calcule´ un encadrement de la probabilite´ qu’un point u ∈ Γ(0) a` distance +r de 0 soit un MPR1 en fonction de sa distance a` 0. Pour cela, nous conside´rons un +point u ∈ Γ(0) a` distance r (0 < r ≤ R) de 0. Nous fixons ces deux points (u et +0) et distribuons les points du processus de Poisson dans B(0, 2R) inde´pendamment +de ces deux points. Nous cherchons alors quelle est la probabilite´ que ce nœud soit +un MPR1(0). Dans la proposition suivante, nous proposons un encadrement de cette +probabilite´. +88 CHAPITRE 4. DIFFUSION +Proposition 7 Soit u un point a` distance r (0 < r ≤ R) de 0. +Z R+r +  +(u ∈MPR ) ≥ 1− exp {−λ(πR2 − A(r))} f(v, r,R) exp {−λ(2πR2P 1 − A1(R, v, R))}dv +R +( )2 +A(R+ r) +P (u ∈MPR1) ≤ 1− 1− exp {−λ } +2 +Preuve 7 La borne infe´rieure est obtenue de la meˆme fac¸on que la borne infe´rieure +du nombre de MPR1 donne´e dans la proposition 6, mais la distance entre 0 et u est +cette fois fixe´e. La borne supe´rieure est obtenue a` partir de l’ide´e suivante. S’il existe +des points v dans les deux demi-intersections de cercle illustre´s sur la figure 4.12, la +plupart des voisins de u appartenant a` Γ(u) ∩ Γ2(0) sont couverts par ces points v +(en plus de u) et ne sont donc pas isole´s. Concernant les points non couverts par les +points v, nous pouvons montrer facilement que la meˆme borne reste valable. Cela nous +donne une probabilite´ que u ne soit pas un MPR1, de laquelle nous pouvons de´duire +la probabilite´ que u soit un MPR1.  +Upper semi−intersection +0 u +Lower semi−intersection +r R +FIG. 4.12 – Les deux demi-intersections utilise´es dans la preuve de la proposition 7. +4.6.3 Re´sultats nume´riques et simulations +Afin d’estimer de fac¸on nume´rique les re´sultats obtenus pre´ce´demment, nous avons +simule´ l’algorithme de se´lection des MPR. Nous utilisons le meˆme mode`le que celui +e´tudie´ lors de l’analyse the´orique, a` savoir que les nœuds sont re´partis sur une boule +B(0, 2) (R = 1) avec un processus ponctuel de Poisson d’intensite´ λ > 0. Nous +ajoutons le point 0 au centre de la boule et e´tudions le nombre de MPR se´lectionne´s par +ce point a` chaque e´tape de l’algorithme. La figure 4.13 repre´sente des e´chantillons du +mode`le pour diffe´rentes valeurs de λ. Le point 0 pour lequel nous e´tudions l’algorithme +est le point noir central. Les points a` l’inte´rieur de cercle sont les points de Γ(0), les +4.6. ANALYSE DE LA SE´LECTION DES MPR DANS OLSR 89 +(a) λπ = 6 (b) λπ = 45 +FIG. 4.13 – Se´lection des MPR pour λpi = 6 et λpi = 45. +plus gros e´tant les MPR1. Les points a` l’exte´rieur du cercle sont les voisins a` deux +sauts de 0, les points bleus e´tant ceux couverts par les MPR1. +On remarquera que dans les deux cas, la quasi totalite´ du 2-voisinage de 0 est couvert +par les MPR1. L’ajout d’un seul point MPR suffirait a` couvrir l’inte´gralite´ de Γ2(0). +Nous avons vu qu’il existe en moyenne un grand nombre de points isole´s, donnant +naissance a` un grand nombre de MPR1. Ces MPR1 semblent eˆtre re´gulie`rement +distribue´s pre`s de la frontie`re de B(0, R), ce qui confirme les re´sultats obtenus dans la +proposition 7 et explique pourquoi ils couvrent une grande partie de Γ2(0). + 20 +analytic lower bound 1 +analytic upper bound +18 number of MPR selected at the step 1 total number of MPR + 16 0,8 + 14 +0,6 + 12 + 10 +0,4 + 8 + 6 +0,2 + 4 + 2 0 +0,2 0,3 0,4 0,5 0,6 0,7 0,8 0,9 + 20 40 60 80 100 120 +mean number of neighbors distance from the origin +(a) Nombre moyen de MPR et MPR1 obtenus (b) Bornes infe´rieure et supe´rieure de la +par simulation et bornes analytiques du nombre de probabilite´ pour un voisin de 0 d’eˆtre un +MPR1. MPR1(0) en fonction de la distance au +point 0. +FIG. 4.14 – Comparaison des re´sultats analytiques et de simulation. +La figure 4.14(a) montre le nombre moyen de MPR et MPR1 obtenus par simulation +ainsi que les bornes analytiques du nombre de MPR1. On observera qu’approxima- +tivement 75% des MPR sont e´lus lors de la premie`re e´tape de l’algorithme (et sont +number of MPR +90 CHAPITRE 4. DIFFUSION +des MPR1), ce qui confirme le fait que les MPR1 couvrent la quasi-totalite´ du 2- +voisinage. Comme mentionne´ auparavant, la borne infe´rieure est une borne tre`s fine du +nombre de MPR1 moyen. +L’encadrement de la probabilite´ qu’un voisin de 0 soit e´lu comme MPR1(0) (donne´ +dans la proposition 7), nous permet de montrer que lesMPR1 sont re´partis a` proximite´ +de la frontie`re de la porte´e radio R de 0. La figure 4.14(b) montre ces bornes pour une +distance r entre les nœuds 0 et ses voisins variant de 0.2 a` 0.999 pour λ = 15. On +remarque que ces re´sultats de´pendent de λ : plus λ augmente, plus la distance entre 0 +et ses MPR1 augmente aussi (puisque 0 a plus de chances d’avoir des voisins proches +de la frontie`re). +4.6.4 Conse´quences +Comme nous l’avons vu dans les sections pre´ce´dentes, le but recherche´ en introduisant +les MPR est de minimiser le nombre de relais lors de la diffusion du trafic de controˆle. +Le nombre de MPR doit donc eˆtre aussi petit que possible. Bien que plusieurs travaux +aient cherche´ a` optimiser l’algorithme glouton de se´lection des MPR, seule la seconde +e´tape de l’algorithme peut eˆtre ame´liore´e puisque la premie`re est indispensable pour +couvrir l’ensemble du 2-voisinage d’un nœud. Or, comme nous avons pu le constater +au cours de nos analyses et simulations, cette premie`re e´tape me`ne a` la se´lection de +plus de 75% des MPR. Cela signifie que les ame´liorations pouvant eˆtre apporte´es ne +portent que sur 25% des MPR, ce qui explique que les variantes de l’algorithme de +se´lection ne produisent aucune ame´lioration significative. +Malheureusement, cette caracte´ristique peut e´galement eˆtre une source de proble`me de +robustesse. En effet, si 75% des MPR de u couvrent au moins un nœud isole´, la perte +d’un de ces nœuds engendre une forte probabilite´ qu’au moins un voisin v a` 2 sauts de +u ne rec¸oive plus un message envoye´ u. Il se peut bein suˆr que v rec¸oive le message +de u via un autre chemin mais ce dernier serait plus optimal comme le clame OLSR. +De plus, si v est tel que v ∈ MPR(u) et v ∈/ MPR(w), il peut recevoir un message +pour la premie`re fois par w plutoˆt que u mais ne le re-transmettra pas puisqu’il n’est +pas un MPR de w. Cela peut conduire a` l’isolation de certaines parties du re´seau lors +d’une diffusion, comme l’illustre la figure 4.15. Les nuages repre´sentent deux parties +connexes du re´seau, connecte´es par les nœuds b et c. Comme le nœud e est un nœud +isole´ pour a, a e´lit c en tant que MPR. Il ne choisit pas b puisque le nœud d couvert +par b l’est e´galement par c. Supposons que le lien entre c et a tombe et que la diffusion +se propage avant que a n’ait pu recalculer ses MPR. Bien que le re´seau soit encore +connecte´, la partie droite du re´seau ne sera pas touche´e par la diffusion car b n’e´tant +pas MPR de a, il ne re-transmettra pas le message. Ce phe´nome`ne peut expliquer les +mauvais re´sultats obtenus par les MPR lors de l’e´tude de la robustesse des protocoles +de diffusion en section 4.5. De plus, les liens entre un nœud et ses MPR ont de fortes +probabilite´s de casser dans un environnement mobile puisque, comme nous avons pu le +constater, les MPR sont situe´s a` proximite´ de la frontie`re de la porte´e de transmission +des nœuds. Ils sont donc plus enclins a` basculer en dehors de la zone de transmission +et ainsi a` casser le lien radio. +4.7. CONCLUSION ET PERSPECTIVES 91 +b +d +a +c e +(a) +FIG. 4.15 – Exemple. +4.7 Conclusion et perspectives +Dans ce chapitre, nous avons tire´ avantage de certaines caracte´ristiques des clusters +forme´s par notre heuristique pour proposer une utilisation supple´mentaire de la struc- +ture. En effet, la structure d’arbres sous-jacente des clusters permet l’application d’un +protocole de diffusion aussi bien dans un cluster que sur l’ensemble du re´seau, ceci +avec un couˆt faible et borne´ et une maintenance quasi-locale. Nous avons analyse´ de +fac¸on the´orique le nombre de re´ceptions par nœud lors d’une diffusion. Puis, nous +avons pu constater que notre algorithme de diffusion proposait le meilleur compromis +couˆt en e´nergie - latence - robustesse parmi les protocoles de diffusion existant dans la +litte´rature. +Dans le futur, il serait inte´ressant d’e´tudier ce protocole dans un environnement plus +mobile. Dans notre approche, nous conside´rons une couche MAC ide´ale afin de pouvoir +comparer les protocoles de niveau 3 sans s’occuper des proble`mes qui peuvent surve- +nir aux niveaux infe´rieurs et influer sur les performances de chacun de ces protocoles. +Cependant, comme nous l’avons mentionne´, plus le nombre de messages e´change´s +est important, plus fortes sont les collisions survenant aux niveaux infe´rieurs. Il sem- +blerait donc inte´ressant d’e´tudier un protocole de diffusion qui ne soit pas cloisonne´ +a` la couche re´seau mais qui prenne en conside´ration les caracte´ristiques de plusieurs +couches en meˆme temps, plutoˆt que de chercher a` optimiser un protocole a` un niveau +particulier. +92 CHAPITRE 4. DIFFUSION +4.8 Publications +1. Journaux et revues avec comite´ de lecture : +(a) Efficient Broadcasting in Self-Organizing Sensor Networks. Nathalie Mit- +ton, Anthony Busson et E´ ric Fleury. International Journal of Distributed +Sensor Networks (IJDSN), Volume 1, Janvier 2006. +2. Colloques et confe´rences internationaux avec comite´ de lecture : +(a) Efficient Broadcasting in Self-Organizing Multi-Hop Wireless Network. +Nathalie Mitton, E´ ric Fleury. Conference on AD-HOC Networks & Wire- +less (Ad Hoc Now’05), 6-8 Octobre 2005, Cancu`n, Mexique. Se´lectionne´ +parmi les meilleurs papiers pour une soumission a` une issue spe´ciale du +journal JDA. +(b) An analysis of the MPR selection in OLSR and consequences. Anthony +Busson, Nathalie Mitton and E´ ric Fleury. Mediterranean Ad Hoc Net- +working Workshop (MED-HOC-NET’05), Juin 2005, Ile de Porquerolles, +France. +(c) Broadcast Analysis in Multi-hop Wireless Networks. Nathalie Mitton, An- +thony Busson and E´ ric Fleury. Invited Paper at Spatial Stochastic Modeling +of Wireless Networks (SpasWIN’05), Avril 2005, Riva de Garda, Italie. +(d) An analysis of the MPR selection in OLSR. Anthony Busson, Nathalie Mit- +ton and E´ ric Fleury. Spatial Stochastic Modeling of Wireless Networks +(SpasWIN’05), Avril 2005, Riva de Garda, Italie. +3. Colloques et confe´rences nationaux : +(a) Une analyse de la se´lection des MPR dans OLSR. Anthony Busson, Natha- +lie Mitton et E´ ric Fleury. ALGOTEL’05, Mai 2005, Presqu’ıˆle de Giens, +France. +4. Rapports de recherche : +(a) Broadcast in Self-organizing Wireless Multi-hop Network. Nathalie Mitton, +Anthony Busson and E´ ric Fleury. RR-5487. Fe´vrier 2005. +(b) An analysis of the MPR selection in OLSR. Anthony Busson, Nathalie Mit- +ton and E´ ric Fleury. RR-5468. Janvier 2005. +5. Journaux en cours de soumission : +(a) Efficient Broadcasting and Self-Stabilization in Self-Organizing Multi-hop +Wireless Networks. Nathalie Mitton, E´ ric Fleury, Isabelle Gue´rin-Lassous +and Bruno Se´ricola and Se´bastien Tixeuil. ”Best Papers of Adhoc Now +2005” special issue of the Journal of Discrete Algorithms (JDA). +6. Se´minaires, pre´sentations, expose´s : +(a) Diffusion efficace dans les re´seaux sans fil multi-sauts. Nathalie Mitton, +E´ ric Fleury. Journe´es RESCOM - Villeneuve d’Ascq - France - 6-7 Mars +2005. +(b) An analysis of the MPR selection in OLSR. Anthony Busson, Nathalie Mit- +ton, Eric Fleury. Se´minaire ACI FRAGILE - Aussois - France - 23-24 Mars +2005. +4.9. ANNEXES 93 +4.9 Annexes +Nous pre´sentons ici les preuves des propositions 1 et 2 donnant le nombre de re´ceptions +par nœud lors de la diffusion d’un message. +Preuve de la proposition 1 E´ tant donne´ un processus ponctuel stationnaire Φ d’in- +tensite´ λ (λ > 0), soit ΦRelay d’intensite´ λRelay un amincissement de Φ. Les points de +ΦRelay repre´sentent les relais. Nous supposons que ΦRelay est toujours un processus +ponctuel stationnaire. On cherche a` montrer que le nombre moyen de re´ceptions d’un +meˆme message par nœud r est : [ ] +o ′r = E Φ(B ) +[ ] ΦRelay 0 +′ +ou` oEΦ ΦRelay(B0) est l’espe´rance sous Palm par rapport au processus Φ (et donc la +l y ) d b d l i d ′va eur mo enne u nom re e re a s ans B0. +Pour un point donne´, c.a`.d. le point 0 sous les probabilite´s de Palm, le nombre moyen +de re´ceptions correspond au nombre moyen de points de ΦRelay dans le voisinage de 0 +(a` distance infe´rieure ou e´gale a` R). +A` partir de la formule de Mecke [76], on peut de´duire que le nombre total de re´ceptions +Z rec¸ues par l’ensembl[e∫des nœuds d’une surfa]ce S est :[ ] +′ o ′Z = E ΦRelay(Bx)Φ(dx) = λEΦ ΦRelay(B0) +S +Par stationnarite´ [d∫es deux processus pon]ctuels [Φ∫et ΦRelay , nous avon]s : +′ ′ +E ΦRelay(Bx)Φ(dx) = E Φ(Bx)ΦRelay(dx) +S S +La partie gauche de l’e´quation est le nombre total de re´ceptions rec¸ues par les nœuds de +la surface S, sachant que les nœuds en bordure peuvent recevoir le message depuis des +nœuds en dehors de S. La partie droite de l’e´quation est le nombre de re´ceptions rec¸ues +par l’ensemble des nœuds du processus Φ mais ge´ne´re´es uniquement par les relais se +trouvant dans S. En appliquant la formule de Mecke de part et d’autre de l’e´quation, +on obtient : +[ ] [ ] +o ′ o ′λEΦ ΦRelay(B0) = λREΦ Φ(B )Relay 0 +d’ou` : +[ ] [ ] λ [ ] +r = o +′ ′ Relay ′ +EΦ Φ (B ) = +o o o +Relay 0 EΦ Φ(B ) P (0 ∈ Φ ) = E Φ(B )Relay 0 Φ Relay λ ΦRelay 0 +94 CHAPITRE 4. DIFFUSION +Preuve de la proposition 2 E´ tant donne´ un graphe ale´atoireG(V,E) et un ensemble +de relais Relay ⊂ V ou` les degre´s des nœuds et des relais ainsi que le nombre de +re´ceptions par nœud sont e´qui-distribue´s. On cherche a` montrer que le nombre moyen +de re´ceptions par nœud r s’e´cr[it : ∣∣∣ ]r = E δ(v1) v1 ∈ Relay P(v1 ∈ Relay) (4.2) +Soient N une variable ale´atoire repre´sentant le nombre de sommets dans G (N = |V |) +et Z le nombre total de re´ceptions induites sur les nœuds du re´seau par la diffusion. +Pour tout u ∈ V , nous de´finissons δR(u) comme le nombre de relais dans le voisinage +de u. +Comme seuls les relais e´mettent le message, les liens e´tant bidirectionnels, le nombre +de re´ceptions du message perc¸ues par un nœud (qu’il soit lui-meˆme relais ou non) +correspond au nombre de relais dans son voisinage. Nous avons donc : +r = E[δR(u)], ∀u ∈ V +ou` E[δR(u)] est l’espe´rance de la variable δR(u) et correspond a` sa valeur moyenne. +Les liens e´tant bi-directionnels, Z peu∑t s’e´crire de deux fac¸ons : +Z = δR(u) (4.3) +u∈V +ou ∑ ∑ +Z = δ(v) = δ(v)1lv∈Relay (4.4) +v∈Relay v∈G +ou` 1lv∈Relay = 1 if v ∈ Relay et 1lv∈Relay = 0 sinon. +A` partir de la pre[mie`r]e formulation[de∑+∞ ∑ +Z (e´quation 4.3), on a +k +Z δ (u ) ∣∣∣ +] +i=1 R i +E = E N = k P(N = k) +N k +k∑=1+∞∑k 1 [ ∣∣ ] += E δR(ui)∣N = k P(N = k) +k +k∑=1 i=1+∞ k [ ∣∣ ] += E δR(u1)∣N = k P(N = k) +k +k∑=1+∞ [ ∣∣∣ ]= E δR(u1) N = k P(N = k) +k=1 += E [δR(u)] +Couple´ a` la de´finition de r donne´ en e´quation[4.2,]on a : +Z +r = E +N +4.9. ANNEXES 95 +[ ] +Cette dernie`re e´galite´ nous permet de calculer la valeur moyenne de ZN : +Z +E N en +utilisant cette fois la deuxie`me formulation de Z (e´quation 4.4). Nous conditionnons +cette quantite´ par les diff[e´ren]tes valeurs de N : +Z +r = E [N∑ ] +v∈V δ(v)1lv∈Relay= E +∑ [+∞ ∑ +N +k +i=1 δ(vi)1lvi∈Relay ∣∣∣ +] += E N = k P(N = k) +k +k∑=1+∞∑k 1 += E [δ(vi)1lv ∈Relay]P(N = k) +k i +k∑=1 i=+∞ [1 += E δ(v1)1lv ∈Relay∣∣∣ ]N = k P(N = k)1 +k=1 += E [[δ(v1)1l∣∣ v ]1∈Relay∣ ]= E δ(v1) v1 ∈ Relay P(v1 ∈ Relay) +ou` v1 est un nœud choisi arbitrairement parmi les sommets de G. +96 CHAPITRE 4. DIFFUSION +Chapitre 5 +Localisation et routage +5.1 Introduction +Nous avons propose´ un algorithme de clustering pour organiser le re´seau (chapitre 3) +afin de pouvoir utiliser le re´seau sans fil multi-sauts sur de larges e´chelles. Nous avons +vu comment une telle structure de clusters peut eˆtre utilise´e pour effectuer une dif- +fusion efficace, aussi bien dans tout le re´seau que dans un cluster. Dans ce chapitre, +nous expliquons comment nous comptons utiliser notre organisation de clusters pour +le routage et permettre a` toute paire de nœuds de communiquer. Dans tout type de +re´seau, pour router un message vers un nœud destination v, un nœud u doit avoir une +information sur la position de v. Dans les re´seaux filaires, l’information de routage +est encapsule´e dans l’adresse du nœud, celle-ci e´tant de´pendante de la topologie du +re´seau. Par exemple, une adresse IP identifie un nœud et en meˆme temps permet de le +situer puisque le pre´fixe du re´seau est inclus dans l’adresse IP. Dans les re´seaux sans fil, +l’identifiant permanent du nœud ne peut inclure sa position du fait de sa mobilite´ et est +donc inde´pendant de la topologie sous-jacente. Les protocoles de routage utilise´s dans +les re´seaux filaires ne peuvent eˆtre applique´s. Une approche possible est d’utiliser un +routage indirect. Une ope´ration de routage est qualifie´e de indirecte si elle s’effectue +en deux e´tapes : (i) le look-up qui permet de situer le nœud cible, puis, (ii) le routage +qui permet a` la source de communiquer directement avec le nœud cible´. La figure 5.1 +illustre un routage indirect. Le nœud u veut communiquer avec le nœud v mais il doit +d’abord le localiser. Pour cela, il effectue l’ope´ration de look-up : il demande a` une +troisie`me entite´ (ici, le nœud w) ou` se trouve v. Cette entite´ est un point de rendez- +vous : v enregistre re´gulie`rement sa position aupre`s de w qui garde une trace de la +position de v. Une fois que w a re´pondu a` u, u est en mesure de contacter directement +v Ce principe de routage est par exemple utilise´ dans les re´seaux de te´le´phonie GSM1. +ou dans le protocole Mobile IP2, ou` la position de la destination est pre´alablement de- +mande´e respectivement aux HLR (Home Location Register) ou aux Home Agent avant +1http ://www.gsm.org +2http ://www.ietf.org/rfc/rfc2002.txt +97 +98 CHAPITRE 5. LOCALISATION ET ROUTAGE +d’e´tablir directement la communication entre le demandeur et la destination. Cepen- +dant, un tel principe ne peut eˆtre mis en œuvre dans un re´seau sans fil de type ad hoc +car tous les nœuds sont susceptibles de bouger, y compris les Home Agents potentiels. +w +2. V is at (X,Y) +1: Where is v? v +3. Route towards v +u +FIG. 5.1 – Routage indirect : le nœud u veut communiquer avec le nœud v mais ne +connaıˆt pas sa position. Il demande donc dans un premier temps a` une troisie`me entite´ +(ici, le nœud w) ou` se trouve v. w sait ou` se trouve v car v enregistre re´gulie`rement sa +position aupre`s de w qui peut re´pondre a` u. u est alors en mesure de contacter v. +Nous nous proposons d’appliquer un sche´ma de routage indirect pour router dans des +re´seaux sans fil multi-sauts a` large e´chelle. Nous de´sirons une solution qui permette le +passage a` l’e´chelle du re´seau et qui doit donc maintenir le moins d’information pos- +sible sur les nœuds. Nous voulons e´galement e´viter les situations ou` la distance entre +la source (le nœud u sur la figure 5.1) et le point de rendez-vous (le nœud w) est plus +importante que la distance entre la source (le nœud u) et la destination (le nœud v). +En effet, si la requeˆte de localisation doit traverser deux fois le re´seau avant qu’une +communication entre deux nœuds qui peuvent eˆtre proches s’e´tablisse, nous occupons +inutilement la bande passante et introduisons une forte latence, ce qui empeˆche le pro- +tocole d’eˆtre extensible. +Un moyen d’appliquer un routage indirect est d’utiliser une Table de Hachage Dis- +tribue´e (DHT - Distributed hash table). L’imple´mentation des DHT dans les re´seaux +sans fil a donne´ naissance a` de nouvelles proble´matiques [64]. De plus, un tel adres- +sage offre une approche prometteuse pour permettre le passage a` l’e´chelle [30]. Les +DHT fournissent une association ge´ne´rale entre une clef et toute sorte d’information +(comme l’identite´ d’un nœud ou une position). Elles utilisent un espace d’adressage +virtuel V . Des partitions de cette espace virtuel sont alloue´es aux nœuds du re´seau. +L’ide´e est d’utiliser une fonction depuis un espace re´el vers un espace virtuel V . Cette +fonction, dite de hash, permet aux nœuds d’identifier certains points de rendez-vous +aupre`s desquels ils enregistrent leur position. Cette fonction de hash est connue de tous +les nœuds du re´seau et peut ensuite eˆtre utilise´e par un nœud source pour retrouver ces +meˆmes points de rendez-vous et leur demander la position du nœud qu’ils recherchent. +Une information connue de tous (comme le nom de notre destinataire) est hashe´e en +une clef (hash(v) = clev) de l’espace d’adressage virtuel V . Les informations as- +socie´es a` cette clef (comme la position des nœuds) sont ensuite stocke´es sur le (ou les) +nœud(s) responsable(s) de la partition de l’espace virtuel auquel la clef appartient. Par +exemple, sur la figure 5.1, nous avons hash(v) = Position nœud v ∈ I ⊂ V et +le nœud w est responsable de l’intervalle I . En connaissant I , les nœuds v et u sont +5.1. INTRODUCTION 99 +capables de trouver w soit pour s’enregistrer (pour le nœud v) soit pour lui demander +ou` se trouve v (pour le nœud u). On remarque que les nœuds u et v n’ont pas besoin de +connaıˆtre la vraie identite´ dew, mais juste son adresse virtuelle dans V . Cette ope´ration +retournant le(s) nœud(s) responsable(s) d’une certaine clef dans les syste`mes utilisant +des DHT, est appele´e look-up. Plus de de´tails au sujet des ope´rations de look-up sont +donne´s dans [10]. +Dans la litte´rature, les DHT sont utilise´es a` deux niveaux : au niveau de la couche appli- +cation et au niveau de la couche re´seau. Les DHT sont utilise´es au niveau applicatif en +particulier dans les syste`mes pair-a`-pair. La clef ”hache´e” dans ces syste`mes de partage +de fichiers est l’identifiant d’un fichier (cle = hash(fichier)). L’information associe´e +a` la clef et maintenue par le nœud responsable de cette clef est l’identite´ des nœuds +du re´seau qui de´tiennent ce fichier. Les adresses virtuelles des nœuds (ou partitions de +V dont ils sont responsables) forment un re´seau overlay (c.a`.d un re´seau virtuel base´ +sur le re´seau physique qui maintient des liens logiques entre les nœuds) sur lequel les +requeˆtes sont route´es. Ce qui diffe´rencie majoritairement les diffe´rentes propositions +de re´seaux pair-a`-pair dans la litte´rature est la ge´ome´trie de ce re´seau overlay. En effet, +la forme de ce re´seau va de l’anneau (Chord [73]) au graphe de De Bruijn (D2B [33]) +en passant par des arbres (Tapestry [84], Kademlia [54]), des espaces d-dimensionnels +(CAN [68]), des structures en forme de papillon [52] ou encore des structures hybrides +arbres-anneaux (Pastry [70]). +Lorsqu’elles sont utilise´es au niveau de la couche re´seau, les DHT distribuent les in- +formations de position des nœuds a` travers le re´seau et sont utilise´es pour identifier +un nœud pouvant fournir des informations permettant de joindre le nœud destination. +C’est de cette fac¸on que nous nous proposons d’utiliser les DHT. Quand un nœud u +doit envoyer une information a` v, il doit d’abord le localiser et pour cela, demander a` +un nœud w, responsable de la clef k = hash(v). Parmi les DHT applique´es au niveau +re´seau, le routage utilise´ dans les diffe´rentes propositions est de deux sortes : un rou- +tage inde´pendant de la DHT (le routage n’utilise pas l’espace virtuel V) et un routage +de´pendant de la DHT (le routage utilise l’espace virtuel V). +Lorsque le routage est inde´pendant de la DHT, les nœuds disposent ge´ne´ralement de +leur coordonne´es ge´ographiques absolues (obtenues par exemple avec un GPS) ou re- +latives (comme dans [17]). C’est cette information qu’ils associent a` la clef. En ef- +fectuant hash(destination), un nœud u obtient des coordonne´es ge´ographiques d’une +”zone rendez-vous” A. u peut alors appliquer un routage ge´ographique classique afin +d’envoyer sa requeˆte vers un nœud v se trouvant dans la zone A et qui de´tient les +coordonne´es ge´ographiques de la destination cherche´e par u. De la`, u effectue de nou- +veau un routage ge´ographique mais cette fois, directement vers la destination. Ce type +de routage inde´pendant de la DHT est utilise´ par exemple dans [6, 57, 58], dans les +projets ”Terminodes” [15, 16] et ”Grid” [48]. Dans notre cas, les nœuds ne disposent +d’aucune information concernant leur position ge´ographique et nous aimerions e´viter +l’utilisation d’un GPS. De ce fait, nous ne pouvons utiliser ce type de routage indirect. +Dans le cas ou` le routage est de´pendant de la DHT, l’espace virtuelV qui lui est associe´, +est utilise´ non seulement pour identifier les points de rendez-vous mais e´galement pour +router vers ces points et vers la destination finale. Dans ce cas, l’adresse virtuelle d’un +100 CHAPITRE 5. LOCALISATION ET ROUTAGE +nœud de´pend de sa position. La cohe´rence du protocole de routage repose alors sur +la cohe´rence de la distribution des partitions de l’espace virtuel V sur les nœuds du +re´seau. Le routage est effectue´ sur la structure logique et ne tient plus compte du +re´seau physique sous-jacent. Dans de tels scenarii, un nœud u cherchant le nœud w +re´cupe`re l’adresse virtuelle du point de rendez-vous v avec la fonction de hachage +hash(w) = Idvirtuel(v). Les requeˆtes de look-up sont route´es dans V jusqu’a` v qui +retourne l’adresse virtuelle de w. De la`, u joint w en utilisant son adresse virtuelle et en +routant dans V . Ge´ne´ralement, le routage dans l’espace virtuel est un routage glouton : +”Transmet a` ton voisin dans V dont l’adresse virtuelle est la plus proche de l’adresse +virtuelle de la destination”. C’est ce qu’on trouve par exemple dans Tribe [78, 79] ou +L+ [22] sur lequel se base SAFARI [69]. La principale difficulte´ ici est de re´partir les +partitions de l’espace virtuel V de fac¸on a` ce que les routes obtenues en routant dans V +ne soient pas beaucoup plus longues que les routes physiques. +5.2 Localisation et routage sur une structure de clus- +ters +Dans notre proposition, chaque nœud de´tient une information concernant sa position +relative : l’identite´ de son cluster. C’est cette information que les nœuds vont associer +a` la clef de hachage. Comme nous avons une structure d’arbres, nous proposons de +partitionner l’espace virtuel V dans chaque arbre. V e´tant ainsi duplique´ autant de fois +que l’on a de clusters, on retrouve un nœud responsable d’une clef donne´e dans chaque +arbre/cluster. Chaque nœud enregistre alors sa position dans chaque espace virtuel et +donc dans chaque arbre. De cette fac¸on, lorsqu’un nœud v recherche un nœud u dans le +re´seau, il a juste a` chercher dans son propre cluster. Comme l’excentricite´ d’un nœud +dans un cluster est faible (voir chapitre 3.6.2), la distance a` parcourir pour atteindre +le nœud de rendez-vous est e´galement faible. Partitionner ainsi plusieurs fois l’espace +virtuel plutoˆt qu’une seule fois sur tout le re´seau e´vite les situations ou` la distance +entre la source et le point de rendez-vous est supe´rieure a` la distance entre la source et +la destination, puisque la source et le point de rendez-vous appartiennent toujours au +meˆme cluster alors que la destination peut eˆtre n’importe ou` dans le re´seau. +Pour distribuer les partitions de l’espace virtuel V de la DHT de telle fac¸on que, e´tant +donne´e une adresse virtuelle, un nœud u soit en mesure de joindre le nœud en question +sans information supple´mentaire, nous utilisons un sche´ma d’e´tiquetage d’arbre (tree +Interval Labeling Scheme) pour ensuite permettre un routage par intervalle sur notre +structure logique. +Dans les diverses propositions de DHT que nous avons pre´sente´es, les deux phases du +routage indirect (look-up et routage) sont toujours du meˆme type : inde´pendantes de +la DHT et effectue´es dans l’espace physique ou de´pendantes de la DHT et effectue´es +sur l’espace logique. Dans notre approche, les deux e´tapes de routage indirect sont ef- +fectue´es diffe´remment. Le look-up est effectue´ en utilisant un routage par intervalle sur +les adresses virtuelles des points de rendez-vous alors que l’e´tape de routage s’effectue +dans l’espace physique, inde´pendamment de V . +5.2. LOCALISATION ET ROUTAGE 101 +Le routage par intervalle s’est ave´re´ tre`s attractif de par sa simplicite´. Il a e´te´ introduit +dans les re´seaux filaires par Santoro et Khatib dans [72] dans le but de re´duire la taille +des tables de routage. L’ide´e est de repre´senter la table de routage de chaque nœud +de manie`re compacte, en agre´geant l’ensemble des adresses destination qui peuvent +eˆtre atteintes en utilisant le meˆme port de sortie, au moyen d’intervalles d’adresses +conse´cutives. Par exemple, si l’on conside`re le graphe repre´sente´ sur la figure 5.2(a), le +nœud 0 doit utiliser le port a pour atteindre les nœuds 4, 5 et 6, le port b pour atteindre +1 et 2 et le port c pour atteindre 3. Plutoˆt que de cre´er une entre´e dans sa table de +routage par nœud destination, il cre´e une entre´e par port de sortie et plutoˆt que de lister +tous les nœuds accessibles via ce port, il stocke seulement l’intervalle contenant les +adresses de ces nœuds : [1, 2] pour le port a, [4, 6] pour le port b et [3] pour le port +c. Le principal avantage de ce type de routage est qu’il ne´cessite peu de me´moire sur +les nœuds puisque la taille de la table de routage d’un nœud u est en O(δ(u)). Le +routage est exe´cute´ de fac¸on distribue´e : a` chaque nœud interme´diaire x, si x n’est pas +le nœud destination y, le message est transfe´re´ sur le port de sortie dont l’e´tiquette est +un ensemble d’intervalles I tel que y ∈ I . +Un Interval Labeling Scheme (ILS) est la fac¸on d’allouer les e´tiquettes des nœuds +(adresses virtuelles) pour pouvoir de´finir les intervalles a` assigner aux areˆtes de chaque +nœud, de fac¸on a` pouvoir effectuer un routage par intervalle efficace avec des routes +aussi courtes que possible. Les auteurs de [77] ont montre´ qu’un arbre non-oriente´ +supportait un routage par intervalle avec de plus courts chemins (dans l’arbre) et en +n’utilisant qu’un intervalle par areˆte sortante a` condition de distribuer les e´tiquettes +(ILS) en effectuant un parcours en profondeur de l’arbre. +Dans les re´seaux filaires, dans un arbre, les nœuds doivent stoker un intervalle pour cha- +cune des areˆtes sortantes. La taille de la table de routage d’un nœud u est en O(δ(u)). +Dans un environnement sans fil, l’e´mission d’un message atteint tous les nœuds se trou- +vant a` porte´e radio de l’e´metteur. Les areˆtes du graphes sont en re´alite´ des hyper-areˆtes +(voir figure 5.2). La proble´matique est donc un peu diffe´rente puisque une requeˆte +e´mise sera entendue par tous les voisins de la source, qu’elle leur soit destine´e ou pas. +Comme les nœuds n’ont qu’une hyper-areˆte sortante, ils peuvent ne stocker qu’un seul +intervalle. Nous proposons ici de tirer avantage de la nature diffusante du me´dium ra- +dio. Les nœuds stockent l’intervalle global pour lequel leur sous-arbre est responsable +et non plus un intervalle pour chaque voisin. Par exemple, si on conside`re la figure 5.2, +le nœud 0 ne ge`re plus 3 intervalles mais un seul : [0, 6]. Cela donne une taille de table +de routage en O(1) par nœud. Quand une requeˆte est envoye´e, tous les nœuds a` porte´e +radio la rec¸oivent mais seuls ceux concerne´s y re´pondent. +5.2.1 Re´sume´ et analyse de complexite´ +Pour re´sumer, nous proposons d’appliquer un routage indirect sur la structure en arbres +de notre re´seau auto-organise´, en utilisant une DHT qui associe chaque nœud a` sa +position dans le re´seau : son cluster. L’ensemble des adresses virtuelles V de la DHT +est partitionne´ et re´parti sur les nœuds de chaque cluster. Comme le nombre de clusters +102 CHAPITRE 5. LOCALISATION ET ROUTAGE +6 +[1,5] a +[6] +6 +b a[6] [5] 5 [5] +[6,4] 54 c [4,6] 4 +a [0,3] +[1 2] [0,6] +[1,2] a [4,6] +0 +1 +b [3,0] [3] +1 0b [3] [2] 3a c 2 +[2] +[3,1] [4,2] +a a2 3 +(a) Routage en environnement filaire. Les nœuds (b) Routage en environnement sans fil. Les +stockent un intervalle par areˆte sortante. nœuds stockent un seul intervalle (un par +hyper-areˆte). +FIG. 5.2 – Areˆtes dans un re´seau filaire (a) Vs hyper-areˆtes dans un re´seau sans fil (b). +est borne´ par une constante et que les clusters sont homoge`nes (chapitre 3), chaque +nœud maintient finalement O(1) informations de position. +Quand un nœud u doit joindre un nœud v, il obtient l’adresse virtuelle d’un point de +rendez-vous en utilisant la fonction de hash : hash(v) = keyv ∈ V . Puis, a` partir +de cette adresse, en appliquant un routage par intervalle sur l’espace virtuel V de son +propre arbre, il re´cupe`re la position C(v) de v. Comme les intervalles des voisins de u +ne sont pas maintenus par u, u stocke uniquement l’intervalle dont son arbre est res- +ponsable. La taille de la table de routage de u est en O(1). Une fois que u connaıˆt C(v), +il peut atteindre C(v) en employant un routage pro-actif entre clusters puis un routage +re´actif pour joindre v une fois que le cluster destination est atteint. Comme le nombre +de clusters est borne´ par une constante, chaque cluster a O(1) routes a` maintenir vers +les autres clusters. +5.3 Notre proposition +5.3.1 Pre´liminaires +Chaque nœud u posse`de deux adresses : +– Une adresse universelle Id(u) ∈ IR (souvent note´e u par la suite). Cette adresse est +unique dans le re´seau et ne change jamais. Elle est le ”vrai” nom de u. +– Une adresse logique i(u) ∈ V . Cette adresse est unique dans un cluster. Elle peut +changer a` chaque re-distribution des partitions de V parmi les nœuds d’un cluster. +Elle identifie le nœud u dans son espace logique. +5.3. NOTRE PROPOSITION 103 +Soit I(u) la partition de V assigne´e au nœud u. I(u) est telle que I(u) = [i(u), ...[ +ou` i(u) est l’adr +T ⋃esse logique de u dans V . i(u) de´pend donc de I(u). On noteItree(s (u)) = v∈sT (u) I(v) l’intervalle/partition de V pour lequel le sous-arbre +de racine u est responsable. |I| de´signe la taille de l’intervalle I . +5.3.2 Distribution des partitions de l’espace virtuel - ILS +Comme mentionne´ dans la section 5.2, une distribution optimale des intervalles sur un +arbre est obtenue via une nume´rotation des nœuds obtenue par un parcours en profon- +deur ILS (Depth First Search DFS-ILS). +Comme dans tout ILS traditionnel, les partitions de V sont attribue´es a` chaque nœud +u ∈ V de sorte que : +– Les intervalles des nœuds de sT (u) forment un intervalle continu. +– La taille de l’intervalle dont un sous-arbre est responsable est proportionnelle a` la +taille de ce sous-arbre : |Itree(sT (u))| ∝ |sT (u)|. Et donc, pour tout nœud v ∈ +sT (u), |Itree(sT (u))| ≥ |Itree(sT (v))|. +V V ⋃– est entie`rement distribue´ parmi les nœuds du cluster : = v∈C(u) I(v). +– Les diffe´rents intervalles s’excluent mutuellement : ∀v ∈ C(u),∀w ∈ C(u),v 6= +w I(v) ∩ I(w) = ∅. +Nous proposons une re´partition des intervalles distribue´e, qui s’effectue en paralle`le sur +chaque branche de chaque arbre. Chaque nœud u ne´cessite des informations pouvant +se trouver jusqu’a` dtree(u,H(u)) sauts de lui ou` dtree(u,H(u)) est le nombre de sauts +dans l’arbre entre u et son cluster-headH(u). La distance dtree(u,H(u)) est borne´e par +la hauteur des arbres qui est elle-meˆme borne´e par une constante (voir chapitre 3.6.2). +Cette distribution peut donc eˆtre qualifie´e de quasi-locale selon la taxonomie e´tablie +en [81], ce qui implique une maintenance rapide du processus. +Notre algorithme s’exe´cute en deux temps : une premie`re phase pendant laquelle les +nœuds remontent des informations depuis les feuilles de l’arbre jusqu’a` sa racine et une +seconde phase ou` les nœuds internes distribuent re´cursivement les intervalles parmi +leurs fils. La distribution des intervalles s’effectue en paralle`le sur chaque branche de +chaque arbre, chaque phase ayant une complexite´ temporelle en O(Tree depth). La +complexite´ temporelle totale de l’algorithme de distribution des intervalles pour un +cluster est donc de 2 × (Tree depth). Comme la hauteur des arbres Tree depth est +borne´e par une constante, la complexite´ temporelle devient O(1). +La figure 5.3 illustre cette distribution d’intervalles pour V = [1, 17[. +E´ tape 1. Comme nous l’avons de´ja` vu dans le chapitre 3.6.2, chaque nœud u est en +mesure de savoir en un temps borne´ qui l’a choisi comme pe`re parmi ses voisins et +donc connaıˆt son nombre de fils. Si un nœud est feuille, la taille de son sous-arbre +est 1. De`s qu’un nœud interne a rec¸u la taille des sous-arbres de chacun de ses fils, il +calcule la taille de son propre sous-arbre qui est la somme de la taille +| T | | { }⋃ T | ∑des sous-arbres dechacun de ses fils plus 1 : s (u) = u v∈Ch(u) s (v) = 1+ v∈Ch(u) |sT (v)|. +Chaque nœud envoie la taille de son sous-arbre a` son pe`re et ainsi de suite jusqu’a` +atteindre le cluster-head. C’est ce qu’illustre la figure 5.3(a). +104 CHAPITRE 5. LOCALISATION ET ROUTAGE +E´ tape 2. Une fois que le cluster-head connaıˆt la taille des sous-arbres de chacun de ses +fils, il partage V e´quitablement entre lui-meˆme et ses fils. Chaque fils u se voit attribuer +une partition de V , Itree(sT (v)), de taille proportionnelle a` la taille de son sous-arbre. +Chaque nœud interne re-distribue alors l’intervalle qu’on lui a alloue´ entre lui et ses +fils, et ainsi de suite, jusqu’a` atteindre les extre´mite´s des branches de l’arbre. Cette +e´tape est illustre´e sur la figure 5.3(b). +Ainsi, une fois les deux e´tapes de l’algorithme accomplies, chaque nœud est respon- +sable d’une partition de V qui est de taille e´gale pour tous les nœuds d’un meˆme cluster. +La figure 5.3(c) illustre le re´sultat d’une distribution des intervalles. Le nœud u se voit +attribuer l’intervalle I(u) et est de´sormais responsable des clefs contenues dans cet +intervalle et il doit stocker les positions des nœuds v tels que hash(v) ∈ I(u). On +remarque qu’il peut exister plusieurs nœuds vi tels que hash(vi) = hash(vj). +Chaque nœud interne u garde e´galement en me´moire l’intervalle alloue´ a` son sous- +arbre Itree(sT (u)), sans pour autant stocker les informations associe´es a` toutes les +clefs de Itree(sT (u)). Cela lui servira lors du routage des requeˆtes, comme nous le +verrons dans la section 5.3.6 +Comme nous l’avons mentionne´ dans le chapitre 3.6.2, un nœud interne a en moyenne +peu de fils a` qui distribuer une partie de V . Cette ope´ration ne ge´ne`re donc que peu de +calcul sur chaque nœud. +5.3.3 Enregistrement +Afin d’eˆtre localise´ par la suite, chaque nœud u doit enregistrer sa position (l’identite´ +de son cluster) aupre`s de chaque nœud responsable de la clef hash(u) dans son cluster, +mais e´galement dans les autres clusters du re´seau. Pour s’enregistrer dans son propre +cluster, u a juste besoin d’envoyer une requeˆte d’enregistrement ou Registration Re- +quest, comme nous le de´taillerons plus tard dans la section 5.3.6. Pour s’inscrire dans +les autres clusters, u doit tout d’abord joindre un nœud vi dans chaque cluster Ci. Puis, +chaque vi envoie une Registration Request dans son propre cluster Ci au nom de u. Les +nœuds vi peuvent eˆtre trouve´s via un routage pro-actif vers le cluster Ci, comme de´crit +plus tard dans la section 5.3.7. +Les nœuds s’enregistrent toutes les ∆(t) unite´s de temps. Une approche commune´ment +adopte´e dans la litte´rature [1, 35, 56] est que les informations de localisation sont mises +a` jour sur les points de rendez-vous en fonction de la distance de ces points de rendez- +vous a` la source. Plus la distance est courte, plus les mises a` jour sont fre´quentes. +5.3.4 De´parts et arrive´es +Quand un nœud arrive dans un cluster, il n’est responsable d’aucun intervalle pour un +certain temps. +Quand un nœud disparaıˆt, les informations dont il e´tait en charge sont perdues (mais +toujours disponibles dans les autres clusters). Chaque nœud interne u est constamment +5.3. NOTRE PROPOSITION 105 +1 [1, 17[ + 2 + + +4 [3, 5[  [13, 17[ + + + + [6, 13[ + + + +  + + + + + + + 1  2       + + +1  [7, 9[  [9, 13[ [15, 17[ +  + + + + +  + + + + + + + + + + + + + + +1  [11, 13[ + + + + + + + +(a) E´ tape 1 : chaque nœud envoie la (b) E´ tape 2 : chaque nœud interne par- +taille de son sous-arbre a` son pe`re. Les tage l’intervalle donne´ par son pe`re entre +feuilles (nœuds jaunes hachure´s verti- lui-meˆme et ses fils, proportionnellement +calement) envoient 1. Les nœuds in- a` la taille des sous-arbres de chacun. Les +ternes (nœuds oranges hachure´s horizon- intervalles note´s sur les fle`ches corres- +talement) rassemblent les informations de pondent a` ce qui est alloue´ par un nœud +tous leurs fils et calculent la taille de leur a` ses fils, c.a`.d l’intervalle dont le sous- +propre sous-arbre avant de l’envoyer a` arbre de chacun est en charge. +leur propre pe`re, et ainsi de suite, jusqu’a` +atteindre la racine (le cluster-head), nœud +rouge hachure´ en diagonal. +[1, 3[ + + + + + + + + + + + + [13, 15[ + + +[3, 5[  [5, 7[   + + + +  + + +  + +[7, 9[ [9, 11[ [15, 17[ + + + +[11, 13[ +(c) Re´sultat : chaque nœud se voit attri- +buer un intervalle de V dont il est respon- +sable. +FIG. 5.3 – Distribution des partitions de l’espace virtuel. +106 CHAPITRE 5. LOCALISATION ET ROUTAGE +au courant des arrive´es et de´parts de ses fils graˆce aux paquets HELLO. S’il constate +des changements trop importants parmi eux, il peut de´cider localement de redistri- +buer l’intervalle Itree(sT (u)) dont son sous arbre est en charge entre lui-meˆme et ses +fils. Plus un nœud interne est proche du chef de cluster, plus les re´-attributions qui +de´couleront de sa de´cision seront importantes, puisqu’elles se re´percutent de pe`re en +fils jusqu’a` atteindre les feuilles. De plus, une nouvelle attribution des intervalles im- +plique un changement d’adresse logique pour les nœuds. Cependant, comme constate´ +pre´ce´demment, plus un nœud est proche du chef de cluster, plus son voisinage est +stable. +Lorsque les intervalles sont re-distribue´s, chaque nœud u qui e´tait pre´alablement res- +ponsable de l’intervalle Iold et qui se voit de´sormais attribuer la partition Inew ne +conserve que les informations relatives aux clefs de Iold ∩ Inew . De fac¸on a` ne pas +perdre pour autant les informations associe´es aux clefs de Iold \ Inew , u envoie des +Registration Request au nom de tous les nœuds v dont il n’est plus en charge c.a`.d les +nœuds v tels que hash(v) ∈ Iold \ Inew. +5.3.5 Ajouter de la redondance et de la robustesse +Comme mentionne´ dans la section 5.3.4, quand un nœud u disparaıˆt d’un cluster C(u) +ou quitte le re´seau, les informations dont il e´tait responsable sont perdues dans ce clus- +ter jusqu’au prochain enregistrement des nœuds. De fac¸on a` pallier cet inconve´nient, +un nœud peut enregistrer sa position d fois dans chaque cluster, d e´tant une constante. +Pour cela, l’espace virtuel V doit eˆtre distribue´ d fois dans chaque cluster, chaque nœud +se voyant de´sormais attribuer d partitions inde´pendantes de V et posse´dant alors d +diffe´rentes adresses logiques. Comme d est une constante, la taille me´moire requise +sur les nœuds reste en O(1) puisque, en moyenne, si c est le nombre de clusters, un +nœud devra stocker d ∗ c positions au lieu de c (c et d e´tant deux constantes). Ainsi, +meˆme lorsqu’un nœud meurt, la position d’un nœud dont il e´tait responsable a tou- +jours des chances d’eˆtre trouve´e dans le meˆme cluster. Cependant, cela ge´ne`re plus de +messages puisque les requeˆtes devront de´sormais suivre d routes, une pour chaque oc- +currence de V . Dans le pire cas, le routage des requeˆtes dans l’espace virtuel conduira +a` une diffusion dans un cluster. Mais, comme nous l’avons e´tudie´ dans le chapitre 4, +une telle diffusion peut s’effectuer en suivant les branches des arbres de fac¸on efficace +et peu couˆteuse. +5.3.6 Ope´ration de look-up : Routage dans l’espace virtuel V de la +DHT +Nous de´taillons ici comment les requeˆtes sont route´es dans les arbres sur la base +d’un routage par intervalle. Ceci correspond a` la premie`re e´tape du routage indirect, +l’ope´ration de look-up. +Chaque nœud u a un identifiant unique Id(u). Comme dans tout sche´ma base´ sur une +DHT, chaque nœud connaıˆt une fonction spe´cifique hash qui associe a` chaque adresse +universelle une adresse logique de l’espace virtuel V . +5.3. NOTRE PROPOSITION 107 +hash : IR→ V +Id(u)→ hash(u) +Plusieurs nœuds peuvent avoir la meˆme valeur retourne´e par la fonction hash. +Les informations de ces nœuds seront stocke´es sur le meˆme nœud de rendez-vous. +Dans la suite, nous utilisons la clef suivante pour identifier un nœud x : key = +{hash(x), id(x)}. +Une requeˆte est route´e dans l’espace virtuel jusqu’a` atteindre un nœud v responsable +de la clef key contenue dans la requeˆte : v est tel que key ∈ I(v). Une requeˆte peut +eˆtre de trois types : +– u veut enregistrer une position : +u doit enregistrer sa propre position ou, s’il est un nœud frontie`re, il peut vouloir +enregistrer un nœud u′ d’un autre cluster qui lui en a fait la demande. u doit donc +trouver le nœud responsable de sa propre adresse logique hash(u) ou de celle de u′, +hash(u′) : key = {hash(u), u} (resp key′ = {hash(u′), u′. }) +Dans ce cas, u utilise une Registration Request (RR) 〈RR, key, C(u), f lag〉 (resp. +〈RR, key′, C(u′), f lag〉). +– u doit localiser x : +Dans ce cas, u cherche le nœud responsable de l’adresse logique de x : hash(x). +Il utilise une Location Request (LR) 〈LR, key = {hash(x), x} , i(u), f lag〉. +L’adresse logique de u, i(u), est ensuite utilise´e pour envoyer la requeˆte de re´ponse +a` u. +– u doit re´pondre a` une requeˆte LR concernant une clef dont il est responsable +(key ∈ I(u)) : +u a rec¸u une requeˆte de type Location Request : +〈LR, key = {hash(x), x} , i(w), f lag〉 envoye´e par le nœud w et contenant +une clef telle que key ∈ I(u). u doit re´pondre a` w. +Dans ce cas, il utilise une requeˆte de type Location Reply (Reply) +〈Reply, key = {i(w),−1} , C(x), f lag〉. On remarque qu’ici la clef key n’a +pas besoin de contenir l’adresse re´elle de w. +Pour chaque type de requeˆte, le champ flag est mis a` 1 par le nœud faisant suivre la +requeˆte si la clef key appartient a` l’intervalle de son sous-arbre, a` 0 sinon. Comme nous +le verrons par la suite, ce champ est utilise´ pour prendre des de´cisions de routage. +On remarque qu’un nœud u connaıˆt de´ja` la position (ou cluster) de ses voisins, de son +chef de cluster et des nœuds dont il est responsable. Ainsi, pour un nœud v tel que +{v ∈ H(u) ∪ Γ1(u)} ou hash(v) ∈ I(u), u n’a pas besoin d’effectuer la proce´dure de +look-up et peut directement envoyer le message a` v, en suivant la proce´dure de routage +dans le re´seau physique, comme de´crite dans le chapitre 5.3.7. +Du fait de la nature diffusante du me´dium radio, un nœud rec¸oit toutes les requeˆtes +e´mises par ses voisins, meˆme celles ne le concernant pas. Les requeˆtes de look-up +suivent uniquement les areˆtes de l’arbre de clustering, donc un nœud ne sera pas +108 CHAPITRE 5. LOCALISATION ET ROUTAGE +concerne´ par une requeˆte de look-up provenant d’un de ses voisins qui ne sera ni son +pe`re ni l’un de ses fils. Les nœuds prennent la de´cision de re´-e´mettre une requeˆte de +look-up en se basant non-seulement sur la cle´ et le champ flag contenus dans la requeˆte +mais e´galement sur l’identite´ de leur voisin qui leur l’a transmise. Le champ flag est +renseigne´ a` chaque re´-e´mission de la requeˆte par un nœud. Le processus de routage +d’une requeˆte est le meˆme quel que soit son type (LR, RR or Reply). Il est de´crit par +l’algorithme 1. +Vu que le routage des requeˆtes de look-up est ope´re´ sur l’espace virtuel V , il ne +ne´cessite pas la connaissance des adresses universelles des nœuds, il n’a besoin que +des adresses logiques. +Sur re´ception d’un message M (RR, LR or Reply) contenant la clef key = +{hash(x), x} provenant du nœud u (u ∈ Γ1(v)), le nœud v arreˆte le processus s’il +est responsable de la clef key (donc si key ∈ I(v)) ou s’il est lui-meˆme le nœud +cherche´ (si key = {hash(v), v}). Ce second cas arrive ne´anmoins rarement vu qu’il +implique que l’initiateur de la requeˆte x soit dans le meˆme cluster que v (C(x) = C(v)) +et que v se trouve sur la route suivie par la requeˆte de x vers le nœud responsable de la +clef. +Lorsqu’une requeˆte de type RR 〈RR, key = {hash(u), u} , C(u), f lag〉 atteint sa des- +tination v, v met a` jour la position du nœud u dans sa table. Lorsqu’une requeˆte +de type Reply 〈Reply, key = {i(u),−1} , C(x), f lag〉 arrive a` sa destination u, u +est alors capable d’entamer la seconde e´tape du routage indirect. Enfin, lorsqu’une +requeˆte de type LR 〈LR, key = {hash(x), x} , i(w), f lag〉 atteint sa destination v +(en charge de hash(x)), v re´pond a` l’initiateur de la requeˆte par une requeˆte Reply : +〈Reply, {i(w),−1} , C(x), f lag〉. +Si key 6= {hash(v), v}, le nœud v re´-e´met M dans les trois cas suivants : +– Si u = P(v) et key ∈ Itree(sT (v)) (M a e´te´ transmis a` v par son pe`re et le sous- +arbre de v contient la cle´ de la requeˆte). Voir figure 5.4(a). +– Si u ∈ Ch(v) (M a e´te´ transmis a` v par un de ses fils u), v re´-e´met M si : +– Si key ∈/ Itree(sT (v)) (le sous-arbre de v n’est pas responsable de la clef du +message), le message doit poursuivre son chemin en remontant dans l’arbre vers +la racine. Voir figure 5.4(b). +– Si key ∈ Itree(sT (v)) et key ∈/ Itree(sT (u)) (flag = 0) (le sous-arbre de v +contient la clef mais pas celui de u), v doit re´-e´mettre M afin que le message +redescende sur une autre branche du sous-arbre de v. Voir figure 5.4(c). +La requeˆte est ignore´e dans tous les autres cas, c’est a` dire : +– Si u ∈/ P(v) ∪ Ch(v) (la requeˆte arrive par un lien n’e´tant pas dans l’arbre). Voir +figure 5.5(a). +– Si u ∈ Ch(v) et key ∈ Itree(sT (u)) (flag = 1) (le message parvient a` v par un de +ses fils dont le sous-arbre est responsable de la clef). Graˆce au champ flag mis a` 1, +u sait que le sous-arbre de l’e´metteur est en charge de la clef et donc ne s’en occupe +pas. La requeˆte redescend le sous-arbre de v. Voir figure 5.5(b). +– Si u = P(v) et key ∈/ Itree(sT (v)) (u rec¸oit M depuis son pe`re et son sous-arbre +n’est pas en charge de la clef). u n’est pas concerne´ par la requeˆte, il l’ignore. Un de +ses fre`res s’en chargera. Voir figure 5.5(c). +5.3. NOTRE PROPOSITION 109 +a I(a) = [0, 8[ a I(a) = [0, 8[ +q = <6, a, 1> +q = <1, e, 0 > +b I(b) = [1, 3[ d I(d) = [3, 8[ b I(b) = [1, 3[ d I(d) = [3, 8[ +c I(c) = [2, 3[ e I(e) = [5, 8[ f I(f) = [4, 5[ c I(c) = [2, 3[ e I(e) = [5, 8[ f I(f) = [4, 5[ +g I(g) = [6, 7[ g I(g) = [6, 7[ +h I(h) = [7, 8[ h I(h) = [7, 8[ +(a) Cas 1 : le message descend dans l’arbre. a (b) Cas 2 : le message remonte. e cherche le +cherche le nœud responsable de la clef 6. nœud en charge de la clef 1. +a I(a) = [0, 8[ +b I(b) = [1, 3[ d I(d) = [3, 8[ q = <4, e, 0> +c I(c) = [2, 3[ e I(e) = [5, 8[ f I(f) = [4, 5[ +g I(g) = [6, 7[ +h I(h) = [7, 8[ +(c) Cas 3 : le message remonte dans une +branche pour re-descendre dans une autre. e +cherche le nœud en charge de la clef 4. +FIG. 5.4 – Diffe´rents cas de figures ou` une requeˆte rec¸ue par d est re´-e´mise. +110 CHAPITRE 5. LOCALISATION ET ROUTAGE +a I(a) = [0, 8[ a I(a) = [0, 8[ +q = +q = <7, e, 1 > +b I(b) = [1, 3[ d I(d) = [3, 8[ b I(b) = [1, 3[ d I(d) = [3, 8[ +c I(c) = [2, 3[ e I(e) = [5, 8[ f I(f) = [4, 5[ c I(c) = [2, 3[ e I(e) = [5, 8[ f I(f) = [4, 5[ +g I(g) = [6, 7[ g I(g) = [6, 7[ +h I(h) = [7, 8[ h I(h) = [7, 8[ +(a) Cas 1 : le message ne provient pas d’une (b) Cas 2 : e cherche le nœud en charge de +branche de l’arbre. la clef 4. Le message monte et redescend les +branches du sous-arbre de e en e´tant entendu +par d qui ignore la requeˆte. +a I(a) = [0, 8[ +q = <2, a, 1> +b I(b) = [1, 3[ d I(d) = [3, 8[ +c I(c) = [2, 3[ e I(e) = [5, 8[ f I(f) = [4, 5[ +g I(g) = [6, 7[ +h I(h) = [7, 8[ +(c) Cas 3 : a cherche le nœud en charge de +7. Cette cle´ n’est pas dans l’arbre de nœud d. +FIG. 5.5 – Diffe´rents cas de figures ou` un message est entendu par le nœud d et ignore´. Les +fle`ches pointille´es repre´sentent un chemin possible suivi par la requeˆte dans ces cas. Les areˆtes +pointille´es repre´sentent les liens du graphe G non contenus dans l’arbre T . +5.3. NOTRE PROPOSITION 111 +Algorithm 1 Routage dans l’espace virtuel +Pour tout nœud u, sur re´ception d’une requeˆte 〈Type, key = {hash(x), x} , X, flag〉, +X de´pendant du type de requeˆte, provenant d’un nœud v ∈ Γ1(u) et initie´e par le +nœud y : +if (key ∈ u ∪ I(u)) then +⊲ u est responsable de la clef. La requeˆte a atteint sa destination. +if (Type = LR) then +Re´pond en envoyant 〈Reply, {X = i(y),−1} , C(x), flag〉. Exit +end +if (Type = RR) then Enregistre la position de x. Exit end +if (Type = Reply) then +Route vers le cluster destination X. Exit +end +end +if (v = P(u)) then +⊲ Le message descend les branches de l’arbre. +if (key ∈ Itree(sT (u))) then +⊲ ∃w ∈ sT (u) tel que key ∈ I(w). cf. figure 5.4(a). +Met le champ flag a` 1. +Re´-e´met. +else +Ignore. +⊲ cf. figure 5.5(b). +end +else +if (v ∈ Ch(u)) then +⊲ La requeˆte remonte les branches de l’arbre depuis un fils de u. +if (key ∈/ Itree(sT (u))) then +Met le champ flag a` 0. +Re´-e´met. +⊲ cf. figure 5.4(b). +else +⊲ ∃w ∈ sT (u) \ {u, v} tel que key ∈ I(w). +if (flag = 0) then +Met le champ flag a` 1. +Re´-e´met. +⊲ key ∈/ Itree(sT (v)) mais puisque key ∈ Itree(sT (u)), u doit transmettre +la requeˆte a` ses autres fils. Celle-ci redescend l’arbre par une autre branche u. +Cf. figure 5.4(c). +else +⊲ La requeˆte transite par v avant de redescendre. Cf. figure 5.5(c). +Ignore. +end +end +else Ignore. +⊲ Cf. figure 5.5(a). +end +end +112 CHAPITRE 5. LOCALISATION ET ROUTAGE +5.3.7 Routage sur le re´seau physique +Dans cette section, nous explicitons la seconde phase du routage indirect : le routage +dans l’espace physique. Comme nous l’avons de´ja` mentionne´, nous proposons une +approche hie´rarchique base´e sur la structure de clusters dans laquelle nous appliquons +un protocole pro-actif entre les clusters (comme par exemple OLSR [25]) et re´actif +a` l’inte´rieur des clusters (comme par exemple DSR [43] ou AODV [62]). Comme le +nombre de clusters est constant quand la densite´ des nœuds augmente, le nombre de +nœuds par cluster augmente aussi (O(n) nœuds par cluster). Comme le nombre de +clusters est constant, il en est de meˆme pour le nombre de routes entre ces clusters et +chaque cluster a O(1) routes a` maintenir vers les autres clusters. Bien que le nombre +de nœuds augmente, l’excentricite´ moyenne des nœuds dans un cluster reste faible et +constante (entre 3 et 4 sauts en moyenne). Ainsi, une route re´active dans un cluster peut +eˆtre trouve´e a` la demande sans trop de latence et avec un faible nombre de sauts. +Un routage pro-actif entre clusters signifie que chaque cluster ou nœud maintient en +permanence la liste des clusters a` traverser pour aller d’un cluster A vers un cluster B. +Il reste maintenant a` de´finir qui, dans un cluster maintient ces routes pro-actives vers les +autres clusters. L’approche la plus commune´ment admise est la suivante. Si tre`s peu de +messages sont route´s vers les autres clusters, seul le chef de cluster ou quelques nœuds +peuvent me´moriser ces routes et les fournir sur demande aux autres nœuds du cluster. +Si au contraire, cela arrive plus fre´quemment, la table de routage entre clusters peut +eˆtre distribue´e a` tous les nœuds en appliquant par exemple l’algorithme de diffusion +efficace dans un cluster introduit en section 4.4. +Supposons que le nœud u cherche a` joindre le nœud v. Si v est le chef de cluster de u +ou un de ses voisins (v ∈ Γ1(u) ∪ {H(u)}), u sait de´ja` comment joindre v et n’a donc +pas besoin de faire appel a` la fonction de look-up. Dans le cas contraire, u doit d’abord +localiser v (connaıˆtre C(v)) avant de pouvoir ensuite lui envoyer un message suivant +le processus de routage illustre´ sur la figure 5.6. Si C(v) = C(u), alors u initialise un +routage de type re´actif dans son cluster pour joindre v. Sinon, graˆce au routage pro-actif +entre clusters, u connaıˆt la liste des clusters a` traverser pour atteindre C(v). Soit C(w) +le premier cluster a` traverser. u initialise un routage re´actif vers un nœud x ∈ C(u) qui +est un nœud frontie`re avec C(w) : x tel que x ∈ C(u) et ∃y ∈ Γ1(x) ∩ C(¯w). +x fait alors suivre le message de u a` l’un de ses voisins y se trouvant dans C(w). y +re´ite`re alors le meˆme processus de routage, et ainsi de suite, jusqu’a` joindre le cluster +de la destination C(v). +Ce processus de routage est donne´ dans l’algorithme 2. Nous notons +Next Hop(cluster1, cluster2) la fonction qui retourne le prochain cluster a` +traverser pour atteindre le cluster2 depuis le cluster1. Cette fonction illustre le +routage pro-actif entre clusters et est connue par tous les nœuds. +5.3. NOTRE PROPOSITION 113 +Cluster B +4 +Cluster C +Cluster A 2 Y 3 Z T 5X V +1 +U +FIG. 5.6 – u souhaite joindre le nœud v. Graˆce a` l’ope´ration de look-up, il sait que +C(v) = C. Il connaıˆt le prochain cluster a` traverser pour atteindre C : le cluster B. Il +joint le nœud x, voisin de B avec un protocole re´actif (fle`che 1). x transmet le message +a` son voisin y du cluster B (fle`che 2). y sait que les clusters B et C sont voisins, +il transmet le message a` un nœud z de son cluster, voisin du cluster C (fle`che 3). z +transmet a` son voisin t dans C (fle`che 4) qui joint finalement v graˆce a` un routage +re´actif dans son cluster (fle`che 5). +Algorithm 2 Routage hie´rarchique +Pour un message M envoye´ par le nœud x ∈ C(x) au nœud y ∈ C(y) +Ccurrent = C(x) +Cnext = C(x) +while (Cnext 6= C(y)) do +Cnext = Next Hop(Ccurrent, C(y)) +Envoie M avec un routage re´actif vers le nœud u ∈ Ccurrent tel que ∃v ∈ Γ1(u) ∩ +Cnext. +u envoie M a` son voisin v. +Ccurrent = Cnext +end +⊲ Le message a atteint le cluster destination. +Envoie M avec un routage re´actif vers le nœud destination y. +end +Enregistrer la position d’un nœud . Si le nœud u souhaite seulement enregistrer sa +position dans un autre cluster que le sien, il utilise le meˆme sche´ma. Par exemple, +si u souhaite s’enregistrer dans C, il exe´cute l’algorithme 2 (sans avoir a` effectuer +l’ope´ration de look-up vu qu’il connaıˆt de´ja` le nom des clusters existants ainsi que la +liste des clusters a` traverser pour les joindre) jusqu’a` atteindre un nœud dans C, quel +qu’il soit (le nœud t dans notre exemple). t envoie alors une Registration Request : +〈RR, key = {hash(u), u} , A, f lag〉 dans C. On remarque que, comme la requeˆte +passe par le nœud y dans le cluster B, y peut faire de meˆme et enregistrer u dans b +en meˆme temps. +114 CHAPITRE 5. LOCALISATION ET ROUTAGE +5.4 Simulations +Comme nous l’avons de´ja` mentionne´, il n’a e´te´ propose´, a` notre connaissance, qu’un +autre protocole de routage hie´rarchique qui propose une approche re´active a` l’inte´rieur +des clusters et pro-active entre les clusters : le protocole SAFARI [69]. Dans cette +section, nous e´valuons par simulation notre algorithme de localisation/routage sur notre +structure de clusters en la comparant aux performances de SAFARI. +5.4.1 SAFARI +SAFARI propose une organisation hie´rarchique de l niveaux, c.a`.d que les clusters +(appele´s cellules dans SAFARI) sont re´cursivement re-groupe´s en clusters de niveaux +supe´rieurs et ainsi de suite. Les simples nœuds sont conside´re´s comme des clus- +ters/cellules de niveau 0. Le nombre de niveaux s’e´tablit automatiquement en fonction +de la taille et de la densite´ du re´seau. +Le rayon des cellules de SAFARI est de´fini a priori. Le rayon D1 des cellules de ni- +veau 1 (e´quivalentes aux clusters de notre algorithme, e´galement appele´es cellules fon- +damentales) est fixe´ et les rayons Di des niveaux supe´rieurs sont de´finis re´cursivement +a` partir de D1. La hie´rarchie de cellules construite par SAFARI se base sur une +auto-se´lection des nœuds en tant que drums (cluster-heads). Un drum de niveau i est +e´galement un drum de tout niveau infe´rieur j tel que 0 ≤ j ≤ i. Un drum de niveau i +de´cide d’augmenter ou de de´cre´menter son niveau en fonction du nombre de drums de +niveaux i+ 1 et i se trouvant a` une certaine distance de lui. Si un drum de niveau i n’a +aucun drum de niveau i + 1 parmi ses voisins a` moins de Di sauts, il incre´mente son +niveau et s’auto-de´clare drum de niveau i+ 1. Si deux drums de niveau i sont distants +de moins de Di sauts, seul le drum de plus grand identifiant reste drum de niveau i, +l’autre de´cre´mente son niveau et devient drum de niveau i− 1. +Cette hie´rarchie attribue a` chaque nœud un anceˆtre (chef) unique a` chaque niveau. A +partir de cette algorithme de clustering hie´rarchique, chaque nœud se voit attribuer +une adresse/coordonne´e logique (qui sera son adresse dans l’espace de la DHT). La +coordonne´e d’un nœud de niveau i est la concate´nation de la coordonne´e de son drum +de niveau i+ 1 et d’un nombre ge´ne´re´ ale´atoirement. +Soient COORD(di) la coordonne´e d’un drum di de niveau i, PARENT (di) le pe`re +de di (le drum de niveau i+ 1 de di) et Rand un nombre ale´atoire. La coordonne´e de +di est comme suit : +COORD(di) = COORD(PARENT (d0)) pour i = 0 += COORD(PARENT (di)).Rand pour 0 < i +Les drums de niveau 0 (les simples nœuds) sont des feuilles dans cet arbre de coor- +donne´es. Tous les nœuds d’une meˆme cellule fondamentale ont la meˆme coordonne´e +logique. +Chaque drum de niveau i envoie un paquet appele´ beacon toutes les Ti unite´s de +temps, Ti de´pendant du niveau i. Plus le niveau hie´rarchique est e´leve´, plus la pe´riode +5.4. SIMULATIONS 115 +d’e´mission des beacons correspondants est grande. Un beacon de niveau i envoye´ par +le drum di est transmis a` tous les nœuds de la cellule de di ainsi qu’a` tous les nœuds +se trouvant dans une cellule de niveau i dont le drum de niveau i + 1 est le pe`re de +di. Par exemple, sur la Figure 5.4.3, les beacons de niveau 1 envoye´s par le drum de +niveau 1 de la cellule F seront envoye´s a` tous les nœuds des cellules F et G, puisque +ces deux cellules appartiennent a` la meˆme cellule de niveau 2. Chaque nœud stocke +tous les beacons qu’ils relaient dans une table appele´e Drum Ad Hoc Routing Table +(DART) en leur associant la date de re´ception et le nœud par lequel il a e´te´ rec¸u. +Les coordonne´es des nœuds forment l’espace d’adressage de la DHT de SAFARI. +La fonction de hachage retourne k diffe´rentes coordonne´es de points de rendez-vous +pour chaque niveau i. Contrairement a` notre heuristique ou` les points de rendez-vous +se trouvent dans le meˆme cluster que le demandeur, les points de rendez-vous dans +SAFARI sont re´partis sur l’ensemble du re´seau. Le look-up se base sur l’ide´e qu’en +ge´ne´ral, les nœuds communiquent plus avec les entite´s proches d’eux. Lorsqu’un nœud +x veut s’enregistrer, il hache son identifiant et obtient k coordonne´es pour chaque ni- +veau i (0 ≤ i ≤ l) par la DHT. x va s’inscrire k fois dans chaque niveau. Pour chacune +de ces coordonne´es c retourne´e par la DHT, il va s’enregistrer aupre`s du nœud qu’il +trouve qui a la coordonne´e la plus proche possible de la coordonne´e c. Pour cela, il +envoie sa requeˆte d’enregistrement au nœud u se trouvant dans sa DART et dont la co- +ordonne´e est la plus proche de la coordonne´e c. u fait de meˆme et transmet la requeˆte +de u au nœud de sa propre DART dont la coordonne´e est la plus proche de c et ainsi de +suite jusqu’a` atteindre un nœud d’une cellule fondamentale (tous les nœuds de la meˆme +cellule fondamentale ont la meˆme coordonne´e) qui n’a aucune entre´e dans sa DART +avec une coordonne´e plus proche de c qu il ne l est lui meˆme Ce nœud 3’ ’ - . devient le +nœud aupre`s duquel le nœud u enregistre sa position. Lorsqu’un nœud x veut re´cupe´rer +la coordonne´e d’un nœud y, il va d’abord chercher dans les cellules de niveau 1 appar- +tenant a` la meˆme cellule de niveau 2 que lui. S’il ne trouve pas, il cherchera au niveau +supe´rieur et ainsi de suite : il cherche dans toutes les cellules de niveau i appartenant a` +la meˆme cellule de niveau i+ 1 que lui, jusqu’a` atteindre l’ensemble du re´seau. Lors- +qu’un nœud x veut re´cupe´rer les coordonne´es d’un nœud y, il hache la coordonne´e de +y et envoie sa requeˆte au nœud u se trouvant dans sa DART et dont la coordonne´e est +la plus proche de la coordonne´e retourne´e par la DHT pour le niveau conside´re´, et ainsi +de suite, jusqu’a` atteindre un nœud r. Si r connaıˆt les coordonne´es de y, il les retourne +a` x qui pourra alors joindre y de la meˆme fac¸on qu’il a joint r. Si r ne de´tient pas la +coordonne´e de y, x re´-ite`re sa requeˆte au niveau supe´rieur. x peut donc envoyer jusqu’a` +l requeˆtes de look-up pour localiser y. Nous verrons par la suite que meˆme au bout de l +fois, le look-up de SAFARI peut e´chouer. Dans nos simulations, k est fixe´ a` 3, comme +le sugge`re les auteurs de SAFARI. +Nous nous sommes inte´resse´s dans un premier temps a` la formation des clusters de +chacun des deux algorithmes, puis, nous avons e´value´ les performances du look-up et +du routage de chacun des protocoles. +3Tous les nœuds d’une cellule fondamentale ayant la meˆme coordonne´e, plusieurs nœuds peuvent poten- +tiellement stocker la position de u mais SAFARI n’explicite pas s’il s’agit du drum ou d’un nœud particulier +de la cellule +116 CHAPITRE 5. LOCALISATION ET ROUTAGE +5.4.2 Comparaison des structures +Comme notre heuristique construit des clusters de rayon compris entre 3 et 4 sauts +(chapitre 3), nous avons fixe´ D1 a` 3 dans SAFARI, de fac¸on a` pouvoir comparer les +cellules fondamentales de SAFARI aux clusters de notre algorithme. C’est d’ailleurs la +valeur choisie par les auteurs de SAFARI dans leurs simulations. +La diffe´rence principale entre les deux heuristiques est que SAFARI construit l ni- +veaux hie´rarchiques de cellules alors que notre algorithme ne forme qu’un seul niveau +de clusters. Le nombre de niveaux e´tabli par SAFARI s’adapte automatiquement en +fonction de diame`tre du re´seau. La table 5.1 donne le nombre de niveaux construits par +SAFARI sur diffe´rentes topologies. Nous verrons par la suite que le nombre de niveaux +impacte les performances du look-up de SAFARI. +Topologie Nombre de niveaux +10× 10 Grille a` 4 voisins entre 3 et 4 +15× 15 Grille a` 4 voisins 4 +Chaıˆne de 50 nœuds entre 4 et 5 +Chaıˆne de 75 nœuds 5 +Chaıˆne de 100 nœuds 6 +Topologie Poisson λ = 500, R ≤ .1 entre 3 et 4 +Topologie Poisson λ = 500, R < .1 entre 2 et 3 +TAB. 5.1 – Nombre de niveaux de cellules construits par SAFARI en fonction de la +topologie sous-jacente. +Bien que le diame`tre du re´seau intervienne sur le nombre de niveaux hie´rarchiques, seul +le degre´ des nœuds influence les caracte´ristiques des clusters, tout comme dans notre +algorithme, les heuristiques e´tant locales et distribue´es. Les re´sultats de la table 5.2 +montrent que les clusters construits par les deux heuristiques ont des caracte´ristiques +moyennes e´quivalentes (nous ne conside´rons que les clusters de niveau 1 pour SA- +FARI). Cependant, comme le montre l’e´cart type du nombre de nœuds par cluster, les +clusters de SAFARI sont moins homoge`nes que ceux de notre heuristique. +Comme nous l’avons e´tudie´ dans le chapitre 3, lorsqu’un nœud inte`gre le re´seau or- +ganise´ avec notre algorithme, il ve´rifie son voisinage, calcule sa densite´ et se choisit +un pe`re. L’algorithme stabilise rapidement en un temps proportionnel a` la hauteur de +l’arbre. Dans SAFARI, lors de la phase d’initialisation, les nœuds attendent un temps +ale´atoire avant de prendre la de´cision d’e´ventuellement augmenter leur niveau. Cette +de´cision est base´e sur les informations contenues dans la DART de chaque nœud. Le +temps de stabilisation de SAFARI est donc lie´ a` la pe´riode initiale d’attente ale´atoire et +a` la fre´quence Ti d’e´mission des beacons (donc a` T1 pour les cellules fondamentales). +Dans nos simulations, les nœuds tirent un temps ale´atoire uniforme´ment entre 0 et 5 +unite´s de temps et T1 = 2 unite´s de temps, comme le sugge`rent les auteurs de SAFARI. +De fac¸on a` comparer e´quitablement les deux heuristiques, nous supposons que les bea- +cons de niveau 1 sont e´change´s a` la meˆme fre´quence que les paquets Hello dans notre +5.4. SIMULATIONS 117 +heuristique (T1). +λ 500 600 700 +Densite´ SAFARI Densite´ SAFARI Densite´ SAFARI +Nb clusters 11.70 16.2 10.08 12.6 8.06 11.4 +Taille clusters 39.91 32.58 45.64 39.76 54.43 43.57 +σ(taille) 18.66 13.88 17.88 17.83 16.59 20.28 +Diame`tre 4.99 4.67 5.52 4.62 5.50 4.76 +CH/drum excen. 3.01 2.69 3.09 2.67 3.37 2.80 +Temps stab. 5.27 107.67 5.34 113.41 5.33 91.95 +σ(Temps stab) 0.63 132.41 0.74 135.56 0.85 123.69 +λ 800 900 1000 +Densite´ SAFARI Densite´ SAFARI Densite´ SAFARI +Nb clusters 7.03 9.10 6.15 8.10 5.57 7.40 +Taille clusters 61.23 54.80 70.41 60.58 73.72 66.21 +σ(taille) 15.59 23.20 15.29 25.01 14.27 26.61 +Diame`tre 5.65 4.83 6.34 4.77 6.1 4.73 +CH/drum excen. 3.17 2.77 3.19 2.72 3.23 2.82 +Temps stab. 5.34 90.55 5.43 60.61 5.51 61.97 +σ(Temps stab) 0.99 111.18 1.21 115.58 1.44 118.69 +TAB. 5.2 – Caracte´ristiques des clusters pour chaque heuristique pour R = .1. +Le temps de stabilisation des algorithmes est pre´sente´ dans la table 5.2. Parfois, nous +avons pu remarquer qu’au bout de 350 unite´s de temps (temps sugge´re´ par les au- +teurs de SAFARI), la structure de SAFARI n’e´tait pas e´tablie. Dans ces cas, SAFARI +ne converge pas. Nous n’avons pris en compte dans ces statistiques que les cas ou` +SAFARI converge. On remarque que l’intensite´ des nœuds n’influence pas le temps +de stabilisation des deux protocoles. SAFARI est beaucoup plus long a` stabiliser que +notre algorithme et son temps de stabilisation est loin d’eˆtre re´gulier comme le montre +l’e´cart type σ. Certaines instances du protocole convergent tre`s rapidement alors que +d’autres n’ont toujours pas converge´ apre`s un temps de 350 unite´s de temps. En effet, +un nœud peut osciller entre diffe´rents e´tats en fonction des valeurs ale´atoires choisies. +La figure 5.7 donne un exemple dans lequel SAFARI ne converge pas. Dans la fi- +gure 5.7(b), le re´seau est en phase d’initialisation. La pe´riode d’attente ale´atoire du +nœud 3 est la premie`re a` expirer : le nœud 3 devient le premier drum de niveau 1. Puis, +les pe´riodes d’attente de plusieurs nœuds expirent. Ceux parmi eux qui entendent un +drum de niveau 1 a` moins de D1 = 3 sauts s’attachent a` lui. Les autres s’auto-e´lisent +drum de niveau 1. Dans notre exemple, la pe´riode du nœud 1 a expire´ avant celles de 4, +12 et 25 et celle de 6 a expire´ avant celles des nœuds 23, 8, 26 et 16. Si au contraire, la +pe´riode du nœud 23 avait expire´ avant celle du nœud 6, par exemple, 23 aurait cre´e´ son +propre cluster et 6 se serait ensuite rattache´ a` 23. D’un autre coˆte´, on peut remarquer +que si la pe´riode du nœud 19 expire avant celle du nœud 1, 19 s’attache dans un premier +temps au drum 3 avant de s’attacher a` 1 lorsque celui-ci se de´clare drum. Ainsi, sur la +118 CHAPITRE 5. LOCALISATION ET ROUTAGE +figure 5.7(c), les nœuds 6 et 1 deviennent des drums de niveau 1, les nœuds 0, 9, 7 +s’attachent au nœud 0, les nœuds 21, 19, 12, 4 et 25 s’attachent au nœud 1 et les nœuds +0, 7 et 9 s’attachent a` 3. Ceci montre l’importance du temps d’attente ale´atoire dans la +formation des clusters de SAFARI. Comme il n’existe aucun drum de niveau 2 a` moins +de D2 = 6 sauts du nœud 3, celui-ci devient ensuite un drum de niveau 2. les cellules +de niveau 1 des drums 1 et 6 s’attachent a` la cellule de niveau 2 de 3 (figure 5.7(d)). +Puis, la pe´riode d’attente du nœud 17 expire. Comme celui-ci n’entend aucun drum de +niveau 1 a` moins de D1 sauts, il devient un drum de niveau 1. Lorsque les autres nœuds +se re´veillent, ils s’attachent a` lui. Comme le drum 17 de niveau 1 n’entend aucun drum +de niveau 2 dans son voisinage a` D2 sauts, il devient un drum de niveau 2. Sa cellule de +niveau 2 ne se compose que d’une seule cellule de niveau 1. De la meˆme fac¸on, comme +le drum 3 de niveau 2 n’entend aucun drum de niveau 3 dans son voisinage a` D3 sauts, +il devient un drum de niveau 3. C’est ce que l’on peut voir sur la figure 5.7(f). Dans +SAFARI, si un drum de niveau i n’entend pas au moins deux drums de niveaux i− 1, +il baisse son niveau. Ainsi, dans notre exemple, comme le drum 3 de niveau 3 n’entend +qu’un seul drum de niveau 2 (le drum 17), il re-devient un drum de niveau 2. De meˆme, +comme le drum 17 de niveau 2 n’entend aucun drum de niveau 1, il re-devient drum de +niveau 1. C’est a` dire que nous revenons a` la structure de la figure 5.7(e). La structure +va ensuite e´voluer pour re-devenir celle illustre´e par la figure 5.7(f) et ainsi de suite. +Un cycle apparaıˆt et SAFARI ne converge jamais. +5.4.3 Look-up et routage +Cette section analyse les performances du look-up effectue´ dans chaque algorithme +ainsi que le routage qui s’en suit. +Dans notre algorithme, les requeˆtes de look-up sont route´es a` l’inte´rieur d’un cluster +en effectuant un routage par intervalle sur l’espace virtuel de la DHT (Section 5.3). Les +diame`tres des clusters e´tant relativement petits, la requeˆte ne parcourra qu’un nombre +de sauts borne´ pour atteindre le nœud rendez-vous. Ceci n’est pas le cas dans SAFARI +ou` les nœuds rendez-vous se trouvent dans la plupart des cas dans d’autres clusters. +De plus, comme nous l’avons de´ja` e´voque´, dans un cas de re´seau statique, avec une +couche MAC ide´ale, tous les look-ups de notre algorithme re´ussiront, ce qui n’est pas +le cas dans SAFARI. Et meˆme lorsqu’un look-up de SAFARI re´ussit, il peut avoir +utilise´ plusieurs requeˆtes alors qu’une seule suffit a` notre algorithme. Cela s’explique +par le phe´nome`ne suivant. Les drums de niveau i de SAFARI envoient leurs beacons +aux nœuds des cellules de niveau i ayant le meˆme drum i+ 1 qu’eux. Donc, dans une +hie´rarchie de 3 niveaux ou plus, tous les nœuds ne recevront pas les beacons de tous +les drums. Si on prend l’exemple de la figure 5.4.3, le drum de la cellule fondamentale +B envoie ses beacons aux nœuds des cellules A, B et C mais les nœuds des cellules D +ou E ne les rec¸oivent pas. +Quand le nœud d cherche a` s’enregistrer, il hache son identifiant et regarde dans sa +table DART quel nœud v a la coordonne´e la plus proche de la valeur retourne´e par la +DHT. En effectuant le look-up sur son propre identifiant, d finit par s’enregistrer aupre`s +d’un nœud h. Cependant, il faut noter que h est le nœud trouve´ a` partir de la DART +5.4. SIMULATIONS 119 +21 1 +0 +19 +25 11 +drum de niveau 0 (simple noeud) 3 9 +4 +22 +7 24 +5 12 15 20 +drum de niveau 1 2 18cellule fondamentale 14 8 26 +23 17 +drum de niveau 2 cellule de niveau 2 6 16 10 13 +drum de niveau 3 cellule de niveau 3 +(a) Le´gende (b) +21 1 21 1 +0 +19 11 0 19 11 +3 9 4 +25 +9 4 2522 3 +7 22 +5 12 15 +24 7 +20 5 12 15 +24 +20 +14 2 26 188 14 2 8 26 +18 +23 17 23 17 +6 16 10 13 6 16 10 13 +(c) +(d) +21 1 +21 1 +0 +19 +25 11 0 +3 9 4 19 1122 9 4 253 +7 24 22 +5 12 15 7 2420 5 12 15 20 +14 2 8 26 +18 +14 2 18 +23 17 8 2623 17 +6 16 10 13 6 16 10 13 +(e) (f) +FIG. 5.7 – Exemple ou` SAFARI oscille et ne converge jamais. +120 CHAPITRE 5. LOCALISATION ET ROUTAGE +de d. h n’a pas toujours exactement la meˆme coordonne´e que celle retourne´e par la +DHT, il est juste un nœud dont la coordonne´e est proche. Le proble`me vient alors du +fait que les nœuds posse`dent une table DART diffe´rente les uns des autres lorsque le +cluster est organise´ en plus de 2 niveaux hie´rarchiques. En effet, quand un nœud s veut +envoyer un message a` d, il hache l’identifiant de d et ainsi obtient des coordonne´es. Il +va alors envoyer sa requeˆte aux nœuds de sa DART dont les coordonne´es sont les plus +proches de celles retourne´es par la DHT. Il va atteindre un nœud n. Or d ne s’est pas +enregistre´ aupre`s de n car n de figure pas dans la DART de d et n’est pas atteignable +depuis la DART de d. De meˆme, les nœuds h aupre`s desquels d s’est enregistre´ ne +sont pas toujours contenus dans la table DART de s et dans ces cas-la`, le look-up, ne +peut re´ussir. Ainsi, plus le nombre de niveaux hie´rarchiques est e´leve´, plus le taux de +re´ussite des look-ups de SAFARI est faible. +level−0 drum (regular node) +1 +level−1 drum +level−2 drum d +level−3 drum C h +fondamental cell B +level−2 cell +level−3 cell F A D +G 2 +n +E s +FIG. 5.8 – Exemple de clusters de SAFARI. +La table 5.3 pre´sente diffe´rentes valeurs que nous avons releve´es lors de nos simu- +lations de look-up et routage de chacun des deux algorithmes. La` encore, les valeurs +concernant SAFARI ne sont prises en compte que lorsque l’algorithme converge. +Le champ ”Nb de requeˆtes” indique le nombre de requeˆtes qu’un nœud u doit envoyer +en moyenne avant de joindre un nœud qui de´tient l’information recherche´e (avant de +re´ussir le look-up). Ce champ est toujours e´gal a` 1 pour notre heuristique puisqu’une +seule requeˆte est ne´cessaire. +Le champ ”Longueur du Look-up” donne le nombre de sauts que parcourt une requeˆte +de look-up en moyenne dans chaque algorithme. Les nœuds de rendez-vous de notre +algorithme e´tant toujours dans le meˆme cluster que la source de la requeˆte et ceux de +SAFARI e´tant distribue´s sur l’ensemble du re´seau, les routes sont e´videmment plus +courtes dans notre heuristique. A` cela s’ajoute que SAFARI peut lancer une requeˆte de +plus en plus loin en augmentant le niveau apre`s un e´chec de requeˆte de look-up. Ces +valeurs sont influence´es par la densite´ locale du re´seau (degre´ des nœuds) puisque les +5.4. SIMULATIONS 121 +λ 500 600 700 +Densite´ SAFARI Densite´ SAFARI Densite´ SAFARI +Nb de requeˆtes 1 1.71 1 1.82 1 1.78 +Taux de re´ussite 100% 95.70% 100% 92.20% 100% 90.90% +Longueur du Look-up 3.02 14.94 3.07 12.56 3.15 10.68 +Longueur des chemins 6.31 7.28 6.67 5.87 6.37 6.17 +Longueur globale 12.39 37.16 12.81 30.99 12.67 27.53 +λ 800 900 1000 +Densite´ SAFARI Densite´ SAFARI Densite´ SAFARI +Nb de requeˆtes 1 1.79 1 1.58 1 1.54 +Taux de re´ussite 100% 85.80% 100% 90.50% 100% 91.00% +Longueur du Look-up 3.16 10.36 3.21 8.63 3.24 5.04 +Longueur des chemins 6.75 5.88 6.61 5.73 6.66 5.09 +Longueur globale 13.07 26.60 13.03 22.99 13.14 15.17 +TAB. 5.3 – Comparaison de notre algorithme et de SAFARI. +caracte´ristiques des clusters en de´coulent. Cependant, ce facteur de´pend e´galement de +l’e´talement du re´seau pour SAFARI car plus le re´seau est e´tendu, plus le nœud rendez- +vous peut eˆtre e´loigne´. +Le champ ”Longueur des chemins” donne le nombre de sauts a` parcourir dans la +deuxie`me phase du routage indirect, en suivant les sche´mas de routage propose´s dans +chacun des algorithmes. Le champ ”Longueur globale” donne le nombre moyen de +sauts a` parcourir avant d’atteindre enfin le nœud destination. Il est e´gal a` la longueur +des routes de la deuxie`me e´tape plus deux fois la longueur des routes du look-up car la +requeˆte de look-up doit effectuer un aller-retour. +On remarque que les chemins de look-up dans SAFARI sont plus longs que les chemins +emprunte´s par les messages lors de la deuxie`me phase du routage indirect, ce qui peut +induire une latence importante. Ce n’est pas le cas dans notre approche ou` les requeˆtes +de look-up sont contenues dans un cluster et donc suivent un chemin dont la taille est +borne´e par le diame`tre des clusters, lui-meˆme borne´ par une constante. (Cf. chapitre 3). +Les longueurs des routes (suivies par les requeˆtes de look-up et par les messages de +donne´es) de´pendent bien suˆr de la densite´ locale du re´seau comme toutes les autres +caracte´ristiques e´tudie´es pour ces deux protocoles. Cependant, les routes emprunte´es +dans la deuxie`me phase du routage indirect de´pendent e´galement de l’e´talement du +re´seau. Plus le re´seau est grand, plus la distance se´parant deux nœuds du re´seau est +grande. Dans SAFARI, il en est de meˆme pour la taille des routes suivies par les +requeˆtes de look-up. Dans notre approche, la longueur des routes du look-up reste +constante lorsque le re´seau s’e´tale car elle est limite´e par le diame`tre des clusters qui +lui-meˆme reste constant. Ainsi, meˆme si pour les re´sultats de simulation obtenus, la +longueur des routes de look-up dans notre approche repre´sente pre`s de la moitie´ de +la taille du chemin global, elle tend a` devenir ne´gligeable devant la taille des routes +vers le nœud destination lorsque le re´seau s’e´tale, ce qui n’est pas le cas de SAFARI +pour lequel le ratio longueur look−uplongueur totale reste constant avec l’e´talement du re´seau. Les +122 CHAPITRE 5. LOCALISATION ET ROUTAGE +comparaisons mene´es ici peuvent sembler avoir e´te´ mene´es sur un re´seau trop peu +e´tendu. Cependant, le but recherche´ ici e´tait de comparer notre algorithme a` SAFARI +et pour un re´seau plus large, SAFARI construit un plus grand nombre de niveaux et ne +converge plus. C’est pourquoi, nous n’avons pu simuler le routage sur un re´seau plus +e´tendu qu’avec notre me´trique. Les re´sultats donne´s dans la table 5.4 sont obtenus sur +un re´seau ou` le degre´ moyen des nœuds (et donc l’intensite´ λ du processus de Poisson) +est constant mais avec une taille de re´seau de plus en plus importante. Les re´sultats sont +donne´s pour λ = 500 (δ ≈ 15.7) mais le comportement de l’algorithme est le meˆme +quelle que soit l’intensite´ conside´re´e. +Les re´sultats montrent qu’effectivement, bien que le re´seau grandisse, la longueur des +routes emprunte´es par les requeˆtes de look-up reste constante et que seule la longueur +totale des routes pour joindre le nœud destinataire augmente. +Les routes emprunte´es lors de la deuxie`me phase du routage indirect ne sont pas op- +timales dans la mesure ou` elles ne sont pas calcule´es sur la topologie des nœuds mais +sur la topologie de clusters On retrouve le meˆme principe que dans BGP 4. ou` les +se´quences des AS (Autonomous System) ne donnent pas toujours le nombre de sauts +optimal entre clusters. Le champ ”E´ tirement” donne l’e´carte en nombre de sauts entre +la longueur des routes emprunte´es lors de la deuxie`me phase du routage indirect et la +longueur des routes dans le graphe (plus courts chemins) en nombre de sauts. On re- +marque que le facteur d’e´tirement survenant dans la seconde phase du routage indirect +est ne´gligeable devant la longueur totale des routes. Seul l’ajout des sauts ne´cessaires +au look-up importe. +Nb de nœuds 500 600 700 800 900 1000 +Nb de Clusters 11.70 14.20 15.80 17.50 21.42 24.30 +Longueur du Look-up 3.02 2.97 3.07 3.05 2.99 3.07 +Longueur des chemins 6.31 6.88 7.08 8.06 8.69 9.05 +E´ tirement 0.69 0.74 0.78 0.82 0.86 0.92 +Longueur globale 12.39 12.90 13.55 13.97 14.98 15.43 +TAB. 5.4 – Proprie´te´s de notre approche de routage avec λ = 500 (degre´ moyen des +nœuds constant δ = 15.7) lorsque le re´seau s’e´tale. +5.5 Conclusion +Dans ce chapitre, nous avons propose´ un protocole de routage hie´rarchique pou- +vant s’appliquer sur notre organisation de cluster. Cette approche hie´rarchique suit le +sche´ma inverse que ceux commune´ment de´crits dans la litte´rature. En effet, nous pro- +posons d’appliquer un protocole de routage re´actif a` l’inte´rieur des clusters et pro-actif +entre les clusters. Une telle approche suppose un routage indirect utilisant une table de +4www.freesoft.org/CIE/RFC/1772/ +5.5. CONCLUSION 123 +hachage distribue´e. Notre approche tire avantage des caracte´ristiques intrinse`ques du +me´dium radio et des clusters pour a` la fois proposer un sche´ma d’e´tiquetage efficace +des sommets des arbres de clustering pour distribuer les partitions de l’espace logique +d’adressage de la DHT et permettre un routage global impliquant une taille me´moire +sur les nœuds en O(1). Les requeˆtes de look-up peuvent ensuite eˆtre route´es graˆce a` +un routage par intervalle sur cet espace. La deuxie`me phase du routage indirect se fait +alors dans l’espace physique avec des chemins quasi-optimaux. +Afin d’e´valuer les performances de notre algorithme, nous l’avons compare´ au +seul autre protocole de notre connaissance qui utilise le meˆme sche´ma de routage +hie´rarchique : SAFARI. Il s’est ave´re´ que notre approche offre de meilleures ca- +racte´ristiques sur diffe´rents crite`res : temps de stabilisation, succe`s des look-ups, taille +des chemins, etc. Cependant, ces re´sultats sont a` mode´rer de par le fait qu’il n’existe +encore que tre`s peu de protocoles proposant cette approche de routage hie´rarchique. +Dans la continuite´ de cette approche, nous souhaiterions analyser plus en profondeur +les pe´riodes de rafraıˆchissement des enregistrements des nœuds, en fonction de leur +mobilite´. Comme les algorithmes pre´sente´s dans cette the`se peuvent eˆtre qualifie´s de +”quasi-locaux” et que la structure de clusters sous-jacente a pre´sente´ de bons compor- +tements face a` la mobilite´ des nœuds, nous espe´rons qu’il en sera de meˆme pour le +protocole de localisation/routage. +Comme nous l’avons vu, seulement peu de propositions utilisent une approche pro- +active entre les clusters et re´active a` l’inte´rieur des clusters. Nous avons compare´ +notre approche a` une autre qui utilisait ce meˆme mode`le. Cependant, il peut e´galement +s’ave´rer inte´ressant d’e´tablir des comparaisons avec une approche ”classique” de la +litte´rature, c.a`.d. qui propose un routage re´active entre clusters et pro-actif au sein d’un +cluster. +124 CHAPITRE 5. LOCALISATION ET ROUTAGE +5.6 Publications +1. Journaux et revues avec comite´ de lecture : +(a) Distributed Node Location in clustered multi-hop wireless networks. Na- +thalie Mitton et E´ ric Fleury. GESTS International Transaction on Computer +Science and Engineering, Volume 21, De´cembre 2005. +2. Colloques et confe´rences internationaux avec comite´ de lecture : +(a) Distributed Node Location in clustered multi-hop wireless networks. Na- +thalie Mitton, E´ ric Fleury. Asian Internet Engineering Conference (AIN- +TEC’05), 13-15 De´cembre 2005, Bangkok, Thailande. +(b) Distributed Node Location in clustered multi-hop wireless networks. Na- +thalie Mitton, E´ ric Fleury. LOCALITY’05, 26 Septembre 2005, Cracovie, +Pologne. +3. Rapports de recherche : +(a) Distributed Node Location in clustered multi-hop wireless networks. Na- +thalie Mitton et E´ ric Fleury. RR-5723. Octobre 2005. +4. Se´minaires, pre´sentations, expose´s : +(a) Localisation dans les re´seaux sans fil multi-sauts grandes e´chelles. Natha- +lie Mitton, E´ ric Fleury. Se´minaire ACI Pair a` Pair - Arcachon - France - 5-6 +Septembre 2005. +Chapitre 6 +Conclusion et perspectives +6.1 Conclusion +Mon objectif, au travers de cette the`se, a e´te´ de de´velopper une solution d’utilisation +des re´seaux sans fil sur de larges e´chelles afin de re´pondre aux besoins naissants de +notre socie´te´. Pour cela, il me paraissait important d’e´tudier les diffe´rentes contraintes +de tels re´seaux avant de pouvoir proposer une solution viable et fonctionnelle, meˆme +sur de grandes e´chelles. +J’ai pour cela propose´ une solution distribue´e qui se de´compose en plusieurs e´tapes. +Chacune des e´tapes re´pond a` une application de tels re´seaux tout en en conside´rant +les contraintes. Chaque algorithme est ne´ d’une e´tude des contraintes ou des structures +et se compose d’algorithmes distribue´s, auto-stabilisants et robustes, ne´cessitant peu +de ressources en e´nergie, bande passante ou taille me´moire. Toutes ces e´tapes ont e´te´ +e´tudie´es analytiquement et par simulation. Chaque solution a e´te´ compare´e a` d’autres +solutions propose´es dans la litte´rature et s’ave`re soit offrir de meilleurs re´sultats, soit +de meilleurs compromis. +La premie`re e´tape permet de structurer logiquement le re´seau en clusters. A partir de +l’e´tude de la structure ainsi forme´e, plusieurs caracte´ristiques ont pu eˆtre de´gage´es. Ces +caracte´ristiques ont alors guide´ la conception des algorithmes des e´tapes suivantes. La +seconde e´tape a cre´e´ des liens entre ces clusters afin de pouvoir effectuer des diffusions +ge´ne´rales d’information de fac¸on efficace. L’algorithme de diffusion en soi est simple, +il se´lectionne un sous-ensemble de nœuds autorise´s a` relayer le message. Cette sim- +plicite´ intrinse`que est d’autant plus riche qu’elle utilise une structure existante, sans +en cre´er de nouvelles. L’algorithme de diffusion e´conomise ainsi des messages et des +ressources. +Enfin, la dernie`re e´tape permet a` deux entite´s individuelles de communiquer, quelles +que soient leurs positions dans le re´seau. Ce processus de routage pre´sente plusieurs +originalite´s. En effet, dans un premier temps, il conside`re une approche inverse a` +125 +126 CHAPITRE 6. CONCLUSION ET PERSPECTIVES +celle propose´e jusqu’a` maintenant afin de pre´server une faible taille me´moire sur les +nœuds. Ensuite, il emprunte des solutions algorithmiques a` d’autres domaines comme +les tables de hachage distribue´es issues du domaine du Pair a` Pair et le routage par +intervalle issu des re´seaux filaires. +6.2 Perspectives +Les diffe´rents algorithmes propose´s dans chaque e´tape de ma proposition pre´sentent +tous des caracte´ristiques qui peuvent eˆtre e´tudie´es plus en profondeur ou des points +qui me´riteraient certaines optimisations. Par exemple, le comportement de chaque al- +gorithme pourrait eˆtre analyse´ dans un environnement plus mobile. Un autre point im- +portant est que toutes les analyses re´alise´es sur les diffe´rents algorithmes de ma propo- +sition ont e´te´ conduites en supposant une couche MAC ide´ale et un mode`le ”Unit Disk +Graph” pour de´finir le voisinage des nœuds. Conside´rer une couche MAC ide´ale per- +met de n’e´tudier que les caracte´ristiques propres a` l’algorithme conside´re´, ce qui e´tait le +but recherche´ dans cette the`se. Cependant, un protocole de niveau 3 est utilise´ conjoin- +tement avec des protocoles de niveaux infe´rieurs. De meˆme, l’aire de transmission d’un +nœud est rarement un cercle puisque la propagation des ondes de´pend du milieu et des +obstacles que peut rencontrer le signal. Il serait donc inte´ressant d’e´valuer les diffe´rents +algorithmes propose´s dans ce manuscrit, en conside´rant diffe´rents protocoles pour les +couches infe´rieures et diffe´rents modes de propagation des ondes suivant les environ- +nements, aussi bien en ce qui concerne les analyses par simulation que les analyses +the´oriques. En effet, dans nos analyses the´oriques, nous avons e´galement conside´re´ le +mode`le ”Unit Disk Graph” mais d’autres mode`les d’e´tude ont e´te´ propose´s comme par +exemple dans [27] ou [9] qui conside`re le mode`le CDMA utilise´ dans 802.11. De plus, +comme dans un environnement sans fil re´el, de nombreux parame`tres d’environnement +entrent en jeu pour assurer ou non l’existence d’un lien, on peut e´galement conside´rer +un mode`le ou` un lien existe avec une certaine probabilite´. +Par ailleurs, les re´seaux sans fil couvrent une large famille de re´seaux, comme les +re´seaux ad hoc ou les re´seaux de capteurs. Bien que posse´dant tous des caracte´ristiques +semblables, chacun a une utilisation plus pre´cise et des proprie´te´s supple´mentaires. La +solution d’utilisation grande e´chelle que j’ai de´crite ici est ge´ne´rique et peut s’appliquer +a` tout type de re´seau sans fil. Cependant, il me semble que pour concevoir un re´seau +efficace, il faut e´galement conside´rer l’application du re´seau. Ainsi, j’aimerais par la +suite conside´rer plusieurs applications plus cible´es et un type de re´seau plus pre´cis +comme par exemple les re´seaux de capteurs. +En effet, les re´seaux de capteurs offrent un certain nombre de de´fis et de verrous scienti- +fiques. Ils sont le reflet de l’e´volution a` la fois des syste`mes, des re´seaux, de leurs com- +posants mais aussi de leur organisation et des inter-actions et communications entre +syste`mes. Malgre´ des tailles souvent petites, ils inte`grent une forte complexite´, notam- +ment de par l’infrastructure logicielle qui se retrouve distribue´e a` une grande e´chelle et +qui se doit d’offrir des services d’auto-adaptabilite´. +6.2. PERSPECTIVES 127 +Les re´seaux de capteurs sont de plus en plus de´ploye´s et offrent des perspectives nou- +velles chaque jour. Aujourd’hui, on cherche a` de´ployer un re´seau de capteurs pour la +surveillance des feux de foreˆts par exemple, afin de pre´venir d’un incendie et d’inter- +venir avant qu’il n’ait cause´ trop de de´gaˆts. A` moyen terme, on cherche a` inte´grer ces +capteurs dans les structures des baˆtiments et ne les faire s’activer que si le baˆtiment +s’e´croule afin de guider les secours. Les contraintes de base restent les meˆmes : e´nergie +et bande passante limite´es. Cependant, avec les nouvelles applications et le de´ploiement +de re´seaux de plus en plus grands, d’autres points sont a` conside´rer, comme la mobilite´ +des capteurs (un re´seau de capteurs peut eˆtre embarque´ dans une voiture par exemple +ou servir a` traquer des animaux), la robustesse de la structure globale (il faut s’assurer +que le re´seau de base soit stable avant de penser a` l’e´tendre) ou encore la se´curite´. Pour +une meilleure optimisation, tous ces aspects se doivent d’eˆtre e´tudie´s conjointement. +La solution que j’ai de´veloppe´e dans cette the`se reste applicable, meˆme si les capteurs +pre´sentent des proprie´te´s supple´mentaires par rapport au mode`le ge´ne´rique des re´seaux +sans fil. Par exemple, lorsque l’on conside`re un re´seau de capteurs, bien que la topolo- +gie reste dynamique du fait des apparitions ou disparitions de capteurs dues a` la mort, a` +l’endormissement ou au re´veil des entite´s, les capteurs ne se de´placent pas toujours. De +meˆme, les mode`les de communication sont diffe´rents dans un re´seau de capteur. Deux +capteurs n’ont ge´ne´ralement pas besoin de communiquer directement. On observe sur- +tout des communications de la station de base vers l’ensemble des entite´s (pour une +synchronisation par exemple) ou des entite´s vers la station de base (pour retourner une +mesure prise par un capteur par exemple). Les algorithmes que j’ai propose´s peuvent +eˆtre optimise´s en fonction de ces caracte´ristiques plus pre´cises. +Les contraintes a` e´tudier, quelles qu’elles soient, doivent eˆtre conside´re´es dans toutes +les couches de communication, qu’il s’agisse de la conception au niveau signal, liaison +de donne´es ou routage. Tous les niveaux doivent conside´rer que les capteurs ont des +capacite´s limite´es en e´nergie et en taille me´moire, et non pas seulement la couche +re´seau. Tous ces de´fis rencontre´s dans de tels re´seaux ont e´te´ traite´s a` diffe´rents niveaux. +Les diffe´rentes propositions de protocoles de niveau physique cherchent a` minimiser +l’e´nergie de´pense´e en e´mission et en re´ception. Les protocoles de niveau MAC e´tudient +des re`gles d’endormissement des nœuds afin de ne faire travailler qu’un sous-ensemble +de capteurs a` la fois. Les protocoles de routage cherchent a` minimiser les inondations +de de´couverte et maintenance des routes et a` limiter le nombre de nœuds participant a` +ces diffusions. Cependant, toutes ces recherches d’optimisation restent inde´pendantes +les unes des autres et ne sont pas toujours compatibles. Par exemple, les protocoles de +routage peuvent avoir de´signe´ certains capteurs pour diffuser un message que la couche +MAC aura endormis. Dans ce cas, les messages ne seront pas relaye´s, ce qui peut avoir +de graves conse´quences suivant l’usage du re´seau de capteurs. De la meˆme fac¸on, la +couche la plus haute et la couche la plus basse ne peuvent eˆtre totalement de´corre´le´es, +les capteurs physiques devant re´pondre aux contraintes des applications. +Ainsi, chaque couche a besoin des informations des autres couches. Pour optimiser +au maximum les communications dans les re´seaux de capteurs, toutes ces couches ne +peuvent rester inde´pendantes les unes des autres et travailler seules. Il faudrait parvenir +a` supprimer ce de´coupage en couche et a` fusionner les qualite´s logicielles et mate´rielles +des capteurs. Le routage et les applications doivent pouvoir eˆtre de´termine´s en fonction +128 CHAPITRE 6. CONCLUSION ET PERSPECTIVES +des capacite´s physiques des capteurs et vice-versa. Les applications du re´seau de cap- +teurs doivent e´galement guider les fonctionnalite´s qui doivent apparaıˆtre aux niveaux +infe´rieurs. Ceci sera d’autant plus important quand on en viendra a` faire communi- +quer des objets he´te´roge`nes qui auront des fonctions de surveillance diffe´rentes dans +le re´seau. En effet, il faudra maintenir l’inter-ope´rabilite´ entre les composants et le bon +fonctionnement global du re´seau. 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IEEE Journal +on Selected Areas in Communications, 22(1), January 2004. diff --git a/examples/theses/Thesis_Calligari.pdf b/examples/theses/Thesis_Calligari.pdf new file mode 100644 index 00000000..03a8dda1 Binary files /dev/null and b/examples/theses/Thesis_Calligari.pdf differ diff --git a/examples/theses/Thesis_Calligari/fulltext.pdf b/examples/theses/Thesis_Calligari/fulltext.pdf new file mode 100644 index 00000000..03a8dda1 Binary files /dev/null and b/examples/theses/Thesis_Calligari/fulltext.pdf differ diff --git a/examples/theses/Thesis_Calligari/fulltext.pdf.txt b/examples/theses/Thesis_Calligari/fulltext.pdf.txt new file mode 100644 index 00000000..c389c8da --- /dev/null +++ b/examples/theses/Thesis_Calligari/fulltext.pdf.txt @@ -0,0 +1,5930 @@ +Signature of protein adaptation to warm deep sea +environments: the case of Initiation Factor 6 studied by +molecular simulation and neutron scattering. +Paolo Calligari +To cite this version: +Paolo Calligari. Signature of protein adaptation to warm deep sea environments: the case of +Initiation Factor 6 studied by molecular simulation and neutron scattering.. Biological Physics. +Universite´ Pierre et Marie Curie - Paris VI, 2008. English. +HAL Id: tel-00368866 +https://tel.archives-ouvertes.fr/tel-00368866 +Submitted on 17 Mar 2009 +HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est +archive for the deposit and dissemination of sci- destine´e au de´poˆt et a` la diffusion de documents +entific research documents, whether they are pub- scientifiques de niveau recherche, publie´s ou non, +lished or not. The documents may come from e´manant des e´tablissements d’enseignement et de +teaching and research institutions in France or recherche franc¸ais ou e´trangers, des laboratoires +abroad, or from public or private research centers. publics ou prive´s. +THÈSE DE DOCTORAT DE +L’UNIVERSITÉ PIERRE ET MARIE CURIE - PARIS 6 +Spécialité: +interfaces de la biologie avec la physique, la chimie et +l’informatique +Pour obtenir le grade de +Docteur de l’Université Pierre et Marie Curie +Presenté par: +paolo calligari +S IGNATURE DE L’ADAPTAT ION DES PROTÉ INES +À L’ENVIRONNEMENT DES FONDS MARINS CHAUDS : +le cas du Facteur d’Initiation 6 étudié par simulation moléculaire et diffusion de neutrons +Paris, 18 Dcembre 2008 +Devant le jury composé par: +Prof. Cristian Micheletti (Rapporteur) +Prof. Roger Fourme (Rapporteur) +Prof. Françoise Gaill (examinatrice) +Dr. Joel Pothier (examinateur) +Dr. Giuseppe Zaccai (examinateur) +Prof. Mark Johnson (examinateur) +Prof. Gerald R. Kneller (directeur de thse) + +thèse préparée au sein de: +INSTITUT LAUE LANGEVIN (Grenoble) +et +LABORATOIRE LEON BRILLOUIN (CEA Saclay, Gif-sur-Yvette) + +Dedicated to Francesca Romana. + +ABSTRACT +Signature of protein adaptation to warm deep sea environments: the case of Initiation Fac- +tor 6 studied by molecular simulation and neutron scattering. +The protein Initiation Factor 6 (IF6) takes part in the protein synthesis regulation of several +organisms. It was also found in archeaebacteria such as Methanoccoccus Jannascii which lives in +deep-seas near hydrothermal vents where temperature reaches 80◦C and pressure is between +250bar and 500bar. The aim of this work was to study for the first time dynamical and +structural properties of IF6 produced by M.Jannaschii and comparing them with those of +the IF6 homologue present in Saccharomyces cerevisiae which lives at "normal" environmental +conditions (27◦C and 1bar). +Molecular simulation gave here new insights into the adaptation of these two proteins to their +respective physiological conditions and showed that the latter induced similar dynamical and +structural properties: in their respective "natural" conditions, IF6s show very similar structural +fluctuations and the characteristic relaxation times which define their dynamical properties +shows similar changes when comparing unfavorable conditions to physiological ones. The +creation of these corresponding states between the two homologues has been interpreted by +the fractional Brownian dynamics model and by a novel method for the characterization of +protein secondary structures. The latter is presented here in detail together with some exam- +ples of other applications. Experimental data obtained from quasi-elastic neutron scattering +seemed to support the results obtained by molecular simulations. +Keywords : Initiation Factor 6, molecular dynamics, neutron scattering, pressure, fractional +Brownian dynamics model, warm deep sea, protein secondary structure +vii +RÉSUMÉ +Signature de l’adaptation des protéines à l’environnement des fonds marins chauds: le +cas du Facteur d’Initiation 6 étudié par simulation moléculaire et diffusion de neutrons. +Le Facteur d’Initiation 6 (IF6) est une protéine qui participe, dans plusieurs organismes, à +la régulation de la synthèse des autres protéines. Elle a été trouvée aussi dans l’archaebactérie +Methanoccoccus Jannascii qui vit au fond de la mer, près des cheminées hydrothermales, où la +température atteint 80◦C et la pression hydrostatique est entre 250 et 500bar. L’objectif de ce +travail a été celui d’étudier pour la première fois les propriétés dynamiques et structurales de +la IF6 issue du M.Jannaschii en comparaison avec celles de son homologue présent dans le +Saccharomyces cerevisiae qui vit dans des conditions environnementales "normales" (27◦C et +1bar). +La simulation moléculaire nous a permis de montrer que l’adaptation de ces deux protéines +aux conditions physiologiques induit des propriétés dynamiques et structurales similaires: +dans leur conditions "naturelles" respectives, les deux protéines montrent des fluctuations +structurales très similaires et les temps caractéristiques qui identifient leur propriétés dy- +namiques subissent les mêmes changements dans la transition d’une condition défavorable +vers la condition physiologique. +Cette création d’ "états correspondants" entre les deux protéines a été étudiée par le modèle +de dynamique Brownienne fractionnaire et par une nouvelle méthode pour la caractérisation +des structures secondaires des protéines. Cette dernière est présentée en détail avec des brefs +exemples d’autres applications. Les données préliminaires obtenues par diffusion de neutrons +semblent confirmer les résultats issues des simulations moléculaires. +Mots clés : Facteur d’Initiation 6, dynamique moléculaire, diffusion de neutrons, pression, +modèle Brownien fractionnaire, fond marins chauds, structure secondaire des protéines. +viii +PUBL ICAT IONS +Some ideas and figures have appeared previously in the following publications: +1) Calligari P.A. et al., Inhibition of viral group-1 and group-2 neuraminidases by oseltamivir: +a comparative structural analysis by the ScrewFit algorithm. Biophysical Chemistry, accepted +for publication (2008). +2) Calligari P.A. and Kneller G.R., ScrewFit : a novel approach for continuum protein sec- +ondary structure assessments. Submitted (2008). +3) Calandrini V., Hamon V., Hinsen K., Calligari P., Bellisent-Funel M.-C. and Kneller G.R., +Relaxation dynamics of lysozime in solution under pressure: combining molecular dynamics +and quasielastic neutron scattering. Chemical Physics, 345, 289-297 (2008). +4) Hamon V., Calligari P., Hinsen K., Kneller G.R. Simulation studies of structural changes and +relaxation processes in lysozyme under pressure, J. of Non-Crystalline Solids, 352, 4417-4423 +(2006). +5) Kneller G.R. and Calligari P., Efficient characterisation of protein secondary structure in +terms of screw motions. Acta Crystallographica D62, 302-311, (2006). +ix + +Il est certain que beaucoup de choses vont bien dans la nature, +c’est-à-dire vont en sorte de pouvoir durer et se conserver, ce +qu’elles ne pourraient faire autrement. Mais une infinité d’autres +vont mal (et peut-être un plus grand nombre), sont mal organisées, +moralement et physiquement, avec un immense inconvénient pour +les créatures; ces choses auraient pu à peu de différence près être bien organisées. +— Giacomo Leopardi, Zibaldone di pensieri [N. 4248] +REMERCIEMENTS +Ce travail de thèse a été effectué à l’Institut Laue Langevin de Grenoble et au Laboratoire +Léon Brillouin au Commissariat à l’Energie Atomique de Saclay, sous la direction du +professeur Gerald KNELLER à qui s’adressent mes premiers remerciements pour m’avoir +accueilli dans son équipe et pour avoir su équilibrer, dès le primer jour, mon enthousiasme +envers la biologie avec des bonnes doses de physique théorique. Je lui serai toujours +reconnaissant de ne pas avoir laisser que j’oublie mes origines de physicien. +Je suis pareillement reconnaissant envers Mark JOHNSON, qui à co-diriger ma thèse. A lui +vont mes remerciements pour avoir suivi et coordonner mon travail en me laissant toute la +liberté d’expérimenter, d’essayer et de me planter devant les problèmes comme le font les +"vrais" chercheurs. Je lui doit tout ma gratitude pour la confiance qu’il m’a réservé ainsi que +pour son support dans les moments les plus difficiles. +Envers mes deux directeurs un remerciement supplémentaire pour avoir su être amis en +outre que simples "chefs"... +Je voudrais aussi exprimer ma gratitude envers les membres du jury: la présidente +Françoise GAILL, Cristian MICHELETTI et Roger FOURME qui ont accepté d’être +rapporteurs de mon mémoire, Giuseppe ZACCAI et Joel POTHIER. +Je tiens ensuite à remercier les collaborateurs du professeur Kneller, Vania CALANDRINI +et Konrad HINSEN pour tout ce qu’ils m’ont appris et pour leur aide précieuse dans mon +travail partagé entre les neutrons et les simulations numériques. +xi +Je suis particulièrement reconnaissant envers Jacques OLLIVIER et Jean-Baptiste ARTERO +qui ont partagé avec moi "la quotidienneté" de mon travail (et notamment des expériences de +laboratoire, pas toujours encourageantes...!). Je remercie Jacques pour ce qui m’a appris, pour +sa patience envers les cotés plus étranges (surtout au monde des neutrons) de mon projet de +thèse et pour m’avoir accompagné dans nos expériences de diffusion de neutrons au Paul +Scherrer Institut (Zurich, Switzerland) et au NIST (Maryland, USA). +Une partie fondamentale de ce projet a été possible seulement grâce aux enseignements +de Jean-Baptiste qui m’a guidé dans le monde de la biologie moléculaire et dans les +expériences lourds et souvent peu généreux d’expression et purification des protéines. Je +sais qu’il a du prouver un goût très particulier en voyant un pauvre physicien faire des +bêtises sur la paillasse mais moi j’ai trouvé ma "vengeance" avec la coupe du monde de +football....."Campioni del mondo!!!" +Je ne peux pas oublier les autres collègues des laboratoires qui ont vu ma présence, souvent +fugace, durant mon séjour à Grenoble: j’ai parcouru ma mémoire des deux années passées et +je vous ai tous retrouvés pour votre amitié, vos encouragements, votre patience (je pense +surtout aux collègues du DEUTERATION LAB !! ), votre aide direct et constant, pour avoir +supporté mon travail et pour beaucoup d’autres choses.... Merci! +A mes amis et ma famille: +A Paris: Andrea et Adrien, merci pour les discussions hors cerveau et/ou hors logique, elles +ont souvent sauvé ma stabilité mentale. A Grenoble: Mauro, merci pour nos nombreuses +pauses café à mi-chemin entre nos rêves et nos ambitions. Merci à Giada, Bea, Fabrizio, i +Fratini pour les beaux moments. Un merci générale à tous mes amis pour avoir supporté ma +passion pour l’évolutionnisme et pour avoir écouté avec patience mes contes sur l’histoire du +pauvre Kiwi. +Un merci à ma famille et à mes amis à Rome qui ont vécu et participé à distance mes petits +succès et faillites... +En fin, au dehors de toute cette liste, une seule personne n’a pas besoin d’être remerciée ici +parce que elle a vécu tout ce que j’ai vécu et elle sais bien que tout cela n’aurait jamais pu +être sans sa présence, son support, sa compréhension et sa confiance pleins d’amour. Cette +personne est devenue, au fil de cette thèse, mon épouse et c’est à elle que tous ces années de +travail sont dédiés: "grazie amore". +xii +Part I +RÉSUMÉ SUBSTANTIEL + +RÉSUMÉ SUBSTANTIEL +0.1 introduction +Dès le début du dernier siècle, les acquis sur la matière inanimée ont amenés les physiciens +à se demander comment ces connaissances pouvaient être aussi appliquées à la matière +biologique. La matière vivante présentait aux chercheurs une hétérogénéité et complexité de +cas que ils n’avaient jamais rencontré en physique. Elle a ainsi donné naissance à un nouveau +filon de recherche interdisciplinaire qui, alliant les domaines de la physique, la chimie et la +biologie, a fourni des résultats très importants et utiles pour des applications successives en +médecine et en biotechnologie. +Ce travail de thèse puise ses sources dans le considérable progrès fait dans le domaine de la +physique biologique notamment en ce qui concerne le développement de nouvelles méthodes +de calcul, ainsi que à l’application des techniques de spectroscopie sur des échantillons +biologiques. +0.1.1 Organismes adaptés aux environnements extrêmes +Organisms are integrated entities, not collections of discrete objects 1 +Les effets de la pression et de la température sur les propriétés structurales des protéines +sont visibles à plusieurs échelles, des interactions non-covalentes des très courte portée, telles- +que les liaisons hydrogène, jusqu’aux interactions à plus longue portée comme les interactions +électrostatiques. Tout changement dû à une variation des variables thermodynamiques peut +être interprété par le principe de Le Chatelier, selon lequel toute perturbation sur un système +à l’équilibre provoque une réaction contraire de façon à diminuer l’effet de cette perturbation. +Dans le cas considéré, l’application de la pression à une protéine favorise des processus +qui s’accompagnent d’une diminution du volume. Ces processus agissent directement sur +la structure de la protéine, entraînant des changements des interactions non-covalentes +1 "Les organismes sont des entités intégrées, ils ne sont pas des collections d’objets discrets". The spandrels of San Marco +and the Panglossian paradigm: a critic to the adaptationist programme, S.J. Gould and R.C. Lewontin, Proc. +Royal Soc. London B, 205, 581-598, (1979). +xv +qui se forment ou se défont à l’intérieur de la structure. Ces changements produisent des +effets différents sur les trois niveaux de structuration des protéines (secondaire, tertiaire et +quaternaire)[144]. +Dans cette thèse nous avons abordé les effets de la pression et de la température dans +un contexte particulier, celui des environnements des fonds marins près des cheminées +hydrothermales où l’on trouve normalement des pressions et des température très hautes. En +outre, comme suggéré par la phrase citée au début de cette section, nous voulons souligner le +fait que l’étude de l’adaptation des protéines aux environnements extrêmes pourrait être +largement améliorée par la connaissance du cadre général de l’adaptation cellulaire. Dans le +texte de cette thèse nous avons donné un bref aperçu du sujet tout en renvoyant à d’autres +publications pour des approfondissements de l’argument [85, 93, 182, 158, 107, 151, 191, 58]. +La biosphère, c’est à dire la surface de le terre connue comme lieu accueillant la vie, +varie entre les régions abyssales des fonds marins et les hauteurs de l’Himalaya et offre une +grande variété d’exemples d’organismes adaptés aux conditions extrêmes. D’un point de +vue qualitative les limites physiques et chimiques pour accueillir des formes de vie sont les +suivantes[92]: +• −40◦C < T < 115◦C +• P < 1.2kbar +• ∼ 1 < pH < 11 +D’un point de vue évolutionniste, les organismes qui vivent dans des conditions proches de +ces limites ont dû trouver des façons pour compenser tous les effets chimiques et physiques +que ces limites mêmes peuvent générer sur l’ensemble de structures constituant les cellules. +Autrement dit, les organismes qui sont devenues extrêmophiles ont trouvé des stratégies pour +protéger leur système de vie des dégâts produits par l’environnement. D’après le peu qu’on +connaît sur le fonctionnement de ces mécanismes, il y a deux démarches principalement +suivis par les organismes. La première est la compensation des processus de dégradation +à travers d’un réglage fin des taux de synthèse des biomolécules de façon qu’il soient +compatibles avec le temps moyen de survie des molécules. La deuxième est l’incorporation +de mutations ponctuelles dans les séquences des protéines à fin d’augmenter leur stabilité +structurale, leur permettant de fonctionner plus longtemps. Apparemment, cette stratégie ne +produit pas de différences remarquables dans la distribution globale des acides aminés dans +xvi +des protéines extrêmophiles par rapport à celles mesophiles, c’est à dire issues d’organismes +vivant dans des conditions dites normales (température à 300K et pression à1bar) [48]. +Par conséquence, il semble assez évident que l’adaptation des biomolecules doit être liée à +la présence de différents motifs locaux dans les séquences des acides aminés entraînant une +réorganisation des interactions faibles non-covalentes qui règlent la stabilité et la flexibilité +des protéines. Le new deal pour la stabilité des protéines extrêmophiles se fait donc par une +réorganisation des mécanismes sensibles aux changements environnementaux. D’un point de +vue physique, une mesure quantitative de la stabilité des protéines peut être obtenue par +les différences d’énergie libre de Gibbs, ∆G(T ,P,N), entre l’état le plus stable et les minima +locaux les plus proches. Jaenicke et Böhm [96] ont montré que les protéines mesophiles +et extrêmophiles partagent un ∆G du même ordre de grandeur (∼ 50kJmol−1) même si +les extrêmophiles montrent une plus large variabilité dans l’intervalle 10 − 100kJmol−1. +Les différences trouvées entre les protéines mesophiles et extrêmophiles correspondent à +l’énergie nécessaire à la formation ou à la rupture de quelques interactions non-covalentes, ce +qui confirme le rôle fondamental que ces dernières jouent dans le contexte de l’adaptation +moléculaire [157, 147, 151, 158]. +Le point central dans l’adaptation des biomolécules reste, de toute façon, la conservation +des fonctionnalités biologiques représentant un compromis bien équilibré entre stabilité +et flexibilité [197, 92]. Le processus d’adaptation se manifeste, donc, sous forme d’une +transformation des propriétés des protéines mesophiles vers les conditions extrêmes, c’est à +dire, vers des conditions physiologiques qui rendent les propriétés moléculaires des variétés +extrêmophiles très similaires à celles des mesophiles. Cette translation est obtenue par la +réorganisation des liaisons non-covalentes. Plusieurs expériences ont mis en évidence ce +processus [217] et elles ont montré que les propriétés dynamiques de quelques enzymes +mesophiles à une température de 25◦C sont très similaires à celles des leurs homologues +extremophiles à 70◦C. Des résultats analogues ont été obtenus par une étude de simulation +de dynamique moléculaire sur les différents homologues de la rubredoxine [69]. +Dans ce contexte Jaenicke [93] a supposé que l’adaptation moléculaire à des environnements +extrêmes puisse fonctionner grâce à un maintien d’états correspondants entre les environ- +nements natifs, en tenant compte de la topologie générale, de la flexibilité et de l’hydratation +des protéines. Même si cette idée a trouvé plusieurs confirmations dans le passé, des études +récentes ne semblent pas la confirmer entièrement[158]. +xvii +0.1.2 L’environnement typique des fonds marins chauds +Contrairement à l’opinion générale, les environnements terrestres, où la pression est d’environ +1bar, occupent seulement 1% du volume total de la biosphère. Une partie considérable de la +surface terrestre (70%) est couverte par les océans qui ont une profondeur moyenne de 3800 +mètres et donc une pression moyenne de 380bar. Plus du 60% de la biosphère marine est à +1000 mètres sous le niveau de la mer. La vie au dessous de cette profondeur, normalement +considérée comme le limite pour les environnements dits fonds marins, doit faire face à +plusieurs conditions défavorables liées aux changements de la pression (de 1 à 1.1 kbar ) et de +la température (de 1 à 110◦C) qui ont des impacts très important sur les mécanismes vitaux. +Une nouvelle ligne de recherche sur les organismes qui vivent dans les sédiments marins +a été entreprise entre le XIXème et le XXème siècle par Certes[30, 29] suivi par ZoBell et +Johnson [220] dont les recherches ont mieux éclairées les stratégies de survie employées par +les organismes pour faire face aux conditions extrêmes. +Grâce à ce courant de recherche nous pouvons aujourd’hui distinguer les organismes en +fonction de leur capacité d’adaptation aux hautes pressions: les barophiles (ou piezophiles) +qui ont une croissance optimale à des pressions supérieures à celle atmosphérique; les +barotolerants (ou piezotolerants) qui sont des organismes capables de vivre à hautes pressions +tout en ayant leur taux de croissance optimale à pression atmosphérique; enfin, les organismes +piezosensibles qui se distinguent des autres parce que leur croissance est très sensible aux +pressions élevées. +A la fin des années 70, les premières colonies d’organismes dans les fonds marins ont été +trouvées à proximité des cheminées hydrothermales, des courants qui se forment où la lave +extrudée se refroidit en se contractant et permet à l’eau de mer d’entrer dans les fissures +des rochers basaltiques à peine formées. L’eau de mer est en suite expulsée très enrichie de +métaux lourds formant des courants à très haute température [98]. +La vie autour des cheminée hydrothermales est devenue très rapidement l’un des sujets les +plus intrigants dans le domaine de la biologie des fonds marins et la plupart des organismes +barophiles connus à ce jour sont de facto aussi thermophiles, c’est à dire ils ont montré un +plus haut taux de croissance à des températures plus élevées (typiquement entre 50 et 90◦C) +que celles caractéristiques des fonds marins (environ 2◦C) [1]. +xviii +Cet environnement des fonds marins chauds a introduit sous le plan biologique et +évolutionniste plusieurs questions de grand intérêt qui ont demandé aussi des nouvelles +explications par la biochimie et la physique. +methanococcus jannaschii Cette thèse a comme objet l’étude d’une protéine +produite par une archaebacterie, le Methanococcus Jannaschii, qui vit près des cheminées +hydrothermales. Cet organisme, découvert en 1963 [102], vit normalement à des températures +entre 48 et 94 ◦C, avec une température optimale de 85◦C, et à des pressions supérieures aux +200 bar (profondeur in situ 2600 mètres). +Le génome du M Jannaschii a été le premier parmi les génomes des archaebacteries dont on +a obtenu le sequençage complet [18] ce qui révéla des relations évolutives complexes entre +les archaea, les eucaryotes et les bactéries: seulement moins de la moitié des gènes trouvés +dans son génome pouvait, en fait, être reliée a ceux des autres organismes. Dans le cadre de +cette thèse, d’un point de vue de la biologie moléculaire, la propriété la plus intéressante +de cet organisme est due au fait que tout en partageant les mécanismes de biosynthèse des +eucaryotes, le M.Jannaschii possède des gènes pour la fonction d’initiation du processus de +traduction homologues soit à ceux des eucaryotes soit à ceux des bactéries. Cette fonction est +une partie fondamentale de la traduction de l’ARN messager et sera présentée en détail plus +avant dans le texte. +Des études ont montré que le métabolisme du M Jannaschii et sa croissance à haute +température sont favorisés par la pression jusqu’à 750 bar et que les limites pour la croissance +sont atteints à 90◦C soit à basse ou à haute pression [102]. Ces résultats suggèrent que le +M.Jannaschii est effectivement un organisme barophile et pas seulement barotolerant. Cette +conclusion semble être aussi confirmé par des études de réaction enzymatique qui ont montré +que l’application d’une pression de 500bar peut augmenter jusqu’à cinq fois le temps moyen +de vie de l’hydrogènase du M.Jannaschii à 90◦C [74] et jusqu’à 3 fois celui de la protease à 125 +◦C [138]. Néanmoins, des études récentes ont montré que la pression inhibait la fonction du +20S proteasome du M Jannaschii [55], suggérant ainsi que dans certains cas la moindre activité +d’une protéine à la pression native pourrait être un mécanisme de régulation conférant des +avantages à la cellule entière. Par conséquent, un comportement bien plus complexe de la +cellule par rapport aux hautes pressions et aux hautes températures devra être envisagé. +xix +0.1.3 Le facteur d’anti-association +Nous présentons ici une brève introduction sur la protéine qui fait l’objet de ce travail de +thèse, appelé Facteur d’anti-association [170, 199]. +Le facteur d’anti-association fait partie de la famille des facteurs d’initiation et il prend aussi +le nom de Facteur d’initiation 6 (IF6). +Le IF6, comme les autres facteurs d’initiation, prend part aux premières étapes du processus +de traduction ARN-messager des ribosomes. Le rôle du IF6 dans l’initiation de la traduction +est bien plus complexe que celui des autres facteurs d’initiation parce qu’il engendre diverses +fonctions qu’on connaît très mal. D’abord, IF6 n’agit pas comme un vrai facteur d’initiation +parce qu’il ne forme aucun complexe d’initiation, c’est à dire qu’il ne forme pas de complexe +macromoléculaire avec les mARN, tARN et les sous-unités du ribosome dans les premières +étapes de la traduction. Ceci est prouvé par le fait que la déplétion du IF6 ne bloque pas la +traduction du mARN in vitro [178]. +Les fonctions principales de cette protéine peuvent être résumées comme suit: +- IF6 est requis dans la biogenèse de la sous-unité ribosomale 60S soit dans les archaebac- +téries que dans les eukaryotes [173, 178, 177, 212] +- elle agit de facto comme un facteur qui règle l’association des sous-unités ribosomales +60S et 40S dans le cytoplasme [178, 28] +Ces fonctions, conservées dans plusieurs organismes, ont été prouvées par un grand +nombre d’études et sont vérifiées par la présence de cette protéine dans le cytoplasme et dans +les noyau des cellules. Dans le cadre de ce travail de thèse il est important aussi de noter que +le IF6 a été montré comme très sensible aux hautes températures : dans certains homologues +eukaryotes[178, 10], l’activité du IF6 a affiché un optimum autour de 37◦C alors qu’elle était +totalement absente entre 50 et 60 ◦C. A l’état actuel, il parait très difficile d’établir si cet arrêt +des fonctions du IF6 correspond aussi à une dénaturation. +D’un point de vue moléculaire, les IF6 sont des protéines d’environ 26kDa qui partagent une +séquence conservée de 224 résidus avec une similarité de 30%. Toutes les formes eukaryotes +de la IF6, contiennent une partie carboxy-terminale de 21 acides aminés. Même si cette queue +ne semble pas être directement impliquée dans la fonction d’anti-association du IF6[66], il a +été prouvé qu’elle était reliée à cette dernière[28]. +En 2000, les premières structures moléculaire du IF6 ont été résolues par des études +de cristallographie par rayon-X [66]. Il s’agit des structures de deux homologues du IF6: +xx +celui du M.Jannaschii et celui du Saccharomyces ceraevisie. Les deux structure ont révélé une +pseudo-symétrie interne crée par la disposition, autour d’un centre commun, de cinq copies +d’un domaine α/β d’environ 45 résidus. Chaque domaine contient: une longue hélice α, +une autre plus courte ou une hélice 310 et trois brin β. Contrairement à la structure des +premiers 224 résidus qui est connue et a été prouvée par homology modeling être conservée +evolutivement[66], très peu a été révélé sur la structure de l’extension C-terminale de 21 +acides aminées. +D’un point de vue structural, il faut aussi remarquer que les cinq domaines sont disposés +d’une façon qui ne crée pas un centre hydrophobique. Au contraire, dans leur association, ils +produisent un "tore" hydrophobe qui, à son tour, forme un centre creux dans la structure de la +protéine. Cette cavité est assez large pour faire passer plusieurs molécules d’eau. Seize de ces +molécules ont été trouvé aussi dans les structures cristallographiques, dans une configuration +très ordonnée à couches pentagonales et dont les hydrogènes interagissent avec les oxygènes +carbonyles des résidus dans les brins β voisins. Dans l’homologue provenant de la levure +(Saccharomyces ceraevisie), le IF6 montre cette cavité fermée par une arginine (résidu 61) dont +le groupement guanidinium forme plusieurs liaisons hydrogènes avec les glycines des courtes +hélices α de chaque domaine. +0.2 matériels et méthodes +Cette section propose un bref aperçu des techniques utilisées pour la préparation des échan- +tillons qui ont été étudiés par diffusion des neutrons et de ceux qui ont été simulés par +dynamique moléculaire. Pour une présentation complète du cadre théorique dans lequel +ces techniques ont été appliquées nous renvoyons au deuxième chapitre de la thèse et aux +références [3, 56, 13, 129]. +Dans le texte qui suit, les deux IF6 homologues seront indiqués par les acronymes suivants: +- aIF6: IF6 extremophile produit par Methanococcus Jannaschii +- eIF6: IF6 mésophile produit par Saccharomyces cerevisiae +0.2.1 Production des échantillons expérimentaux +Les échantillons expérimentaux étudiés ici par diffusion de neutrons, ont étés produits à +travers des étapes préliminaires qui demandaient notamment des connaissances en biologie +xxi +moléculaire. Cette thèse rapporte un protocole développé pour le IF6 qui vise à obtenir un +rendement suffisant et compatible avec les quantités d’échantillons requis par les expériences +de diffusion de neutron. Ce protocole suit le schéma usuel pour la production de protéines et +qui peut être résumé comme suit: +- Clonage de la partie de l’ADN génomique de Methanococcus Jannaschii et Saccharomyces +cerevisiae qui codifie le IF6. +- Expression du gène identifié dans un organisme hôte, dans le cas considéré ici le E.coli, +à fin de produire une grande quantité de protéines. +- Purification de la protéine produite par l’organisme hôte à fin de la séparer des autres +protéines et d’obtenir une solution assez pure ne contenant que la IF6. +Afin d’améliorer le rendement, du protocole de purification, nous avons utilisé une queue +N-polyhistidine N-terminale (H-Tag) qui a permis de maintenir une concentration suffisante +aussi pour des expériences de diffusion de neutrons à hautes pressions, ce qui, comme +on le verra après, demande l’utilisation de grands volumes de solution. Néanmoins, des +raisons techniques ont fortement limité le clivage de cette queue "marqueur" du IF6 en +grands volumes de solution. Pour cette raison, ce clivage a été fait seulement à pression +ambiante où les expériences pouvaient être faites avec des volumes adaptés. Il a été montré +que la présence de la H-Tag n’a pas d’effets significatifs sur la structure des protéines [23] +mais, vu son exposition au solvant qui entoure les protéines, elle pourrait avoir un effet +dynamique important. Pour cette raison, afin de vérifier les effets produits dans le cas du +IF6, des simulations de dynamique moléculaire ont été réalisés aussi sur un modèle du aIF6 +jointe avec la H-Tag. +clivage du fragment c-terminal du eif6 Pendant les tests préliminaires pour +l’optimisation du protocole ( cfr. ci-dessus) un clivage protéolytique du eIF6 a été observé +(voir Figure 13, dans le texte de cette thèse, pour vérification SDS-PAGE) soit dans la partie +soluble soit dans celle insoluble des fractions de purification du lysate cellulaire. A cause de +son poids moléculaire modéré, le fragment clivé a été supposé être le même trouvé par Groft +et al. [66]. Ces derniers ont rapporté le fait que les tentatives d’expression et purification du +eIF6 étaient rendues très difficiles par le clivage protéolytique du fragment C-terminale. +La partie clivée du eIF6 est formée de 21 acides aminés avec une séquence, affichée dans +le Tableau 1, présente uniquement dans les homologues eukaryotes du IF6 dont on sait +xxii +très peu. En outre, une caractérisation par alignement multiple avec des bases de données +d’autres séquences connues a montré que ce fragment n’est présent que dans les IF6, ce qui +prouve son importance pour la fonctionnalité du IF6 même ou bien pour son histoire évolutive. +Table 1: La séquence du fragment C-terminal du eIF6 (CTAIL). La numérotation suit celle utilisée dans +le PDB 1G62. +Glu225 Asp226 Ala227 Gln228 Pro229 Glu230 Ser231 Ile232 +Ser233 Gly234 Asn235 Leu236 Arg237 Asp238 Thr239 Leu240 +Ile241 Glu242 Thr243 Tyr244 Ser245 +Afin de mieux comprendre la structure native de cette queue C-terminale, nous avons +examiné sa structure secondaire à l’aide d’outils de prédiction qui ont vérifié la probable +présence d’une hélice-α dans la partie finale du fragment, la région DTLIE. Ce résultat a +été confirmé par l’inspection du profil hydrophobe du fragment à l’aide de l’échelle de +Kyte/Doolittle [122] qui montre une augmentation de l’hydrophobicité dans la même région. +Finalement, cette étude préliminaire nous a convaincus que le fragment C-terminal du +eIF6 joue un rôle significatif soit dans la dynamique soit dans la structure du eIF6 et donc +aussi dans sa fonction. Cette idée est renforcée par d’autres résultats qui indiquent que les +domaines C-terminaux contribuent à la localisation du eIF6 dans le noyau cellulaire [6]. Ces +conclusions nous suggèrent l’importance d’exprimer et de purifier le eIF6 avec la queue +C-terminale de 21 acides aminés et à ce propos plusieurs tests ont été mis en place pour +réduire le clivage pendant les différentes phases de production. Le protocole présenté dans +ce texte a donné les meilleurs résultats avec une clivage réduit d’environ 30% (voir la Figure +14 dans le texte pour une vérification par spectrométrie de masse MALDI). +stabilité du eif6 Afin d’aborder une étude visant les effets des conditions extrêmes +sur les propriétés d’une protéine, il est nécessaire, tout d’abord, d’établir quelles sont les +limites qui définissent les conditions normales pour la même protéine. Dans le cas des IF6, la +connaissance de ces limites est très limitée à cause d’un manque d’études approfondies sur +les propriétés chimiques de cette protéine. Ainsi, si pour le aIF6 on peut facilement supposer +xxiii +au moins une réponse réversible aux hautes pressions et températures, les conclusions sur les +eIF6 sont très limitées. +Dans notre démarche, nous avons d’abord procédé à un examen préliminaire à fin de +vérifier la stabilité de eIF6 aux hautes températures. Pour cela, nous avons fait référence au +travail de Valenzuela et al. qui a montré la cessation de l’activité du eIF6 à des températures +au-dela de 60 ◦C. Une étude par diffusion de lumière, réalisée pour vérifier les conclusions +de Valenzuela et al., a montré l’augmentation irréversible du rayon hydrodynamique des +molécules au delà de la température de 50◦C. Ce résultat semble indiquer pour le eIF6 des +conditions non-denaturantes à des températures inférieures à 50◦C. Cette limitation a été +tenue en compte dans les mesures expérimentales, toutefois, des simulations de dynamique +moléculaire ont été quand même réalisées afin de vérifier la présence effective d’un processus +de dénaturation ou simplement son amorce. +echantillons finaux Afin de pouvoir réaliser les expériences de diffusion des neu- +trons sur aIF6 et eIF6, les deux protéines ont été préparées dans des solutions deuterées +avec une concentration d’environ 40 mg/ml et une pD de 7.0. La concentration finale de +ces solutions a été vérifiée avec des mesures d’absorption UV-VIS à une longueur d’onde de +280nm. Cette mesure a donné cependant des résultats très imprécis à cause du nombre réduit +de chromophores (qui normalement absorbent les UV à 280nm) dans les acides aminés de +la séquence des IF6. Le manque de valeur précise a engendré des fortes limitations dans les +mesures de diffusion des neutrons. +0.2.2 Expériences de diffusion des neutrons +Dans ce travail, les mesures de diffusion des neutrons ont visé les effets de la pression et de la +température sur la dynamique des protéines. Pour les expériences de diffusion quasi-elastique +de neutrons (QENS), ces mesures sont normalement réalisées sur des échantillons en +solution qui sont comprimés dans des porte-échantillons de forme cylindrique. Dans le +cas de cette étude, la grande variation de température explorée a nécessité l’utilisation de +matériels qui ne subissent pas de changements structuraux importants à hautes températures +qui pourraient modifier, par exemple, la résistance mécanique des porte-échantillons. En +outre, les expérience de QENS nécessitent des solutions à très haute concentration afin de +pouvoir bien distinguer le signal provenant des protéines de celui donné par le solvant. +xxiv +Ce dernier fait pose un limitation importante dans le volume total disponible pour les +expériences sur des molécules biologiques car ces molécules ne sont normalement disponibles +qu’en petites quantités. Dans le cas des a/eIF6, cette limitation a constitué un point +crucial pour la mise en place de l’instrumentation nécessaire aux mesures sous haute pres- +sion. Une description complète de la cellule pour les hautes pressions est donnée dans la thèse. +0.2.3 Simulation de dynamique moléculaire +Toutes les étapes de simulation de dynamique moléculaire décrites dans le texte qui suit +ont été réalisées avec le programme AMBER9[27]. Le champ de forces utilisé est le AM- +BER99SB [86], une mise à jour du plus connu champ de forces AMBER94, qui contient des +paramètres permettant une meilleure différentiation des éléments de structure secondaire des +protéines. +Le schéma général pour la réalisation de ces simulations de dynamique moléculaire peut etre +résumé comme suit: +1. La configuration initiale est créée à partir des donnés cristallographiques (codes PDB: +1G61 pour aIF6 et 1G62 pour eIF6). Au système initiale nous avons ajouté des molécules +d’eau représentées par le modèle TIP3P et 14 contre-ions de sodium. Ces derniers ont le +rôle de rendre nulle la charge totale du système. +2. Le système entier est porté vers un état stable en appliquant des algorithmes de +minimisation de l’énergie d’abord sur les seules molécules d’eau et puis sur la totalité +du système. +3. Le système est ensuite porté vers les conditions thermodynamiques souhaitées par +des courtes simulations de dynamique moléculaire d’équilibration. D’abord le système +est équilibré dans un ensemble NVT (volume et température constantes) avec un pas +d’intégration de 1fs et pour une durée de 150ps; puis il est équilibré à pression et +température constantes (1bar et 300K) pendant 700ps. +4. Une fois obtenue l’équilibration du système, plusieurs simulations dans différentes +conditions de pression et de température ont été réalisées. Les cordonnées atomiques +sont stockées toutes les 40fs et la longueur des trajectoires générées est de 2ns. +xxv +Dans cette démarche la régulation de la température a été réalisée avec un thermostat +de Langevin [195] (constante de friction 3.5ps−1) et la pression moyenne a été maintenue +constante par un barostat de Berendsen [14] (temps de relaxation de 1.5ps). +configuration initiale du eif6 La configuration initiale du eIF6 issue des données +cristallographiques eu Saccharomyces cerevisiae (code PDB 1G62) ne contient pas les positions +atomiques des 21 acides aminés qui forment le fragment C-terminale, cette absence étant du +aux clivages protéolytiques déjà mentionnés dans les paragraphes précédents. La construction +de la structure complète du eIF6 exige des étapes supplémentaires par rapport au aIF6. +D’abord la structure du fragment C-terminale (CTAIL, ainsi par la suite) a été modélisée et +partiellement repliée. Ensuite la structure du CTAIL a été attachée au reste de la structure +du eIF6 et l’ensemble a été équilibré vers une configuration stable. Toutes ces étapes ont été +réalisées par des simulations de dynamique moléculaire avec solvant implicite permettant de +réduire considérablement les temps de calcul. Cette méthode consiste dans la substitution +des molécules d’eau par des termes additionnels, dans le champs de force atomique, qui +devraient reproduire les effets du solvant sur la protéine. +Le protocole utilisé pour la modélisation du CTAIL et pour son repliement est basé sur le +schéma suivant: +1. Une configuration "linéaire" du CTAIL a été d’abord créée avec la séquence des acides +aminés montrée dans le Tableau 1 +2. Un repliement initial du CTAIL a été obtenu par une suite de simulations courtes dans +un ensemble NVT (volume et température constants) avec un pas d’intégration entre 0.1 +et 0.5 fs. Le protocole complet de cette étape est affiché dans le tableau ?? de cette thèse. +3. Le processus de repliement est ensuite obtenu par une simulation de 40ns de longueur. +La structure du CTAIL partiellement repliée est montrée par la Figure 16 (voir le texte de cette +thèse). La configuration initiale de la structure complète du eIF6 a été crée par la jonction +entre CTAIL et le eIF6. Cette dernière opération a été effectuée par la création d’une liaison +covalente entre l’azote N-terminal du CTAIL et le carbone C-terminal du eIF6. La structure +ainsi obtenue a été ensuite soumise à une procédure de minimisation et d’équilibration. +Enfin, pour obtenir une meilleure optimisation locale de la structure, nous avons réalisé +une simulation moléculaire avec la méthode de recuit simulé. Grâce à une succession de +simulations à très hautes températures suivies par des autres à 300K, cette méthode permet +d’explorer l’espace des configurations des grandes molécules mieux qu’une simple procédure +xxvi +de minimisation de l’énergie. Dans le cas du eIF6, la structure finale issue de cette méthode ( +voir Figure 17) a une énergie potentielle légèrement inférieure à celle initiale. +La configuration ainsi trouvée a été utilisée ensuite comme état initial pour la procédure de +simulation moléculaire décrite au début de cette section. +Figure 1: Structure du eIF6 issue de la procédure de simulated annealing. +echantillons supplémentaires Afin de mieux comparer les résultats obtenus à +partir des simulations moléculaires avec ceux issues des mesures expérimentales, d’autres +échantillons ont été modélisés et simulés. Les résultats issues de ces simulations, ont fourni +notamment une meilleure compréhension des effets structuraux et dynamiques du CTAIL et +de la queue de poly-histidines (H-Tag) respectivement sur eIF6 et aIF6. Les deux échantillons +sont les suivants: +. eIF6-NoCTAIL: le eIF6 simulé sans le CTAIL attaché. La structure cristallographique a +été utilisé comme configuration initiale et a été soumise à la procédure de simulation +moléculaire énoncée au début de cette section. +. aIF6-HTag: le aIF6 est simulé avec une queue poly-histidine à l’extrémité N-terminale. +Comme déjà expliqué dans ce texte, la présence de ce fragment additionnel a permis +une amélioration considérable du rendement des protocoles de production des IF6. Les +xxvii +expériences de diffusion des neutrons sous pression ont été réalisées sur des échantillons +contenant la H-Tag, ce qui a rendu indispensable la réalisation des simulations du même +échantillon. La création de la structure, composée par le aIF6 et la H-Tag, a été obtenue +avec une procédé similaire à celui utilisé pour le CTAIL. +0.3 méthode de caractérisation de la structure secondaire des pro- +téines +Dans cette section, nous présentons une nouvelle méthode pour la caractérisation de la +structure secondaire des protéines. Le développement de cette méthode, appelée ScrewFit, a +été inspiré par la nécessité d’une analyse fine des effets de l’environnement sur les structures +des protéines. +Nous avons ensuite trouvé que ScrewFit est capable aussi de détecter les motifs qui carac- +térisent la structure secondaire et de donner une évaluation des effets locaux et globaux +résultants des interactions avec un ligand. La méthode et ses applications sont présentées +dans cette thèse par le biais de deux articles, déjà parus ou en cours de publication dans des +revues internationales avec comité d’évaluation : +- Kneller, G.R. and Calligari, P. Efficient characterization of protein secondary structure in +terms of screw motions. Acta Crystallographica D, 62(3), 302-311(2006). +- Calligari, P. and Kneller G.R., ScrewFit: a novel approach for continuum protein secondary +structure assessments. soumis. +Une autre application de cette méthode, en dehors du sujet de cette thèse, est exposée ici : +- Calligari, P. et al., Inhibition of viral group-1 and group-2 neuraminidases by oseltamivir: +a comparative structural analysis by the ScrewFit algorithm. Biophysical Chemistry, +accepté pour publication (2008). +Les résumés des deux articles inclus dans la thèse sont ici traduits et une brève introduction +de la méthode est donnée avec un exemple d’application. +0.3.1 Efficient characterisation of protein secondary structure in terms of screw motions +Nous présentons une méthode simple et efficace pour décrire la structure secondaire +en termes de distances d’orientation entre plans peptidiques consécutifs et paramètres +xxviii +hélicoïdaux locaux. La méthode utilise des fits de superposition de plans peptidiques en +combinaison avec le théorème de Chasles qui affirme que tout mouvement de corps rigide +peut être décrit par un mouvement du type "mouvement de vis". Pour la superposition +de plans peptidiques consécutifs nous avons dérivé les paramètres hélicoïdaux et utilisé +le fit le plus mauvais pour définir une distance d’orientation. Nous avons aussi montré +les applications de la méthode aux modèles théoriques des structures secondaires, aux +protéines appartenant à différentes classes structurales et à la description des changements +structuraux induits dans le lysozyme par une haute pression hydrostatique. Dans cette +dernière application, nous avons utilisé des donnés déjà publiées, issues de la cristallographie +par rayons-X et des mesures par RMN. +0.3.2 ScrewFit: a novel approach for continuum protein secondary structure assessments +Nous présentons ici une nouvelle méthode pour la détection des éléments de la structure +secondaire des protéines combinant une description de la chaîne principale d’une protéine en +terme de "mouvement de vis" (Acta Cryst. 62, 302-311 (2006)) et une approche statistique. +L’application de cette méthode produit des intervalles de confiance qui définissant les +variations naturelles des paramètres hélicoïdaux qui décrivent la chaîne principale. Afin +d’établir ces intervalles pour chaque motif (pattern) de structure secondaire, nous avons +analysé plusieurs bases de données contenant des structure de protéines caractérisées par +un profil structural bien défini. Cette méthode permet une évaluation "continue" de la +structure secondaire d’une protéine et a été démontrée stable par rapport aux variations +structurales, trouvées dans les donnés RMN, et à la résolution expérimentale des donnés +cristallographiques. La comparaison avec d’autres méthodes confirme sa précision et fiabilité. +L’exemple de l’analyse de la structure de l’inhibiteur trypsine pancréatique bovine dans +ses trois différentes formes cristallines montre la capacité de notre méthode de détecter +et d’analyser des petites variations structurales dans des données expérimentales très bruitées. +0.3.3 L’algorithme ScrewFit +A fin de décrire d’une manière simple la structure secondaire des protéines, nous avons utilisé +l’algorithme ScrewFit, qui est basé sur la superposition optimale de structures moléculaires +xxix +[50, 115, 116] et sur le théorème de Chasles [33, 32]. +Nous pouvons considérer deux plans peptidiques consécutifs A et B, comme deux corps +rigides définis par les positions des atomes {O,C,N} de chaque plan. Ces corps rigides +peuvent être superposés en minimisant la fonction suivante: +∑3 +m(q) = (D · xα − x ′ 2α) , (0.1) +α=1 +où {x } et {x ′α α} sont respectivement les positions atomiques de la structure de référence (les +atomes {O,C,N} dans le plan A) et celles de la structure cible (plan B). Le symbole D dénote +une matrice orthogonale qui décrit une rotation. Les deux ensembles des coordonnées sont +définis par rapport à un point de référence qui est la position de l’atome de carbone de +chaque plan {O,C,N}. En utilisant le fait qu’une matrice de rotation peut être exprimée par +les composantes d’un quaternion normalisé q ≡ {q ,q ,q ,q }, où q20 1 2 3 + q2 + q2 + q2 = 1 [4], + 0 1 2 3 + q20 + q21 − q22 − q2 3 +2(−q0q3 + q1q2) 2(q0q2 + q1q3)  + D(q) =  2(q q + q q ) q2 + q2 − q2 − q2 2(−q q + q q )  , (0.2)0 3 1 2 0 2 1 3 0 1 2 3 +2(−q q + q q 2 2 2 20 2 1 3) 2(q0q1 + q2q3) q0 + q3 − q1 − q2 +la fonction (6.1) peut être minimisée par rapport à ces quatre composantes. Comme il a +été montré dans d’autres études [50, 115, 116], la minimisation avec contraintes peut être +transformée dans un problème de valeurs propres d’une matrice M semi-definie positive +M ≡M({x , x ′α α}), +M · q = λq, (0.3) +où les valeurs propres λj = m(qj) sont les possibles erreurs dans la superposition des +deux plans peptidiques défini par (6.1). Le quaternion correspondant à la valeur propre la +plus petite est la solution pour une superposition optimale et ses composantes décrivent +l’orientatio ′n relative de {xα} par rapport à {xα}. La relation: +q ≡ q0  cos(φ/2)=  . (0.4) +qv sin(φ/2)n +nous montre que le quaternion correspondant à la valeur propre la plus petite définit aussi un +angle de rotation φ et un axe de rotation n, ce dernier étant aussi la direction du "mouvement +de vis" décrit dans le théorème de Chasles. La preuve de ce dernier théorème peut être trouvée +dans la référence [114]. La valeur propre la plus grande λmax décrit la "pire" superposition +xxx +possible entre les deux plans peptidiques et donne leur distance euclidienne maximale. Nous +avons utili√sé ce dernier fait pour définir une distance d’orientation unique par∑3 (x − x ′ )2 +∆ = α=1 +α α . (0.5) +λmax +Par définition 0 6 ∆ 6 1. +La caractérisation de la structure secondaire d’une protéine est réalisée dans cette méthode +avec les paramètres suivants: +1. La distance d’orientation entre deux plans consécutifs, défini par Eq. (6.5). +2. Le rayon de la surface cylindrique sur laquelle bouge l’atome de référence (atome C) +en réalisant le "mouvement de vis" entre deux plans peptidique comme décrit par le +théorème de C√hasles, +|t⊥| +ρ = 1+ cot2(φ/2). (0.6) +2 +Ici t⊥ est la composante perpendiculaire à l’axe de rotation n du vecteur t qui relie les +atomes C. +3. Le paramètre de "rectitude" σ. Pour chaque résidu i ce dernier est défini comme suit: +σ = µTi i · µi+1, (0.7) +où +R⊥i+1 −R +⊥ += iµi (0.8) +|R⊥ ⊥i+1 −Ri | +et R⊥i est le point de l’axe hélicoïdal le plus proche de l’atome C du plan peptidique i. +La "rectitude" donne des renseignements sur la courbure des éléments de la structure +secondaire. +0.3.4 Application de ScrewFit à des structures modèles +Nous présentons ici un exemple d’application simple de la méthode ScrewFit. Il s’agit de +structures-modèles différemment configurées et composées de 10 alanines et qui ont été +obtenues par le Image Library of Biological Macromolecules in Jena 2 (les valeurs obtenues +sont affichés dans le tableau 2). +Les résultats remarquables de cette application sont: +2 Institute-of-Molecular-Biotechnology-Jena:http://www.imb-jena.de/IMAGE.html +xxxi +Table 2: Paramètres hélicoïdaux de différentes structures. Ici ρ est la valeur de ρ obtenue en utilisant +Cα +la position des atomes Cα comme référence. Les paramètres τ, pitch et h sont illustrés de +manière approfondie dans la thèse. +Motive ρ [nm] ρ [nm] τ pitch h σ ∆ +Cα +α-helix (R) 0.171 0.227 3.62 0.556 + 1 0.582 +α-helix (L) 0.171 0.227 3.62 0.556 − 1 0.582 +3-10 helix 0.146 0.203 3.28 0.589 + 1 0.670 +π-helix 0.178 0.258 4.16 0.558 + 1 0.471 +β-strand 0.055 0.093 2.03 0.671 − 1 0.875 +extended 0.037 0.055 2.00 0.725 − 0.754 +1. les hélices-α lévogyre et dextrogyre ont exactement les mêmes valeurs, ce qui montre +l’efficacité mathématique de la méthode. +2. Chaque type d’hélice peut être distingué des autres même si, en général, les valeurs des +paramètres pour les hélices sont très similaires. +3. La méthode permet une distinction très nette entre hélices et brins-β. +0.4 résultats +Nous présentons ici les principaux résultats obtenus dans ce travail de thèse soit par le +moyen de simulations de dynamique moléculaire (MD) soit par les expériences de diffusion +quasi-élastique des neutrons (QENS). Ces résultats seront utilisés pour déterminer les effets +locaux et globaux des conditions environnementales sur les deux homologues du IF6. Le lien +entre ces deux types d’effets est assuré par la complémentarité des informations obtenues par +dynamique moléculaire et par diffusion des neutrons. +Les conditions d’environnement appliqués dans les deux cas sont affichées dans les Tableaux +4 et 3. +Le nombre et la variété des mesures expérimentales ont été largement limités par des +problèmes techniques qui seront discutés plus avant dans le texte. La comparaison entre +données QENS et MD a été quand même possible dans un nombre restreint de cas. Pour la +raison énoncée, les données affichées dans cette section sont issues des simulations MD sauf +xxxii +Table 3: Ensemble des configurations environnementales appliquées dans les simulation MD +aIF6 eIF6 eIF6-NoCTAIL +300K - 1bar 300K - 1bar 300K - 1bar +300K - 250bar 320K - 1bar 300K 500bar +300K - 500bar 350K - 1bar 350K - 1bar +350K - 1bar 350K - 500bar 350K - 500bar +350K - 250bar +350K - 500bar +Table 4: Ensemble des configurations environnementales appliquées dans les mesures QENS +aIF6 eIF6 aIF6-HTag +300K - 1bar 300K - 1bar 300K - 250bar +350K - 1bar 350K - 1bar 300K - 500bar +350K - 250bar +350K - 500bar +xxxiii +exceptions signalés. +0.4.1 Effets de la pression et de la température sur la structure des IF6 +Les principaux effets de la température et de la pression sur les deux homologues du IF6 ont +été caractérisés autant d’un point de vue global que local. +Dans le premier cas, nous avons observé les changements du volume moléculaire des +deux protéines ainsi que les changements de leurs rayons de gyration et de leurs surfaces +accessibles au solvant. Dans le deuxième cas, une caractérisation fine des changements de la +structure secondaire a été obtenue par l’étude des fluctuations des atomes de carbone α et +l’analyse effectuée avec la méthode ScrewFit. +Les principaux effets globaux trouvés sont ici résumés: +· Les changements du volume moléculaire et du rayon de gyration montrent que le aIF6 +est moins sensible au changements environnementaux que son homologue mesophile. +Figures 2 et 3 +· Le rayon de gyration et la surface accessible au solvant du aIF6 affichent, aux conditions +naturelles pour Methanococcus Jannaschii (350K -500bar), des valeurs très similaires à +celles du eIF6 dans des conditions normales. Ce résultat semble suggérer la présence d’ +"états correspondants" entre les conditions naturelles des deux homologues. +Les fluctuations des chaînes principales et les variations des paramètres ScrewFit montrent +les résultats suivants: +aIF6 +· A une haute température les régions autour du résidu 60 et comprises entre les résidus +120 et 130 subissent des distorsions indiquant des changements d’orientation des plans +peptidiques de la chaîne principale qui cependant n’entraînent pas de courbures de cette +dernière. Nous avons observé que ces changements ne se produisent pas aux hautes +pressions. +xxxiv +· La haute pression induit une courbure significative sur la structure principale du aIF6 dans +la région comprise entre les résidus 90 et 95. Cet effet engendre aussi une augmentation +des fluctuations atomiques dans la même région. +· La combinaison de haute température et haute pression modifie les configurations des +plans peptidiques autour du résidu 50 vers des orientations relatives plutôt hélicoïdales. +eIF6 +· Des importantes variations dans la région 220-245 sont engendrées par les fluctuations +du CTAIL. Comme on pouvait l’attendre, ces variations augmentent en fonction de la +température. +· Différentes variations dans la région 170-180 se produisent tant à haute température +qu’à haute pression mais elles disparaissent quand la pression et la température sont +appliquées de façon simultanée. +· La combinaison d’une haute pression (500bar) et d’une haute température (350K) produit +une courbure de la partie C-terminale de la longue hélice-α dans la région 35-45. +Certains des ces effets locaux sur la structure ont été ensuite reliés aux possibles effets +sur la fonction du IF6. En particulier, nous avons remarqué que la pression a des effets très +importants sur la configuration des sérines 174 et 175 dans le eIF6. Ces deux derniers acides +aminés ont un rôle essentiel dans la localisation du IF6 dans le noyau cellulaire parce que +leur phosphorylation permet le passage du IF6 entre noyau et cytoplasme. +La présence des états correspondants entre les deux protéines dans leurs conditions naturelles +est ultérieurement confirmée par l’étude du facteur de structure élastique incohérent (EISF, +voir texte de la thèse) qui donne accès aux fluctuations atomiques en fonction de l’échelle +de longueur explorée par les mouvements internes des protéines. La figure 4 montre les +fluctuations carrées moyennes en fonction du transfert de quantité de mouvement, q. +Pour mieux comprendre les effets de la présence du CTAIL dans le eIF6 et celle possible de +la H-Tag dans le aIF6, nous avons réalisé les mêmes études structurales sur eIF6-NoCTAIL et +sur aIF6-HTag. Les résultats les plus remarquables de ces études ont été que le eIF6-NoCTAIL +affiche des changements très similaires à ceux qui ont caractérisé le aIF6 et que l’aIF6-HTag +montre des propriétés similaire a celles du eIF6. Ces observations suggèrent que la présence +d’une "queue" additionnelle dans les deux structures des IF6 joue un rôle crucial dans la +xxxv +300K 1bar +45.5 +300K 500bar A) +350K 1bar +45 350K 500bar +44.5 +44 +43.5 +43 +42.5 +0 500 1000 1500 2000 +time [ps] +300K 1bar +45.5 +300K 500bar B) +350K 1bar +45 350K 500bar +44.5 +44 +43.5 +43 +42.5 +0 500 1000 1500 2000 +time [ps] +Figure 2: Variation du volume moléculaire en fonction de la pression et de la température. Panel A: +aIF6. Panel B: eIF6. +17 17300K 1bar +A) 300K 500bar B) +350K 1bar +16.9 16.9 +350K 500bar +16.8 16.8 +16.7 16.7 +16.6 16.6 +16.5 16.5 +300K 1bar +16.4 16.4 300K 500bar +350K 1bar +350K 500bar +16.3 16.3 +0 500 1000 1500 2000 0 500 1000 1500 2000 +time [ps] time [ps] +Figure 3: Variation du rayon de gyration en fonction de la pression et de la température. Panel A: aIF6. +Panel B: eIF6 (Seuls les résidus entre 1 et 224 ont été pris en compte). +xxxvi +Radius of gyration [A] +Volume [Å3] Volume [Å3] +Radius of gyration [Å] +eIF6(1-224) 300K 1bar +eIF6(1-224) 300K 500bar +0.008 eIF6(1-224) 350K 1bar +eIF6(1-224) 350K 500bar +aIF6 300K 1bar +aIF6 300K 500bar +0.006 aIF6 350K 1bar +aIF6 350K 500bar +0.004 +0.002 +0 20 40 60 80 100 +q [nm-1] +Figure 4: Comparaison des fluctuations atomiques du eIF6 et du aIF6. +détermination des propriétés structurales de chaque homologue. +0.4.2 Effets dynamiques de la pression et de la température +Afin de caractériser les effets dynamiques d’un environnement extrême sur les IF6, les donnés +issues des simulations MD et celles obtenues par mesures QENS ont été comparées. Les +quantités "naturelles" pour l’analyse des simulations MD sont celles reliées à des fonctions +dépendant du temps, tels que le déplacement carré moyen, ou bien aux fonctions des +corrélations comme la fonction intermédiaire de diffusion. Les mesures expérimentales sont +au contraire étudiées par l’analyse du facteur de structure dynamique qui est une quantité +reliée au transfert de la quantité de mouvement et aux variations d’énergie. La fonction +intermédiaire de diffusion et le facteur de structure dynamique d’une protéine peuvent être +bien représentés par le modèle de dynamique Brownienne fractionnaire (fOU, dans la suite) +[119, 20]. Ce modèle donne des temps de relaxation qui définissent la dynamique interne des +protéines en fonction d’une échelle de longueur. +xxxvii + [Å2] +Les résultats sur les effets dynamiques de la pression et de la température peuvent être +résumés comme suit: +Les temps de relaxation définis par le fOU affichent des valeurs très différentes dans les +deux protéines. En particulier, dans le cas du aIF6, ils sont systématiquement plus +rapides que ceux du eIF6 à toutes les échelles de longueur. +Les mêmes temps caractéristiques des deux protéines changent d’une façon différente en +fonction de la pression et de la température. En particulier ils augmentent en fonction +de la pression dans le cas du aIF6 et ils baissent dans le cas du eIF6. +Ces dernières observations identifient plutôt les caractères dynamiques de chaque homo- +logue du IF6 et de sa réponse aux changements des conditions environnementales. Cette +dernière réponse devient par contre évidente si l’on compare les temps de relaxation de +chaque homologue dans ses conditions "naturelles" avec ceux affichés dans des condition +défavorables. Les Figures 5 et 6 montrent que dans les deux homologues les conditions les +plus défavorables produisent des changements non homogènes dans le temps de relaxation et +que ces changements deviennent de plus en plus homogènes en se rapprochant des conditions +"naturelles". +1.6 +1.5 +1.4 +300K-500bar +350K-1bar +1.3 +350K-500bar +1.2 +4 6 8 10 12 14 16 18 +-1 +q [nm ] +Figure 5: Valeurs du paramètre τ issu du fit fOU de eIF6. +Ces résultats principalement issus des simulations MD ont été aussi confirmés par les +expériences de diffusion de neutrons. Ces dernières ont été toutefois limitées par les difficultés +techniques suivantes: +xxxviii +τ/τ300K-1bar +300K-1bar +1.5 300K-500bar +350K-1bar +1.4 +1.3 +1.2 +1.1 +1 +0.9 +4 6 8 10 12 14 16 18 +-1 +q [nm ] +Figure 6: Valeurs du paramètre τ issu du fit fOU de aIF6. +· Le eIF6 a montré une stabilité précaire dans les configurations expérimentales utilisée dans +ce travail +· L’évaluation de la concentration des échantillons en solution a été très difficile à cause de +l’absorption très limitée dans la gamme des UV-VIS tant du aIF6 que du eIF6. +Ces deux problèmes n’ont pas rendu possible une analyse plus fine des données expéri- +mentales. Celles-ci néanmoins ont pu être utilisées pour supporter les résultats obtenus par +dynamique moléculaire. +0.5 conclusions +Dans ce travail nous avons caractérisé la réponse des deux homologues du IF6 à différentes +conditions extrêmes. Ces réponses ont été caractérisées d’un point de vue autant structural +que dynamique. +L’étude structurale a montré que l’aIF6, bien que moins sensible aux changements de +température et de pression, assume dans ces conditions "naturelles" (350K -500bar) des +caractéristiques structurales très similaires à celle du eIF6 à température et pression ambiante. +Nous avons aussi distingués les effets globaux des effets locaux, qui sont très différents +dans les deux IF6. En outre, contrairement aux attentes, les effets des deux variables thermo- +dynamiques ne s’opposent pas les uns aux autres. +D’un point de vue dynamique, le modèle de dynamique Brownienne fractionnaire +nous a permis d’associer des temps caractéristiques à chaque protéine. Ces temps, qui +xxxix +τ/τ350K-500bar +dépendent de l’échelle de longueur considérée, affichent des valeurs différentes dans les +deux protéines dans des conditions environnementales diverses alors qu’ils changent +d’une façon similaire si les protéines sont dans des conditions défavorables. Ces résul- +tats nous ont permis d’identifier d’abord la présence des "états correspondants" des +fluctuations structurales de chaque homologue du IF6 dans ses conditions naturelles. +Deuxièmement ils ont rendu possible la distinction entre les propriétés dynamiques reliées à +la structure de chaque protéine et les propriétés caractérisant l’état naturel de chaque protéine. +xl +Part II +THES I S + +CONTENTS +i résumé substantiel xiii +0.1 Introduction xv +0.1.1 Organismes adaptés aux environnements extrêmes xv +0.1.2 L’environnement typique des fonds marins chauds xviii +0.1.3 Le facteur d’anti-association xx +0.2 Matériels et Méthodes xxi +0.2.1 Production des échantillons expérimentaux xxi +0.2.2 Expériences de diffusion des neutrons xxiv +0.2.3 Simulation de dynamique moléculaire xxv +0.3 Méthode de caractérisation de la structure secondaire des protéines xxviii +0.3.1 Efficient characterisation of protein secondary structure in terms of +screw motions xxviii +0.3.2 ScrewFit: a novel approach for continuum protein secondary structure +assessments xxix +0.3.3 L’algorithme ScrewFit xxix +0.3.4 Application de ScrewFit à des structures modèles xxxi +0.4 Résultats xxxii +0.4.1 Effets de la pression et de la température sur la structure des IF6 xxxiv +0.4.2 Effets dynamiques de la pression et de la température xxxvii +0.5 Conclusions xxxix +ii thesis 1 +1 General Introduction 7 +1.1 Effects of pressure and temperature on proteins 8 +1.2 Organisms adapted to extreme environments 16 +1.3 The warm deep-sea environment 18 +1.4 The anti-association factor 23 +1.5 The thesis project "at a glance". 27 +2 Material and Methods 29 +2.1 Molecular Dynamics 29 +3 +4 Contents +2.1.1 The basic principle 29 +2.2 Neutron Scattering 38 +2.2.1 Incoherent Scattering 41 +2.2.2 Spectrometers 44 +3 Experimental and Simulated Systems setup 47 +3.1 Sample production 47 +3.1.1 Protein expression and purification 47 +3.2 Neutron Scattering measurements setup 54 +3.2.1 Data analysis 58 +3.3 Molecular Dynamics setups 59 +3.3.1 System Setup 60 +3.3.2 eIF6 61 +4 Characterization of protein structure 69 +5 Efficient characterisation of protein secondary structure in terms of screw mo- +tions 71 +5.1 Introduction 72 +5.2 Method 73 +5.2.1 Quaternion superposition fits 73 +5.2.2 Orientational distance 75 +5.2.3 Chasles’ theorem 76 +5.3 Applications 77 +5.3.1 Screw motion description of protein main chains 77 +5.3.2 Model structures 78 +5.3.3 Proteins in different fold classes 80 +5.3.4 Lysozyme under hydrostatic pressure 82 +5.4 Conclusion 87 +5.5 Mathematical Background 89 +5.5.1 Quaternions 89 +5.5.2 Helix parameters in Chasles’ theorem 90 +5.6 Notes 92 +6 ScrewFit: a novel approach for continuum protein secondary structure assess- +ments 93 +6.1 Introduction 94 +6.2 Methods 96 +contents 5 +6.2.1 The ScrewFit algorithms 96 +6.2.2 Availability 99 +6.2.3 Databases 99 +6.3 Results and Discussion 100 +6.3.1 Evaluation of natural parameters 100 +6.3.2 Reliability and consistency of ScrewFit assignments 103 +6.3.3 Comparison with DSSPcont 107 +6.3.4 Application 109 +6.4 Conclusion 112 +6.5 Notes 113 +7 Results 115 +7.1 Effects of pressure and temperature change on IF6s structure 116 +7.1.1 Local effects 117 +7.1.2 Secondary structure changes 121 +7.1.3 Relation between local structural effects and IF6 function 124 +7.1.4 Comparison between ScrewFit profiles of eIF6 and eIF6-NoCTAIL 126 +7.1.5 Comparison between ScrewFit profiles of aIF6 and aIF6-HTag 127 +7.1.6 Elastic Incoherent Structure Factor 129 +7.2 Efffects of pressure and temperature on IF6s dynamics 134 +7.2.1 Dynamical models 134 +7.2.2 Fractional Brownian Dynamics 135 +7.2.3 Analysis of scattering functions obtained from MD simulations 138 +7.3 Comparison with QENS measurements 144 +7.3.1 Ambient pressure measurements 146 +7.3.2 High pressure measurements 150 +7.4 Discussion and Conclusion 151 +8 General conclusions and Perspectives 157 +iii appendix 161 +a Buffers used for protein expression and purification 163 +b Corrections to the Stokes’ law for sphere diffusion. 165 +bibliography 167 + +1 +GENERAL INTRODUCTION +The last century owes the majority of its advances in science and technology to the +investigation of the structure and dynamics of matter at the atomic and subatomic scale +which lead, among others, to a significantly better understanding of the physical and +chemical properties of solids and liquids. +Since the beginning of the century, the knowledge acquired about the inanimate matter lead +physicists to question how this insight could also be applied also to biological matter. To +this end, most of the principles of thermodynamics and classical mechanics were applied to +biological systems to gain new insights into their properties, but only the advent of quantum +theory and statistical mechanics finally allowed them to be investigated at the atomic scale. +These new theories, along with important developments in the techniques of atomic and +molecular spectroscopy lead researchers to revise and interpret from a molecular point of +view several results obtained in biology in the last century. 1 +Living matter presented to researchers a degree of heterogeneity and complexity that they +had never encountered before in physics and stimulated the birth of a new interdisciplinary +field of research which brought together physics, chemistry and biology and which revealed +itself as a source for a large number of key results with further applications in medicine and +biotechnology. +The work presented in this thesis is based on the enormous progress made in the field of +biological physics, in particular with respect to the development of computer simulation +methods, made possible by the rapid improvements in computers, and the application of +spectroscopic techniques to biological samples. +As will be explained more deeply, later in the text, these two techniques can be combined in a +unified approach in which computer simulations helps to better characterize the experimental +results at the atomic scale. +1 As an example, it is worth to cite the famous prediction by E.Schroedinger who inferred from the basic quantum +mechanical principles, that the structure of DNA had to be that of an aperiodic lattice. His prediction was then +confirmed years later by the crystallographic resolution of the DNA structure made by Watson and Crick. +7 +8 general introduction +In the following, a general introduction to this thesis work will be given assuming a basic +knowledge of protein structure elements the explanation of which would be beyond of the +scope of this thesis. This subject is however treated in detail in a number of excellent textbooks +[42, 187] +1.1 effects of pressure and temperature on proteins +In the very first efforts to investigate living matter, physicists focused on the application of +basic principles of mechanics and thermodynamics to interpret the complexity of biological +macromolecules [30]. +As this thesis deals essentially with the effects of temperature and pressure on proteins, the +following sections will concentrate on this subject, giving a short presentation of the known +effects of these two thermodynamic variables on the structure and dynamics of proteins. +Pioneering work on the impact of pressure on proteins was performed by Regnard in 1891 +[160] and by Bridgman in 1914 [17]. The former showed that pressure below 1kbar affects +reversibly the catalytic functions in bacteria, whereas the second proved that pressures +above 8kbar lead to a coagulation of the protein ovalbumin. Moreover, Bridgman also noted +that high temperature reduced the effects of high pressure on albumin, i.e. reduced the +coagulation. +These studies yielded the important result that two types of pressure effects have to be +distinguished: irreversible and reversible effects depending on the magnitude of the applied +pressure [75]. The same observations have been made concerning temperature induced +changes [42, 189]. +When irreversible effects produced by high pressure (as well as by high temperature) are +present, a large change in the spatial conformation affects proteins which loose their native +structure. In these new denaturated states, proteins cannot perform their functions and +tend to have unusual interactions with other proteins leading to large aggregates. Partially +denaturated states (also known as molten globules) can be included among the reversible +effects because when pressure or temperature are brought back to their original values +proteins fold back in their native configuration [42]. +Several more recent works [143, 219, 169, 99], showed also that : i) proteins do not all have +the same characteristic threshold for denaturing pressures: it depends of their size and shape; +ii) denaturing caused by high temperature is often very different from denaturing caused by +1.1 effects of pressure and temperature on proteins 9 +freezing or by high pressure. +In summary, these results, which will be discussed in the following, show that high +temperature and high pressure have similar effects on protein stability but they appear to +be competitive when applied together. Moreover, the structural changes of proteins due to +external pressure are much less homogenous than those induced by temperature changes. +le chatelier’s principle A useful theoretical framework for the comprehension of +how biomolecules respond to changes in thermodynamic conditions is given by the criteria +for the stability of thermodynamic systems and by Le Chatelier’s principle[126]. The latter +states that at equilibrium, a system tends to minimize the effect of any external factor by +which it is perturbed. As briefly shown in the following, Le Chatelier’s principle gives the +physical interpretation of the stability criteria for the thermodynamical potentials which +describe the macroscopic states of the system. Indeed these criteria reflect those demanded +for the intrinsic stability of the thermodynamic system itself. For an equilibrium process +connecting two states A and B, the general expression for the variation of Gibbs free energy, +G(T,P,N) reads as follows: +∑ +∆G = V∆P− S∆T + µi ∆Ni (1.1) +i +where ∆Ni, ∆P and ∆T are, respectively, the variation in number of particles of type i and +the change in pressure and temperature. In the case of the Gibbs free energy, the stability +criteria lead to the condition that the function G(T,P,N) be concave with respect to variables T +and P and convex with respect to Ni [21]. From a mathematical point of view, this means that +the second order derivatives of the function G(T,P,N) with respect to T and P must be negative. +These conditions can be rewritten with respect to the natural thermodynamic variables by +means of the Maxwell relations: +( ) ( ) +∂2G ∂V +( ) =∂P2 T (∂P) 6 0 (1.2)T +∂2G ∂S += − 6 0 (1.3) +∂T2 P ∂T P +As a consequence, an increase in pressure on a system favors a reduction of its conjugated +extensive variable, the volume. Hence, in general, pressure favors all processes that are +10 general introduction +accompained by negative volume changes. +In the case of proteins, which usually have compact and tightly packed structures, three +different types of volumes can be distinguished: the volume of atoms, the void volume due to +imperfect packing of atoms which leave small cavities at the interior of molecular structures +and the volume variations which result from the degree of solvation of peptide bonds and +amino acids residues. All these components influence both the atomic fluctuations and the +weak intramolecular interactions (i.e. those not involving covalent bonds) which govern the +transition between its various conformations. +Besides giving a general framework for the understanding of the effects of pressure on +proteins, the Le Chatelier principle also introduces a first explanation of the antagonistic +relation between temperature and pressure. The principle states in fact that perturbations +on a system directly induce processes that attenuate the perturbations themselves but its +response also induces indirectly other processes that reduce the initial perturbation. A +phenomenological demonstration of this extension of principle, which is usually called +LeChatelier-Braun principle, can be found in references [21, 161]. +From a molecular point of view, the antagonism between the two variables can be inter- +preted by the microscopic ordering principle, which states that an increase in pressure at +constant temperature leads to a decrease in the entropy of the system, which corresponds to +an increase in the ordering of molecules in the system itself. +This is a general property of molecular systems but it has also a strict sense for protein stability +as proven by Brandts et al. [16] and Hawley [72] who showed that the pressure-temperature +phase diagram which determines the transition between functional and denaturated states +of proteins has elliptic boundaries, meaning that there exist several combinations of the P,T +variables which are compatible with the stability criteria. This peculiar behavior has been +ascribed to the exposure of hydrophobic groups to the solvent when the protein folds. It is +worth to note that this behavior is found neither in nucleic acids [73] nor in lipids [47]. The +elliptic phase boundaries, which are also found in liquid crystals, seems to be produced by a +fine balance between aromatic and aliphatic parts of molecules. +effects of pressure on intermolecular interactions The stability of +biomolecules results from a cooperation of interactions involving its components and the +external environment [93]. In the case of proteins, once the primary structure is formed +1.1 effects of pressure and temperature on proteins 11 +by the peptide bonds, the interactions that play a significant role in this cooperation are +essentially weak [94]. +The electronic structure of atoms and the covalent bonds are directly modified by +pressure only for values greater than 30kbar [51]and 15kbar [67, 144], respectively, but their +compression is negligible[62]. Their breaking is responsible for big changes in free volume +and leads to a totally irreversible protein denaturation. The formation of covalent bonds has a +∆V = −10ml.mol−1, whereas ∆V values for the changes in bonds or bond angle changes are +nearly zero [200]. Besides the peptide bonds that form the primary structure of proteins, the +only type of covalent bond which plays a significant role in protein stability is the interchain +disulphide bonds formed by non-contiguous cysteine residues [43]. +In contrast to covalent bonds, weak non-bonding interactions give a large contribution to +the observed ∆V due to pressure changes. +■♦♥✐❝ ✐♥t❡r❛❝t✐♦♥s Ion pairs in proteins cause attractive, short-range interactions that occur +between negatively and positively-charged amino-acid side chains over a distance of 4 Å[42]. +The role of ion pairs in proteins is to stabilize the tertiary [76] and quaternary structure. +For example, interprotein salt bridges provide a mechanism for solvent exclusion from the +interfacial domain of the cytochrome b5-cytochrome c complex, in addition to maintaining +the stability and specificity of the complex formed [165]. +When an ion is formed in solution, the nearby water dipoles are compressed by the +Coulombic field of the ion; this phenomenon, which is accompained by a volume decrease, is +usually called electrostriction. Because of this volume contraction, pressure is expected to favor +the disruption of ion-pair but Michels et al. [139] have showed that this should be eliminated +by high temperature due to the disruption of the highly ordered structure of electrostricted +water. +The solvation of ions in water produces a ∆V = −10ml ·mol−1 whereas the dissociation of +a neutral molecule into ions induces a volume contraction of about −20ml ·mol−1. These +facts confirm that electrostriction is favored by pressure but does not give insights into the +effect on protein stability. Indeed, this phenomenon can have opposite results depending +on the structural effects it produces locally: it can induce denaturation like in the case of +chymotrypsin where pressure produces the dissociation of a salt-bridge in the active site +region bringing the protein reversibly to an inactive state[77]; on the other had, it can also +engender an increase in protein stability if there are weak intersubunit ion-pair interactions +12 general introduction +not exposed to solvent, which may be strengthened by pressure. +❍②❞r♦❣❡♥ ❜♦♥❞s Studies on simple model molecules showed that hydrogen bonds are +stabilized by high pressures up to 4kbar [105, 200]. This results from the smaller inter-atomic +distances in the hydrogen-bonded atoms. The stabilizing effect of pressure on hydrogen +bonding in proteins was first detected by the pressure dependence of the infrared spectra of +the α-helix in myoglobin[127] and from a comparison of the effect on the intermolecular +interactions in hydrogen-bonded versus non-hydrogen-bonded amides[65]. In particular +hydrogen bonds play a fundamental role in the formation of the secondary structure due to +their role in creating the α-helix and β-strand motifs. +It is worth to note also that pressure may promote intermolecular hydrogen bonds at the +expense of intramolecular hydrogen bonds, causing increased conformational fluctuations +[38]. However, a very small if not negligible ∆V value is observed for processes in which +there is an exchange between the existing hydrogen bonds [200, 24]. +❍②❞r♦♣❤♦❜✐❝ ✐♥t❡r❛❝t✐♦♥s In general hydrophobic interactions describe the tendencies +of hydrocarbons to form aggregates in the presence of aqueous media. In proteins, they +direct non-polar side chains to the interior of proteins and are a major driving force for +proper folding [110]. In 1959, Kauzmann [109] suggested that the volume changes for the +association of hydrophobic molecules in water should be positive. His hypothesis was based +on the observations made on the large entropic effects of the transfer of hydrocarbons from a +nonpolar solvent to water. Weber et al [207], on the other hand, showed that the association +of aromatic molecules is enhanced by pressure and later Van Eldik et al.[200] confirmed +that interactions that pack aromatic rings parallel to each other engender negative volume +changes. These results give account of two different hydrophobic effects, one related to the +solubility of apolar molecules into water and another one which concerns the solvent-induced +interaction between apolar species. +The former class of hydrophobic effects was initially considered as a good model (called +oil-drop model)[7] for protein folding as it was confirmed by works on thermal denaturation +but could not be confirmed by the pressure effects on protein unfolding because the volume +change upon unfolding is positive at low pressures but negative at pressures of about 1-2 +kbar. The transfer of hydrocarbons into water shows exactly the opposite behavior, with ∆V +being negative at low pressures and positive at high pressures[110]. +1.1 effects of pressure and temperature on proteins 13 +The major role in pressure effects in protein denaturation is commonly attributed to the +hydration of hydrophobic cores. Indeed, the presence of solvent around the proteins gives a +significant importance to the cavities created by the imperfect packing of protein structure. +Solvents, and in particular water, can often enter these void volume areas and come into +contact with inner regions, destabilizing the hydrophilic/hydrophobic equilibrium which +maintained the protein’s stability. Due to its higher compressibility compared to proteins, +water under pressure can also assume local ordering that can easily cause an important +increase in the density of hydrogen bond acceptors/donors, which in turn enhance the +hydrophilic properties of those amino acids that are able to produce hydrogen bonds [213]. +Although several works confirmed this essential role of hydrophobic interactions, discrepan- +cies in experimental [74, 139, 138] and theoretical [87] results on how their role in protein +folding/unfolding is accomplished, have not yet allowed the acceptance of the ’oil-drop’ +model as a common framework for the interpretation of the different physico-chemical +contributions to the related volume variations [168]. +It is worth to note here the work by Hummer et al. [87] which proposed a different role of +hydrophobic interactions in temperature and pressure-induced denaturations. They suggested +that pressure denaturation corresponds to the infiltration of water into the protein, whereas +heat denaturation corresponds to the transfer of nonpolar side-chain groups into water. As a +consequence, pressure denaturation processes lead to (partially or totally) unfolded protein +structures with reduced compactness which are, however, considerably more ordered than +those in heat-denatured proteins, as probed by NMR experiments of hydrogen exchange +[218]. +In the context of hydrophobic interactions, it is well established that a significant contribution +is made by the van der Waals (VDW) forces [153, 187, 42]. The effects of pressure on VDW +forces present the same contradictory results as hydrophobic interactions in general, which +does not permit a simple framework to be defined for their physical interpretation. From a +general point of view, VDW forces are likely to be enhanced by pressure since they tend to +maximize the packing density of proteins and thus reduce the volume. Indeed, packing density +is maximized by VDW interactions because the dipole moment attractions they produce +improve the packing of the hydrophobic core [67, 95]. On the other hand, VDW forces can +also contribute to protein destabilization under pressure. In particular for oligomeric proteins, +pressure below 3 kbar promotes the replacement of some weak non-covalent interactions +between amino acid residues with amino acid-water interactions causing changes in peptide +14 general introduction +chain conformations and resulting in dissociation [180]. These protein-water interactions are +promoted by pressure because they produce stronger and shorter bonds that decrease the +overall volume [144, 180]. +❈♦♠♣r❡ss✐❜✐❧✐t② The atomic density in proteins is similar to that in solids and can +even exceed the latter locally [87] which makes proteins very insensitive to compression. +Most of the data available on protein compressibility are obtained by sound velocimetry +measurements and the volume change usually observed is around 1% of the protein’s total +volume[60]. Such a small volumetric variation is induced only by the weak interactions we +presented earlier in this section and does not receive any contribution from covalent bonds +in the protein backbone [206]. The major effect is due to the hydrophobic interactions: the +higher the hydrophobic content is in a protein, the more the latter is compressible [180]. +A significant role in compressibility is played by the effects of pressure on the hydration. In +particular, as stated in the previous paragraph, the infiltration of water molecules into void +cavities produces a significant change in the local atomic fluctuations which results in the +destabilization of the hydrophilic/hydrophobic equilibrium of the protein. In general the +cavities filled by the solvent can act as two-ways-valves or one-way-valves, depending on the +local molecular environment in the protein [133], i.e. they can form volumes that solvent +molecules can continuously enter or leave or they can instead incorporate water molecules, +separating them from the bulk solvent. These two type of behavior engender differences in +compressibility of cavities and in the whole protein structure [39]. +In contrast to temperature, pressure does not seem to have a uniform effect all over the +protein [61]. A molecular simulation study by Paci and Marchi [148] proved that short +distances are rather less compressed than longer one. This was also confirmed by x-ray +experiments performed by Kundrot et al. [121] which showed that side-chains in lysozyme +have a larger response to pressure than backbone. +The physical origin of this heterogeneity in structural response to pressure has been explained +by a phenomenological model of non-covalent interactions where each pairwise interaction +in the protein’s native structure was replaced by an effective harmonic force with a distance +dependent force constant. Interestingly the short-ranged interactions were characterized by +effective force constants larger than long-ranged ones [82, 80], meaning that the former are +stronger and less compressible than the latter. +1.1 effects of pressure and temperature on proteins 15 +pressure impact on protein structure levels To summarize, we can conclude +from the previous section that a protein’s reaction to pressure increase is often due to +a complex balancing of opposite effects which tend to combine differently at different +pressures. The effects on the interactions that determine the internal protein structure, have +consequences on all the levels of structural organization (i.e. on secondary, tertiary and +quaternary structures). In the following, we report schematically these repercussions on each +level with reference to the experimental techniques which were used to detect them. +◗✉❛t❡r♥❛r② str✉❝t✉r❡ is mainly maintained by hydrophobic interactions and for this rea- +son it is the most sensitive to pressure. As mentioned in the previous section, moderate +pressure below 1.5kbar favours dissociation of oligomeric proteins [180] which results in +very large and negative volume changes. Sometimes pressure-induced dissociation leads +to formation of individual non-denaturated subunits, as in the case of tryptophane syn- +thethase at 1.5kbar[149], but more frequently it is followed by subsequent conformational +changes in individual subunits[150]. When quaternary structure is maintained by either +pressure-insensitive interactions like hydrogen-bonds or by pressure-enhanced interactions +like aromatic clustering (due to hydrophobic interaction), dissociation can appear also at +pressures higher than 3kbar [132]. +Pressure effects on quaternary structure are usually investigated by electrophoresis, ultracen- +trifugation [152], fluorescence spectroscopy[180] and NMR spectroscopy[100]. +❚❡rt✐❛r② str✉❝t✉r❡ can be irreversibly changed by pressures above 2kbar. However, some- +times reversible denaturation can be found also at pressure between 4 and 8kbar[171]. This +shows that the volume changes are not completely dominated by hydrophobic interactions +but that other type of weak interactions can also play an important role. An important feature +of pressure denaturation is the formation of a molten globule in which proteins, even though +retaining their intact secondary structure, change their tertiary structure adopting conforma- +tions with hydrodynamic radii 10-20% higher than that of the native state[154]. For the studies +of the tertiary structure changes induced by pressure, the more frequently used methods are +NMR spectroscopy, X-ray, UV-visible and fluorescence spectroscopy[121, 180, 100]. +❙❡❝♦♥❞❛r② str✉❝t✉r❡ undergoes significant changes at very high pressure, above 3-7kbar. +These changes, in contrast to those that affect tertiary structure result always in non-reversible +protein denaturation. Indeed, such pressures induce a high compression of protein +structure resulting in the rupture of hydrogen bonds, which play a major role in the +16 general introduction +formation of secondary elements like α-helices and β-sheets [211]. As regards the secondary +structure, one of the most suitable methods to detect changes is Fourier transform infrared +(FTIR)spectroscopy which gives insights into the protein vibrational spectra where the band +corresponding to the vibration of C=O bond of the amide group is easily detectable. The latter +is very sensitive to the conformation of the polypeptide. Another technique frequently used +to detect changes in secondary structure is circular dichroism (CD) spectroscopy which can +rapidly give the percentage of α-helices, β-strands and random-coil in a protein solution [196]. +The fact that every pressure range affects roughly only one structure level makes this +physical variable a rather better tool to investigate protein structure stability than any other +perturbation like temperature or pH changes. +1.2 organisms adapted to extreme environments +Organisms are integrated entities, not collections of discrete objects 2 +While in the previous section the general effects of pressure and temperature on +proteins were presented, here I want to focus on the particular aspect of the chemical and +physical properties of proteins from organisms which live under extreme conditions. More +precisely, a special case of extreme environment, the warm deep-sea, in which both high +pressure and high temperature can be found, will be presented. Furthermore, inspired +by the phrase that opens this section, I want to point out the fact that the study of +protein molecular adaptation to extreme environments could be highly improved by +the knowledge of the framework of the whole-cell adaptation. Although this section is +intended to be an introduction to the subject of the biology of extreme environments, it is +inevitably incomplete and mainly reflects the personal view and interests of the author. Many +more aspects are described in a number of excellent reviews [85, 93, 182, 158, 107, 151, 191, 58]. +The biosphere, i.e. the surface of the earth known to host life, ranges from the abyssal +region of the deep sea to the heights of the Himalaya and shows a wide range of example of +adaptation to ’extreme’ environments. From a quantitative point of view, physical limits to +life today known are the following3[92]: +2 From The spandrels of San Marco and the Panglossian paradigm: a critic to the adaptationist programme, S.J. Gould and +R.C. Lewontin, Proc. Royal Soc. London B, 205, 581-598, (1979). +3 As a reference: the critical point of water is at 374◦C and 2.2kbar +1.2 organisms adapted to extreme environments 17 +• −40◦C < T < 115◦C +• P < 1.2kbar +• ∼ 1 < pH < 11 +In the previous section we have discussed the effects of pressure on proteins structure, +here we want to recall some critical effects of temperature on biological chemistry: i) at 100 +◦C thermal degradation outruns biosynthesis[92, 95]; ii) at 110-140 ◦C hydrophobic hydration +effects in protein vanish [92]; iii) and at 150 ◦C amino acids start to fall apart [141, 140]. +These are obviously the extreme boundaries that do not permit life developing but their +knowledge is useful to understand the increasing effects that organisms have to face when +approaching these limits. From an evolutionary point of view, this means that organisms +should have to find a way to compensate these effects.Hence, organisms which became +extremophiles [167] found some mechanisms to protect themselves against the chemical and +physical damages induced by the environment. +Little is known on how this is accomplished[90, 49] but presumably two parallel strategies +are followed: the first one is the compensation of degrading processes made through a tuning +of the synthesis rate of biomolecules that would be compatible with the average lifetime +of the molecules [92]; the second one is the incorporation of point mutations in protein +sequences in order to increase their structural stability, resulting in a longer lifetime and thus +a longer time of functioning[93]. +Nevertheless, this strategy adopted in molecular adaptation does not seem to engender +significant differences between the global distribution of amino acids in mesophile proteins, +i.e. obtained from ’normal’ organisms, as compared to the extremophile ones. Deckert et +al. showed, for example, that the distribution of amino acids contents in mesophilic and +thermophilic proteomes, even though not identical, do not present any significant differences +that could lead to a simple method to distinguish them [48]. +As a consequence, adaptation of biomolecules seems to be related exclusively to dif- +ferent local patterns in amino acids sequences resulting in a reorganization of the weak +non-convalent interactions that govern protein stability and flexibility[147, 94]. The new deal +for the stability of extremophile proteins is thus played by the re-organization of mechanisms +that are, as we have seen in the previous paragraphs, sensitive to environmental changes; +they are for example: increased number of hydrogen bonds, salt bridges, improved core +18 general introduction +packing, shorter and/or tighter surface loops, enhanced secondary structure propensities, or +oligomerization[134, 135, 136]. +From a physical point of view, a first quantitative experimental measure of protein stability +can be made by means of differences in the Gibbs free energy, ∆G(T ,P,N), between the more +stable global minimum and its nearest minima. Jaenicke and Böhm [96] showed that mesophile +and extremophile proteins share ∆G of the same order of magnitudes (∼ 50kJmol−1) even +though extremophiles may show a variability in the range 10− 100kJmol−1. The difference +between the typical values for mesophilic proteins and the variation found in extremophilic +ones correspond to the energy of a few non-covalent interactions and confirm the significant +role the latter play in molecular adaptation[157, 147, 151, 158]. +The central issue in the adaptation of biomolecules remains, however, the conservation +of biological functionality which means a well-balanced compromise between stability +and flexibility[197, 92]. Hence, the process of adaptation has to translate the properties +of mesophilic proteins toward the relative extreme conditions which means towards physio- +logical conditions that make molecular properties of extremophilic counterparts very similar +[93]. This translation is perfomed by a re-organization of non-covalent interactions. Several +experiments have provided evidence for this process [217] and showed that dynamical prop- +erties of some mesophilic enzymes at temperature of 25◦C are very similar to those of their +extremophilic homologues at 70◦C. Analogous results were obtained on rubredoxin by a +molecular dynamics study [69]. +In this context Jaenicke [93] proposed that molecular adaptation to extreme environments +should tend to maintain corresponding states between respective native environments, which +take into account overall topology, flexibility and hydration of proteins. Even though this idea +found confirmation by experiments in the past, recent works seem to not entirely confirm it +[158]. +1.3 the warm deep-sea environment +In contrast to common opinion, terrestrial environments, where the ambient pressure is 1bar, +occupy only the 1% of the total volume of the biosphere. A large fraction of the earth’s surface +(70%) is covered by oceans which have an average depth of 3800 meters and thus an average +ambient pressure of 380 bar4. More than 60% of the marine component of the biosphere is +4 Hydrostatic pressure increases at a rate of 10.5kPa per meter depth, compared with 22.6kPa per meter for +lithostatic pressure. +1.3 the warm deep-sea environment 19 +below 1000m 5. Life below this depth, which is usually defined as the upper boundary of +the "deep sea", has to face several unfavourable conditions such as high pressure (from 1 to +1.1kbar) or temperature (from 1 to 110◦C) 6 which have strong impact to life mechanisms. +After the pioneering studies of Certes in 1884 [30, 29] which helped to establish the +existence of microorganisms in deep sea sediments, the first systematic studies of ZoBell and +Johnson[220], gave the birth in 1949 to a new research line which helped, during the last +century, to better understand the survival strategies employed by organisms to face extreme +conditions. +It allowed for example to elucidate the different adaptation to pressure in several groups +of microorganisms which can be divided into two distinct groups: barophiles (or piezophiles) +which are micro-organisms that possess optimal growth rates at pressures above atmospheric +pressure, whereas barotolerant (or piezotolerant) microorganisms are capable of growth at +high pressure, as well as at atmospheric pressure, but can be distinguished from piezophiles +because they do not have optimal growth rates at pressures above one atmosphere. +Both groups of microorganisms can also be distinguished from piezosensitive ones, whose +growth is sensitive to elevated pressure, because they can grow at 50 MPa at a rate that +is above 30% of their growth rate at atmospheric pressure [107, 108]. Moreover, from a +molecular point of view, barotolerant organisms differentiate themselves from normal +piezosentive ones by the production of some "pressure-shock" proteins induced as reponse to +high pressure environment [97]. These proteins have some equivalents in the "heat-shock" +proteins found in organisms which undergo thermal stress [67, 174] but their mechanism is +far from being completely understood. +In late 70s, the first colonies of "deep-sea" organisms were found also near the hydrothermal +vents[8]. The latter are warm currents which form where freshly extruded lava contracts +upon cooling and allows seawater to penetrate in the newly formed crust of basaltic rocks. +Seawater is then expulsed, highly enriched in heavy metals, creating hot vents which +significantly change the temperature in the nearby area [98]. +Obviously the life of organisms near hydrothermal vents became very rapidly the most +intriguing subject in the deep-sea biology and de facto most of the barophilic organisms +known today are also thermophilic which means that they have been proven to also have +greater growth rates at high temperatures (typically from 50 to 90◦C) than at usual deep-sea +5 The greatest depth in oceans, in the Mariana Trench is near 11000 meters whereas the deepest floor found in +freshwaters is at 1632 meters in the Lake Baikal +6 From a biochemical point of view it is worth to note for exemple that both light and photosynthesis are available +only until 300 meters of depth +20 general introduction +temperatures ( around 2◦C) [1]. +This environment, usually called the warm deep-sea, introduced several interesting ques- +tions from a biological and evolutionary point of view which demanded also new explanation +from biochemistry and physics. +pathways of adaptation to warm deep-sea environments Before focusing on +some aspects of the molecular adaptation of proteins to this environment, here some well +known facts about the whole-cell adaptation are reported schematically, for they play a +fundamental role in defining the general framework in which all molecular results should be +interpreted. The main features of biological adaptation to high hydrostatic pressure are[182]: +Adaptation to pressure allows deep-living species to thrive under high pressure but it +can also reduce their ability to live at moderate depths. This means that deep-living +species are usually barophilic and not barotolerants[179]. +Common patterns of adaptation appear in widely different types of deep-sea +organisms[179]. +Most of the physiological and biochemical processes which are in general found to +be pressure-sensitive in normal organisms, are rather stable under high pressure in +deep-living ones and exhibit, at in situ temperatures and pressures, values similar to +those found in terrestrail or shallow-living organisms at 1bar pressure[41, 44]. +Species living in deep sea hydrothermal vents show that adaptation to both temperature +and pressure are essential for cellular growth and physiological function. This means +that adaptation to high pressure does not pre-adapt organisms from cold deep sea to the +environment typical of the hydrothermal vents[182, 45]. +While the first three points seem to confirm the idea of the existence of corresponding states +between mesophilic and extremophilic organisms, the last point reveals the fundamental +interplay of pressure and temperature in warm deep-sea environments. This means, however, +that evolution has to cope with complex superpositions of parameters which are difficult to +separate and renders impossible the definition of strategies of molecular adaptation. +1.3 the warm deep-sea environment 21 +In an extremely simplified view, the complex mechanism which governs the life of a cell +can be schematically divided in two parts: protein synthesis, which furnishes all the "tools" +(the proteins) necessary for the cell machinery to work; and cellular metabolism, which +includes all the process that constitute the cellular life itself. +Following this scheme, we present the principal properties of protein adaptation to a warm +deep-sea environment, focusing on proteins that participate in the cellular metabolism and +those which have a role in other protein synthesis. +Enzymes, by their role as catalysts and regulators of metabolism, are the mediators by +which living systems function and reproduce. Somero et al [183] proposed that the successful +adaptation of an organism entering the deep sea would require the maintenance of the +same balance of enzyme synthesis, catalytic activity, and regulation as its surface-living +counterparts. Indeed, from several studies of enzymatic functions of deep-living organisms, a +few convergent common properties were found [130, 98]: i) the preservation of an enzyme’s +capacity to bind substrates under deep-sea conditions is essential in adapting metabolism +to that environment; ii) structural changes induced at pressures as low as 50-100 bar may +modify enzyme function sufficiently to induce evolutional selection for pressure insensitivity; +and finally iii) the capacity of an enzyme to function independently of pressure is acquired at +the cost of a reduction in catalytic efficiency. +Furthermore, in the context of the combined adaptation to temperature and pressure, it is +worth noting that for several hydrogenase enzymes from widely different warm deep-sea +organisms, pressure was found to significantly increase their thermal stability [45, 188]. This +type of enzyme undergoes large conformational change and hydration during its activity and +this makes them particularly well suited for investigating the effects of pressure. +In general for deep-sea organisms from the hydrothermal vents, the stabilization of catalytic +proteins was often found as the result of some point mutations in primary sequences +whose outcome could either be the increase of the size of the hydrophobic core and +its compactness (essentially substitutions with hydrophobic amino acids with larger +side-chains), the augmentation of hydrogen bonds (substituiting lysine with arginines ) or +the reduction/deletion of amino acids with side-chains sensitive to high temperatures ( +asparagines, glutamines, cysteines and tryptophane) [142]. +Protein synthesis is ideally divided into two steps: transcription, in which the genetic code +is copied from DNA to a RNA messenger (mRNA); and translation where peptides are bound +22 general introduction +together with the help of ribosomes and where genetic code in mRNA is decoded into amino +acids sequences. Both process are found to be highly sensitive to pressure [124]. +Early studies investigating the effects of pressure on E. coli revealed that an essentially +complete cessation of protein synthesis occurred at growth-inhibiting pressures of 680 atm +[67]. Subsequent comparison of protein synthesis of E. coli and known barotolerant organisms +permitted the barotolerance properties to be associated to the activity of ribosome [124] and +in particular to its 30S subunit [125]. +Indeed, ribosomes are made of two subunits (a smaller and a larger one) which are capable +of associating and dissociating. As we will discuss later in the text, this phenomenon is +important because the initiation of protein synthesis requires free ribosomal subunits in order +to allow the formation of a complex containing the mRNA anchored to the small subunit +before the joining of the large subunit. The ribosome’s subunit association is known to be a +rate-limiting process in the protein synthesis [162] and was found to be inhibited at elevated +hydrostatic pressures in mesophilic organisms [185]. +This effect was previously discussed as a possible reason for the inhibition of protein synthesis +and, hence, of cell growth by hydrostatic pressure [91] but later more sophisticated in vitro +studies showed that ribosomal complexes retain their "associated" state over the whole range +of biologically relevant pressures [68]. Other studies on ribosomes from mesophilic organisms +showed that association can be regulated also by temperature which usually enhances the +association equilibrium towards the associated species[83, 184]. Interestingly, these results +show that under estimated physiological conditions in several eukaryotes, ribosomes are +present almost exclusively in their associated form. The cell must therefore possess some +mechanisms for maintaining a pool of free ribosomal subunits. These mechanisms have to +account for protein synthesis inhibition under extreme conditions. Unfortunately, very little +is known about the differences between the protein synthesis machinery of extremophiles +and mesophiles. +methanococcus jannaschii This thesis will focus on a protein produced by an +archaeon7 microbe living near the hydrothermal vents, Methanococcus Jannaschii. This +organism, discovered in 1963 as a "methane-producer" [102], usually lives at temperatures +ranging from 48 to 94 ◦C with an optimum temperature at 85◦C and at pressures of more +than 200 bar (in situ depth 2600 meters). +7 The archaea are known as a primitive form of life significantly different from both prokaryots and eukaryotes. +For this reason is often referred to as the third domain of life. +1.4 the anti-association factor 23 +M Jannaschii’s genome was the first archaeon genome to be completely sequenced [18] +and revealed the complex evolutionary relationships between archaea and eukaryotes and +bacteria: only less than an half of the genes found in its genome could be matched to those +of other organisms. In the context of this thesis work, from a molecular biology point of +view, the most interesting feature of this organism is that while sharing the same protein +biosynthesis machinery (both transcription and translation) as eukaryotes, it does also have +genes homologous to both eukaryotes and bacteria for the initiation part of the translation +process. The latter is a fundamental and rate-limiting part of the translation and will be +discussed more deeply in the next section. +It has been shown that M Jannaschii’s metabolism and growth at high temperatures are +enhanced by pressure up to 750 bar whereas the upper limit for growth is 90◦C either +under low or high pressure [102]. These results suggested that M.Jannaschii is effectively a +barophilic organism and not just barotolerant. The finding seemed to be confirmed by studies +on enzymatic reaction: it was shown that application of 500 bar increased the thermal half-life +of hydrogenase from M. jannaschii 4.8-fold at 90 ◦C ◦C [74] and increased the half-life of a +protease from the same organism 2.7-fold at 125 ◦C [138]. Nevertheless, recent works showed +that pressure inhibits the 20S proteasome function from M Jannaschii [55], suggesting that in +some cases lower protein activity at the in situ pressure could be a regulatory mechanism +that confers some advantage to the whole cell. Hence, a more complex behaviour of the cell +response to high pressure and high temperature should be envisaged. +1.4 the anti-association factor +In the following we want to give a short introduction to the protein studied in this thesis, +which is called the Anti-Association Factor[170, 199]. A complete description of the molecular +biology background which is necessary to introduce the function of this protein, would +be largely out of the scope of this thesis and we limit our discussion to the essential key points. +The anti-association factor belongs to the familiy of initiation factors and is usually also +called initiation factor 6. In the following, in order to maintain a coherence with the cited most +recent bibliographic references, I will call it by the short name IF6 sometimes preceded by a +prefix indicating the domain of life from which it comes: eIF6, for eukaryotic initiation factor +24 general introduction +6, pIF6 for its prokaryotic counterpart and aIF6 for the archaeon one. +IF6, like the other initiation factors, takes part in the first steps of the translation process. +Translation initiation can be subdivided into three steps: first, binding of the specific initiator +Met-tRNA to the small ribosomal subunit; second, binding of the resulting complex to a +mRNA and locating the initiation codon; and third, joining of the large ribosomal subunit +to generate a translation competent ribosome. All these steps are facilitated by soluble +proteins termed translation initiation factors, and the structures of many of them have been +characterized at the atomic level. It is worth noting that while the essential part of this process +is shared by both prokaryotes and eukaryotes, the process itself is decidedly more complex +in eukaryotes than in prokaryotes and in part reflects the fact that much of the regulation in +prokaryotes is via the coupling of transcription and translation. Such coupling is not possible +in eukaryotes as transcription occurs in the nucleus while translation occurs in the cytoplasm. +The eukaryotic initiation factors can be divided into two groups: those that bind and +operate on ribosomal particles promoting subunit dissociation and association, initiator +Met-tRNA binding, and mRNA binding; and those that are aimed at mRNA and engaged in +preparing its upstream region for initiation. The first group contains the factors analogous to +prokaryotic pIF1, pIF2 and pIF3, namely eIF1 ( and eIF1A), eIF2 and eIF3 respectively, as +well as several additional factors, such as eIF2B, eIF5 and eIF6. The second group seems to +have no analogs in prokaryotes and includes special mRNA-binding and mRNA-unwinding +proteins facilitating initiation of translation; these are the factors of eIF4 group, namely eIF4A, +eIF4B, eIF4F and eIF4E [186]. +The role of IF6 in the translation initiation is more complex than those of the other initiation +factors because it engenders different functions about which very little is known. First of all, +IF6 does not act as a true initiation factor because it does not form any initiation complex8 +either with RNAs and ribosome subunits as proved by the fact that yeast cells depleted of +eIF6 remained active in translation of mRNAs in vitro [178]. Its principal functions can be +resumed as follows: +- it is required for biogenesis of the 60S ribosomal subunit both in archaebacteria and +eukaryotes [173, 178, 177, 212] +8 Initiation complexes are macromolecular complexes formed by mRNA, tRNA and ribosome subunits which +come together to form the machinery that perform the first two steps of the translation. IF6 does not take part +directly into this mechanism. +1.4 the anti-association factor 25 +- it acts as de facto anti-association factor of the 60S and 40S subunit in the cytoplasm +[178, 28] +Moreover, a very recent work also uncovered another evolutionary conserved function +of IF6 in the microRNA-mediated post-transcriptional silencing[34] which could extend +significantly the peculiarities of IF6. +Si and Maitra showed that depletion of eIF6 in yeast cells resulted first in a decrease in +the rate of protein synthesis and then in cessation of cell growth [178] and Basu et al. [10] +showed also that the protein depletion caused in cells a selective reduction of 60S ribosomal +subunits. These two results and the previous one confirmed the evolutionarily conserved +main role of IF6 in biogenesis and assembly of ribosomal units and also the absence of its +direct participation into the translation process. +The suggestion of these two functions of IF6 is also strengthened by the localization of +the protein in both nucleus and cytoplasm[6] where ribosome subunit biogenesis and +ribosome assembly take place respectively. Furthermore, Basu and coworkers [10] showed +that phosphorylation of eIF6 regulates its distribution in nucleus and cytoplasm [11]. +As a whole, the multiple functions of IF6 make of this protein an essential factor for cellular +growth and protein synthesis. Very little is known about its participation in the 60S biogenesis +whereas several works in the past decades better elucidated its role of anti-association factor +at a molecular level [28]. This function has been identified in eukaryotes as part of process +which involves a protein promoter of ribosome translation, RACK1 and a protein kinase PKC. +In the context of this work, it is worth noting that eIF6 has been proven to be very sensitive +to heat: in homologues from wheat germ [170] and calf liver[199], eIF6 activity had an +optimum at around 37◦C but was completely abstent between 50 and 60◦C. Whether the +cessation of activity is due to a partial or complete protein denaturation is not known. +From a molecular point of view, IF6s are 26kDa proteins which share a phylogenetically +conserved sequence of 224 residues with 30% similarity. All known eukaryotic IF6 contain +an additional carboxyl terminal extension of 21 amino acids. Even though this tail does +not seem to be directly involved to the anti-association function of IF6[66], as proved in +in vitro reactions, it has been proven to be somehow related to this process through the +26 general introduction +phosphorylation of a serine residue (Ser235) by the protein kinase PKC [28]. +In 2000, the first molecular structure of an IF6 homologues was resolved by x-ray +crystallography by Groft and coworkers [66] who obtained the structures of two homologous +IF6s issued from M.Jannaschii and from Saccharomyces ceraevisie. Both structures revealed a +very unusual internal pseudo-symmetry made by the disposition around a common axis of +five copies of a repeating α/β subdomain of about 45 residues. Each subdomain contains: one +long α helix, a shorter α-helix or a 310-helix and three β-strands. While the global structure +of the first 224 residues is well known and has been proven to be evolutionarily conserved by +homology modelling [66], nothing is known about the structure of the C-terminal extension +of 21 amino acids. +Figure 7: Cartoon representation of IF6 backbone. The color scheme highlights different type of protein +secondary structure. One of the pseudo-subdomain is shown on the left-hand side as +reference. +1.5 the thesis project "at a glance". 27 +From a structural point of view is also worth-noting the fact that the five subdomains do +not make a unified hydrophobic center of the protein. Instead, they produce an hydrophobic +"torus" by their association which in turn creates a cave-like hollow in the center of the +structure. The cavity is large enough to let water molecules enter and in the crystallographic +data sixteen of them were found in a well-ordered conformation of pentagonal layers and are +hydrogen bonded to the carbonyl oxygen atoms of two residues in the neighboring β-strands. +In the yeast (Saccharomyces ceraevisie) eIF6 this cavity is closed by an arginine (residue 61) +whose guanidinium group makes several hydrogen bonds with glycines in the short α-helix +of subdomains. +1.5 the thesis project "at a glance". +As stated earlier in this introduction, the key point for molecular evolution is the maintain of +biological function. This is accomplished in proteins either by point mutations or by simple +structure re-arrangements. Nonetheless, evolution does not have a unique pathway to follow +this procedure. +This thesis focused on the way proteins evolutionarily "react" to large environmental +changes, i.e. how they adapt to function even in organisms which live in extreme conditions. +Following this idea, this work concentrated on the study of the adaptation of the IF6 from +Methanococcus Jannaschii to extreme environments. In this context the comparison with +proteins in normal (mesophilic) conditions would have been essential to finely characterize +the ability to adapt to extremes conditions. +IF6s from Saccaromyces cerevisiae was chosen as mesophilic counterpart of Methanococcus +Jannaschii. They share only 33% of identity in sequence but their structures are significantly +similar to each other and to most of the other IF6s homologues [66]. As a whole, this means +that IF6’s function was highly conserved during evolution but it does not explain how +function and, apparently, structure have been maintained in the adaptation to a wide variety +of environmental conditions. +In this context, the work presented here will try to give a first answer to the following +questions: +Where does the extremophilic signature come from ? +If structure cannot be the origin for this, can it be the dynamics?? +28 general introduction +Of course all answers given here will be limited to the particular case of adaptation to the +warm deep-seas and will not be neither exhaustive nor general but could introduce a new +approach in study of protein evolution. +The main tools used in this work are molecular dynamics simulation and neutron +scattering experiments. After a brief introduction to the main concepts of the theoretical +frameworks that guided this work, the experimental setups will be presented. +In the following chapter a wide and detailed presentation of a novel method for the +characterization of the protein secondary structure is given. The method, called ScrewFit, was +developped in the context of this thesis but it has rapidly found some different applications +of the analysis of protein structures. Some examples already published as scientific articles in +international peer-reviwed journals will be given. +Finally the results of this work on IF6 homologues will be presented and discussed. Some +general outcomes will be then used in the tentative of giving answers to the questions about +protein evolution proposed above. +2 +MATERIAL AND METHODS +2.1 molecular dynamics +2.1.1 The basic principle +Molecular simulations used in combination with experimental methods, are a very +useful tool to give new insights into the dynamics and structure of complex molecular +systems. Simulation methods are used within different approximations, depending on the +experimental results with which they are confronted. +In this sense, neutron scattering techniques are well matched to molecular dynamics +simulation (MD) method which combines the classical equations of motions with empirical +force fields obtained from a priori quantum-dynamical calculations of atomic interactions +in the building blocks of the systems of interest. The basic approximation made in MD +is the Born-Oppenheimer approximation which states that due to the large difference in +masses between electrons and atomic nuclei, the electron dynamics is orders of magnitude +faster than that of the nuclei and, therefore, it can be assumed that electronic shells adapt +instantaneously to the positions of the nuclei. Moreover the dynamics of the nuclei is treated +by classical mechanics. +De facto, the MD gives information about the dynamics of the same objects that are directly +seen by neutrons: the atomic nuclei. As a consequence, MD and neutron scattering give +access to the same length and time scales (ranging from 1 Åto 100 Åand from 0.1ps to 10ns, +respectively). +In an MD simulation each atom is represented by a point mass whose dynamics is described +by the classical Newton’s equations of motion: +mir¨ = Fi, i = 1, . . . ,N (2.1) +29 +30 material and methods +where mi is the mass of atom i and Fi is the total force acting it. The force Fi is derived +from the potential energy U(r1 . . . rN) through: +∂U(r1 . . . rN) +Fi = − (2.2) +∂ri +As already mentioned, the energy U(r1 . . . rN) is an effective energy which describes all +types of atomic interactions. The generic form of the potential energy is : +∑ +Utotal = Kr(r− r +2 +eq) +b∑onds ++ Kθ(θ− θ +2 +eq) +ang∑les Vn ++ [1+ cos(nφ− γ)] +d∑ 2ihedralsAij Bij ++ − +12 6 +∑ Rij +From these equations it is evident that a change in pressure can be obtained by changing +the virial through the rescaling of the interatomic distances rij. The latter leads to a rescaling +of the total volume of the simulated system and of its atomic coordinates. The method +originally proposed by Berendsen and coworkers [14] uses the rescaling of distances to +regulate the macroscopic pressure of the system. For this purpose the equation that relates +the time derivative of atomic coordinates with velocities, r¨ = v should be modified with the +introduction of an extra term : x¨ = v− αx. The volume of the system should also change +accordingly: V¨ = α3V . +The pressure variation in the pressure bath is defined by: +( ) +dP P0 − P += (2.13) +dt bath τp +2.1 molecular dynamics 37 +where P0 is the target pressure value. Additionally, the pressure change is generally also +related to the isothermal compressibility β by: +( ) +dP 1 dV 3α += − = − , (2.14) +dt T βV dt β +where the last equality is obtained by applying the requested volume re-scaling. +Equations (2.13) and (2.14) leads to: +P0 − P +α = −β (2.15) +3τp +Hence, the equation of motion now reads: +P0 − P +x¨ = v−β x (2.16) +3τp +The solution of this equation, as obtained by the finite difference methods used in MD +simulations gives a rescaling factor for the atom coordinates and the linear dimension of the +simulation box which is equal to (at the first order in the time step ∆t)1: +β∆t +µ = 1− (P0 − P). (2.17) +3τp +leapfrog integrator In the program suite AMBER9, the integration of the equations +of motion for the extended system corresponding to the NPT ensemble used in this work, is +implemented through the use of the Leapfrog integrator [56, 3]. The latter is a symplectic and +time-reversible integrator whose general form is derived by the Taylor series expansion of +Newton equations for the atom position r, at timestep t and for its velocity at an intermediate +time step t+∆t/2 [56]: +1 +vi(t+∆t/2) = vi(t−∆t/2) + Fi∆t (2.18) +mi +ri(t+∆t) = ri(t) + vi(t+∆t/2)∆t (2.19) +The velocity vi(t+∆t) can be computed a posteriori with the relation: +1 +vi(t) = [vi(t+∆t/2) + vi(t−∆t/2)] (2.20) +2 +1 The isothermal compressibility β does not need to be known exactly because its value influence only the +accuracy of τp without any consequence to the dynamics +38 material and methods +When applied to an extended system issued by the use of the Langevin thermal bath and +Berendsen barostat, (2.19) reads: +1 +vi(t+∆t/2) = vi(t−∆[t/2) + ∆t [Fi − γivi(t) +mi ]Ri(t)] (2.21) +P0 − P +ri(t+∆t) = ri(t) + vi(t+∆t/2) −β ri(t) ∆t (2.22) +3τp +2.2 neutron scattering +Neutrons are one of the most useful probes to study the structural and dynamical properties +in condensed matter. Neutrons for scattering experiments are usually moderated to be at +thermal equilibrium at room temperature with typical energies of ∼ 25 meV and wavelength +around 1.78Å, which corresponds to the same time and length scale of the thermally excited +atoms motions. These facts make neutrons very sensitive to both amplitude and frequencies +of atomic motions. For macromolecules, cold neutrons which have typical energies around +2.3meV and wavelength ∼ 5Å, are however better adapted to explore longer length scale and +slower dynamics. +Figure 9: Scheme of neutron scattering +Neutrons interact directly with atomic nuclei via a very short range potential which can +be considered as a direct collision between the neutron and a nucleus (see Figure 2.2). An +incident monochromatic neutron beam can interact with matter through both absorption +and scattering. When scattered, neutrons can be characterized by their wave vector kout and +energy Eout [129, 13]. +2.2 neutron scattering 39 +The number of incident neutrons with wave vector kout which are scattered with a wave +vector kout in the elementary solid angle dΩ around the direction of kout and with an +energy exchange dω is called differential cross section and it is defined as: +d2σ · |kout|= N S(q,ω), (2.23) +dΩdω |kin| +where N is the number of scatterers in the sample. +The function S(q,ω) is called the dynamic structure factor and it gives access to sample +dynamics as a function of q and ω which represent the momentum and the energy transfer +respectively: +∆p = h (kin − kout) = h q (2.24) +h 2 +∆E = E in − Eout = hω = (k +2 +in − k +2 +out) (2.25)2mn +The value of √|q| is related to the energy transfer hω by the relation:√√√ √h ω h ω +|q| = kin 2− − 2 1− cos θ (2.26) +Ein Ein +This formulation of the problem takes into account the fact that in scattering phenomena +neutrons more easily loose energy in interacting with matter. Equation in (2.26) is of crucial +importance for the determination of the accessible range in the experimental settings of +quasielastic neutron scattering measurements. +Linear response theory allows the dynamic structure factor to be written in terms of +equilibrium fluctuations of the sample and thus, using the fluctuation-dissipation theorem +[201], S(q,ω) can be written as the Fourier transform of the intermediate scattering function +F(q, t): +∫ +1 +∞ +S(q,ω) = dtF(q, t)e−iωt∞ , (2.27)2π − +∑ ∫1 +∞ −iq·r 1 ∑ 〈 iqTF(q, t) = Γ G (r, t)e dr = Γ e ·rα(t) e−iqT·r∞ ¸˛ β(0)αβ αβ 〉 (2.28)N Nα,β − α,β +40 material and methods +2 2Γαβ = bαbβ + δαβ(bα − bα ) (2.29) +where "〈· · ·〉" denotes an ensemble average and if A(t) and B(t) are two time-dependent +functions, "〈A(t1)B(t2)〉" is usually referred to as a correlation function. The parameter b¸/˛, +called the scattering length, is an effective linear dimension of the nucleus α/β with respect to +its interaction with neutrons. The function G¸˛(r, t) in (2.28) is referred to as the Van Hove +pair correlation function and represents the probability that, given a particle at the origin at +time t = 0, any particle (including the same one) is at r at time t. +The intensities of the neutron-nucleus interactions are defined by the scattering lengths b of +each nucleus in the sample which depend on the isotope and the relative orientation between +the spin of the two interacting particles. If the spins of the nuclei and the neutron are not +maintained in a special orientation one can assume a random relative orientation and that +spin and position of the nuclei are uncorrelated. +For this, F(q, t) in (2.28) takes into account the random distribution of nuclear spins in the +sample through the parameter Γαβ defined in (2.29) where the average over isotopes and +relative spin orientations of neutron and nucleus is expressed by · · ··. +The parameter Γαβ can be divided into two terms: +Γαβ = bα,cohbβ,coh + δαβ(bα,incbα,inc) (2.30) +where, +b√α,coh = bα (2.31) +2 2bα,inc = bα − bα (2.32) +are linked to the total scattering cross section by the relation: +σ = 4π(b2 + b2α α,coh α,inc). +The outcome of equation (2.30) is also that F(q, t) can now be recast as a sum of two parts: +the coherent part Fcoh(q, t) which results from the correlations in time between the positions +of the atom α (autocorrelation term) and those of different atoms β (cross-correlation term); +the incoherent part Finc(q, t) which results only from the time auto-correlation of the positions +of the same atom α: +1 ∑ +F (q, t) = b b 〈eiqT·rk(t) e−iqT·r, , j(0)coh α coh β coh 〉 (2.33) +N +α,β +2.2 neutron scattering 41 +1 ∑ +F (q, t) = b2 〈 iqTe ·rk(t) Te−iq ·rj(0)inc α,inc 〉 (2.34)N +α +2.2.1 Incoherent Scattering +Neutron scattering from biological samples is mainly dominated by the incoherent part +of the scattering of the hydrogen nucleus. This fact is due to the large difference between +the incoherent term from hydrogens and the incoherent and coherent terms from the other +isotopes that are usually present in biological samples. This fact is clearly shown in Table +2.2.1 +Isotope bcoh(fm) binc(fm) σcoh(barn) σinc(barn) +1H -3.74 25.27 1.76 80.27 +2H 6.67 4.04 5.59 2.05 +12C 6.65 0 5.56 0 +14N 9.37 1.98 11.03 0.49 +16O 5.80 0 4.23 0 +32S 2.80 0 0.99 0 +Table 5: Incoherent and coherent scattering lengths of the most common isotopes found in biological +samples. Data reported from [175]. +The characteristic cross section of hydrogens is mainly due to a large incoherent +contribution of the most favorable state of the interacting system composed by the incident +neutron and the hydrogen nucleus. From a practical point of view, this fact constitutes a +significant advantage in studying biological samples because they present large amounts of +hydrogens uniformly spread over their chemical components. Therefore, the scattering from +samples will represent the dynamics of the whole molecule even though they are mainly +due to only one type of atom. Moreover, the great difference between the cross section of +hydrogen (1H) and the one of deuterium (2H) allows some contrast to be created between +different parts of the same molecule or between the molecule and the aqueous content of the +surrounding solvent yielding a better characterization of the structure and dynamics of the +42 material and methods +sample itself. +Elastic and Quasielastic Incoherent Scattering +A typical spectrum from neutron scattering measurements is shown in Figure (2.2.1) where +one can easily distinguish three different regions: the elastic peak which results from scattering +without exchange of energy between the interacting particles and gives insights into the +structural configuration of the sample; the quasi-elastic part which results from small energy +changes and describes all the stochastic dynamics of atoms in the sample, such as rotational +and translation diffusion; the inelastic part which is present only if the energy change is +sufficient to modify the equilibrium state of the sample and gives access to vibrational +motions. +As mentioned in the previous paragraph, the large quantity of hydrogens in proteins or +DNA lets us perform the following approximation: +F(q, t) ≈ N b2H,inc FH(q, t) (2.35) +where +1 ∑ +F (q, t) = 〈eiqT·rα(t) e−iqT·rα(0)H 〉 (2.36) +N +α∈{H} +The relative dynamic structure factor can be written using the relation (2.27) +∫ +1 +∞ +S (q,ω) = dtF (q, t)e−iωtH ∞ H , (2.37)2π − +and it is the main part of the dynamic structure factor that can be directly measured by +neutron scattering experiments. +In the case of samples with confined internal motions, such as biological macromolecules, +the intermediate scattering function defined in (2.36) can be decomposed into a time- +dependent part and a time-independent one: +F (q, t) = F ′H H(q, t) + FH(q,∞) (2.38) +2.2 neutron scattering 43 +Figure 10: A typical spectrum from neutron scattering measurements. +This is due to the fact that the atom positions at different instants become independent of +time as the latter goes to infinity. +In simple liquids, where any confined motion is present, the time-independent term is strictly +zero because of the atomic brownian motion which contributes in totally de-correlating +atom positions, whereas in proteins, where the atomic internal motions are confined, the +time-independent part is a non-zero constant. +The time-independent part of (2.38) is usually called Elastic Incoherent Structure Factor (EISF) +and can also be used to redefine the dynamic structure factor in the following manner: +S (q,ω) = EISF(q)δ(ω) + S ′H H(q,ω) (2.39) +44 material and methods +In this form, SH(q,ω) presents an elastic and δ(ω)-shaped component related to the EISF +along with another part, S ′H(q,ω) issued from the quasi-elastic and inelastic spectra of the +s∫ample. Moreover the two parts on the right-hand side of (2.39) are restrained by the relation+ +−∞∞ SH(q,ω)dω = F(q, 0) = 1 (with appropriate normalization) which leads to: +∫+∞ +dωS ′∞ H(q,ω) + EISF(q)δ(ω) = 1 (2.40)− +By definition, the EISF relates to the ensemble of positions that the scattering nuclei +(hydrogens) can attain during an infinite time and it gives insights into the configurational +space volume the latter can explore. +In practice, the definition of EISF given above suffers from two main biases: from the +experimental point of view δ(ω) cannot be obtained exactly because of the finite resolution +of the instrument used for the measurements and it typically assumes a larger-width shape +(usually fitted as a triangular, gaussian or a lorentzian distribution); from a numerical point +of view, the calculation of the EISF as the limit to infinity of the intermediate scattering +function is very difficult due to the very low statistics attainable for time scales close to the +total time-window used to observe the sample dynamics. +Nevertheless, one can easily overcome these problems by redefining the EISF in both cases: the +measured EISF can be rewritten as the ratio of the elastically scattered intensity integrated over +the frequencies ω to the total integrated intensity (the sum of the elastic and the quasi-elastic +part): +∫+ +EISF (q) = −mes ∫∞∞ dω Selasticmes (q,ω)+∞∞ (2.41)−∫ dω Smes(q,ω) +where , +S (q ω) = ∞∞ S (q,ω ′)R(ω − ω ′)dω ′mes − mes takes into account the effects of +the finite experimental resolution represented by the function R(ω) of half-width-at-half- +maximum (HWHM) equal to Γ ; the numerical EISF can be written instead as: +1 ∑ +EISFnum(q) = b +2 +α,inc〈|exp(iq · rα)|2〉 (2.42)N +α +2.2.2 Spectrometers +The choice of the type of spectrometer to be used to perform the measurements and its +resolution is highly related to the time and length scales of interest. In case one wants to +2.2 neutron scattering 45 +investigate the effects of pressure or temperature on the internal dynamics of biological +samples such as proteins, which requires the use of samples in liquid solutions, the +spectrometer resolution should be attentively set to reduce the contribution of the global +diffusion of the sample to the measured signal. +Time-of-flight spectrometers are typically used for measurements of quasielastic scattering +spectra in solids, liquids and molecular crystals. +Time-of-flight spectrometers +In time-of-flight spectrometers, such as the one illustrated in 2.2.2, neutrons from the reactor +strike a sequence of choppers: passing through them the beam is first pulsed and then +selected with respect to its energy E0 and wave vector k0. Therefore the neutrons leave the +last chopper, placed at a known distance dCS from the sample, as a pulsed monochromatic +beam. An array of 3He detectors is arranged at a known fixed distance dSD from the sample, +and scattered neutrons arrive at the detectors at times determined by their scattering energies. +The time-of-flight of a neutron from the last chopper to one of the detectors, the incident +Figure 11: Example of time-of-flight spectrometer. +neutron energy and the distances dCS and dSD are directly obtainable from measurements +and allow the calculation of the final energy of scattered neutrons. Moreover, the knowledge +of the angles of scattering allows to solve spectra as a function of momentum and energy +transfer q and h ω. +46 material and methods +The time-of-flight spectrometers typically measure energy transfers in the range 10− 10−2meV , +hence they are used to investigate dynamics that occur in the time range 10−10 − 10−13s. +All time-of-flight measurements for this work have been performed with the following +spectrometers: +- FOCUS (Paul Scherrer Institut, Zurich, Switzerland ) which is a time-of-flight spectrom- +eter with a variable incident wavelength from 2 to 15 Å. Its energy resolution varies +from 50µeV to 300µeV in the setup with higher incident neutron flux and a maximum +momentum transfert of 8Å−1. +- IN6 (Institut Laue Langevin, Grenoble, France) which is a time-of-flight spectrometer +with incident wavelength of 4 to 5.9 Åwith corresponding energy resolution from 50 +µeV to 170 µeV . The maximum momentum transfert available is 2.6 Å−1. +3 +EXPER IMENTAL AND S IMULATED SYSTEMS SETUP +3.1 sample production +3.1.1 Protein expression and purification +In the following we will discuss the methods used to produce samples for both neutron and +in silico experiments. +Both approaches demand a wide knowledge of techniques some of which have been already +presented in the previous chapters. The experimental samples also needs some preliminary +steps for their own production which require knowledge in molecular biology. The discussion +of these aspects in detail would be beyond the scope of this thesis, nevertheless, this part of +the work has been fundamental for the following experimental steps as it allowed us to setup +a stable protocol whose yield was adapted to neutron experiments. +The protocol reported here followed the usual scheme for protein production which can be +summarized in a very simplified way, as follow: +- Cloning of the part of the genomic DNA from both Methanococcus Jannaschii and +Saccaromyces cerevisiae which encode the a/eIF6 proteins. +- Massive expression of the identified gene into an host organism, here E.coli, to produce +large amount of proteins. +- Purification of the protein solution obtained from the host organism to obtain an as +much as possible pure solution containing only the a/eIF6 proteins. +cloning Two cloning experiments have been performed to produce the genes encoding +eIF6 and aIF6 proteins. Following the nomenclature found in literature we will call TIF6 the +gene that encodes for eIF6. For M. jannaschii, the genomic DNA fragment encompassing the +aIF6 gene was obtained from TIGR/ATCC Bult et al. [18]. The resulting cDNA was then +amplified by PCR amplification using the nucleotides showed in Table (6). +For S. cerevisiae, TIF6 construct was produced by PCR amplification using genomic DNA +from S. cerevisiae as a template. Cloning experiments were performed using the nucleotides +47 +48 experimental and simulated systems setup +Table 6: default +aIF6-forward AAA CAT ATG ACC ATG ATT ATA AGA AAA TAC TTC TC +aIF6-reverse TTT TGC GGC CGC TCA TTA AAT CAG GCC TAA AGC ATC TT. +TIF6-forward CGG GAT CCC ATA TGGCTA CCA GGA CTC AA +TIF6-reverse GGG AAT TCC TAT GAG TAG GTT TCA ATC AA +showed in Table (6). +The forward primers introduced a NdeI restriction site and the reverse primers introduced a +NotI restriction site. The aIF6 and TIF6 PCR products were cloned into a pET28a expression +vector (Novagen). This plasmid contains a kanamycin resistance gene for selection of +transformed cells, and a pBR322 replication origin. The target gene is placed under the control +of the T7 RNA polymerase promoter, and is expressed as a fusion with a N-terminal hexahis- +tidine tag followed by a thrombin cleavage site. Escherichia coli strain BL21(DE3) (Stratagen) +chemically competent cells were transformed with this plasmid in order to express the protein. +The DE3 gene encodes for the T7 RNA polymerase (under the control of the galactose operon). +Transformation was done by heat shock: 1ng of plasmid DNA was mixed with 100µl of +competent cells, and then incubated on ice for 20min. Following adsorption of the plasmid +onto the cell membrane cells are placed at 42◦C for 45 sec, and then on ice for 2 min. 500µl of +SOC medium is added and the cells were incubated 1 h at 37◦C. To select cells which have +been properly transformed, the culture was then plated on LB-agarose plates containing +kanamycin (10 mg/l). +The plates were incubated at 37◦C overnight. The next day 20 ml of LB containing 10 mg/l +kanamycin were inoculated with 1 colony. The cells were grown until the OD600 reached 0.6 +AU. 1 ml of the cell suspension was complemented with 100µl of sterilized glycerol, and the +mix was frozen by immersion into liquid nitrogen. The aliquot was stored at -80◦CC. +protein expression The expression was carried out in Erlenmeyer flasks. A 50ml +preculture was prepared on the previous day by inoculating 50 ml LB (with 10 mg/l +kanamycin) with cells scraped from the top of the frozen stock. For cultures in Erlenmeyer +flasks, 2.5 l flasks were filled with 1 l of LB media complemented with 10 mg/l kanamycin. +3.1 sample production 49 +Each flask was inoculated with 10 ml preculture, then incubated at 37◦C with 200 rpm +agitation until the OD600 reached 0.6-0.8 AU. The temperature was then decreased to +23◦C for 30 min, and 0.5 ml of isopropyl-thiogalactosidase (IPTG) 1 M (0.5 mM final) was +added to induce expression of the cloned protein (via induction of the T7 RNA polymerase). +Incubation was continued in the same conditions for 5 h. The cells were pooled into 1 l +bottles and harvested by centrifugation for 15 min at 5000 g. Cell pellets were frozen by flash +cooling in liquid nitrogen and stored at -80◦C. +protein purification For each protein preparation 10 g of frozen cellular paste were +resuspended in 40 ml of lysis buffer + 40mg of lysozyme (Appendix A). 3 pills of antiprotease +complete EDTA free cocktail and 4 µl of Benzonase enzyme were added. The bacterial +suspension was incubated 20 min on ice with agitation. Then, the cells were lysed twice by +cell disruption (Constant System) at 1.4 Kbar. 1mM β-mercaptoethanol was added to the +solution. Here two different approaches were used for aIF6 and eIF6: i) the crude extract +expressing aIF6 was incubated for 1 hour at 75◦C taking advantage of its heat resistance +properties; ii) the eIF6 was was rapidly brought to the next step to reduce the probability of +proteolytic clevage (see next paragraph). The soluble and insoluble fractions of aIF6 and eIF6 +were separated by ultra-centrifugation (1.5 h, 250000 g) for both preparations. The soluble +part of the crude extract was then incubated with 3 ml Talon superflow Cobalt affinity resin +(Clontec) previously equilibrated with lysis buffer; incubation was done at 4◦C for 1.5 h +with gentle agitation. The resin was transfered in a column and washed successively with 10 +column volumes of wash solution (Appendix A, 1M NaCl) by gravity. The histidine tagged +IF6 protein was then eluted from the resin using 8 volumes of elution buffer (Appendix A, +250 mM imidazole), and collected in 1.5 ml fractions. Fractions were loaded on a denaturing +gel to check for presence of the overexpressed IF6 protein. +Fractions containing the protein were pooled and dialysed twice for 2 h against imidazole +free, dialysis buffer (Appendix A). The protein concentration was determined by measuring +the OD280 of the solution and thrombin was added (1 u per 150 µg of protein) to +selectively cleave the N-terminal histidine tag of the protein. The cleavage step was done by +incubation overnight (approx. 16 h) at room temperature, and stopped by addition of 0.2 +mM (final concentration) phenylmethylsulfonyl-fluoride (PMSF). The completeness of the +proteolysis was checked by SDS-PAGE.The protein was concentrated to 10 mg/ml using a +UltraFree (Millipore) ultrafiltration device (5 kDa membrane cutoff) prior to size exclusion +50 experimental and simulated systems setup +MW Clys Fractions +Figure 12: Denaturing gel verification of overexpressed IF6 protein. Cell lysate shown as reference. +chromatography. Gel filtration was performed using a Superdex-75 HR 10/30 (Pharmacia) +column previously equilibrated in the protein storage buffer (appendix 1). Both OD280 +(optical density at 280nm) and OD260 were monitored during the chromatography to control +the absence of nucleic acids and 500 µl fractions were collected. Peak fractions were pooled +and concentrated a last time using a Centricon (Millipore) ultra-filtration device with a +membrane cutoff of 10 kDa. +poly-histidine tag The use of polyhistidine tags helped to obtain a considerable yield +from the above protocol which allowed a reliable protein concentration to be maintained even +for neutron scattering measurements in high pressure systems where a large solution volume +is necessary. Nevertheless, for technical reasons the selective cleavage of this tag was not +suitable for large volume solutions. For this reason, the cleavage procedure explained above +was performed only on ambient pressure measurements where more convenient volumes +could be used. As a consequence, this protocol must be considered as a first effort toward a +more satisfactory procedure adapted to neutron scattering experiments. +The presence of the histidine tag is not expected to have strong effects on protein structures, +as proved by Carson and coworkers [23] on a wide set of crystallographic structure, but it +could significantly affect the global protein dynamics. For this reason, as shown in Results, +some supplemental tests have been performed to quantify the dynamical contribution of the +tag in the case of a/eIF6. +3.1 sample production 51 +clevage of carboxyl-terminal tail in eif6 During some preliminary tests for +protocol optimization, a proteolytic clevage of the eIF6 protein was observed (see Figure 13 +for the corresponding SDS-PAGE verification), either in the soluble and in insoluble fractions +of the cell lysates. +Figure 13: SDS-PAGE verification of partial clevage in eIF6 samples. Cell lysate shown as reference. +Due to its apparent small molecular weight, the cleaved fragment detected in this work +was supposed to be the same found by Groft and coworkers [66]. The latter reported that +attempts to express and purify S.cerevisiae eIF6 were complicated by proteolytic cleavage of +the divergent C-terminus. They also remarked that truncation beyond residue 224 eliminated +this problem, and eIF6(1-224) could be purified using the same aIF6 purification scheme. +Interestingly, the cleaved part of eIF6 contained a tail made of 21 aminoacids, with sequence +shown in Table 7, which can be found only in eukaryotes homologous of IF6 and very little is +known about its structure. +A preliminary characterization of the fragment was performed by the means of the Basic +Local Alignement Search Tool (BLAST) which compares the aminoacid sequence of the +fragment against sequence databases in order to find some similarities with other known +proteins. For eIF6, the only significant scores were obtained from other IF6 homologous +meaning that this sequence fragment must be strictly peculiar for the function of this class of +52 experimental and simulated systems setup +Table 7: Sequence of the C-terminal fragment of eIF6 (CTAIL). Numbers of residues start at 225, +according to the sequence in eIF6. +Glu225 Asp226 Ala227 Gln228 Pro229 Glu230 Ser231 Ile232 +Ser233 Gly234 Asn235 Leu236 Arg237 Asp238 Thr239 Leu240 +Ile241 Glu242 Thr243 Tyr244 Ser245 +initiation factor or of its evolutionary history. +In order to obtain more insights into the native conformation of this C-terminal tail, a test of +secondary structure prediction was performed with two distinct methods: +- PSIPRED server [101], which performs structure predictions based on position-specific +scoring matrices +- APSSP2 server [156], which predicts secondary structure conformations using nearest +neighbor and neural network approaches. +Both methods found a reasonably probable formation of a α-helix in the ending part +of the fragment, in the region Asp238 Thr239 Leu240 Glu241. These results are also +corroborated by the inspection of the hydrophobic profile of the fragment with the help of +the Kyte/Doolittle hydrophilicity scale [122] which shows an increasing hydrophobicity in +the regions Pro229-Ser231 and Asp238-Glu242. +These results lead to the convinction that the fragment could have a significant role either +in dynamics or structure stability of eIF6 and thus also in protein function. This idea is +comforted by recent results which indicate that C-terminal subdomains contribute to the +localization in the cellular nucleus of eIF6 [6]. +This outcome suggested the importance of maintaining the 21 C-terminal fragment as part +of the investigated sample. For this purpose, several tests on the production of eIF6 were +performed in order to limit the proteolytic cleavage during the production itself without +effect on the total final yield. +The protocol presented here gave the best results with a cleavage reduced to around 30% +as resulted from the preliminary MALDI mass spectrometry analysis reported in Figure 14 +where two large peaks are evident at molecular weights equal to both the entire protein and +the truncated structure (1-224). The height of these peaks gives an estimation of the relative +3.1 sample production 53 +Voyager Spec #1=>BC=>NF0.7=>SM21[BP = 28472.8, 442] +28469.98 +100 +90 +80 +8667.46 +70 +60 +10648.91 28654.25 +50 +14238.52 +40 16653.33 +11525.53 +8246.39 +30 10141.64 14332.58 27129.39 +28870.80 +20 13561.33 27269.91 +10 +0 +7999.0 13399.4 18799.8 24200.2 29600.6 +Mass (m/z) +Figure 14: MALDI-MS essay on eIF6 solution. +amount in solution. +stability of eif6 When performing studies on the effects of extreme conditions on +protein structure and dynamics it is important to know beforehand the boundaries which +define the normal conditions for the specific protein of interest. +Nevertheless, in the case of IF6 homologues, there is a scarcity of works on the general +chemical properties with respect to temperature and pressure changes. Although aIF6 is +presumably able to reversibly respond to high temperature and high pressure values, very +little can be said about the eIF6. In an early paper on biological properties of eIF6, Valenzuela +and coworkers [199] reported that anti-association factor 6 from calf liver was found to +undergo a cessation of its activity at temperature of ∼ 60◦C. As the inactivation of a protein +function may not correspond to the total and irreversible denaturation of the protein itself, +the latter was tested here by means of dynamic light scattering measurements in the range of +interest of the present work. The measurements of the hydrodynamic radius of eIF6 were +performed with a DynaPro-Titan© fixed-angle light scattering system. The results, listed +in Table 8, shows that, at 50◦C, eIF6 forms aggregates or partially unfolds. Moreover, when +brought back to 30◦C it does not find its initial state, suggesting that the transition is not +reversible. +These preliminary reults together with the outcome of the work made by Valenzuela and +% Intensity +54 experimental and simulated systems setup +coworkers, suggested to limit all neutron scattering experiments on eIF6 into the non- +denaturating temperature range. However, as explained in the next sections, some in silico +exmperiments have been performed on eIF6 also at high temperature and high pressure +to verify the presence or more simply the beginning of a denaturating process. It is also +worth noting that the reported values of hydrodynamic radius for eIF6 at 20◦C correspond +only to an effective value due to a spherical approximation of the whole protein structure: +the conserved pseudo-globular part formed by residues 1-225 and the C-terminal tail of 21 +aminoacids. +Table 8: Variation of the hydrodynamic radius of eukaryotic eIF6 +20◦C 30◦C 50 ◦C back to 30 ◦C +RH [nm] 3.32 3.61 29.76 24. 23 +final samples For both aIF6 and eIF6, deuterated protein solutions were prepared at a +concentration of ∼ 40mg/ml and pD ∼ 7.0. All labile hydrogen atoms in the samples were +exchanged overnight by dialysis and then filtered with an Amicon Filter Ultra (membrane +cutoff 5kDa) against a thirty-fold excess of pure deuterated solvent. The final solution was +centrifuged to eliminate possible aggregates. The final concentration was measured by +UV-VIS absorption at 280nm. The latter measurement gave results with a possible systematic +error greater than 10% due to the very low amount of chromophore amino acids (such as +tryptophan, tyrosine, phenylalanine and histidine) in the sequence of both proteins. Although +the limits for solution concentration of both samples were not known from literature, several +preliminary DLS assays seemed to comfort the observation of monodisperse solutions of eIF6 +around 40mg/ml. +3.2 neutron scattering measurements setup +In this work the reported measurements of neutron scattering spectra were performed in +order to investigate the effects of the pressure and temperature changes into the dynamics of +3.2 neutron scattering measurements setup 55 +proteins. For quasielastic neutron scattering experiments (QENS), the easiest way to apply +pressure to a biological sample is to put it in a liquid solution and then compress the +volume in which it is contained. This is usually done in sample containers with a cylindrical +geometry. In this work, two different sample containers of this shape have been used for +the measurements at ambient and higher pressure, respectively. The relatively wide range +of temperature values, explored in measurements, imposed for both sample containers, the +choice of materials which do not undergo significant structural changes at high temperature +that could modify, for example, their mechanical resistance. +Moreover, when performing QENS experiments on samples in solution, one often needs +to use high concentrations to maintain the signal due to the sample itself significantly +distinguishable from the one coming from the buffer. For biological macromolecules this fixes +a constraint to the total solution volume used in the experiment as the biological samples +are often available in small quantity mainly due to expression protocols yields. In the case of +a/eIF6, although the protocol presented in the previous section was conceived to obtain a +maximum amount of samples, this was still a limiting factor for the total volume available for +measurements. For this reason the sample containers used in this work were also chosen for +their effective volume. +Ambient pressure An approximate scheme of the sample container used for these +measurements is shown in Figure 15 (panel A). The container is made of two concentric +hollow aluminum cylinders with a diameter of 19mm and 20mm, respectively. The irradiated +region was ∼ 50mm in height. The space between the walls of the two cylinders were +filled by the samples and closed on the top by a disc made of Teflon© in order to avoid +the sample to exit the space due to capillarity effects. The Teflon© cap was supposed +to be out of the irradiated region. The total volume available for samples were limited to 1.2ml. +High pressure The pressure cell was developed at the Institut Laue Langevin in Grenoble +(France) and was conceived to carry out experiments on liquid solutions at moderate high +pressure. In particular the dimensions of the cylindrical geometry were determined to +withstand pressure up to 2kbar: internal diameter of 10mm and wall thickness of 1.5mm. The +global geometry of the cell, shown in Figure in 15 (panel B), was inspired by another one +previously used for high pressure studies on lysozyme and reported in [20]. +In contrast to the latter, however, here the pressure is applied without transmitting media +and directly on the sample which is compressed by a pump connected to the pressure cell by +a very thin capillary (0.1mm diameter). Moreover, the irradiated part of the cell was made of +56 experimental and simulated systems setup +Figure 15: Sample can for high pressure measurements +an alloy of copper-berylium which permitted the wall thickness to be significantly reduced +without affect their mechanical resistance. In order to reduce the multiple scattering due to +the protein solution an insert with a diameter of 9 mm was used. As a whole the pressure +system required a total volume of ∼ 3ml of protein solution which is considerably smaller +than the volume commonly used in this type of QENS experiments and suitable for the +typical amount of a/eIF6 production yields. +instrumental resolution The QENS measurements reported in this thesis have +been performed mainly to investigate the internal dynamics of proteins. For this purpose +it was important to filter out of the quesielastic spectra all other contributions coming for +example from the global translation and rotation of proteins in solution. The standard method +to accomplish this task is the choice of an adequate experimental energy resolution which +should be larger than the width HWHM (half-height at half-maximum) of quasielastic signal +due to global motions. The energy width of the latter can be estimated from knowledge of +the translational and rotational diffusion constant of the protein. Unfortunately in the case +3.2 neutron scattering measurements setup 57 +of a/eIF6 no reference can be found in litterature and these values could only be estimated +from the available crystallographic structures. Nevertheless, as reported in Results, some a +posteriori finer estimations have been made by means of molecular dynamics simulations. +The values obtained for the conserved structure (residues 1-224) in aIF6 and eIF6 were around +8.4 · 10−3 Å2/ps which correspond, in terms of HWHM, to an energy width of 20 µeV for +a value of q = 1Å−1el . This result should be however corrected by a factor 0.20 due to the +higher viscosity of D2O with respect to that of H2O. The experimental resolution chosen for +measurements at the spectrometers FOCUS (Paul-Sherrer Institut) and IN6 (Institut Laue +Langevin) reported with other experimental settings in Table 9, was not sufficient to totally +eliminate the effects of global motions to the protein spectrum but was enough to significantly +reduce it with respect to the quasielastic signal corresponding to internal diffusive motions. +In this discussion only the translational diffusion constant was taken into account. To estimate +the influence of rotational diffusion on the measured QENS spectra the following formula for +the diffusion constant for rotational diffusion [36] was used: +kBT +γr = . (3.1) +4πηR3H +The above relation is used assuming that the approximation of eIF6 as a spherical-shaped +protein is reliable1. Here RH is the radius of the protein and η is the shear viscosity of +the solvent (water). For a/eIF6, which has a radius of RH = 2.81nm, one obtains γr = +0.14 · 108 s−1 at T = 293K. This corresponds to a width of 6 · 10−5meV , which is far below the +instrumental resolution. Therefore, spectral contribution from the global rotational diffusion +are expected to be largely within the chosen energy resolutions. +Table 9: Instrumental settings used in this work. +Incident waveleght Energy resolution Sample environment Time per run +[Å] HWHM [meV] [hours] +FOCUS 5.92 ∼ 0.020 ambient pressure 15 +IN6 5.98 ∼ 0.020 high pressure ∼ 10 +1 In the Results, I will show that a better approximation of IF6’s shape can be given by the Perrin correction to the +Stoke’s law for the diffusion of a sphere.This refinement will not change however the considerations made here. +58 experimental and simulated systems setup +3.2.1 Data analysis +The usual procedure for the analysis of data from neutron scattering measurements, is +preceded by some preliminary as follows: +- Normalization to the total number of incident neutrons during a single measurement. +This normalization is needed to account for the differences in time length and in incident +neutron flux for each measurement +- Correction for the detector efficiencies. It is performed in two steps. Firstly by the +normalization to the spectrum of vanadium performed with the same experimental +environment which corrects for relative efficiencies of detectors with respect to each +other. Secondly a correction is made with respect to the energy dependent efficiency of +detectors. A vanadium spectrum is used for the first calibration because it is a completely +elastic incoherent scatterer in the range of q of interest in time-of-flight experiments. +- Grouping of spectra over angles is made to increase the statistics related to data. +The latter procedure was crucial because the signal-to-noise ratio in measurements of +biological samples in solution is usually very low. +In QENS measurements on protein solutions, the detected signal does not come exclusively +from the protein but shows also significant contribution from the bulk solvent and from +the sample environment, like for example, the sample containers and background noise. +The spurious contributions are usually subtracted from the total signal to obtain scattering +functions related only to the protein dynamics. This procedure can be summarized by the +following relation: +S˜protein(q,ω) = (SS(q,ω) − τ ∗ SE(q,ω)) − (1−α) ∗ (SB(q,ω) − τ ∗ SE(q,ω)) (3.2) +where τ takes into account the transmission of the protein solution2 and α is the volume +fraction of the protein and its first hydration shell in the solution sample.The latter must be +known to apply a correct subtraction of solvent contribution in protein solution spectra. +The parameter α was estimated from the following relation between the mass density of +proteins and their mo[lecular weight (M((KDa)) [54]: )] +M(KDa) +ρ(M)[g/cm3] = 1.41+ 0.145 · exp − (3.3) +13 +2 Through out this thesis the transmission of the protein solution was approximated to the one of the buffer alone +3.3 molecular dynamics setups 59 +For a/eIF6 one obtains ρ = 1.43g/cm3, which gives a specific volume ν = 0.70cm3prot /g. +Multiplying by the estimated concentration of 40mg/ml one has the volume fraction α = +0.028. The hydration shell needs to be included as part of the protein because the dynamics +of water molecules in this shell is different from the one of bulk water due to the weak +interactions occurring between the protein and solvent molecules. +Gerstein and Chothia [63] showed that hydration water volume is equal to 24 Å3 which +means it is 20% smaller than the volume of bulk water. Hence, the increase of protein specific +volume due to its first hydration shell can be estimated as follows: +ν = νprot + νshellN +where N is the number of protein molecules in the unit volume and +νshell = rshell ·Awater +In the above equation rshell represents the radius of the spheres with the same volume of +water molecules in the first hydration shell and Awater is the surface area of the protein +accessible to solvent molecules with radius rshell. For lack of more precise estimations, in the +case of IF6, the value of νshell was approximated with the Surface Accessible Surface Area +(SASA) calculated on the crystallographic structure of aIF6. The obtained value corresponds +to a hydration layer composed by approximately 850 water molecules per protein molecule. +Hence, the final volume fraction α was found equal to 0.04. +As stated at the end of the previous section, the measurement of the protein concentration +in the final samples was made very difficult by the poor UV-VIS absorption of a/eIF6. As +a consequence, all values obtained from the considerations made above, which are strictly +dependent to the knowledge of the real protein concentration, have to be considered here as +strong approximations and they will be used only as references in the Results. +3.3 molecular dynamics setups +We performed all the stages of the molecular dynamics simulations using the AMBER9 +simulation code[27]. The whole set of final simulations for both the homologues used the +AMBER99SB force field [86]. The latter is an upgraded version of the AMBER94 force field, +usually used for protein molecular dynamics, and it contains a reparametrization of the back- +60 experimental and simulated systems setup +bone torsion terms and achieves a better balance of the different secondary structure elements. +3.3.1 System Setup +aIF6 +The initial configuration of the IF6 protein issued from the M.Jannaschii was taken from a +crystal structure with a refined resolution of 1.30 Å(available from the Protein DataBank with +the code: 1G61)[66] together with all the water molecules found within a distance of 2nm +from the protein center of mass in the crystallographic data. The coordinates of the missing +hydrogen atoms were added using the algorithms implemented in the LEaP program from +the AMBER9 package. +The protein was placed in a orthorhombic periodic box filled with water molecules +parametrized as TIP3P. The crystallographic water represented by oxygen atoms, within a +distance of 2nm from the protein center of mass, were replaced by the same type of water +molecule models. The final total amount of water molecules was 8136. The whole system +includes also 14 sodium (Na+) counterions in order to obtain a neutral global charge for the +Ewald calculations. +The whole system was initially minimized in two steps with combined use of steepest- +descent and conjugated-gradient algorithms: i) 200 cycles of conjugated-gradient after 4 steps +of steepest-descent with position restraint on protein atoms and counter ions; ii) 200 cycles +of conjugated-gradient after 4 steps of steepest-descent for the whole system without restraint. +As a preliminary step of the real molecular dynamics simulation, we first performed +a system equilibration step in which the simulated system attained a stable equilibrium +conformation compatible with the environmental constraints, i.e. constant pressure and +temperature. For this purpose, a short simulation of 150ps in a NVT ensemble, i.e. with +fixed total volume and temperature kept equal to 300K was performed, followed by a 700ps +long simulation in the final NPT ensemble, with T = 300K and P = 1bar. In all simulations +performed in this work the time-step used for the integration of motion equation was equal +to ∆t = 0.001ps = 1fs (fs is femto-seconds). The equilibration in the NVT ensemble was +made with the calculation of the contribution of the forces slowly-varying in space only every +3.3 molecular dynamics setups 61 +two steps, resulting in a shorter CPU-time without significant changes in the total energy of +the system. +From the equilibration at 300K and 1bar all other simulations branched to other NPT +conditions of interest. In every case the equilibration steps were followed by production +simulations of length equal to 2ns which was used for the calculation of dynamical properties +of the system itself. +In each simulation the control of temperature was performed with a Langevin thermostat3 +with a collision rate of 3.5ps−1, whereas pressure was constrained by a Berendsen barostat +relaxation time τp = 1.5ps. +3.3.2 eIF6 +The initial configuration of the IF6 protein issued from the S.cerevisiae was taken from a +crystal structure with a refined resolution of 2.5 Å(available from the Protein DataBank with +the code: 1G62)[66]. Nevertheless, the crystallographic data contained in the original PDB +file did not give the atom positions of the 21 amino acids long C-terminal tail which was +not crystallized with the rest of the proteolytic cleavage protein because of the structural +instability that was encountered in this work during the sample production, as mentioned in +Section 3.1.1. The presence of this tail, even though it does not seem to influence the function +of eIF6 [66], certainly has some effects on protein mobility [6]. +The construction of the complete structure of eIF6 required some supplementary steps with +respect to the case of aIF6. Firstly the structure of the C-terminal tail (CTAIL, in the following) +was modeled and partially folded. Secondly the complete structure was assembled and +equilibrated to an appropriate equilibrium state. +Both steps of this preliminary procedure were performed by means of molecular dynamics +simulations with implicit solvent in order to significantly reduce the CPU-time [198]. This +method consist of the substitution of the explicit calculation of the dynamics of solvent +molecules -usually very time-consuming - with an additional mean forces term in the protein +force-field which should take account of all solvent effects on the protein. This approach +3 The chosen collision rate for Langevin thermostat did not produce artifacts on IF6 dynamics as verified +by comparison of effective friction constant calculated from NPT ensemble with the one obtained from a +NVE (constant energy) simulation of the same system. Friction constant was estimated by memory function +calculation[118]. +62 experimental and simulated systems setup +clearly contains some strong approximations and it does not always give the right description +of dynamics if compared with explicit solvent calculations [146] but it is however a valuable +tool to rapidly explore the configuration space of large systems in order to find an appropriate +equilibrium state. The implicit solvent model used throughout this thesis was the pairwise +Generalized Born solvation model (GB), developed by Hawkins and coworkers [70, 71], +where mean forces are obtained from the estimation of the total solvation free energy of the +molecule into water. A complete description of the method can be found in many textbooks +on methods in computational physics and biology [12]. +ctail folding Here a brief summary of the protocol used for the modeling and the +initial folding of CTAIL is reported. The whole procedure was performed using the LEaP and +Sander programs from the AMBER9 package. +. A "linear" configuration was firstly created for the polypeptide with sequence shown in +Table 7. +. Initial folding of the linear structure was then performed in a NVT ensemble with the pro- +tocol for the temperature re-scaling shown in Table 10. The time step for the integration +of equation of motion was varied between 0.1 and 0.5 fs, in order to reduce the extent +of force variation and thus the probability of unnatural atom contacts which would +prevent the CTAIL from folding correctly. +Table 10: default +Total time Partial time Initial T Final T time step +[ps] [ps] Kelvin Kelvin [fs] +10 10 0 50 0.1 +260 250 50 100 0.5 +510 250 100 150 0.5 +560 50 150 200 0.5 +610 50 200 250 0.5 +660 50 250 300 0.5 +3.3 molecular dynamics setups 63 +. The final step of this procedure was a very long equilibration simulation in which the +protein fragment could fold. The total time length of this simulation was ∼ 40ns. A +shorter simulation with explicit solvent was also performed to verify the absence of +solvent-specific effects in CTAIL folding. +Interestingly, the final folded structure of CTAIL, shown in Figure 16 (Panel A), contains a +small helix in the region 14-18 whose shape is similar to an α-type. The inclusion of this helix +into the protein sequence corresponds to the one found in Section 3.1.1 by means of structure +prediction and hydrophobic arguments. +Figure 16: Modeling of CTAIL in implicit solvent. Panel A shows structure folded without contraints. +Panel B: structure folded with a position restraint in amino-terminus. Color scheme: purple +for α-helix, blue for 310-helix, cyan for turns and white for random coil. +It is worth noting that the folded configuration obtained here might not correspond to the +one that CTAIL would reach when folded together with the rest of the protein sequence. For +this reason, the same procedure was repeated with the amino-terminal position fixed in space +by an harmonic force, F = −Kx, with K = 10 kcal mol−1 Å2 . The resulting final structure +was compared with the previous one in order to better understand the effects of the spatial +constraints in the folding pathways. The resulting structure after a total simulation time of +40ns is shown in Figure (Panel B). Inspection by eye reveals that secondary and tertiary +structures are slightly different. This comparison indicate that CTAIL folding is very sensitive +64 experimental and simulated systems setup +to the number of degrees of freedom available for its three-dimensional configurations. +modeling of eif6’s complete structure The above paragraph showed the +importance of an ultimate verification of the actual conformations of CTAIL when the latter is +joined to the rest of the protein. A complete study on this subject would be out of the scope +of this thesis and would need a more exhaustive simulation of folding of the whole protein. +Here I would like to focus on more qualitative considerations about the effects induced on +the rest of the eIF6 structure by the presence of CTAIL. For this purpose, in the following it +will be supposed that the conserved region of aIF6 and eIF6 (residues 1-224) does not attain a +different fold in the presence of CTAIL. This assumption seems to be confirmed as reliable by +homology modeling study of different homologues of IF6 from a wide range of different +organisms [66]. +On these bases, another molecular dynamics simulation with implicit solvent was +performed on the system composed by CTAIL directly joined to the rest of "already-folded" +eIF6 structure. The initial configuration used for this simulation was composed by CTAIL +folded through the procedure described above and the crystallographic structure of eIF6. +The binding of the two subunits of the system was performed by the creation of the peptide +bond between the nitrogen atom in the C-terminus of the residue 224 and the nitrogen atom +in the N-terminus of CTAIL. The latter structure was then minimized with restraints in +atom positions in residues from 1 to 200 and with fixed hydrogen covalent bond-length (the +SHAKE algorithm[35] for rigid molecule dynamics was used here). The procedure consisted +of 900 steps of minimization using the steepest-descent gradient method followed by 1100 +steps performed with the conjugated-gradient algorithm. +The energy minimization was followed by a short equilibration run of molecular dynamics +(30ps) in a NVT ensemble, i.e. with constant volume and temperature. The Langevin +thermostat was used to keep temperature constant. Here, in order to significantly improve the +thermal coupling between the system and the thermostat a very high friction constant value +(γ = 500 ps−1). A short time step (∆t = 0.5 fs) for the Leapfrog integrator was used in order to +avoid improper fluctuations of potential energy which would result in total energy divergence. +Local optimization of the protein conformation found through the previous steps, was +performed using the simulated annealing method which consists, as for the real annealing of +3.3 molecular dynamics setups 65 +matter, in a sequence of heating and cooling phases. The latter, which is commonly used +for finding of the global minimum of potential surfaces in the case of small molecules, was +shown to not be reliable for systems with a broad distribution of energy scales. Nevertheless, +several works demonstrated that it remains very useful method for local optimization of +larger molecules conformations, such as proteins, because unlike minimization methods, it is +able to locate local minima even far away from the initial conformation[208]. The sequence of +annealing steps used in this work is shown in Table 11 and was performed with the same +parameters settings as the previous equilibration step. +Table 11: Simulated Annealing of eIF6’s complete structure +Total time Partial time Initial T Final T time step +[ps] [ps] Kelvin Kelvin [fs] +50 50 300 400 0.5 +100 50 400 400 0.5 +150 50 400 500 0.5 +200 50 500 500 0.5 +250 50 500 300 0.5 +300 50 300 300 0.5 +Figure 18 shows the time evolution of RMSD for the region 1-224 (hydrogens not taken +into account) with respect to the initial equilibrated conformation, expressed as a function of +time by the relatio√n:∑N(R (t) −R (0))2i i iRMSD(t) = (3.4) +N +where Ri(t) represents the position vector of the atom i at time t. In the same figure the +evolution of total potential energy during the simulated annealing is shown. Both results give +evidence of a new conformation far from the initial one and with a slightly lower energy.The +final structure is shown in Figure 17. +It is worth noting that, after minimization and simulated annealing, the root-mean-square- +deviation of the eIF6 backbone in region 1-224 with respect to the original crystallographic +66 experimental and simulated systems setup +Figure 17: Final structure issued from the minimization and simulated annealing procedures. +structure is however small (1.5Å), meaning that, although the core region of eIF6 moved away +from its initial minimum, its global arrangement is not significantly changed by the presence +of CTAIL, at least on the time scale explored here. +The structure resulting from the sequence of procedures discussed above, was used as +initial structure for molecular dynamics simulations performed with explicit solvent and +with the same protocol used in the case of aIF6. +supplemental samples In order to compare results from molecular simulations with +the experimental measurements and to obtain more insights into the dynamical and structural +effects of CTAIL, two other samples were modeled and analyzed (they are reported here with +the short names used through out this thesis to refer to them): +. eIF6-NoCTAIL: the eIF6 simulated without the attached CTAIL. The crystallographic +structure was used as initial configuration after a preliminary step of minimization to +let it attain an equilibrium conformation compatible with the buffer environment. Due +to the low resolution of x-ray data, any crystallographic water was found in the initial +PDB file. All buffer molecules were modeled as made for aIF6. +3.3 molecular dynamics setups 67 +Figure 18: Time evolution of RMSD for the region 1-224. Insert: evolution of potential energy of +the whole protein during the annealing procedure. Both quantities use the previously +equilibrated conformation as reference (see text for more details). +. aIF6-htagged: As explained in Section 3.1.1, for technical reasons due to the specific experi- +mental setup, high pressure measurements were performed on samples produced with +a specific tag of six consecutive histidines (His-tag) which significanlty improved the +yield of the production protocol. In order to compare these measurements with those +obtained from molecular dynamics, the structure of aIF6 complexed with the His-tag +was modeled following the same procedure used for the global structure of eIF6. +Both samples were simulated following the protocol used for aIF6 and eIF6. + +4 +CHARACTER IZAT ION OF PROTE IN STRUCTURE +In the next chapters a new method for the characterization of protein secondary structure +will be presented. The development of this method, called ScrewFit, was inspired by the task +of finely characterize the environmental effects on protein structures. +ScrewFit was then found to be able to make precise assessments on protein secondary +structure motifs and also to find local and global structural effects induced by ligand binding. +The text proposed here has been already published or is under review as scientific articles +in international peer-reviewed journals. The original text is reprinted here together with +supplemental data and notes at the end of each article. +Next chapters formerly appeared as the following scientific articles: +Kneller, G.R. and Calligari, P. Efficient characterization of protein secondary structure in +terms of screw motions. Acta Crystallographica D, 62, 302-311 (2006). +Calligari, P. and Kneller G.R., ScrewFit: a novel approach for continuum protein secondary +assessments. Submitted (2008). +Another application of the method ScrewFit can be found in: +Calligari, P. et al., Inhibition of viral group-1 and group-2 neuraminidases by oseltamivir: +a comparative structural analysis by the ScrewFit algorithm. Biophysical Chemistry, +accepted for publication (2008). +69 + +5 +EFF IC IENT CHARACTER ISAT ION OF PROTE IN SECONDARY +STRUCTURE IN TERMS OF SCREW MOTIONS +We present a simple and efficient method to describe the secondary structure of proteins in +terms of orientational distances between consecutive peptide planes and local helix parame- +ters. The method uses quaternion-based superposition fits of the protein peptide planes in +conjunction with Chasles’ theorem, which states that any rigid body displacement can be +described by a screw motion. From the best superposition of consecutive peptide planes we +derive the helix parameters, and the “worst” fit is used to define the orientational distance. +Applications are shown for standard secondary structure motifs of peptide chains, for some +proteins belonging to different fold classes, and for a description of structural changes in +lysozyme under hydrostatic pressure. In the latter case we use published reference data which +have been obtained by X-ray crystallography and by structural NMR measurements. +71 +72 efficient characterisation of protein secondary structure in terms of screw motions +5.1 introduction +The determination and characterisation of protein secondary structure is a fundamental +task in molecular biology, crystallography and in simulation studies. In many situations +arises the necessity to quantify in particular structural changes of a protein, which are due +to a change of its environment. The influence of temperature or pressure on the fold of a +protein is a typical example. Standard motifs in protein secondary structure are traditionally +described in terms of two torsional angles, φ and ψ, per residue, which define for each +Cα-atom the rotation of the left and right peptide plane about the N−Cα and Cα −C +bond, respectively [187]. In the past different methods have been developed to determine +secondary structure elements [106, 163, 57, 190] and to describe their geometry in more +detail [9, 181, 194]. A rigourous mathematical description of protein secondary structure +can be obtained by applying the theory of screw motions, where the winding of the protein +backbone is described in terms of local helix parameters. The theory of screw motions goes +back to the mathematician M. Chasles [32, 33], and a useful recent introduction can be found +in the book by Selig [176]. In a recent paper, Quine [155] uses screw motion theory and +constructs local helix parameters for a protein from the torsion angles φ and ψ. An important +step is the introduction of quaternions which can be related to the (φ,ψ)-angles on one hand, +and to the rotation/helix axis on the other hand. +In this article we present an efficient method for the characterisation of protein secondary +structure, which is based on quaternion superposition fits of consecutive peptide planes. +From the resulting quaternion parameters we construct the local helix geometry of the protein +backbone, and we show that the superposition method may also be used to define a scalar +measure for the orientational distance between consecutive peptide planes. The latter allows +to distinguish between all common secondary structure motifs, such as different helix types +and β-strands, except for handedness. +In the following section the method is briefly explained and applications are presented in +Section 5.3. The first one concerns an illustration for simple model structures, such as right- +and left-handed α-helices and β-strands. We show then how our method works for proteins +which fall into different fold classes, and discuss finally in more detail how it can be used +to quantify changes in the secondary structure of lysozyme which are caused by external +pressure. For this purpose we use published reference structures which have been obtained +from X-ray crystallography and from structural NMR measurements. The essential results are +summarised and discussed in Section 5.4. In the Appendix we recall the essential properties +5.2 method 73 +of quaternions and give a short constructive proof of Chasles’ theorem, which demonstrates +the usefulness of quaternion calculus. +5.2 method +As stated in the introduction, our method for the description of protein secondary structure +relies on quaternion-based superposition fits of molecular structures. The method is well +established, and we refer to articles by Kearsley [111] and by Kneller [115] for details. Here +we use that the quaternion method does not only yield the “best” fit, from which local helix +parameters describing the winding of the protein backbone can be constructed, but also the +“worst” fit, from which an orientational distance measure can be derived. +5.2.1 Quaternion superposition fits +Suppose that {r } and {r ′~α ~α} are two sets of vectors describing the positions of atoms repre- +senting equivalent molecular structures A and B, respectively. Both structures contain the +same number of atoms and are somehow placed in space. A rigid-body displacement A→ B +can be defined as an optimisation problem, where structure A is fitted onto structure B in a +least squares sense. In case that both structures are identical, the resulting fit error will be +zero. One starts by constructing the translation vector ~t = ~R ′ − ~c Rc connecting the two centres +of rotation, C and C ′, which are to be chosen in the same way for A and B, and computes +the coordinate sets {x } and {x ′α α} containing the relative atomic positions to the respective +rotation centres. Here and in the following the prime refers to the target structure B. The +optimal rotation is obtained by minimising the target function +∑N +m(q) = w (D · x − x ′ 2α α α) (5.1) +α=1 +with respect to a set of angular variables which parametr∑ise the orthogonal rotation matrix +D. Each atom is assigned a positive weight wα, with αwα = 1. A convenient set of +angular variables are normalised (real) quaternion parameters, q ≡ {q0,q1,q2,q3}, with +q2 + q2 + q2 + q20 1 2 3 = 1. In this case D takes the form [4] +  + q20 + q21 − q22 − q2 3 +2(−q0q3 + q1q2) 2(q0q2 + q1q3)  +D(q) =  2(q q + q q ) q2 + q2 − q2 − q2 2(−q q + q q )  (5.2)0 3 1 2 0 2 1 3 0 1 2 3 +2(−q0q2 + q1q ) 2(q q + q +2 2 2 2 +3 0 1 2q3) q0 + q3 − q1 − q2 +74 efficient characterisation of protein secondary structure in terms of screw motions +and describes a proper rotation with det(D) = +1. Using the orthogonality of D, the target +function m(q) can be written as a quadratic form in the quaternion parameters, +m(q) = qT ·M · q, (5.3) +where q = (q ,q ,q ,q )T0 1 2 3 is a column vector and M is a positive semi-definite matrix. The +superscript “T” denotes a transposition. The matrix M has the form [111, 115] +∑  N (x − x ′ 2 T α α) uαM = w α  , (5.4) +α=1 uα Pα +where uα and Pα are given by +u = 2x ∧ x ′α α α, (5.5) +P = x · x ′T + x ′ · xTα α α α α. (5.6) +The minimization of m(q) with respect to the quaternion parameters must be performed +with the side constraint qT · q = 1. Using the method of Lagrange multipliers one is lead +to the eigenvector problem +M · q = λq. (5.7) +Sincem(q) > 0 the matrixM is positive semi-definite, and one obtains a set of four real eigen- +values, {λj}, with λj > 0 (j = 1, . . . , 4), and a set of corresponding orthonormal eigenvectors, +{q }, with qTj j · qk = δjk. Here δjk is the Kronecker symbol. It follows from (5.3) and (5.7) that +m(qj) = λj. (5.8) +The eigenvalues are thus the residuals of the fit and can be ordered such that +λ1 6 λ2 < λ3 6 λ4. (5.9) +The quaternion corresponding to the smallest eigenvalue, λ1, is thus the solution for the +optimal fit, and the quaternion parameters q describe the relative orientation of {x ′1 α} with +respect to {xα}. +We note that one obtains two twofold degenerate eigenvalues if the structures to be +superposed are linear. In this case one has [115] +∑ ( ) +λ = w |x |2 + |x ′ |2 ∓ 2|x ||x ′a,b α α α α α| , (5.10) +α +5.2 method 75 +where a = 1, 2, b = 3, 4, and both the rotation leading to the minimum and maximum distance +are not uniquely determined. Any normalized linear combination of the two eigenvectors +associated with λa and λb, respectively, describes an equivalent rotation. +The use of quaternion parameters in not only very convenient for finding a rigid-body +transformation between two sets of coordinates, but the result can also be directly related to +conventional representations ofrotations. Here the following relation is of importance: +q ≡ q0  cos(φ/2)=  . (5.11) +qv sin(φ/2)n +From the scalar part of a quaternion, q0, one obtains thus directly the rotation angle and +the rotation axis can be extracted from the vectorial part, qv. It should be noted that the +transformation φ → φ+ 2π, which leaves the rotation matrix D(n,φ) invariant, leads to a +global change in sign of the quaternion parameteres. One verifies easily that q(n,φ+2π) = −q. +The pair of quaternions {Q,−Q} is thus mapped onto the same rotation matrix D(q). +5.2.2 Orientational distance +The eigenvalue describing the “worst” superposition – λ4 according to the ordering scheme +(5.9) – can b√e used to define an orientational distance between two molecular structures via +M11 +∆Ω = . (5.12) +λ4 +Eq. (5.4) shows that the matrix elementM11 contains the squared Euclidean distance between +the vectors sets {x } and {x ′~α ~α}, and therefore ∆Ω is the Euclidean distance normalised to its +maximum possible value. Consequently, +0 6 ∆Ω 6 1. (5.13) +It is important to note that definition (6.5) yields a unique orientational distance of two +linear molecular structures, whose relative orientation has no unique description in terms +of angular variables. Supposing that |x ′α| = |xα| for α = 1, . . . ,N, we see from eq. (5.10) that +for linear rigid bodies ∆Ω = 0 in the parallel configuration and ∆Ω = 1 in the anti-parallel +configuration. We note here that λb, as given by eq. (5.10), is a strict upper limit for the +Euclidean distance of two molecular structures in general [116]. +76 efficient characterisation of protein secondary structure in terms of screw motions +5.2.3 Chasles’ theorem +T −→Let r = (x,y, z) be a column vector containing the coordinates of a radius vector ~r = OP +of a point P in a rigid body, where O is the origin of the coordinate system. An arbitrary +rigid-body displacement is described by a rotation about a point C, which is not necessarily +located inside the rigid body, and a subsequent translation. Let Rc be the coordinates of +−→ −−→ +the radius vector ~R = OC and let t be the coordinates of the translation vector ~t = CC ′c , +where C ′ is the centre of rotation after the translation. The coordinates of P after a rigid body +displacement are then given by +r ′ = Rc +D · (r−Rc) + t, (5.14) +where D is an orthogonal 3× 3 matrix. In the following only proper rotations with det(D) = ++1 will be considered. If n = (n ,n ,n )Tx y z contains the components of the unit vector n~ , +pointing in the direction of the rotation axis, and φ is the angle of rotation, the corresponding +rotation matrix can be written as +D(n,φ) = P‖ + cos(φ)P⊥ + sin(φ)N, (5.15) +where P = n ·nT‖ and P⊥ = 1 −P‖ are, respectively, the projectors onto n~ and its complement, +and N is the antisymmetric matrix + 0 −nz ny +N =   + +n 0 −n  . (5.16)z x +−ny nx 0 +The theorem of Chasles states that one can find a reference point X, whose radius vector +−→ +~Rx = OX has the coordinates Rx, such that +r ′ = Rx +D(n,φ) · (r−Rx) +αn. (5.17) +This coordinate transformation describes a screw motion, with translation α parallel to +the axis of rotation. For the following considerations we introduce the difference vector +~u = ~R − ~x Rc. Equating relations (5.14) and (5.17) and using that n is an eigenvector of D, one +finds that the coordinates of ~u satisfy the following set of linear equations +(1 −D) · u = t⊥. (5.18) +Here t⊥ = P⊥ · t. As shown in Section 5.5, the above equation has a linear manifold of +solutions, +u(λ) = u⊥ + λn, λ ∈ R, (5.19) +5.3 applications 77 +where u⊥ is perpendicular to n and has the explicit form +1( ) +u⊥ = t⊥ + cot(φ/2)n∧ t . (5.20) +2 +In absolute coordinates the axis of the screw motion is given by +Rx = Rc + u⊥ + λn, (5.21) +and +R⊥x = Rc + u⊥ (5.22) +contains the coordinates of the radius vector ~R⊥ relating the origin with the point X⊥x on the +helix axis which is closest to the reference point C. In the following X⊥ will be referred to +as centre of screw motion. The radius ρ of the corresponding screw motion is given by the +Euclidean length of u , since the latter is the vector pointing from ~R to X⊥~⊥ c . Using (5.20) one +finds +√ +|t⊥| +ρ = 1+ cot2(φ/2). (5.23) +2 +It should be noted that ρ diverges if φ is a multiple of 2π, corresponding to pure translations, +and if |t⊥| 6= 0. +5.3 applications +5.3.1 Screw motion description of protein main chains +The method described above, which will be referred to as ScrewFit in the following, is now +applied to define the local helical structure of polypeptides and proteins. The rigid bodies are +here the triangles formed by the atoms {O,C,N} in the backbone of polypeptides – see Fig. 19 +– which define the so-called peptide planes. Here the C-atoms are the centres of rotation, and +the translation vectors are thus the position differences between the C-atoms in consecutive +amino acids, ti = RC(i+1) −RC(i). The quaternion parameters qi are obtained from the fit of +the {O,C,N}-triangle of peptide bond i onto the one of peptide bond i+ 1. From each set of +quaternion parameters the direction n~ of the rotation axis and the rotation angle φ can be +computed from relation (6.4). +The following parameters are used to define the local helix structure of a polypeptide: +• The helix radius ρ defined in eq. (6.6). +78 efficient characterisation of protein secondary structure in terms of screw motions +• The number of amino acids per turn, +2π +τ = . (5.24) +φ +• The pitch, which is defined as +p = |R⊥ −R⊥x,i+1 x,i|τ. (5.25) +Here ~R⊥ is the radius vector pointing from the origin to the centre X⊥x,i i of the screw +motion relating peptide plane i and peptide plane i+ 1. +• The handedness, which is defined as the sign of the projection of the translation vector +~ti onto the direction n~ i of the local helix axis, +h = sign(nTi · ti). (5.26) +• The straightness parameter σ of the local helix axis. For residue i the latter is defined as +σ = µTi i · µi+1, (5.27) +where +R⊥x,i+1 −R +⊥ +x,i +µi = . (5.28) +|R⊥ ⊥x,i+1 −Rx,i| +• The orientational distance between the peptide planes {O,C,N} in residues i and i+ 1, +which is defined through relation (6.5). +5.3.2 Model structures +We apply ScrewFit first to well-known model structures for polypeptides which have been +taken from the Image Library of Biological Macromolecules in Jena 1. Table 13 shows the +corresponding local helix parameters which have been defined in the previous section. All +model peptides are polyalanine molecules containing 10 residues, except for the extended +conformation, which is represented by the alanine-tripeptide shown in Fig. 19. In all cases +the N-terminus is the starting point of the respective polypeptide chain. In the context of our +study all motifs are considered as helices, a β-strand being simply a thin left-handed helix +with 2 amino acids per turn2. +1 Institute-of-Molecular-Biotechnology-Jena:http://www.imb-jena.de/IMAGE.html +2 See also note 5.6 at the end ot this article. +5.3 applications 79 +Figure 19: A tri-peptide with two peptide bonds in the extended conformation, where the symbol “R” +stands for non-specified side-chains. The screw motion relating the yellow triangles formed +by the {O,C,N} atoms of the peptide planes defines the local helix which is schematically +represented by the cylinder in purple and the corresponding screw arrow. The radius of the +cylinder corresponds to the radius of the screw motion. +Table 12: Helix parameters for different model structures. Here ρ is the helix radius with the C-atom +of the peptide plane on the helix surface, ρ is the corresponding radius if the C-atom is +Cα +replaced by the Cα-atom, τ is the number of residues per turn, h is the handedness, and σ +the straightness parameter. The latter equals 1 for all model structures, since none is curved. +The straightness parameter for the extended conformation cannot be defined, since the model +structure for the latter consists of only three residues (see Fig. 19). More explanations are +given in the text. +Motive ρ [nm] ρ [nm] τ pitch h σ ∆ +Cα Ω +α-helix (R) 0.171 0.227 3.62 0.556 + 1 0.582 +α-helix (L) 0.171 0.227 3.62 0.556 − 1 0.582 +3-10 helix 0.146 0.203 3.28 0.589 + 1 0.670 +π-helix 0.178 0.258 4.16 0.558 + 1 0.471 +β-strand 0.055 0.093 2.03 0.671 − 1 0.875 +extended 0.037 0.055 2.00 0.725 − 0.754 +80 efficient characterisation of protein secondary structure in terms of screw motions +The parameters concerning the different secondary structure motifs shown in Table 13 may +be compared to those published in the study of Barlow and Thornton [9]. Here one must pay +attention to the fact that the helix radius depends on the reference point which is chosen to +lie on the helix surface. In our case this is the carbon atom in the {O−C−N} peptide plane. +If the carbon Cα-atom is chosen instead, we find the values given in the column with the +header “ρ ”. +Cα +The parameters we find for the right-handed α-helix are very close to the ones given +by Barlow and Thornton, who compare different standard definitions with average values +computed from a set of 291 helices in “real” proteins. The parameters listed in the above +reference are in the intervals 0.23 6 ρ 6 0.24, 3.54 6 τ 6 3.67, and 0.52 6 p 6 0.55, +respectively, using our notation and units (ρ and p in nm). In case of the 3-10 helix the +spread of the parameters given by Barlow and Thornton is 0.18 6 ρ 6 0.20, 3.0 6 τ 6 3.2, +and 0.58 6 p 6 0.60. Parameters for π-helices are not listed. It should be noted that the +orientational distance takes well distinguishable values for the different secondary structure +motifs, but left and right-handed motifs cannot be distinguished by this parameter. +5.3.3 Proteins in different fold classes +In the following we will show the results of ScrewFit for proteins which fall into the four +main fold classes according to the SCOP scheme [145]: +1. Carbonmonoxy-myoglobin (PDB code 1A6G), which belongs to the “all alpha” class. +2. Protease inhibitor ecotin (PDB code 1ECY), which belongs to the “all beta” class. +3. Triose phosphate isomerase from chicken muscle (PDB code 1TIM), which belongs to +the “alpha/beta” class. Proteins falling into this class consist mainly of parallel β-sheets, +which are separated by α-helices. +4. Hen egg white lysozyme (PDB code 193L), which falls into the “alpha + beta” class. Pro- +teins of this type contain mainly anti-parallel β-sheets and separated regions containing +α-helices. +The latter application is postponed to the next section, where we consider structural changes +of lysozyme under pressure. In this context the ScrewFit parameters will also be discussed in +more detail. Here we give only an impression of the results, as compared to DSSP. +Figs. 20 to 22 shows the comparison first three proteins in the list given above. In each figure +we give the local orientational distance, ∆Ω, the local helix radius, ρ, and the straightness +5.3 applications 81 +Figure 20: ScrewFit description of the main chain of Carbonmonoxy-myoglobin (PDB code 1A6G, “all +alpha” in the SCOP scheme). The vertical green stripes indicate α-helices found by the +DSSP method and the horizontal lines indicate the reference values given Table 13. +Figure 21: ScrewFit description of the main chain of Protease inhibitor ecotin (PDB code 1ECY, “all +beta” in the SCOP scheme). The vertical blue stripes indicate β-strands found by the DSSP +method and the horizontal lines indicate the reference values given in Table 13. +82 efficient characterisation of protein secondary structure in terms of screw motions +Figure 22: ScrewFit description of the main chain of Triose phosphate isomerase (PDB code 1TIM, +“alpha/beta” in the SCOP scheme). The vertical green and blue stripes indicate, respectively, +α-helices and β-strands found by the DSSP method. The green and blue horizontal lines +indicate the respective reference values from Table 13. +parameter, σ. All calculations have been performed on the basis of the respective entries in +the Brookhaven Protein Data Bank (PDB). The vertical stripes correspond to the secondary +structure motifs found by the DSSP method by Kabsch and Sander, which is based on +hydrogen bonding criteria and which is widely used for the determination of secondary +structure elements in proteins [106]. The colouring scheme indicates α-helices in light green +and β-strands in light blue. +One recognises that the ScrewFit method often leaves some ambiguity concerning the +boundaries of secondary structure elements. This is simply due to the fact that it is sensitive +to deviations from ideal geometries. This effect is in particular visible in the behaviour of +straightness parameter. Similar observations have been made by comparing the method by +Barlow and Thornton with DSSP [9]. +5.3.4 Lysozyme under hydrostatic pressure +In the following we apply our method to visualise structural changes in lysozyme due to the +application of an external pressure. For this purpose we consider protein structures which +have been obtained from X-ray crystallography and from NMR measurements. The X-ray +structures are taken from the entries 193L and 3LYM of the Brookhaven Protein Data Bank +(PDB), which contain the atomic coordinates of hen egg-white lysozyme at pressures of, +5.3 applications 83 +respectively, 1 bar and 1 kbar [202, 121]. The NMR structures are taken from PDB entries +1GXV and 1GXX, corresponding to 1 bar and 2 kbars, respectively [159]. Fig. 23 shows +the backbone of lysozyme at 1 bar (blue tube) obtained from the crystal structure together +with the line joining the centres of screw motion mapping each peptide plane onto the +consecutive one (red line). The centres of the screw motions have been constructed according +to expression (5.22). Inspection by eye shows that that the red line passes right through the +geometrical centres of the helices. +More details can be obtained from Figs. 24 and 25 which show the same parameters as +in Figs. 20 to 22. In both cases the curves corresponding to the structures under pressure +are given in red. The green and blue horizontal lines correspond again, respectively, to the +reference values for an α-helix and a β-strand given in Table 13. Here the vertical stripes +indicate the secondary structures according to the PDBsum data base. The latter uses the +PROMOTIF program for secondary structure determination [89], which is itself based on the +DSSP method. In addition to α-helices we indicate also 3-10 helices in dark green. +For the crystal structure entries 193L and 3LYM the PDBsum database displays three long +helices in the residue intervals {5− 14}, {25− 36}, and {89− 99}, and four short ones in the +residue intervals {80− 84}, {104− 107}, {109− 114}, and {120− 123}. In addition three short +β-strands of 2–3 residues are displayed in the regions {43 − 45}, {51 − 53}, and {58 − 59}, +respectively. We note here that only the long helices are described in the work by Barlow and +Thornton [9]. Concerning the NMR structures, the PDBsum database lists again the three +long helices ({5− 14}, {25− 36}, {89− 98}), but only two short ones ({80− 84}, {109− 114}). In +contrast, the short β-strands are displayed at almost the same positions as for the crystal +structures ({44− 46}, {50− 53}, {58− 59}). As for the crystal structures, the structural motifs +are found for both pressures at identical positions. +Looking first at Fig. 24 displaying the parameters corresponding to the crystal structures +shows that the orientational distance is a good measure to localise rapidly secondary structure +elements in the amino acid sequence of a protein. For the moment we discuss only the +structure at ambient pressure. The analysis of the helix radius and the straightness gives +more detailed information. The three long helices and also the three short β-strands are +easily localised. We find that the first helix ({5− 14}) is straight only in the region {5− 11}. +Towards the C-terminus the straightness drops considerably and the orientational distance +rises. The helix radius stays approximately constant up to about residue number 15. We +find that the second helix ({25− 36}) is deformed as well towards its C-terminus, but here +the orientational distances stays more or less constant, whereas the helix radius and the +84 efficient characterisation of protein secondary structure in terms of screw motions +Figure 23: Minimal model for Lysozyme at normal pressure. The red line joins the centres of screw +motions, X⊥, mapping each peptide plane onto the following one. +straightness change considerably. We consider this helix to be straight in the range {25− 32}. +Similar observations can be made for the third long helix, which we find to be straight in the +range {89− 96}. We note here that Barlow and Thornton consider the first of the above helices +as “irregular” and the others as “curved”, using, however, different criteria. Concerning the +shorter helices, which are not considered helices by Barlow and Thornton, we confirm less +well defined helices in the ranges {80− 84}, {104− 107}, {119− 123}, and {109− 114}. According +to the orientational distance, the first three of them are 3-10 helices. As for the β-strands, our +analysis would confirm the short one in the range {58− 59}, but yield longer strands in the +regions {42− 46} and {50− 53}. It is worthwhile mentioning that the straightness parameter +indicates hairpin turns between the β-strands, leading to antiparallel β-sheets. +Applying ScrewFit to the NMR structure of lysozyme at ambient pressure yields the +following results: the three long helices indicated by PDBsum are retrieved, and, using the +orientational distance as criterion, we confirm less well defined helices in the ranges {80− 84} +(3-10 helix) and {109− 114} (α-helix). According to our analysis the first β-strand is longer +than the one displayed in the PDBsum database (approximately in {41− 45}). +Let us now look at the changes in secondary structure of lysozyme due to the exertion +of an external pressure. We start with the analysis of the crystallographic data by Kundrot +and Richards [121]. The black line in Fig. 26 shows that the structural change obtained from +the crystal structures is localised at residue no. 72. All parameters show a change in the +5.3 applications 85 +Figure 24: ScrewFit description of Lysozyme for crystallographic structures at pressures of 1 bar (black +line) and 1 kbar (red line) (PDB entries 193L and 3LYM) [202, 121]. According to the SCOP +scheme lysozyme falls into the “alpha+beta” class. The horizontal lines show the reference +values given in Table 13 and the vertical stripes indicate here the secondary structures +according to the PDBsum database. More explanations are given in the text +. +Figure 25: The same as Fig. 24, but for NMR structures at 1 bar (black line) and 2 kbar (red line) [159]. +86 efficient characterisation of protein secondary structure in terms of screw motions +same place. Fig. 27 shows the change of straightness of the crystal structure of lysozyme in a +tube representation, using a colouring scheme where red corresponds to a negative change, +green to no change, and blue to a positive change. In their study Kundrot and Richards +perform a difference distance matrix analysis of the structural changes and report that the +least changes are seen in helix 2 ({25− 36}) and in the loop and β-sheet region {42− 60}, +whereas a stronger structural change is seen in region {61− 87}, which appears to expand. +We note here that Kundrot and Richards call this region “loop region”, not counting the short +3-10 helix {80− 84}. This observation is coherent with ours, which shows in particular a strong +rise of the local helix radius at residue 72, corresponding to a swelling of the corresponding +loop region. +Figure 26: Differences for the parameters shown in Figs. ?? and 25 (X-ray crystallography = black line, +NMR = magenta line). +The corresponding analysis for the NMR structures is less clear (see Fig. 25, magenta +lines). Here the orientational distance and the helix radius do not exhibit significant changes, +whereas the straightness shows a strong decrease at residue no. 60. which is located at the +very beginning of the long loop in residue range {60 − 80}. Refaee et al. report the most +extensive deformations in the loop and what they call “β-sheet domain” ({40− 88}), which is +certainly in agreement with a very localised change in secondary structure at residue no. 60. +We do, however, not see considerable changes in the hairpin turns {47− 49} and {54− 57} seen +by Refaee et al.. Fig. 28 shows the change in straightness for the NMR structure of lysozyme +in a tube plot in which the same colouring scheme is used as in Fig. 27. +5.4 conclusion 87 +Figure 27: Change in straightness between the crystallographic structure of lysozyme at 3 kbar and +1 bar. The colouring scheme is chosen such that blue, green, red correspond to, respectively ++2 (maximum positive change), 0, and -2 (maximum negative change). +Figure 28: Change in straightness between the NMR structure of lysozyme at 2 kbar and 1 bar. The +colouring scheme is the same as in Fig. 27. +5.4 conclusion +We have presented a simple method – ScrewFit – for the characterisation of protein secondary +structure which uses quaternion-based superposition fits of consecutive peptide planes in +88 efficient characterisation of protein secondary structure in terms of screw motions +the backbone. The combined use of the quaternion fit method and Chasles’ theorem allows +to express protein secondary structure in terms of local helix parameters. The superposition +method yields also an orientational distance measure for consecutive peptide planes. The +latter is obtained from the “worst” possible quaternion fit and yields a simple measure for the +rapid localisation of secondary structure elements along the protein backbone. The analysis +of standard motifs of protein secondary structure and of proteins belonging to different fold +classes showed that all common motifs are well discriminated by the orientational distance +measure, and that the straightness parameter and the helix diameter are useful to characterise +non-ideal secondary structure elements, keeping a minimal set of parameters. +Using ScrewFit to study conformational changes in Lysozyme due to application of an +external pressure revealed different localised changes in the loop regions. The structural +changes extracted by difference distance matrix analysis from the crystallographic data could +be confirmed, giving, however, a more precise description of these changes. Concerning the +NMR structures, we find the essential conformational changes in a different position than the +authors of the reference article, although both results agree in so far, as the changes are found +in the same region. Prior to these analyses we tested that the localisation of the essential +secondary structural elements found by crystallography and NMR is confirmed. +ScrewFit allows to pinpoint secondary structure changes precisely, which is more difficult +to achieve by the standard analysis of positional differences. The reason is that the latter +might indicate important structural differences in a large region, although the corresponding +position differences are induced by one single localised change in the winding of the protein +backbone. +A point which should also be mentioned is the numerical efficiency of the quaternion- +based superposition algorithm we use as a basis of our method. The superposition of two +molecular structures can be performed in a few millisceconds [115], and this fact has been +exploited in many studies of rigid body motions in molecular systems, using the molecular +dynamics analysis package nMoldyn [120, 166]. Using the method presented in this article, +the characterisation of the secondary structure of a protein can be done in about a second on +a normal PC, and this efficiency could for example be used in database-oriented applications +and for analyses of molecular dynamics trajectories of proteins. In this context it is important +to note that the protein backbone can be completely reconstructed from the helix parameters +defined in this article. This is an interesting aspect for homology modelling. Another useful +application could be the characterisation of structural variability in different structural models +which are used to construct protein 3D structures from NMR distance data. +5.5 mathematical background 89 +5.5 mathematical background +5.5.1 Quaternions +Quaternions are hypercomplex numbers which are composed by linear superposition of one +real unit element 1 and three imaginary imaginary unit elements I, J,K. The latter satisfy +the non-commutative algebra I2 = J2 = K2 = −1 and IJ = −JI = K (cycl.). An arbitrary +quaternion Q is written as Q = q01 + q1I+ q2J+ q3K, where qj ∈ R (j = 0, . . . , 3). The +component q0 is called the scalar component, and {q1,q2,q3} are the vectorial components. +It is useful to introduce the column vector q = (q ,q ,q )Tv 1 2 3 comprising the three vectorial +components of a q√uaternion. Analogously to complex numbers, the length of a quaternion is +defined as ‖Q‖ = q2 + q2 + q2 + q2 and its conjugate is given by Q∗0 1 2 3 = q01 − q1I− q2J− +q3K. +Let A and B be quaternions with components {a0,a1,a2,a3} and {b0,b1,b2,b3}, respec- +tively. The components of C = A±B are obtained by cj = aj ± bj (j = 0, . . . , 3) and from the +algebra of the imaginary elements one finds that the components of the product C = AB are +givenby    +c   a b − aT0 0 0 v · bv = , +cv a0bv + b0av + av ∧ bv +where “∧” denotes a vector product. In general AB 6= BA. The inverse of a quaternion A is +defined as +A∗ +A−1 = ‖ ‖ .A 2 +Due to the non-commutative algebra of quaternions one has in general A−1B 6= BA−1. +Similarly to complex numbers of unit length, which represent rotations in the plane, +normalised quaternions represent rotations in space. Let r = (x,y, z)T a column vector +comprising the components of a radius vector ~r, let R = xI+ +yJ+ zK be the corresponding +spatial quaternion and let Q be a normalised quaternion with ‖Q‖ = 1. One finds that the +scalar component of R ′ = QRQ∗ vanishes too, and that the vectorial components of R ′ are +given by +r ′ = D · r, +where D represents the rotation matrix (6.2). The bilinear transformation R ′ = QRQ∗ repre- +sents thus a rotation in space. +90 efficient characterisation of protein secondary structure in terms of screw motions +5.5.2 Helix parameters in Chasles’ theorem +Chasles’ theorem can be easily proven using quaternion algebra. For this purpose we start +from Eq. (5.18) and introduce the spatial quaternions U and T⊥, representing, respectively, +the column vectors u and t⊥. Expressed in quaternions, Eq. (5.18) becomes +U−QUQ∗ = T⊥. +Multiplication with Q from the right and using that Q∗Q = 1 yields +UQ−QU = T⊥Q. +Using the multiplication rule for quaternions, the above equation can be expressed in the +form      + −uT · q Tv   −qv · u   −t⊥ · qv − = . +q0u+ u∧ qv q0u+ qv ∧ u q0t⊥ + t⊥ ∧ qv +Herewe can make use of relation (6.4) +q0  cos(φ/2)= , +qv sin(φ/2)n +from which we conclude that t⊥ · qv = 0, since t⊥ ⊥ n. We are thus left with the vector +equation    + 0   0 =  , +2u∧ qv q0t⊥ + t⊥ ∧ qv +which can be reduced to +1( ) +n∧ u = − cot(φ/2)t⊥ + n∧ t⊥ (5.29) +2 +if φ 6= 2kπ (k ∈ Z). Now one can apply on both sides a vectorial multiplication with n, using +that n∧ (n∧ a) = −a for an arbitrary column vector a. This yields +1( +⊥ ) +u⊥ = t⊥ + cot(φ/2)n∧ t , +2 +if one uses that n∧ (n∧ t⊥) = −t⊥ and that n∧ t⊥ = n∧ t. Relation (5.20) is thus proven. +The general solution of Eq. (5.29) has obviously the form +u(λ) = u⊥ + λn, λ ∈ R, +5.5 mathematical background 91 +which shows that u⊥(λ) is the solution of minimum length. +Acknowledgements: All figures containing molecular graphics have been generated using +the VMD code for molecular dynamics simulation and visualisation of biomolecules [88]. The +screw motion calculations have been performed with modules from the MMTK package [79]. +92 efficient characterisation of protein secondary structure in terms of screw motions +5.6 notes +[i] It is worth to note here that, in the context of ScrewFit algorithm, all motifs are +considered as helices, a β-strand being simply a thin left-handed helix with 2 amino acids +per turn. This fact can be easily seen in Fig. 29 where the blue cylinder represent the extent of +the helix obtained according to the definition of the C-atom of the peptide plane lying on the +helix surface, for the right-handed α-helix and the β-strand. +Figure 29: Visualisation of a straight right-handed α-helix (left-side) and a straight β-strand (right-side) +in terms of the local helix parameters given in Table 1. The arrow indicates the direction of +the helix axis. Here the hydrogen atoms. +6 +SCREWFIT: A NOVEL APPROACH FOR CONTINUUM PROTE IN +SECONDARY STRUCTURE ASSESSMENTS +We present a novel approach for the detection of protein secondary structure elements, +which combines a description of the protein backbone in terms of screw motions (Acta +Cryst. 62, p. 302-11 (2006)) with a statistical approach, yielding confidence ranges for the +corresponding helix parameters on the basis of natural variations. To establish these ranges +for each type of secondary structure element, we analyzed several databases of protein +structures, exhibiting each well defined structural profiles. The method allows for a continous +assessment of protein secondary structure elements and is proved to be stable with respect to +both structural variations found in NMR data and resolution problems in crystallographic +data. The comparison with other methods supports its reliability and accuracy. A structural +analysis of bovine pancreatic trypsin inhibitor in three different crystal forms illustrates the +capability of the method to detect secondary structure elements in noisy data and to describe +at the same time small but systematic structural variations in the latter. +93 +94 screwfit : a novel approach for continuum protein secondary structure assessments +6.1 introduction +In the last decades, a variety of newmethods has been developed for the analysis of experimen- +tal and simulation data in structural biology. One of the standard tasks is the determination +of secondary structure elements in proteins, in particular for the characterization of changes +in protein structure. Such conformational changes may be induced by binding of ligands or +by external stress, such as temperature, hydrostatic pressure, or chemical agents. +Traditionally secondary structure elements are described in terms of two torsional angles +per residue, φ and ψ, which define for each Cα-atom in the protein backbone the rotation of +the left and right peptide plane about the N−Cα and Cα −C bond, respectively [187]. This +approach is, however, not well suited to describe non-ideal secondary structure elements, +such as kinked or curved helices, which occur in any protein fold, nor does it easily allow to +detect and to describe structural changes in protein structure. In the past, different methods +have been developed to determine secondary structure elements in polypeptide chains +[106, 163, 57, 190] and to describe their geometry in more detail [9, 181, 194]. One of the +most frequently used methods is the dictionary of protein secondary structure (DSSP) which +detects secondary structure elements through typical hydrogen bond patterns [106, 89]. The +method allows in principle to distinguish eight of the most common motifs, both in secondary +and supersecondary structures, but the results are often biased by the fact that DSSP makes +assessments on protein structure using average hydrogen-bond distances as references which +implicitly include the effects of static and dynamical disorder in crystallographic data. Like +other, so-called “discrete methods”, DSSP assesses secondary structure elements on the basis +of a “true-false” decision, which follows geometrical criteria. All patterns which meet these +criteria within certain thresholds are safely detected by all discrete methods [40], but they +run into difficulties if the natural variability in the secondary structure of a given protein +is too important. Methods like DSSP are, for example, not able to reproduce the variations +between different NMR models which correlate with thermal disorder and local mobility of +structure motifs. This fact has already been observed by Andersen and coworkers [5] [25] +who presented a new method, derived from DSSP, which is called DSSPcont. The suffix +“cont” indicates that the method uses a description of protein secondary structure in terms of +a set of parameters which vary continuously in a predefined range of values. It has been +pointed out in the literature that this continuous approach can more easily distinguish between +natural conformational variations and effective changes in secondary structure profiles [5]. +Indeed, Andersen and coworkers proved that a major improvement of the DSSP method +6.1 introduction 95 +could be obtained simply substituting the single threshold-based definition per secondary +structure element by a quasi-continuum spectrum of assessments obtained by running the +discrete DSSP method with different hydrogen bond distance thresholds. The resulting series +of assessments leads to the final assignment probability of each residue to belong to one of +the eight DSSP classes: the three helix types (α, 310 and π); β strands; helix-turns; β bridges; +bends and not-structured loops. +With these assumptions, DSSPcont was refined in order to maintain a high consistency with +respect to the influences of small structural variations caused by the experimental setups or +by the natural thermal fluctuation of structures. +Motivated by the task to pinpoint changes in the secondary structure of proteins, we have +recently developed the ScrewFit-algorithm [114]. The algorithm uses the Cartesian atomic +coordinates of a protein as input and expresses its secondary structure in terms of screw +motions relating consecutive peptide planes in the protein backbone. In this work we present +further developments of this method which demonstrate that ScrewFit does not only allow +to quantify changes in protein configurations but can also be used to detect all common +secondary structure elements. +By construction, ScrewFit belongs to the so-called continuous methods for secondary +structure assignment, since the local helix parameters quantifying the screw motions are +continuous functions of the residue number. +Nevertheless, the ScrewFit method proposes a new approach to the continuous assignments as +it does not relate to any threshold-based definition but only to simple geometrical criteria that +define the set of parameters. The latter run over continuous ranges of values whose interpre- +tation is not biased by an a priori division into classes and which are simply obtained from an +empirical observation of the natural variations of the parameters in some appropriate protein +structure databases. Moreover, this approach does not limit the values of the parameters which +can vary beyond the ranges found for the most common secondary structure elements and +still be useful to finely characterize the secondary level of uncommon structural configuration. +In the following sections we will first present the ScrewFit-algorithm and then we will +show that structure definitions obtained by this algorithm are as precise as those obtained by +the DSSP discrete method and are less biased by finite resolution of crystallographic data. +96 screwfit : a novel approach for continuum protein secondary structure assessments +In a second application we will compare ScrewFit with the DSSPcont method mentioned +above in order to verify the stability of our set of parameters in respect to the variations +observed in NMR models due to experimental technique and thermal fluctuations. +Finally, as an example of a typical application, we will show the secondary structure profile +of bovine pancreatic trypsin inhibitor (BPTI) in its three different crystal forms and we will +compare the results with those detected with DSSPcont. This example will be useful to +illustrate the advantages of this novel approach which allows to make assessments on protein +secondary structure and also quantitatively characterize all changes it can undergo as an +effect of different external conditions. +6.2 methods +6.2.1 The ScrewFit algorithms +To synthetically describe protein secondary structure, we use the algorithm ScrewFit, which is +based on quaternion superposition fits for molecular structures [50, 115, 116] and Chasles’ +theorem on rigid-body displacements [33, 32]. In this section we sketch the main features of +the method and refer to [114] for more details. +In the following two consecutive peptide planes A and B, containing the atoms {O,C,N}, +are considered as rigid bodies. The latter are superimposed by minimizing the target function +∑3 +m(q) = (D · xα − x ′ 2α) , (6.1) +α=1 +where {x } and {x ′α α} are the atomic positions of the reference (the atoms {O,C,N} in plane A) +and the target structure (plane B), respectively. +The symbol D denotes an orthogonal matrix describing a proper rotation . Both coordinate +sets are defined with respect to a reference point, which is chosen to be the position of +atom C in the respective peptide plane {O,C,N}. Using the fact that a rotation matrix can +6.2 methods 97 +be expressed in the components of a normalized quaternion q ≡ {q0,q1,q2,q3}, where +q2 + q2 + q2 + q20 1 2 3 = 1[4],  + q20 + q21 − q22 − q2 3 +2(−q0q3 + q1q2) 2(q0q2 + q1q3)  + D(q) =  2(q q + q q ) q2 + q2 − q2 − q2 2(−q q + q q )  , (6.2)0 3 1 2 0 2 1 3 0 1 2 3 +2(−q q + q q 2 2 2 20 2 1 3) 2(q0q1 + q2q3) q0 + q3 − q1 − q2 +the function (6.1) is to be minimized with respect to these four parameters. As demonstrated +in previous work [50, 115, 116], the constrained minimization problem can be mapped onto +an eigenvector problem for a positive semi-definite matrix M ≡M({x , x ′α α}), +M · q = λq, (6.3) +whose eigenvalues λj = m(qj) are four possible errors of the superposition fit between the +two peptide planes, defined by (6.1). The smallest eigenvalue is the solution for the optimal fit, +and the components of the corresponding eigen-quaternion describe the relative orientation +of {x ′α} with respectto {xα}. Writing +q ≡ q0  cos(φ/2)=  . (6.4) +qv sin(φ/2)n +one sees that the resulting quaternion defines the rotation angle φ and the corresponding +rotation axis n, which is at the same time the direction of the screw motion, according to the +theorem of Chasles. The proof of the latter can be elegantly given by using the quaternion +calculus [114]. The largest eigenvalue λmax describes the “worst” superposition and gives +the maximal Euclidean distance between the two peptide planes. We use the latter to define a +unique ori√ent∑ational distance via3 (x − x ′ )2 +∆ = α=1 +α α . (6.5) +λmax +By definition 0 6 ∆ 6 1. +To characterize protein secondary structure we use the following parameters: +1. The orientational distance of consecutive peptide planes, which is defined in Eq. (6.5). +2. The radius of the cylindrical surface on which the reference atom (atom C) moves +performing th√e screw motion between two consecutive peptide planes, +|t⊥| +ρ = 1+ cot2(φ/2). (6.6) +2 +Here t⊥ is the component of the vector t relating the C-atoms, which is perpendicular +to the rotation axis defined by n. +98 screwfit : a novel approach for continuum protein secondary structure assessments +3. The straightness parameter σ. For residue i the latter is defined as +σ = µTi i · µi+1, (6.7) +where +R⊥i+1 −R +⊥ += iµi (6.8) +|R⊥ ⊥i+1 −Ri | +and R⊥i is the point on the helix axis, which is closest to the C-atom of peptide plane i. +The straightness gives information about the curvature of a secondary structure element. +Figure 30(Panel A) gives an illustration of the helix (screw motion) parameters defined above. +By definition the C-atoms of the peptide planes are on the surface of the cylinder defining +the envelope of the screw motion. Figure 30 (Panel B) gives a sketch of a typical ScrewFit +profile of a protein (in this figure, bovine pancreatic trypsin inhibitor). +Figure 30: Panel A)A tri-peptide with two peptide bonds in the extended conformation. The yellow +triangles formed by the atoms {O,C,N} of the peptide planes define the local helix structure +of the polypeptide. The green spheres, labeled with “R”, indicate dummy atoms replacing +the side-chains. The radius of the cylinder shown in figure defines the radius ρ of the screw +motion relating the two consecutive peptide planes. Panel B) A typical ScrewFit profile for +a protein structure. In this figure the three parameters refers to the BPTI (PDB code: 4PTI). +The colored stripes on the bottom of the figure indicate the secondary structure motifs +determined by DSSP method (β-strands: blue; α-helices: red; 3− 10-helices: green). Vertical +stripes superimposed on ScrewFit plots represent motifs detected by the latter method +(same coloring scheme as for the DSSP). +6.2 methods 99 +6.2.2 Availability +ScrewFit is implemented in a Python open-source code which uses several modules from the +Molecular Modelling Toolkit library [81]1. A Web-based implementation is under construction. +6.2.3 Databases +We created two subsets of the SCOP structural classification with “all-α” and “all-β” pro- +teins [145], which contain protein domains whose sequence have less than 40% of identity +and whose structure elements are essentially α-helices and β-strands, respectively. For this +purpose we used a subset of the ASTRAL [31] database which contains PDB-style files for +each SCOP classified domain. From the original database, all structures with non-canonical +atom notations were corrected or erased. +After these reductions we obtained two databases: +- A, containing 1027 all-α domains +- B, containing 1336 all-β domains +Every item into these databases is made only by the structurally significant domains and +not by the whole proteins structure. The distribution for the ∆ and ρ parameters obtained +with these databases are represented in Figure 31. +To validate the variation of the ScrewFit parameters and their accuracy obtained by the +approach described in the next section we will use three other sets of proteins with a limited +overlap with our original databases and with a greater structural heterogeneity. For this +purpose we chose: +- C, a subset from the database PDBSelect25[84], containing 2144 chains with sequence +homology lower than 25% and non-redundant folds +- D, a subset obtained directly from the PDB by the culling server PISCES [203][204], +containing 2477 chains with sequence homology lower than 25% and experimental +resolution in the range 0.5− 2.0A˙ +- E, a subset also obtained via PISCES, containing 1829 chains with sequence homology +lower than 25% and experimental resolution in the range 2.1− 3.5A˙ +1 Both codes are freely available at http://dirac.cnrs-orleans.fr/software.html +100 screwfit: a novel approach for continuum protein secondary structure assessments +Each entry in these databases C,D,E is chosen according the same rules which were applied +to constitute databases A and B. The database C is intended for reproduction of most of the +structural heterogeneity present in the whole PDB database. +Finally, a finer comparison between ScrewFit and DDSPcont will be performed to verify +the consistency of assessments made by ScrewFit. For this purpose, we will refer to the same +database of NMR entries used in the original work by Andersen et al. [5]. We will call it : +- F, containing 211 chains from NMR structures each containing at least ten models. +6.3 results and discussion +6.3.1 Evaluation of natural parameters +The algorithm described above has already been tested in [114] for model structures of +polypeptides taken from the Jena Library of Biological Macromolecules (available at 2) and +the resulting parameters will be considered as ideal values in the following. Comparison with +values obtained from real protein structures shows that the parameters fluctuate substantially +around the ideal values, even in well definined structural motifs [114]. Secondary structure +should, therefore, be associated with a range of possible values of the three parameters. In +order to find these ranges we have applied ScrewFit to the large number of protein domains +of known and well classified structures, which belong to databases A and B (see Figure 31 ). +Each peak of the distributions corresponds to the dominant structural pattern in the respec- +tive database and its width gives an estimation of the natural variation of the geometrical +parameter which is considered. To quantify the latter we fitted the dominant peaks in each +distribution by a Gaussian function, +[ (x−m)2 ] +y = a · exp − (6.9) +s2 +Here m is the position of the peak and s its width, which is to be compared with the +parameters for model structures listed in Table 13. +The reader should be aware that 310 and π helices are sometimes present in all-α domains, +but they are clearly under-represented in our database A. As shown in [114], these secondary +structure elements can however be unambiguously distinguished by ScrewFit applied on +their ideal structures. The same is true for the extended conformation with respect to the +2 Available at http://www.imb-jena.de/IMAGE.html +6.3 results and discussion 101 +Figure 31: Panel A) : Normalized distributions for Orientational Distance ∆ in A (in black) and in B (in +red). Fitted Gaussian functions are shown in dashed lines. Correlation coefficients between +distributions and fitted curves are between 0.90 and 0.96. Panel B) : Nomalized distribution +for the helix radii ρ in A (in black) and in B (in red). Fitted Gaussian functions are shown +in dashed lines. Correlation coefficients are between 0.94 and 0.96. +β-strand. From Figure 31 (Panel b), it is also evident that ρ parameter distribution for each +database presents an additional peak at values far from the dominant one. This fact is due to +the presence of some residues in the extended conformation and reverse turns (α, β and γ +type) in both databases. +Table 13: ScrewFit parameters for different structure motifs from model polypeptide and from database +evaluation.Values for 310 and π are only derived by the model polypeptide as given in [114]. +More details in the text. +Motive ρideal ρ ∆ideal ∆ +α-helix 0.171 0.168 ± 0.020 0.582 0.537 ± 0.041 +3-10 helix 0.146 0.146 0.670 0.670 +π-helix 0.178 0.178 0.471 0.471 +β-strand 0.055 0.041 ± 0.018 0.875 0.850 ± 0.062 +extended 0.037 (0.041 ± 0.018) 0.754 0.800 ± 0.057 +102 screwfit: a novel approach for continuum protein secondary structure assessments +Figure 32: Normalized distributions of ∆ (panel A) and ρ (panel B) parameters calculated on a +heterogeneous selection of protein structures obtained from the PDBselect25 database (C). +The full-colored bins represent the natural values obtained from calculation on A and B. +The hollow bins represent the ideal values reprinted from ??. The color-scheme used is: red +for α-helices, blue for β-strands, violet for extended conformations, green for 310-helices +and brown for π-helices. +Figure 32 shows the normalized distributions of the parameters ∆ and ρ obtained from the +application of ScrewFit to the database C introduced in the previous section. Despite their +origin from a wider spectrum of structural domains, these distributions are very similar to a +superposition of those obtained from A and B. Interestingly, the peaks from C are also very +close to those from A and B which are reported in Figure 32 as full-colored bins. +The ideal values reported in Table 13 and obtained from previous works [114] are also reported +in Figure 32 as hollows bins. Here it is worth noting that 310 and π helices, which were +under-represented in our original databases A and B, have ideal values slightly different from +the natural value obtained for the α-helices6.5. This observation supports the assumption that +even using these ideal values one can easily characterize an helicoidal pattern and distinguish +if it belongs to one of the three most frequent classes. +As a whole, these facts confirm that the empirical definitions made for structural elements +and summarized in Table 13 allows to distinguish the structural elements in several types of +protein folds. +6.3 results and discussion 103 +6.3.2 Reliability and consistency of ScrewFit assignments +In the following we want to confirm the reliability of the natural parameters in Table 13, +comparing ScrewFit to other methods and with respect to the refinement of experimental +resolution. +It is worth noting here that a wide variety of methods have been used in the past to make +discrete secondary structure assessments based on different approach: intra-backbone hy- +drogen bonds (DSSP), expert assignements and backbone dihedral angles (STRIDE[57]), +Cα coordinates (P-SEA[123] and DEFINE[163]) and protein curvature (P-curve [181]). Ob- +servations made by Colloc’h et al. [40] showed that DSSP, DEFINE and P-curve share the +same assessment in 63% of cases whereas DSSP and STRIDE agree for 96%. As for several +reasons, DSSP is commonly considered the standard reference in the field, we will limit our +comparison to it, in its discrete (simply DSSP in the following) and continuous (DSSPcont, in +the following) forms, and two other methods with different approach and assume that all +other comparisons can be inferred using the results showed in [40]. +In their original work, Kabsh and Sander [106] applied DSSP on three different crystallo- +graphic structures of decreasing resolution from 1.5 A to 3.0 A in order to study its accurancy +against experimental resolutions. In this work we use the same three structures to compare +our method with DSSP and with the method by Levitt and Greer (LG) [128] also referred in +[106]. The latter is another method based on distance dependent definitions of the secondary +structure motifs and all results obtained from its application are simply reprinted from +reference [106] . The reader should be aware that two of these structures have now been +superseded by new and more accurated ones. Here we use the older structures to refer +directly to the original work by Kabsch and Sander as this will not affect our conclusions. +Nevertheless we also compare the ScrewFit analysis on one of these structures ( PDB code: +2ADK ) with its homologue obtained by the more refined structure ( PDB code: 3ADK) to +make further assessments of the effects of the experimental resolution on our method. +Table 14 shows the results of ScrewFit on pancreatic trypsin inhibitor at 1.5 Å resolution (PDB +code: 3PTI) and cytochrome c550 at 2.5 Å resolution (PDB code: 155C). +The comparison of assignments ScrewFit with those taken from [106] for DSSP and LG, +shows that the three methods are globally equivalent in detecting secondary structure motifs +on the structure at higher resolution but some relevant discrepancies among them begin to +appear at the 2.5 Å resolution structure. In particular, this fact is evident in the region 26-31 +of cytochrome c550, where LG and DSSP do not find the same β-strand and ScrewFit detects +104 screwfit: a novel approach for continuum protein secondary structure assessments +Table 14: Comparison of ScrewFit assignments with two other methods (Levitt&Greer and +DSSP/DDSPcont) for two structures of decreasing resolution. Assessments for both DSSP +and DSSPcont are showed only when they differ. Comments column refers to additional +information obtained by ScrewFit analysis. LG stands for Levitt and Greer method. +Structure LG DSSP/DSSPcont ScrewFit comments +3PTI Res. 1.5 Å +310-helix 2-7 3-6 2-5 +β-strand 14-25 18-24 16-23 +β-strand 28-37 29-35 29-34 +β-strand 43-46 45 45 β-turn +α-helix 47-55 48-55 48-57 +155C Res. 2.5 Å +α-helix 4-16 6-12 6-10 +310-helix - 11-13/ - 11-13 +β-strand 17-23 19-20 19-20 +β-strand 26-31 - 26-30 extended conf. +β-strand 33-39 35-37 - +α-helix 40-44 - - +α-helix 55-65 56-64 57-63 curved C-term. +α-helix 71-80 73-80 72-82 310-like C-term +α-helix 81-90 - - +α-helix 106-118 107-117 106-116 curved C-term. +a region of some β-strand conformations alternated with some extended ones. Equivalent +results are obtained also for α-helices in regions 57-63, 72-82 and 106-116 where ScrewFit +can give quantitative assessments on the curvature and other terminal deformations of each +motif. +6.3 results and discussion 105 +Table 15: ScrewFit assignements for the same protein structure with two different experimental +resolution. Assessments for both DSSP and DSSPcont are showed only when they differ and +assessments by DSSP are printed in italics. +2ADK Res. 3.0 Å 3ADK Res. 2.1 Å +Struct. DSSPcont STRIDE P-SEA ScrewFit DSSPcont STRIDE P-SEA ScrewFit +α-helix 2-7 2-7 2-6 2-6 2-6 1-7 2-7 2-6 +β-strand 10-14 10-14 9-13 10-14 10-15 10-15 9-16 7-16 +α-helix 23-30/23-31 21-31 23-31 23-29 21-31 21-32 21-31 17-30 +β-strand 35-38 35-38 34-38 35-381 35-38 35-38 34-38 33-38 +α-helix 39-48 39-49 41-49 39-47 39-49 39-49 39-49 38-49 +α-helix 52-62 52-62 52-62 52-61 52-61 52-63 52-63 52-61 +β-strand - - - - - - 65-68 65-68 +α-helix 69-83 69-84 69-83 70-83 69-81 69-82 69-83 72-81 +β-strand 90-93 90-93 89-92 86-93 90-93 90-93 89-93 88-93 +α-helix 101-108 101-107 101-108 101-108 99-108 99-108 99-108 99-108 +β-strand - - - - - - 109-112 109-112 +β-strand 114-118 114-118 114-121 113-118 114-119 114-119 114-117 113-120 +α-helix 122-132 122-133 122-133 122-130 122-136 122-136 122-136 122-136 +α-helix 143-157 143-166 144-155 143-155 146-156 145-157 144-155 145-155 +α-helix 160-167 - - 156-165 158-164 159-165 158-167 159-164 +β-strand 170-173 170-173 168-175 170-173 170-174 170-174 170-173 170-174 +α-helix 179-193 179-193 182-193 179-193 179-191 179-192 179-192 178-191 +106 screwfit: a novel approach for continuum protein secondary structure assessments +In both cases assignments made by DSSP and DSSPcont did not show any significant +differences. A more detailed comparison with respect to experimental resolution is made in +Table 15. The accuracy of ScrewFit assignments on adelynate kinase structure at different +resolution ( PDB codes: 2ADK and 3ADK) was compared with those made by the means of +three other methods: DSSP, STRIDE and P-SEA. +Globally the effects of resolution on these methods are the same and only some discrepancies +in N- and C- edges were encountered. This fact is already well known in literature as an +artifact due to the different definitions [40]. +Nevertheless, a more accurate analysis of this comparison shows different response of each +method to the improved resolution. Firstly, at low resolution the assignments made by +ScrewFit overlap very well with those made by DSSP except for a slightly deformed β-strand +in 35-38 which makes ScrewFit assessment quite uncertain. Secondly, DSSP and ScrewFit +detect also two α-helices instead of one unique helix in the region 143-167. This outcome is +confirmed for the four methods at higher resolution. +Additionally, from Table 15 is also evident that P-SEA and ScrewFit improve their accuracy +with resolution detecting two new β-strands in 65-68 and 109-112. +These results confirm those previously shown in reference [114] and suggest that ScrewFit +performance is equivalent to those obtained by the more refined distance-dependent methods +if it is applied on a structure at low resolution. If the resolution is improved on the same +structure, ScrewFit shows instead a significant conservative refinement with respect to the +lower resolution structure and it also adds some new motifs with partial convergence with +the common distance-dependent methods. +To confirm the consistency of ScrewFit assignements with respect to the experimental +resolution, we plotted the normalized distribution of values obtained for the parameters +∆ and ρ calculated over all structures in databases D (resolution less than 2.0Å) and E ( +resolution between 2.1Åand 3.5Å). As shown in Figure 33 the effect of a better resolution is +the slight narrowing of some peaks in the distributions, in particular for those corresponding +to the α-helices values. Interestingly, assignments on β strands seem to be not affected by +the experimental resolution. It is worth noting instead that although the shape of the peak +distributions slightly changed, the position of their maxima stands unchanged. As a whole, +the outcome of the comparison showed in Table 15 and the calculation over the databases D +and E proved that the efficiency of ScrewFit assessments is globally quite insensitive to the +experimental resolution with which the structural data were obtained. +6.3 results and discussion 107 +Figure 33: Normalized distributions of ∆ (panel A) and ρ (panel B) parameters calculated over +databases C (experimental resolution lower than 2.0Å; black lines) and D (experimental +resolution greater than 2.1Å; red lines ). +6.3.3 Comparison with DSSPcont +As we mentioned in the Introduction, the main problem with the most common methods for +the secondary structure assignments is the use of threshold-based definitions which recast +the structural conformation heterogeneity of protein backbones into eight or less classes +without accounting for the effect of the natural variations that could occur into the structures +due, for example, to thermal fluctuations. +Andersen and coworkers [5] presented an improved version of the DSSP method in which +the discrete assignments were substituted by continuous ones obtained from the former +ones variating of the hydrogen-bond distance thresholds defined for each of the eight DSSP +structural classes. The efficency of DSSPcont method in capturing the effects of thermal +fluctuations in NMR structure models has been shown to be higher than that of the discrete +DSSP [5]. +Here we discuss the consistency of the ScrewFit assessments with the same criteria used by +Andersen and coworkers and in particular we verify the stability of our set of parameters +over the database F. +For each NMR structure in F, we first calculated (for both parameters ∆ and ρ) the +standard deviation of values over all the models. We then grouped these results when the +corresponding mean values of the parameters fell within one of the ranges defined in Table +13. The averages over these groups gave an estimation of the stability of parameters ∆ and ρ +108 screwfit: a novel approach for continuum protein secondary structure assessments +as a function of their values and could be compared to those obtained for DSSPcont in [5]. +Results for α-helices, β-strands and extended conformation are presented in Table 6.3.3. +Table 16: Comparison of assessment consistency between ScrewFit and DSSPcont by the means of the +root mean square deviation from average assignments. Value for DSSPcont are reprinted +from [5]. Lines labeled with def refer to amplitudes of the ranges presented in Table 13 with +respect to the corresponding parameter’s value. Extended conformation is given with the +same values of β-strands when a differentiation between the two cannot be made. All values +are in percentage. +α-helix β-strand extended +DSSPcont 13.1 11.3 11.3 +ScrewFit -ρ - NMR 13.7 29.3 29.3 +ScrewFit -ρ - def 11.9 44.0 44.0 +ScrewFit -∆ - NMR 9.1 4.4 8.2 +ScrewFit -∆ - def 7.6 7.2 7.1 +The first outcome of this analysis is that consistency of assignments in ScrewFit seems to +be higher than in DSSPcont only for parameter ∆ and not for ρ. In fact, for the latter, the +large deviation from the average values is clearly due to the lack of two distinct ranges for +β-strands and for extended conformations. This is a direct effect of using continuous ranges +of natural values for the definition of secondary structure elements and these differences +between parameter consistency prove that in ScrewFit the combination of the two parameters, +∆ and ρ, (combined with σ) is essential to make precise assessments. +Moreover, Table 6.3.3 shows that, independently of the type of structural element, the root +mean square differences for NMR models is coherent with the relative amplitudes of the +ranges defined in Table 13. Nevertheless, it is worth to note that the use of ranges did not +permit the same calculation for less represented structural elements like 310 and π helices +and the comparison with DSSPcont with respect to the consistency of assignments remains +incomplete. Corresponding work is in progress in order to obtain comparison also on the +other DSSP structural classes. +6.3 results and discussion 109 +6.3.4 Application +In the following we will show a simple application of our method. This example underlines +the combined approach which allows assessments on the protein secondary structure and +a quantitative characterization of its changes within the same tool and without any further +data treatment. +BPTI Crystal forms +As reported in our previous work [114], ScrewFit can be used to pinpoint small conformational +changes due to several causes ranging from different experimental techniques to external +environment changes like, for example, ligand binding or variation in pH. As an example we +will consider here the case of the three different crystal forms of bovine pancreatic trypsin +inhibitor (BPTI) which are known to be originated by different pH condition: pH values lower +than 9.35 favor the form I and II crystals whereas higher pH values favor the form III. +These three different crystal structures induce some small changes in protein conformation +as reported in [209, 210]. In the original works, the authors compared the three structures +of BPTI by means of inter-atomic distances in the backbone and/or in the side-chains. The +outcome of this type of analysis was the finding of several local changes induced by the +different crystal forms. Nevertheless, a detailed structural characterization of those changes +were not possible. +Here, we will first analyze the secondary structure assignments made by ScrewFit on the +structure obtained from the crystal form I and we will then discuss the differences with the +other two structures. +For the determination of secondary structure motifs, we confront again the ScrewFit +parameters with the secondary structure elements found by the DSSPcont method. The +results are shown in Figure 30 (Panel B). The motifs found by DSSPcont are shown on the +bottom of the figure. We used the same color scheme for both methods: red for α-helices, +blue for β-strands and green for 3-10 helices. Visual inspection shows that most of the motifs +found by DSSPcont correspond to the regions where the ScrewFit parameters are enclosed +by the natural variations. Interestingly, our method is able to identify very well the α-turn +between the two beta strands 19-25 and 30-36. These regions are highlighted in Figure 30 +(Panel B) with colored vertical bands. Minor discrepancies can, however, be observed in some +regions, expecially in the extreme residues of each element. In particular, ScrewFit finds that +the assignment of the 310 between residues 3 and 6, is quite uncertain due to the highly +110 screwfit: a novel approach for continuum protein secondary structure assessments +Figure 34: ScrewFit profile for bovine pancreatic trypsin inhibitor (BPTI) in its three different crystal +forms. This figure shows how ScrewFit is able to pinpoint small differences between similar +structural configuration of the same protein. Here Crystal form I (black solid line, PDB: +4PTI), form II (red solid line, PDB: 5PTI) and forms III (green solid line, PDB: 6PTI) are +represented. Horizontal stripes define the natural variations for β-strands (colored in blue) +and α-helices (colored in red). +6.3 results and discussion 111 +deformed C-terminus which is characterized by abnormally high values for this structural +element in parameters ∆ and ρ and by the value of σ very close to zero in residue 6 which +evidently stands for a kink in the backbone profile. +Let us now look at the effects of the three crystal forms on the structure of the BPTI. Figure +34 shows the parameters calculated in the three different conformations of the protein. In +each plot, the horizontal stripes indicate the range of variation for the ScrewFit parameters +as found in databases A and B (the usual color-code is used here: α-helix highlighted in +red; β-strands highlighted in blue; 310-helix highlighted in green). In the original works the +authors reported some major differences between form I and form II in the regions 15-19, +26-29, 39-41 and 47-50 and between form II and form III mainly localized in residues 15 and 26. +It is worth noting that deviations of backbone close to residue 15 are particularly interesting, +since this residue is part of the active site of the BPTI. The application of ScrewFit to the +three structures confirms some the differences mentioned above and allows them to be better +characterized. In particular, changes around both residue 15 and 26 show major discrepancies +between the conformation in crystal form III and the other two. In residue 15, parameter ∆ +changes, from form I and II to form III, toward values closer to an helix-turn conformation +but the absence of equivalent changes in the other two parameters proves that this change is +only due to a different relative orientation of the peptide planes related to a reorientation of +the side-chains bewteen residues 15 and 16. The analysis of parameters’ values for residue +26 leads to similar conclusions. A confirmation of these findings can be done with a direct +visualization of the structure as showed in Figure 34. Additionally, ScrewFit reveals also a +difference between the crystal form II and the other two at the C-terminus of the α-helix +in region 47-53. In this case the parameter σ shows that in forms II the helix axis is rather +straight whereas in the other two forms it clearly bends. +The application of DSSPcont on the same structures confirmed that the major differences +between crystal form I and crystal form II were localized in the regions around residues 15 +and 26 where it is reported an higher probability, in form II rather than in form I, of having +respectively an not-structured and a helix-turn conformation. Nevertheless, DSSPcont does +not find any relevant change between crystal form II and form III which was detected by +ScrewFit. +112 screwfit: a novel approach for continuum protein secondary structure assessments +6.4 conclusion +We presented the ScrewFit method for the analysis of the secondary structure level of proteins, +which describes the latter in terms of local helix parameters obtained by the screw motions +relating consecutive peptide planes. By construction, this method represents, ipso facto, a +new approach to the so-called continuous methods for the secondary structure assessments +because it does not relate to beforehand threshold-based definitions but only to geometrical +criteria which are verified a posteriori on natural secondary structure elements. +To establish confidence levels for the definition of all types of elements, we applied our +method to different well defined selections of protein structures. The natural variations in +parameters of ScrewFit have been shown to be coherent with the ideal values obtained in a +precedent work. +We have then confirmed the reliability of our definitions by applying our method on a +heterogeneous set of proteins with different type of folds. In order to show the efficiency and +accuracy of ScrewFit we confronted it to other methods, in particular to DSSP and DSSPcont. +The outcome of this comparison showed that ScrewFit can be considered as accurate as +DSSP/DSSPcont in function of crystallographic resolution. As an example, we analyzed the +three different crystal forms of the bovine pancreatic trypsin inhibitor by means of ScrewFit. +This application has shown that ScrewFit finds essentially the same structural elements +as DSSP, but gives also a more detailed description of them, leading in some cases to a +different assessment of secondary structure elements. It is worth noting that the method is +also shown to be efficient in detecting some kind of reverse turns and random coils. Further +improvements to permit more detailed assignments also of these motifs are the subject of +work in progress. +As a whole, with the same application we showed that ScrewFit is able to pinpoint small +structural changes and to give a global view of the structural rearrangements of the protein +as a response to external changes. +In this context, another important feature of the method is the fact of combining in the same +tool a method for detecting secondary structure and a way to find and characterize any +induced structural change. +It should be mentioned that while ScrewFit was developed for the analysis of protein +secondary structures, with some minor improvements, it may also be used to characterize the +protein supersecondary motifs and the folds of DNA and RNA molecules. Corresponding +work is also in progress. +6.5 notes 113 +6.5 notes +[i] It can be easily verified that the ranges found for the parameter for ρ in α-helices and +in 310-helices are fully compatible with those obtained by Barlow and Thornton [9] [ see +section 5.3.2] on a rather smaller set of ∼ 100 structures. + +7 +RESULTS +As stated in the introduction, one of the principal aims of this work was the characterization +of both dynamical and structural aspects in protein adaptation to environmental conditions. +In the present chapter, results obtained in this thesis for the particular case of the IF6s will be +presented and discussed. +After a summary on the samples used in this work and the environmental conditions +investigated, the discussion will focus on the analysis of structural and dynamical effects of +pressure and temperature on each sample. The results will be used to determine both local +and global effects of the environmental conditions to IF6 homologues. The link between the +assessment of both types of effects will be assured by the complementarity of the insights +obtained by molecular dynamics (MD) and quasielastic neutron scattering (QENS). +The samples that have been studied either by MD simulations or by QENS experiments are: +- aIF6: the extremophile IF6 homologue from Methanococcus Jannaschii. +- aIF6-HTag: the extremophile homologue with the supplemental N-terminal poly- +histidine tag (HTag). This sample was used in the high pressure QENS experiments and +was needed during the production phase in order to enhance the expression protocol +yield. +- eIF6: the modeled mesophile IF6 homologue from Saccharomyces cerevisiae. +- eIF6-NoCTAIL: the mesophile homologue with C-terminal cleaved. +The different environmental conditions used in MD are listed in Table 17, whereas those +used in QENS measurements are shown in Table 18. It is worth noting here that the number +and the variety of experimental measurements was largely constrained by several technical +facts as will be exposed later in this chapter. Nevertheless, the comparison to results obtained +from MD were however possible through a limited set of measurements. The environmental +conditions listed in Tables 17 and 18 will be selectively chosen in the next section to present +different aspects. Unless explicitly mentioned, the results shown here were obtained from +115 +116 results +molecular dyanamics simulations. +Table 17: Set of MD simulations of each sample performed with different environmental configurations +aIF6 eIF6 eIF6-NoCTAIL +300K - 1bar 300K - 1bar 300K - 1bar +300K - 250bar 320K - 1bar 300K 500bar +300K - 500bar 350K - 1bar 350K - 1bar +350K - 1bar 350K - 500bar 350K - 500bar +350K - 250bar +350K - 500bar +Table 18: Set of QENS measurements of each sample performed with different environmental configu- +rations +aIF6 eIF6 aIF6-HTag +300K - 1bar 300K - 1bar 300K - 250bar +350K - 1bar 350K - 1bar 300K - 500bar +350K - 250bar +350K - 500bar +7.1 effects of pressure and temperature change on if6s structure +The following section presents a study of the structural response of IF6s to changes in +pressure and temperature. +7.1 effects of pressure and temperature change on if6s structure 117 +When high pressure and high temperature are applied to protein solution, one of the main +effects that one would expect to see is the change in molecular volume and molecular surface +exposed to the solvent. +In Figure 36 is shown the volume change induced in aIF6 and eIF6 by a pressure change +equivalent to 500bar at 300K and 350K. Here the molecular volume was estimated by the +volume related to the surface accessible to solvent molecules. The extremophile IF6 structure +seems to be less sensitive to environmental changes than its mesophilic counterpart. This +observation is also corroborated by Figure 37 which shows the variation of the radius of +gyration (Rgyr)in eIF6 and aIF6, respectively. This quantity, defined by +N +1 ∑ +R = (R −R )2gyr i CM , (7.1) +N +i +is the root mean square distance of atoms from the protein center of mass (RCM). Although +Rgyr is commonly used to give insight into the global shape of proteins, here it cannot be +used to give an exact representation of IF6s, as the latter has a torus-like shape (see Figure 35) +and the atomic mean distance does not distinguish between changes in either the internal +or the external radius of the tours. Nonetheless, Rgyr can be used to give a qualitative +representation of shape changes in IF6s. Indeed Rgyr of aIF6 varies in a narrow range from +16.45 to 16.75 Å, indicating that the protein structure is rather insensitive to environmental +changes. In eIF6, Rgyr does not significantly change at 300K when pressure is applied +whereas it shows a very large variation when pressure is applied at high temperature (350K). +Interestingly radial values of aIF6 at extremophilic natural conditions (350K and ∼ 500bar) are +very similar to those of eIF6 in mesophilic natural conditions (300K and 1bar). +Similar observations can be made with respect to the surface accessible area (SASA) shown +in Figure 38. The differences in variation of SASA between the two homologues, at 350K +reveals that the changes found in Rgyr of eIF6 must be mainly related to the increase of the +total surface exposed to the solvent. +7.1.1 Local effects +The local effects produced by pressure and temperature on IF6s structures can be probed +using the root mean square fluctuations RMSF(i) = 〈R (t) − 〈R 〉〉2i i , where i can refer to +either an atom or a group of atoms (e.g., backbones or sidechains ); in the latter case an +118 results +Figure 35: Cartoons representation of IF6 structure. +300K 1bar +45.5 +300K 500bar A) +350K 1bar +45 350K 500bar +44.5 +44 +43.5 +43 +42.5 +0 500 1000 1500 2000 +time [ps] +300K 1bar +45.5 +300K 500bar B) +350K 1bar +45 350K 500bar +44.5 +44 +43.5 +43 +42.5 +0 500 1000 1500 2000 +time [ps] +Figure 36: Molecular volume of IF6s with respect of pressure and temperature. Panel A: aIF6. Panel B: +eIF6. +Volume [Å3] Volume [Å3] +7.1 effects of pressure and temperature change on if6s structure 119 +17 17300K 1bar +A) 300K 500bar B) +350K 1bar +16.9 16.9 +350K 500bar +16.8 16.8 +16.7 16.7 +16.6 16.6 +16.5 16.5 +300K 1bar +300K 500bar +16.4 16.4 +350K 1bar +350K 500bar +16.3 16.3 +0 500 1000 1500 2000 0 500 1000 1500 2000 +time [ps] time [ps] +Figure 37: Radius of gyration of IF6s as a function of time. Panel A: aIF6. Panel B: eIF6. Only residues +from 1 to 225 are taken into account. +11600 300K 1bar 11600 300K 1bar +300K 500bar A) B) 300K 500bar +350K 1bar 350K 1bar +11400 11400350K 500bar 350K 500bar +11200 11200 +11000 11000 +10800 10800 +10600 10600 +10400 10400 +0 500 1000 1500 2000 0 500 1000 1500 2000 +time [ps] time [ps] +Figure 38: Solvent accessible surface area of IF6s as a function of time. Panel A: aIF6. Panel B: eIF6. +Radius of gyration [A] +Solvent Accesible Surface Area [Å] +Solvent Accesible Surface Area [Å^2] Radius of gyration [Å] +120 results +average over the atoms of the group is performed. +A) B) +Figure 39: Root-mean-square-fluctuation (RMSF) of carbon Cα in aIF6 backbone. +A) B) +Figure 40: Root-mean-square-fluctuation (RMSF) of carbon Cα in eIF6 backbone. Panel A: Region +1-224. Panel B: Region 1-245. +The RMSF of carbon Cα in aIF6’s backbone (Figure 39) shows that at 300K atomic fluc- +tuations of residues are slightly reduced by pressure on the whole structure but a more +significant variation is found in the region 80-90 . The latter region corresponds to the α-helix +of one of the five pseudo-symmetric subdomains which composed the IF6 structure. No +7.1 effects of pressure and temperature change on if6s structure 121 +significant differences are found between RMSF at 250bar and 500bar whereas at 350K the +same region 80-90 shows RMSF increased by pressure. Moreover, as one would expect the +general effect of temperature is to increase RMSF. +The changes due to pressure found in aIF6 are not present in eIF6 where instead RMSF in +region 80-90 is increased by temperature but reduced by pressure. +In both cases, these results lead to the conviction that pressure and temperature can induce +large changes in the exposure to the solvent of the α-helix in region 80-90 which results in a +higher or lower RMSF of Cα atoms in the region. This observation is supported by visual +inspection of both aIF6 and eIF6 sequences which reveals that the α-helix is highly charged +and thus it has an high propensity for interaction with solvent. +Figure 40 shows that eIF6, at both 300K and 350K, has an higher baseline for Cαs fluctuations, +probably due to the presence of the C-terminal tail of 21 amino acids (CTAIL) which could +transmit supplemental fluctuations to the rest of the protein structure. In the same context, it +is worth noting that at high temperature this baseline is particularly increased for residues +from 100 to 220, as shown in Figure 40. +7.1.2 Secondary structure changes +Even though the calculation of RMSF allowed several qualitative assessments on the effects +of pressure and temperature on IF6s’ structures, a finer method is necessary to quantify +them. For this purpose, the ScrewFit method will be used here to characterize the response +of IF6s to the environmental changes. In particular the method will be used to analyze the +molecular structures obtained by time-averaging of the atomic trajectories issued from the MD +simulations in order to make assessments on the local flexibility of the secondary structure of +IF6. +The first application of ScrewFit on the time-averaged structure of both aIF6 and eIF6 at 300K +and 1bar allows to distinguish the very similar secondary structure of the five subdomains +which compose the IF6 structure (Figure 41 shows the aIF6’s profile). The inspection by eye +allows the five motifs to be found through their regular profiles. Here, the discussion will be +limited to the motif in the region 52-100 but the same conclusions can be obtained also from +any of the other structural subdomains. +Groft and coworkers [66], who reported the presence of subdomains in a five-axis pseudo- +symmetry in IF6 structures, stated also that the almost invariant secondary structure profile of +these subdomains was made of a long α-helix, a shorter one (alternatively a 310-helix was also +122 results +found) and three β-strands. Here the analysis of the orientational distance and of the radius +of the helix of screw motion, seems to confirm the presence of a tight α-helix or more likely +a 310-helix in residues 57-60 followed by two β-strands in the region 60-75 (See previous +chapters for reference values). The latter have, however, a very variable straightness, meaning +that they have a very curved form, as one can verify by visual inspection on molecular +structure. +Residues 78-90 clearly form a long and straight α-helix as evident from the comparison +of values of the three parameters. Nonetheless, the C-terminus of this long α-helix shows +a curved region as shown again by the straightness parameter which attains values close +to zero. This result confirms and completes the observation made on the RMSF in the +region around residue 90 in both aIF6 and eIF6. Indeed, variations found in the RMSF +must correspond in changes in the curvature of the C-terminal region of the α-helix. The +subdomain ends with a rather straight short β-strand from residue 90 to 100. +1 +0.9 +0.8 +0.7 +0.6 +0.5 +0.4 +0 20 40 60 80 100 120 140 160 180 200 220 +0.4 +0.3 +0.2 +0.1 +0 +0 20 40 60 80 100 120 140 160 180 200 220 +1 +0.5 +0 +-0.5 +0 20 40 60 80 100 120 140 160 180 200 220 +Residues +Figure 41: Secondary structure profile of aIF6 as detected by ScrewFit algorithm. The subdomain +52-100 is highlighted by grey stripes. +Straightness +Helix Radius Orientational distance +7.1 effects of pressure and temperature change on if6s structure 123 +Once the profile of IF6 secondary structure is characterized by ScrewFit parameters, +one can observe the changes of the same parameters on the effect of high pressure and +temperature. Nevertheless, as reported in [22], a direct comparison of the structures of eIF6 +and aIF6 will not be possible due to the presence of several deletions and insertions in +sequences of both homologues which do not permit a direct structural alignment of the two +IF6s without gaps. +Figures 42 and 43 show the effects of temperature and pressure on both structures by means +of differences of ScrewFit profiles. Profiles at high temperature or pressure were subtracted +from the profile at 300K and 1bar to obtain the differences shown in figures. The outcome of +the analysis of these figures is listed in the following. In both cases distinct effects due to +temperature or pressure have been observed. +aIF6 +- At 350K-1bar aIF6 shows a higher value of orientational distance in region around residue +60 and between residue 120 and 130. In both cases this reflects a significant distortion of +the helical conformation without change in the local curvature of backbone as evidenced +by a rather small variation in straightness values. +- High pressure (500bar), induces a significant change in residues 90-95. The inspection of all +parameters seems to confirm that pressure induces a more curved structure and locally +residues assume a conformation more similar to the neighbor α-helix 78-90 rather than +to β-strand 90-100. +- The combination of high temperature and high pressure has another significant effect +around residue 50 where a transition towards a more curled conformation is evident +from values of orientational distance and helix radius. +eIF6 +- Large variations of all parameters in the region 220-245 are clearly due to the large fluctua- +tions of CTAIL. These variations increase, as expected, with temperature. +- Different variations in the region 170-180 are shown as effects of both temperature and pres- +sure when applied separately but they are not present when a simultaneous application +of high pressure and high temperature is performed(see also Figure 44). +124 results +300K-1bar vs 300K-500bar +0.2 300K-1bar vs 350K-1bar +300K-1bar vs 350K-500bar +0.1 +0 +-0.1 +0 20 40 60 80 100 120 140 160 180 200 220 +0.05 +0 +-0.05 +-0.1 +-0.15 +-0.20 20 40 60 80 100 120 140 160 180 200 220 +1 +0.5 +0 +-0.5 +0 20 40 60 80 100 120 140 160 180 200 220 +Residues +Figure 42: Effects of pressure and temperature on ScrewFit parameters of aIF6 secondary structure. +- Combination of high temperature and high pressure produces an evident change in all +parameters in the region 35-45 which correspond to the long α-helix of the first subdo- +main of IF6 structure. As for region 78-90 in aIF6, also here variations are related to +a major curvature of the C-terminus of the α-helix. Several different configurations of +peptide planes in region 35-45 are shown by variations in orientational distance and +helix radius. +Interestingly, changes in ScrewFit profiles of eIF6 and aIF6 appear in different regions. The +former is more affected in residues between 160 and 245 and between 1 and 50, whereas the +latter is more significantly affected in the central region 50-140. +7.1.3 Relation between local structural effects and IF6 function +Very little is known about how IF6 performs its functions. Only few insights were reported +by Basu et al [11] and by Groft et al. [66]: +• Serines 174 and 175 are found to play an essential role in nuclear localization of IF6s +which must be related to the phosphorylation of these two residues. +Straightness Helix Radius Orientational Distance +7.1 effects of pressure and temperature change on if6s structure 125 +300K-1bar vs 300K-500bar +300K-1bar vs 350K-1bar +300K-1bar vs 350K-500bar +0.4 +0.2 +0 +-0.2 +-0.40 20 40 60 80 100 120 140 160 180 200 220 240 +0.3 +0.2 +0.1 +0 +-0.1 +-0.2 +0 20 40 60 80 100 120 140 160 180 200 220 240 +2 +1 +0 +-1 +-20 20 40 60 80 100 120 140 160 180 200 220 240 +Residues +Figure 43: Effects of pressure and temperature on ScrewFit parameters of eIF6 secondary structure. +Figure 44: Time-averaged structures of eIF6 at 300K-1bar and 300K-500bar. The structure of the C- +terminal region of the α-helix is significantly changed by pressure. This variation affects the +position of Serine 174 and Serine 175.Color scheme: red for eIF6 structure at 300K-1bar and +blue for structure at 300K-500bar. Cartoons representation of secondary structure elements +are built following the DDSP assignements. +Straightness Helix Radius Orientational Distance +126 results +• Arginine 61 in eIF6 is found to close the central hollow of IF6 structure and prevent +water molecules passing throught it. This fact could have effects on the global stability +of IF6s structures. +• The C-terminal region (to be distinguished from CTAIL which is formed by residues +224-245) encompassing the evolutionarily conserved arginines and tyrosines Arg 67, +Tyr 113, Arg 223 and Tyr 202 represents an exellent candidate for the participation in a +biologically relevant protein-protein interaction. Indeed it is suggested as the binding +site for the 60S ribosomal subunit. +Some of the structural changes found in this work and induced by pressure and/or +temperature involved the residues mentioned above, meaning that the corresponding +structural re-arrangements could be related to the functional adaptation of IF6. +In particular it was reported that the region including the two serines 174 and 175 undergoes +structural changes at high pressure (Figure 44) and high temperature separately but it assumes +its normal configuration when both pressure and temperature are increased. This result seems +to be crucial for the assessment of the function of eIF6 under extreme conditions similar to +those of warm deep seas. The C-terminal is obviously also largely influenced by the presence +of CTAIL which induces fluctuations in eIF6 that are not present in aIF6. Also this fact +will be used in the following to discuss the ability of eIF6 to adapt its function to extreme +environments. As a whole, aIF6 seems to show a higher stability with respect to the change +of the thermodynamic variables. Nonetheless, it shows some significant changes in backbone +conformation in regions apparently not related to protein function. +Finally, the comparison of RMSF and ScrewFit parameters for Arg 61 did not give any +significant result in structural changes on the time scales used in this work. +7.1.4 Comparison between ScrewFit profiles of eIF6 and eIF6-NoCTAIL +In order to better understand the role of CTAIL in (de)stabilizing eIF6 structure, a supple- +mental MD simulation was performed on eIF6’s structure without its C-terminal tail. The +protocol used for this simulation was mentioned in the chapter on system setups. +Comparison of ScrewFit profile of eIF6-NoCTAIL (Figure 45) with that of complete eIF6, reveals +the absence of variations that characterized eIF6 in the previous paragraphs. Moreover, the +variations in ScrewFit parameters in eIF6-NoCTAIL are more similar and closer in sequence +localization to those shown for aIF6. +7.1 effects of pressure and temperature change on if6s structure 127 +The observations made above lead to the conclusion that CTAIL could play a important +role in structural adaptation of IF6 to extreme environment. In particular it seems that the +presence of this C-terminal tail induces thermal fluctuations to the backbone of the rest of +IF6 structure leading to a lower protein stability. As will be shown later in this chapter, the +effects of pressure and temperature induced through CTAIL fluctuations do not cause only +structural changes but also a different scheme of IF6 dynamical response to environmental +changes. +300K-1bar vs 300K-500bar +300K-1bar vs 350K-1bar +0.6 300K-1bar vs 350K-500bar +0.4 +0.2 +0 +-0.2 +0 20 40 60 80 100 120 140 160 180 200 220 +0.2 +0.1 +0 +-0.1 +-0.20 20 40 60 80 100 120 140 160 180 200 220 +0.5 +0 +-0.5 +0 20 40 60 80 100 120 140 160 180 200 220 +Residues +Figure 45: Effects of pressure and temperature on ScrewFit parameters of eIF6-NoCTAIL secondary +structure. +7.1.5 Comparison between ScrewFit profiles of aIF6 and aIF6-HTag +As recalled at the start of this chapter, high pressure QENS experiments were performed on +aIF6 with an attached supplemental N-terminal tail of 21 amino acids (HTag). This tail was +essential to improve the yield of protein production. The same sample (aIF6-Htag), was also +studied by MD simulations to make comparison with experimental data possible. aIF6-HTag +Straightness Helix Radius Orientational Distance +128 results +time-averaged structure was initially analyzed by ScrewFit in order to identify differences +with other samples and to verify the structural effect of the HTag on the protein itself. +ScrewFit differences between structures of aIF6-HTag at different pressures and temperatures +are shown in Figure 46. Here the beginning of the residue sequence was shifted to -20 in +order to maintain the usual numbers in the conserved part of the structure. +First of all, the effect of the HTag is clearly present in all parameters as large variations in the +region from -21 to 0 but in contrast to the effects produced by CTAIL on eIF6 structure, here +these changes are localized only in the region of the HTag and do not propagate over the rest +of the structure. +Moreover, the region between residues 40 and 50 seems to undergo the same changes found +in aIF6, meaning that this region is intrinsically sensitive to environmental changes probably +due to its exposure to solvent. +300K-1bar vs 300K-500bar +300K-1bar vs 350K-1bar +0.4 300K-1bar vs 350K-500bar +0.2 +0 +-0.2 +-20 0 20 40 60 80 100 120 140 160 180 200 220 +0.2 +0.1 +0 +-0.1 +-0.2 +-20 0 20 40 60 80 100 120 140 160 180 200 220 +2 +1.5 +1 +0.5 +0 +-0.5 +-20 0 20 40 60 80 100 120 140 160 180 200 220 +Residues +Figure 46: Effects of pressure and temperature on ScrewFit parameters of aIF6-HTag secondary +structure. +Finally, it is worth noting that the major change in the whole structure happens in region +110-115 and is present almost in the same way in all conditions. This fact suggests that the +Straightness Helix Radius Orientational Distance +7.1 effects of pressure and temperature change on if6s structure 129 +latter is a structural arrangement compatible only with the structure at 300K-1bar. +The outcome of this comparison of ScrewFit profiles as well as the others was that both +aIF6 and eIF6 are largely affected by the possible presence of a additional sequence of amino +acids either in their N- or C- termini. Nevertheless, the effects produced strictly depend on +the rest of the protein structure and can be very different. +7.1.6 Elastic Incoherent Structure Factor +As stated in the chapter on Material and Methods, the Elastic Incoherent Strcture Factor gives +insights into the configurational space volume explored by atomic motions in macromolecules. +As for other scattering functions, in the case of biomolecules, also the EISF is largely dominated +by hydrogen contributions and it can be approximated as due to the motions of only one +single representative scattering atom. +The EISF has already been used widely to characterize the structural "flexibility" of proteins +because it can be directly related to atomic mean square displacement (MSD). Indeed, for +small values of the momentum transfer, it can be proved that the equation 2.42 can be +approximated by the following expression [15]: +EISF(q) = lim∞ I(q, t) = exp(−q2〈x2〉), (7.2)t→ +which has Gaussian form. In reality the Gaussian approximation holds strictly only for +q→ 0 [15]. The above equation reveals that 〈x2〉 can be directly obtained by EISF via: +〈x2〉 = − ln(EISF[q])/q2 (7.3) +Using equation 2.42, the EISF of aIF6 and eIF6 have been calculated. Here and in the +following, the quantities of interest are calculated only on the evolutionary "conserved" part +of the IF6, i.e. on the region 1-224, filtering out the contribution of the C-terminal tail. A first +comparison of EISF from aIF6 ( Figure 47 - Panel A) and eIF6 ( Figure 47 - Panel B) underlines +two main differences between the two samples: +- In both cases pressure makes the slope of EISF only slightly change whereas temperature +has a much more evident effect +- Even though aIF6 shows qualitatively the same behavior as eIF6, its variations due to +pressure are very limited. Moreover, at high temperature (350K), EISFs at 1bar and +500bar are almost identical. +130 results +A) B) +Figure 47: Elastic Incoherent Structure Factor for aIF6 and eIF6. +Looking at these results, one would conclude that the difference between the two samples +is mainly related to their stiffness/softness character [216], but the direct comparison of EISFs +in Figure 48 shows also another interesting outcome: EISFs of aIF6 at high temperature are +very similar to those of eIF6 at 300K. This means that configurational spaces explored have +the same extent in both samples when they are both in their natural conditions. +Furthermore, EISF from eIF6 at high temperature shows a much more rapid decrease as a +function of the momentum transfer with respect to the other EISFs. Another interpretation +for this result is given by the atomic position fluctuation, 〈x2〉, obtained from equation 7.3 +and shown in Figure 48 (Panel B). From this figure it seems evident that atomic fluctuations +can be analyzed as function of the momentum transfer. This does, however, not necessarily +mean that the Gaussian approximation given above does not hold, but only that it is not +compatible with the assumption of one single representative scattering atom. It has, in fact, +been shown that the Gaussian model can represent the EISF of a protein up to moderate q +values, since such a model can account for motional heterogeneity. +The 〈x2〉 attains larger values for eIF6 at high temperature (at both pressures), meaning that +fluctuations increase and involve the motion of rather large group of atoms or structural +domains (q < 20nm−1). It is also worth noting here that the EISF (and the corresponding +〈x2〉) from eIF6 at 300K-500bar superpose slightly better than the one at eIF6-300K-1bar to +aIF6 1bar/500bar. +7.1 effects of pressure and temperature change on if6s structure 131 +1 +A) eIF6(1-224) 300K 1bar +eIF6(1-224) 300K 500bar +eIF6(1-224) 350K 1bar +0.8 eIF6(1-224) 350K 500bar +aIF6 300K 1bar +aIF6 300K 500bar +aIF6 350K 1bar +0.6 aIF6 350K 500bar +0.4 +0.2 +0 +0 20 40 60 80 100 +q [nm-1] +B) eIF6(1-224) 300K 1bar +eIF6(1-224) 300K 500bar +0.008 eIF6(1-224) 350K 1bar +eIF6(1-224) 350K 500bar +aIF6 300K 1bar +aIF6 300K 500bar +0.006 aIF6 350K 1bar +aIF6 350K 500bar +0.004 +0.002 +0 20 40 60 80 100 +q [nm-1] +Figure 48: Panel A): Comparison of EISFs from aIF6 and eIF6.Panel B): Atomic mean fluctuations as +obtained from equation 7.3 + [Å2] +EISF +132 results +characterization of eif6-noctail and aif6-htag structure and dynamics +In this chapter, an hypothesis on the characterization of structural and dynamical properties +of eIF6 and aIF6 is proposed. In particular the comparison of different EISFs will be used to +assess the existence of corresponding states between aIF6 and eIF6. +Here, similar characterization will be sketched also for eIF6-NoCTAIL and aIF6-HTag in +order to use them latter in a more detailed discussion of the results. +EISFs from aIF6-HTag are compared to those of eIF6 and aIF6 at different temperature and +pressure and plotted in Figure 49. Interestingly, this result, together with the analysis made +by ScrewFit in the previous sections, shows that aIF6-HTag has the same structural properties +as eIF6. An opposite result was obtained from comparison of EISFs from eIF6-NoCTAIL with +both eIF6 and aIF6 (Figure 50). Here, it seems that, even though EISFs from eIF6-NoCTAIL +are very similar to those from aIF6, they show that the former has a less compact structure as +shown in 51. +1 +aIF6-HTag(1-224) 300K 1bar +aIF6-HTag(1-224) 300K 500bar +aIF6-HTag(1-224) 350K 1bar +0.8 eIF6(1-224) 300K 1bar +eIF6(1-224) 350K 500bar +aIF6 300K 1bar +0.6 +0.4 +0.2 +0 +0 20 40 60 80 100 +-1 +q [nm ] +Figure 49: Elastic Incoherent Structure Factor for aIF6-HTag compared to EISFs from eIF6 and aIF6. +EISF +7.1 effects of pressure and temperature change on if6s structure 133 +1 +aIF6 300K 1bar +aIF6 350K 1bar +eIF6-NoCTAIL 300K 1bar +0.8 eIF6-NoCTAIL 350K 500bar +eIF6 300K 1bar +eIF6 350K 1bar +0.6 +0.4 +0.2 +0 +0 20 40 60 80 100 +Figure 50: Elastic Incoherent Structure Factor for eIF6-NoCTAIL compared to EISFs from eIF6 and +aIF6. +aIF6 300K 1bar +aIF6 350K 1bar +0.008 eIF6-NoCTAIL 300K 1bar +eIF6-NoCTAIL 350K 500bar +eIF6 300K 1bar +eIF6-NoCTAIL 350K 1bar +0.006 +0.004 +0.002 +0 20 40 60 80 100 +q [nm-1] +Figure 51: Atomic mean square displacement (MSD) of eIF6-NoCTAIL as function of momentum +transfer. Comparison with MSD from eIF6 and aIF6 is shown. + [Å2] +134 results +7.2 efffects of pressure and temperature on if6s dynamics +7.2.1 Dynamical models +The data issued from neutron scattering measurements need to be interpreted in a frame of +physical models describing the different types of motions which compose the global status +of the sample. The easiest assumption which is usually made is to consider every type of +motion de-correlated with respect to the others and every atom dynamically equivalent to +the others. For this, the position of the atom i reads: +Ri = RCM + ri + ui (7.4) +where RCM is the position of the center of mass (CM) of the sample, ri is the atom position +with respect to CM and ui is the deviation from the equlibrium position RCM + ri. These +assumptions are reliable for small molecules with some degrees of symmetry but becomes +an approximation when applied to much more complex molecules like proteins. Assuming +that the latter is acceptable, i.e. that atom i represents the average dynamical properties of all +atoms in the sample, the intermediate scattering function can be recast as follows: +FH(q, t) = FCM(q, t) · Frot(q, t) · Fint(q, t) (7.5) +here the "rot" and "int" indexes refer to global rotational and internal motions, respectively. +Fourier transformation of 7.5 gives the relation for the dynamic structure factor which reads +now: +SH(q, t) = SCM(q, t)⊗ Srot(q, t)⊗ Sint(q, t) (7.6) +The term due to translation of the center of mass can be described following the Frick’s law of +diffusion of a free particle [13]. For the latter, particles positions are governed by a Gaussian +probability and thus, the intermediate scattering function F(q, t) will have a Gaussian form +as function of the momentum transfer [164]. The corresponding dynamic structure factor +S(q,ω) will have a Lorentzian form: +1 Dq2 +S(q,ω) = (7.7) +π (Dq2)2 +ω2 +7.2 efffects of pressure and temperature on if6s dynamics 135 +where D is the diffusion constant and the half-width-half-maximum (HWHM) is defined by +Dq2. The contribution to equation 7.6 due to global rotational diffusion is more complicated +to obtain because it requires a description of molecules as rigid-bodies [37]. As stated in +Chapter 2, this term is not taken into account in our QENS measurements because it is largely +beyond the experimental resolution used here. Finally, several models have been developed +to analyze the internal motions of atoms in large molecules like proteins. This means that, +in the simplest case, all types of atomic diffusion motions which can be found into large +molecules, are averaged to find a unique dynamical property for all atoms that characterize +the molecule. This usually results in time-correlation functions characterized by a unique +relaxation time associated with all atoms in molecules. +However, a discussion all these models would be out of the scope of this thesis and accounts +can be found in many excellent reviews. Here a brief summary will be given of the model +used in this work to characterize atomic motions in proteins. +7.2.2 Fractional Brownian Dynamics +To interpret both the simulated and experimental data, the fractional Ornstein-Uhlenbeck +(OU) process [137] is used as an analytical model for the atomic motions in a protein. The +model describes anomalous diffusion in a harmonic potential, where the latter accounts for +the fact that atomic motions in a protein are confined in space. The anomalous diffusion +describes slow, non-exponential structural relaxation in the functional dynamics of proteins, +which has been observed in the past on the microsecond to second time scale by fluorescence +correlation spectroscopy[214] and by kinetic studies[64]. The existence of fractional Brownian +dynamics in proteins on the nanosecond time scale has been recently demonstrated by +analyses of molecular dynamics simulations [119] and the fractional OU process has been +introduced in [113] for the interpretation of QENS spectra from proteins. It can be considered +as an extension of a simple harmonic protein model, which has been used in the past to +describe elastic neutron scattering profiles, in particular to extract the “resilience” of proteins +in terms of an average force constant [216]. The fractional OU process (fOU) adds to this a +description of the relaxation dynamics, which is measured in QENS experiments. +Full details of fOU model and its application to protein dynamics can be found in previous +works [119, 113, 19, 20] and here I will recall only the key points needed for the following +136 results +analysis of MD and QENS data. +time-dependent mean-square displacement The most elementary quantity to +be considered in the context of diffusion processes is the time-dependent mean-square +displacement (tMSD), +W(t) := 〈[x(t) − x(0)]2〉, (7.8) +where x is the position of the diffusing particle and the brackets indicate a thermal average. +In case that the dynamics of the particle is confined in space, the tMSD will tend to a plateau +value, which is giv 2(en by 2〈x 〉. For t)he fractional OU process one has +W(t) = 2〈x2〉 1− E αα(−[t/τ] ) . (7.9) +Here Eα(z) is t∑he Mittag-Leffler function [52]∞ zk +Eα(z) = , (7.10) +Γ(1+αk) +k=0 +where Γ(.) denotes the generalized factorial [2]. One recognizes that for α = 1, where Γ(1+ +αk) = Γ(1+ k) = k!, the exponential function is retrieved from expression (7.10), i.e. E1(z) = +exp(z). In this case the fractional OU process becomes the well-known standard Markovian +OU process, which is characterized by exponential relaxation functions [205, 59, 164]. As +indicated in [117], the fractional counterpart is characterized by non-Markovian memory +effects, which lead to non-exponential correlation functions. +Expressions (7.10) and (7.9) show that the proposed model contains three parameters: +1. the position fluctuation 〈x2〉, +2. the parameter α indicating the deviation from exponential behavior, +3. the time scale parameter τ. +These parameters will be considered as q-dependent and will give account of the multiple +relaxation dynamics the characterize the internal motions on proteins. +relaxation rate spectrum The function E (−[t/τ]αα ) can be considered as a +“stretched” generalized exponential function. The non-exponential character of this func- +tion can be most easily visualized by writing it as a superposition of normal exponential +functions. Using ∫fo∞r simplicity a dimensionless time variable we have +Eα(−t +α) = dλpα(λ) exp(−λt), (7.11) +0 +7.2 efffects of pressure and temperature on if6s dynamics 137 +where pα(λ) is a normalized and positive distribution function, which is of the the form [64, +117] +1 λα−1 sin(πα) +pα(λ) = , 0 < α < 1. (7.12) +π λ2α + 2λα cos(πα) + 1 +In the limit α→ 1 we have [117] +lim pα(λ) = δ(λ− 1), (7.13) +α→1 +in agreement with lim E (−tαα→1 α ) = exp(−t). +modeling incoherent neutron scattering In the following the dynamic struc- +ture factor for incoh∫erent neutron scattering will be considered, +1 +∞ +S(q,ω) = ∞ dt exp(−iωt)I(q, t), (7.14)2π − +where I(q, t) is the incoherent intermediate scattering function, which depends on the position +of the scattering atom +I(q, t) = 〈exp(iq[x− x0])〉. (7.15) +Here q = |q| is the modulus of the momentum transfer which the neutron transfers to the +scattering atom in the scattering process. Within the model it is assumed that the system +under consideration is isotropic and that, as made for EISFs, the protein dynamics, as seen +in incoherent neutron scattering, can be described by one “representative” atom. In this +case it suffices to consider one coordinate of the scattering atom, which is chosen to be the +x-coordinate. In view of the predominance of incoherent scattering by hydrogen atoms, the +representative atom in the model is a representative hydrogen atom. +Within the model the inter∑mediate scattering function has the form∞ 2n +2〈 2〉 q 〈x +2〉n +I(q, t) = exp(−q x ) Eα (−[t/τ αn] ) , 0 < α 6 1, (7.16) +n! +n=0 +where τn is given by +τ = τn−1/αn . (7.17) +The dynamic structure factor associated with the intermediate scattering function (7.16) +reads { ∑∞ }q2n〈x2〉n +S(q,ω) = exp(−q2〈x2〉) δ(ω) + Lα,τn(ω) , (7.18)n! 2π +n=1 +where Lα,τ(.) is the generalized Lorentzian +Lα,τ(ω) = ( 2τ sin(απ/2) ) , 0 < α 6 1. (7.19) +ωτ (ωτ)α + 2 cos(απ/2) + (ωτ)−α +138 results +fitting qens spectra The model introduced in previous paragraphs describes internal +protein dynamics and to be useful for the interpretation of QENS spectra of protein solutions +the effects of global diffusion and of finite instrumental resolution must be incorporated. +Neglecting multiple scattering effects and absorption, and assuming that global diffusion of +the IF6 molecules and internal motions are decoupled, one can write the measured dynamic +structure factor as convolution product (defining ∗ ∫+(f g)(ω) = ∞∞ dω ′ f(ω−ω ′)g(ω ′− )): +Sm(q, t) = (S ∗ l ∗ r)(ω), (7.20) +Here S stands for the dynamic structure factor of the model, l is a Lorentzian describing +translational diffusion (D is the diffusion constant), +1 Dq2 +l(ω) = (7.21) +π (Dq2)2 +ω2 +and r is the resolu(tion fu)nction, which is well described by a Gaussian, +2 +exp − ω +r(ω) = √ 2σ2 , (7.22) +2 πσ +with σ > 0 and a half-w∫ idth at half maximum (HWHM) of ∆E ≈ 1.17σ. Both r(.) and l(.) are +normalized such that +∞∞ ∫and +− dωr(ω) = 1 −∞∞ dω l(ω) = 1. +The convolution product (7.20) for the measured dynamics structure factor can be written +in the following form, using for{S the model (7.18),∑∞ }q2n〈x2〉n +Sm(q,ω) = exp(−q2〈x2〉) (l ∗ r) + (LDα,τ ∗ r)(ω) . (7.23)n! 2π n +n=1 +Here LDα,τ (ω) = (Lα,τn ∗ l)(ω) is the convolution of a generalized Lorentzian with a normaln +Lorentzian, for which an analytical form can be given. Defining +√ +ω˜ = ω2 + (Dq2)2, φ = arg(Dq2 + iω), (7.24) +one obtains [112] +D 2 {(ω˜τ) +α cosφ+ cos([α− 1]φ)} +Lα,τ(ω) = . (7.25)ω˜ {(ω˜τ)α + 2 cosαφ+ (ω˜τ)−α} +7.2.3 Analysis of scattering functions obtained from MD simulations +The “natural” quantities for the analysis of MD simulations are time-dependent MSDs and +time correlation functions, such as the intermediate scattering functions (ISF), which can be +directly computed from the trajectories. In this thesis, the MD analysis package nMoldyn +7.2 efffects of pressure and temperature on if6s dynamics 139 +was used for this purpose [166]. All global motions (translation and rotation) were filtered +out beforehand from all trajectories in order to avoid the presence of unwanted spurious +contributions in the calculation of correlation functions. The procedure used to accomplish +this task is well established and has already been explained in [115]. ISFs from aIF6 and eIF6 +for four different values of momentum transfer are shown in Figures 53 and 54 for different +environmental conditions. +The related time-dependent tMSD is shown in Figure 52. Data were fitted with the fOU model +as explained in the previous section. Values for 〈x2〉 in 7.9 were fixed from direct calculation +on MD simulations. The results of fits together with calculation of atomic 〈x2〉 are reported +in Table 19. +Table 19: Parameters of the fOU model from fits on eIF6 and aIF6. +aIF6 〈x2〉 α τ eIF6 〈x2〉 α τ +[nm2] [nm2] [ps] [nm2] [nm2] [ps] +300K 1bar 2.84 · 10−3 0.42 115 4.13 · 10−3 0.46 225 +300K 500bar 2.96 · 10−3 0.36 198 3.88 · 10−3 0.47 168 +350K 1bar 4.32 · 10−3 0.40 114 6.56 · 10−3 0.56 143 +350K 500bar 4.46 · 10−3 0.42 142 5.36 · 10−3 0.49 168 +Inspection by eye of tMSD plots reveals that eIF6 at 300K as well as aIF6 at 350K are quite +insensitive to pressure whereas they undergo a much more evident change at the non-natural +temperatures. Moreover, at high temperature eIF6 shows large variations due to pressure. +The fitted ISF from both samples are shown in Figures 53 and 54. Here, ISFs of both eIF6 and +aIF6 do not relatively change with respect to pressure when temperature is kept respectively +to 300K and 350K whereas significative variations occurred at different temperatures. +Again also the observations made on tMSD and ISF seem to confirm the presence of +corresponding states between the dynamical properties of the two IF6 homologues in their +natural conditions and defined by apparent similar responses to environmental changes. +Nevertheless, it is worth noting that here the presence of this correspondence is not found +through similar values of these quantities but by means of homologous variations in function +of thermodynamical variables. A further and more complete analysis of dynamical properties +140 results +aIF6 300K 1bar +0.035 +aIF6 300K 500bar +aIF6 350K 1bar +0.03 aIF6 350K 500bar +eIF6(1-224) 300K 1bar +eIF6(1-224) 300K 500bar +0.025 +eIF6(1-224) 350K 1bar +eIF6(1-224) 350K 500bar +0.02 +0.015 +0.01 +0.005 +0 +0 50 100 150 200 +time [ps] +Figure 52: Comparison of time-dependent mean square displacement of aIF6 and eIF6. +can be obtained by means of fractional Brownian dynamics model. As explained in the +previous section, parameters α and τ given in the fOU model, define the heterogeneity of +relaxation dynamics and are valuable tools to characterize the internal motions in proteins. +Values of these two parameters obtained from fit with the fOU model of ISF are plotted as +a function of momentum transfer in Figures 55 and 56. Surprisingly, the fitted parameters +show several differences between aIF6 and eIF6: +- τ in eIF6 is generally larger than in aIF6 by a factor of 3, meaning that its internal +dynamics is characterized by slower motions. Moreover, its variation as function of +pressure is of opposite sign with respect to the one in the extremophile homologue. +- α in aIF6, although similar to the one obtained in eIF6, is always systematically larger +than the latter. Following the definition of α and expression 7.12 this could mean that +the two holomogues are characterized by different distributions of relaxation rates. +The partial discrepancies between the values of {α, τ} from tMSDs and those from ISFs +could be explained from the fact that tMSDs suffer much more than ISFs from the limited +time-length of MD trajectories which do not permit a good sampling to be achieved for +time-correlation functions. +A key point here is the understanding of which of differences found in {α, τ} are related +intrinsically to the differences between the two proteins and which can be taken as a possible +MSD +7.2 efffects of pressure and temperature on if6s dynamics 141 +1 300K 1bar 1 300K 1bar +300K 500bar 300K 500bar +350K 1bar 350K 1bar +0.95 +350K 500bar 350K 500bar +0.98 +0.9 +-1 +qel=4nm +-1 +qel=10nm +0.85 +0.96 +0.8 +0.94 0.75 +0.7 +0.92 +0 50 100 150 200 +0 50 100 150 200 +time [ps] time [ps] +1 300K 1bar 1 300K 1bar +300K 500bar 300K 500bar +350K 1bar 350K 1bar +0.9 350K 500bar 0.9 350K 500bar +0.8 +0.8 -1 -1 +qel=16nm qel=18nm +0.7 +0.7 +0.6 +0.6 +0.5 +0.5 +0.4 +0 50 100 150 200 0 50 100 150 200 +time [ps] time [ps] +Figure 53: Intermediate Scattering Function from MD simulation on aIF6 at different q-values: +4, 10, 16, 18nm−1. +F(q,t) [a.u.] +F(q,t) [a.u.] +F(q,t) [a.u.] +F(q,t) [a.u.] +142 results +1 300K 1bar 1 300K 1bar +300K 500bar 300K 500bar +350K 1bar 350K 1bar +350K 500bar 350K 500bar +0.98 +0.9 +-1 +q =4nm -1 +0.96 el qel=10nm +0.8 +0.94 +0.7 +0.92 +0.6 +0.9 +0 50 100 150 200 0 50 100 150 200 +time [ps] time [ps] +1 300K 1bar 1 300K 1bar +300K 500bar 300K 500bar +350K 1bar 350K 1bar +0.9 0.9 +350K 500bar 350K 500bar +0.8 +0.8 +-1 -1 +q =16nm qel 0.7 el +=18nm +0.7 +0.6 +0.6 +0.5 +0.5 +0.4 +0.4 +0.3 +0 50 100 150 200 0 50 100 150 200 +time [ps] time [ps] +Figure 54: Intermediate Scattering Function from MD simulation on aIF6 at different q-values: +4, 10, 16, 18nm−1. +F(q,t) [a.u.] F(q,t) [a.u.] +F(q,t) [a.u.] F(q,t) [a.u.] +7.2 efffects of pressure and temperature on if6s dynamics 143 +300K 1bar +70 +300K 500bar +60 350K 1bar +350K 500bar +τ 50 +40 +30 +20 +4 6 8 10 12 14 16 18 +0.58 +0.56 +0.54 +0.52 +α +0.5 +0.48 +0.46 +4 6 8 10 12 14 16 18 +-1 +q [nm ] +Figure 55: Parameters for the fOU model obtained from fits on intermediate structure factors of eIF6. +35 +300K 1bar +30 +300K 500bar +25 350K 1bar +350K 500bar +τ 20 +15 +10 +5 +0 +0.64 4 6 8 10 12 14 16 18 +0.62 +0.6 +α 0.58 +0.56 +0.54 +0.52 +4 6 8 10 12 14 16 18 +-1 +q [nm ] +Figure 56: Parameters for the fOU model obtained from fits on intermediate structure factors of aIF6. +144 results +"signature" of adaptation. As will explained later in this chapter the sign of variations +with respect of temperature and pressure should be related to peculiar properties of each +homologue and more generally of each protein, whereas other qualities of these variations, +such as their length scale dependancy, could be related to evolutionary molecular adaptation. +The analysis of EISF was very useful for finding the corresponding states but it does +not show how dynamical properties of proteins are modified moving from unfavorable +conditions to physiological ones. The absolute value of parameter τ which characterizes +relaxation time as function of momentum-transfer, thus as function of length-scale, was +shown to be a useful tool to identify differences between eIF6 and aIF6. Interestingly, +comparing the value of τ of each protein in different environmental conditions to those +in natural conditions, one finds that in both samples, τ variations are q-dependent and +that their extension is related to the quality of extremeness of the particular environmental +condition. This comparison can be made normalizing values of τ to values at natural +conditions as shown in Figures 57 and 58. From these figures one can easily note that +variations in τ become non-uniform as external conditions move too far from the natural +(optimal) ones and they mainly involve the region corresponding to small momentum transfer. +7.3 comparison with qens measurements +In the QENS experiments performed for this thesis work a number of technical difficulties +were encountered which severely limited the amount and the quality of data. Hence, only +a purely qualitative comparison with MD was possible. The main problems related to +experimental measurements were due to the lack of previous knowledge of the chemical +properties of IF6 samples: +eIF6 turned out to have a very low stability in the experimental setups developed for this +work. Indeed, in high pressure experiments after some hours of measurements the +protein started to aggregate and very few spectra were reliable for analysis. Probably +this was due to variations in protein concentration caused by pressure application and +the coexistence of CTAIL and the poly-histidine tag which could interfere with protein +stability. +The evaluation of protein concentration in solution was made very difficult by the very +low quantity of chromophore aminoacids which resulted in low UV absoprtion. As +7.3 comparison with qens measurements 145 +1.6 +1.5 +1.4 +300K-500bar +350K-1bar +1.3 +350K-500bar +1.2 +4 6 8 10 12 14 16 18 +-1 +q [nm ] +Figure 57: Values of τ from fit of eIF6 normalized to value at 300K and 1bar. +300K-1bar +1.5 300K-500bar +350K-1bar +1.4 +1.3 +1.2 +1.1 +1 +0.9 +4 6 8 10 12 14 16 18 +-1 +q [nm ] +Figure 58: Values of τ from fit of aIF6 normalized to value at 350K and 500bar. +τ/τ350 τ/τK-500bar 300K-1bar +146 results +a consequence, the absorption at 280nm, usually measured to estimate the protein +concentration gave systematic errors greater than 10%. +In addition to these limitations, one should recall also the other results found on eIF6 stability +and reported in Chapter 3. For this reason, QENS spectra of eIF6 will not be shown here. +Some preliminary analysis of spectra from aIF6 was, however, still possible and will be used +here to support some of the observations made by means of MD simulations. +7.3.1 Ambient pressure measurements +Measurements at ambient pressure were performed on the spectrometer FOCUS (Paul +Scherrer Institut, Switzerland) as explained in the Chapter 3. Spectra for the empty sample +container, solvent and protein solutions were acquired. The experimental spectra were treated +as mentioned in Chapter 3. The following procedure was used to estimate the sample +container transmission in the presence of samples: i) firstly, the empty cell spectra were fitted +with a normalized Gauss(ian function): +exp (ω−ω0) +2 +− +2σ2 +G(ω;ω0,σ) = √ (7.26) +2 πσ +ii) secondly the Gaussian function with parameters {ω0,σ} fixed from the previous fit on +empty cell was used to estimate the contribution of the sample container in solvent spectra +which were fitted by the following expression: +Ssolvent(q,ω) = A (τ G(ω;ω0,σ) + (1− τ)SB(q,ω)) (7.27) +where A is a normalization factor and +∑2 1 Γ2 +SB(q,ω) = i , (7.28) +π (Γ )2 2i +ω +i +The expression for SB(q,ω) is intended to describe global translation and rotation of +solvent molecules. In order to limit the systematic errors due to the technical constraints listed +above, the resulting spectra containing the contribution of the sample container, the solvent +and the protein itself, were fitted with the fractional Brownian Dynamics model following the +expression: +Smes(q,ω) = C(α ((1− τ ′) S˜ (q,ω) + τ ′S P S˜E(q,ω)) + (1−α) S˜B(q,ω; Γ1, Γ2)) (7.29) +where S˜P(q,ω) was defined by expression 7.23, S˜B(q,ω; Γ1, Γ2) was obtained from previous +fit and S˜E(q,ω)) is the spectrum from the empty sample container. Here, S˜ represents +7.3 comparison with qens measurements 147 +experimental spectra convoluted with instrumental energy resolution as estimated from +vanadium spectra performed with the same setup of the other measurements. +300K exp +300K fOU fit +353K exp +0.001 353K fOU fit +q= 17 nm-1 +0.0001 +0.01 0.1 1 +ω [meV] +Figure 59: Log–log plot of aIF6 experimental QENS spectra for q = 17 nm−1 at 300K (hollow squares) +and 353K (filled triangles) as a function of neutron energy gain ω. Lines represent the fits +of the fOU model defined in the text. +Data were fitted in the range [−1.5 : 0.1]meV . The EISF obtained from this fit is shown +in Figure 60 together with the EISFs obtained from MD simulations. Experimental data +seem to agree very well with those obtained from MD simulation. The diffusion constant +estimated from 7.23 is given in Figure 61 as a function of momentum transfer. The values can +be compared with those given by direct calculation from the IF6 molecular dimensions. Here +it is worth noting that the spherical approximation for the usual Einstein-Stokes expression +of the translation diffusion constant would not fit very well in the case of IF6 as the protein +shape can be better approximated by a disk or by a torus. These corrections to the spherical +case can be performed by means of the Perrin factor and the explicit expression for torus +diffusion constant (Appendix B). The values obtained from aIF6 were calculated using the +volume associated to the solvent accessible surface and are given in Table 20. In the Perrin +factor approximation the dimensions of the disk-shape which describe the IF6 structure was +estimated by a orthorhombic box which included the whole molecular structure. Experimental +values have to be corrected with respect of the viscosity of D2O which is 20% higher than that +S(q,ω) [a.u.] +148 results +of H2O. Hence taking into account this correction, values shown in Figure 61 are included +between the Perrin and the torus approximations. +Table 20: Perrin correction to spherical diffusion constant obtained from bounding box and solvent +accessible surface volume. +Temp&Press axis a axis b Solv. Vol Stokes-Einstein D Perrin D torus +[Å] [Å] [103Å3] [10−3Å2/ps] [10−3Å2/ps] [10−3Å2/ps] +300K-1bar 33.6 48.0 41.36 11.50 12.39 34.66 +350K-1bar 34.2 46.3 40.99 34.23 36.64 95.34 +1 300K fit fOU +300K MD +353K fit fOU +0.8 353K MD +0.6 +0.4 +0.2 +0 +0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 +q [Å-1] +Figure 60: EISF from QENS measurements at ambient pressure and MD simulation of aIF6. +The values of α and τ parameters of the fOU model estimated from the fit of experimental +QENS spectra at 300K and 350K are plotted in Figure 62. Interestingly, the values for parameter +α are still coherent with those found from MD simulations whereas the values for τ are very +different. The discrepancy in the evaluation of τ could be related to the limited energy range +EISF +7.3 comparison with qens measurements 149 +0.055 +300K +353K +0.05 +0.045 +0.04 +0.035 +0.03 +0.025 +0.02 +0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 +q [Å-1] +Figure 61: Diffusion coefficient as function of momentum transfer obtained from fractional Ornstein- +Uhlenbeck from QENS measurements at ambient pressure. +used to perform this fit which was smaller than the one accessed by the time-correlation +functions calculated from MD trajectories. +1 +0.9 300K +α 0.8 350K +0.7 +0.6 +0.5 +0.4 +0.3 +4 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 +3 +τ 2 +1 +0 +0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 +q [Å-1] +Figure 62: Parameters for the fractional Ornstein-Uhlenbeck process obtained from fits to QENS +measurements at ambient pressure. +Diffusion Coefficient [Å2/ps] +150 results +7.3.2 High pressure measurements +As mentioned in the chapter on experimental and simulated systems setups, all the QENS +measurements performed in the pressure cell system required large volumes of protein +solution. This was a limiting factor for the cleavage of the poly-histidine tag (HTag) used to +enhance the expression protocol yield. For this reason, high pressure measurements were +performed with aIF6 with HTag (aIF6-HTag). Also for these measurements the knowledge of +precise protein concentration in sample solution would be essential for the correct analysis of +spectra. As a consequence, a correct treatment for the analysis of quasi-elastic spectra was +not possible. Nonetheless, acquired spectra were used to estimate EISF from aIF6-Htag with +a qualitative approach which was however useful to partially support the observations made +by MD simulations. +Spectra from empty cell, solvent and protein solution were taken and the same procedure for +the estimation of sample container transmission used for ambient pressure measurements +was used here. +The empty cell contribution was subtracted from solvent and protein solution spectra with a +transmission τ = 0.90. EISF from aIF6-Htag was estimated directly from the protein solution +spectra from the expression: +Ssolution(q,ω) = B (β G(ω;ω0,σ) + (1−β)L(q,ω)) (7.30) +where L(q,ω) which accounts for IF6 global and internal motions as well as for solvent +quasi-elastic contribution and G(ω;ω0,σ) is a Gaussian function which should estimate the +EISF from aIF6-HTag. The normalized fitted EISFs at different temperatures and pressures +are shown in Figure 63. The MD simulation of aIF6-HTag was performed in order to compare +experimental data. After filtering out the global motions as the other MD simulations, +the scattering functions were calculated using the nMoldyn package. The EISFs from MD +simulation are plotted together with experimental ones in Figure 63. Experimental results +seem to underestimate EISF with respect to MD but the variation due to pressure and +temperature are qualitatively similar. Here, it is worth noting that in general MD simulations +tend to overestimate EISF due to the limited time length of trajectories which is far from being +sufficiently large to correctly evaluate this quantity. From the experimental point of view, +however, the EISF could be susceptible to systematic errors due to an incorrect subtraction +of the sample container. Indeed, the latter could give a different contribution from the one +7.4 discussion and conclusion 151 +estimated from solvent spectra due to the absorption of protein sample and it could cause a +underestimation of EISF values. +300K 500bar IN6 +300K 250bar IN6 +1 350K 500bar IN6 +350K 250bar IN6 +300K 250bar MD +300K 500bar MD +0.8 350K 500bar MD300K 1bar IN6 +300K 1bar MD +0.6 +0.4 +0.2 +00 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2 +q [A-1] +Figure 63: Comparison EISF from IN6 measurements and MD simulation of aIF6-HTag +7.4 discussion and conclusion +The effects of pressure and temperature on IF6s have been characterized here both from +structural and from a dynamical points of view. Each approach gave different insights +into the response of IF6s to environmental changes: i) global structural responses were +investigated by means of radius of gyration and SASA whereas local effects were studied +by RMSF analysis combined with ScrewFit profiles. The latter, besides giving significant +insights into the conformational changes induced by pressure and temperature, allowed +to assess secondary structure fluctuations induced by the same thermodynamic variables; +ii) dynamical responses were instead investigated by means of scattering functions which +allowed direct comparison between MD simulations and QENS experiments. +EISF +152 results +For the discussion of results shown in the previous sections, it is important to underline +the role of the definition of extreme conditions: in contrast to what it is commonly thought, +the conditions that request a significant re-adaptation of protein structures are not only +those which have unfavorable chemical and thermodynamical conditions in the general +sense. In fact, as already stated in the Introduction, some proteins seem to behave better at +their own natural conditions than in other environmental situations, even though the former +are, in principle, chemically and physically less favorable than the latter. This observation +is comforted by works on enzymes activity which seemed to maintain corresponding states +between different environmental conditions that requested evolutionary adaptation. These +states are usually characterized by similar conformational flexibility [92]. +structure As a whole the effects of pressure and temperature on IF6 structures showed +that the anti-association factor 6 from Methanococcus Jannaschii (aIF6) is much less sensitive +than its mesophilic counterpart from Saccharomyces cerevisiae (eIF6) with respect to extreme +conditions, as shown by variation in solvent accessible surface and in atomic root mean +square fluctuations. In particular it was also found that its structural properties at high +temperature and high pressure were very similar to those of eIF6 at 300K-1bar. This response +is characterized by fluctuations of α-carbons in the protein backbone and by variations in +secondary structures. +Here, the presence of corresponding states was made evident from observations on structural +fluctuations and by the comparison of different EISFs which proved by its relation to the +mean square displacement that this process is linked to the change on spatial confinement of +protein internal motions. The same type of results were obtained by Tehei and coworkers +[191, 192] in the comparison of molecular dynamics in thermophilic and mesophilic proteins. +As a whole, these results suggest that corresponding states are created by local structural +re-arrangements that influences atomic motions in proteins. For this purpose, evolution plays +on sequence point mutations to give the right adjustment of intramolecular interactions and +thus obtain the desired effect on protein structure stability. +Comparison between the EISFs of eIF6 and aIF6 gave the evidence that MSDs are very +similar in the respective natural conditions. The comparison of these results with those +previously obtained on the EISF from lysozyme [20] at ambient pressure (Figure 64), shows a +7.4 discussion and conclusion 153 +surprising correspondence suggesting the presence of a condition for optimal "resilience" of +protein structures. +1 +lysozyme 300K 1atm +eIF6(1-224) 300K 1bar +aIF6 350K 500bar +0.8 +0.6 +0.4 +0.2 +0 +0 20 40 60 80 100 +q [nm-1] +Figure 64: Elastic Incoherent Structure Factor for aIF6, eIF6 and lysozyme. +In IF6’s protein family this condition seems to be achieved thanks to a tail of 21 amino +acids (CTAIL) attached to the C-terminus of the more evolutionarily conserved part of IF6, +because its presence was the source of the lower stability of eIF6 in extreme conditions, +whereas its absence made eIF6-NoCTAIL behave like aIF6. Moreover, the role of CTAIL is +made even more important by the fact that it induces large thermal fluctuations to structural +regions which are supposed to play a direct role in IF6 functions. +Interestingly, similar results have been obtained on EISFs from aIF6-HTag indicating that +even the presence of a fluctuating non-structured tail attached on the N-terminus of aIF6 +could make the latter not suited for warm deep sea environments. +The application of the ScrewFit method to time-averaged structures allowed also some +local effects of pressure and temperature to be detected and characterized by comparison +with three-dimensional structures. The main outcome of this analysis revealed that pressure +EISF +154 results +and temperature have locally different effects on IF6 structures. Some of these effects were +enhanced by separate application of high pressure and high temperature, whereas they +disappeared when both conditions where applied simultaneously. +dynamics The investigation of the dynamical effects refined the structural results. +Scattering functions from the MD simulations of both aIF6 and eIF6 were analyzed by means +of fractional Brownian dynamics (fOU) model. The latter was proved in other works to be +able to finely characterize the multiple relaxation time dynamics of proteins. +The fOU model showed that aIF6 and eIF6 can be distinguished from each other by their +dynamical properties. In particular it was shown that they have different characteristic +q-dependent relaxation times and give different responses to pressure application. Indeed, +when pressure is applied one would expect that slower diffusive motions on large length +scales are slowed down since they require large scale spatial rearrangements which are +increasingly hindered under pressure. Parameter τ from fit of aIF6 seems to confirm this +behaviour whereas it does not for eIF6 in which it is lowered by pressure increase. This fact +could be explained by the possible denaturation of eIF6, which has already been observed in +real experiments and that could be visible already in the nanosecond time-scale. +This outcome suggests that fOU parameters are able to capture dynamical properties of +each protein, being able to pinpoint differences between two homologues of the same protein +family. Moreover, it seems evident that if corresponding states can be found from the atomic +MSD, the fOU model can chracterize how unfavorable environmental conditions differentiate +from the physiological one by means of the dynamical parameters. +Indeed, if variation of dynamical properties due to changes in pressure and temperature, +must be related to each protein characteristic, the general framework in which this variation +happens can somehow be a common property of protein families. In this context comparison +of relaxation times in different environmental conditions showed that the approaching +of a favorable environment corresponds to a non-uniform change in relaxation times. +In particular motions involving large domains are less influenced than more localized motions. +7.4 discussion and conclusion 155 +The limited amount and quality of experimental data did not permit to completely verify +this hypothesis made by means of MD simulations. QENS experiments have shown however +consistency with MD results. In particular EISF and the translational diffusion constant found +by experiment at ambient pressure was found to be comparable with those estimated by MD +simulations. High pressure experiments were largely biased by technical problems and could +not give any quantitative result. Nevertheless, a qualitative comparison with MD simulation +was possible by estimating the EISF contribution from the protein solution spectra. + +8 +GENERAL CONCLUS IONS AND PERSPECT IVES +In the introduction was stated that this work was proposed to give an answer to the following +questions: +Where does the extremophilic signature come from ? +If structure cannot be the origin for this, can it be the dynamics?? +The test case for this extremophilic signature searching was to be found in structural +and dynamical properties of the Inititation Factor 6 from Methanococcus Jannaschii, an +archaebacteria which lives in the warm deep sea, near the hydrothermal chemineys. This +protein was chosen for its important role into the synthesis of other proteins, through its +participation into the biogenesis of major ribosome subunits and the limitation of association +of the two subunits. +IF6 homologue from Saccharomyces cerevisiae was chosen as "normal" conterpart for a +detailed comparison. The approach used in this work, which combined MD simulations and +QENS experiments, presented several new aspects to both techniques that requested the +development of novel theoretical and experimental methods. Firstly, a new computational +method was needed to finely pinpoint even small changes in protein structures induced by +environmental changes. For this purpose, a method based on quaternion superposition fits +in conjunction with Chasles’ theorem on rigid body motions was developed. This method, +called ScrewFit, proved to be efficient in finding variations in secondary structure of proteins +and in characterizing them with respect to the deformations in protein structural motifs. The +method found also further developments in protein secondary structure assignments and in +finding the structural effects due to ligand binding in enzymes. +Secondly, the two IF6 homologues were entirely new samples for QENS experiments and +demanded new protocols for expression and purification in order to obtain adequate +sample concentration in final solutions. The developed protocol reported here had a +yield sufficient for neutron scattering measurements of protein solution. Nevertheless, +it also involved other technical complications due to the presence of a N-terminal poly- +histidine tag which was needed to improve the total yield of protein purification. The +157 +158 general conclusions and perspectives +clavage of the supplemental histidine-tag in large volumes needed for high pressure mea- +surements is prohibitive due to its efficiency, the latter being inversely proportional to volume. +The major results of this work are related to the finding of "corresponding states" in +structure and dynamics of each homologue in its respective natural condition. These "states" +are characterized by very similar atomic mean square displacements, meaning that the +atomic internal motions in respective natural conditions are confined to the same length +scales. This type of correspondence was already found in other works on other proteins both +experimentally [192] and by MD simulations[69]. These results were formerly interpreted as +an indication of different "resiliences" of extremophile and mesophile proteins. In this work I +showed that even if corresponding states are found, they do not involve the same dynamical +behavior in extremophilic and mesophilic homologues. Nevertheless, the variation of charac- +teristic time as function of length-scale seems to be able to capture the optimality of conditions. +Throughout this thesis the dynamical characterization of IF6 samples modeled by MD +simulations was pursued using a fractional Brownian dynamics model which proved to +efficiently characterize the multi-time-scale heterogeneity in protein internal motions. +Besides the general discussion about "corresponding states", this work showed also that in +the case of IF6, pressure and temperature induce different local effects in protein structures. +Some of these effects seems to affect regions that probably host functionality of IF6s. The +structural analysis by means of Screwfit parameter profiles showed that pressure and temper- +ature effects are neither equivalent nor of opposite sign. They are qualitatively different. The +present knowledge of these effects does not permit the association of the latter to the global +effects inscribed into the formation of "corresponding states". +The experimental results which were very limited by the absence of adequate protocols and +previously unknown sample instability, could however support indirectly results obtained +from MD simulations. +perspectives This work proposed a new approach to the investigation of evolutionary +adaptation of proteins to extreme environments from both a structural and a dynamical +point of view. Nevertheless, its novelty had to face some experimental limitations. This +did not prevent experimental results being obtained which supported the MD simulations. +159 +Nevertheless, the results shown here should be verified by MD simulations also for longer +time-scales in order to better explore dynamical properties of IF6s. In this context, some +neutron backscattering experiments, which access longer time-scales, have already been +performed during this thesis on the IN16 (Institut Laue Langevin, Grenoble, France) and +HFBS (NIST, Gaithersbourg, USA) spectrometers. +As a whole, this work must be considered preliminary and requires further development +both in expression/purification protocols of samples and in technical instrumentation for +QENS experiments. In fact, the latter may become a limiting factor when performing mea- +surements on protein solutions which require stable samples even at very high concentrations. +This thesis suggested, however, that IF6 constitutes a very interesting sample for studies +on molecular evolution and it is worth being further investigated both by QENS and +other molecular spectroscopy techniques. In particular small angle scattering (X-ray and +neutrons) should be envisaged to obtain more insights into the structural effects of different +environmental conditions and the role of CTAIL in eIF6 stability. +In addition to its role in molecular evolution studies, IF6 dynamical properties could be +explored by neutron scattering also in relation to its recently uncovered role in regulating the +human tumor cell development[172]. +Finally this work constitutes a new approach for investigating molecular evolution. Sim- +ilar approaches have been recently used to investigate the relation between other physical +properties of proteins and their evolutionary history[215]. + +Part III +APPENDIX + +A +BUFFERS USED FOR PROTE IN EXPRESS ION AND PURIF ICAT ION +Table 21: Buffers used for cell lysis and protein purification +Lysis buffer 50mM Tris-HCl pH 7.4 +200mM NaCl +5% Glycerol +1mM PMSF +Wash buffer 50mM Tris-HCl pH 7.4 +1M NaCl +5% Glycerol +1mM β-mercaptoethanol +Elution buffer 50mM Tris-HCl pH7.4 +200mM NaCl +5% Glycerol +200mM Imidazole +1mM β-mercaptoethanol +163 +164 buffers used for protein expression and purification +Table 22: Buffers for dyalisis and storage +Dialyse buffer 20mM Tris pH 7.9 +200mM NaCl +5mM DTT +Storage buffer 50mM Tris-HCl pH 7.4 +200mM NaCl +5% glycerol +5mM DTT +B +CORRECT IONS TO THE STOKES ’ LAW FOR SPHERE DIFFUS ION . +perrin friction factors Perrin factor is a correction to the translational friction in +the case of a rigid spheroid characterized by an axial ratio σ = a/b where a and b are the +axial and the equatorial semiaxis, respectively. For p > 1 one has stick-shaped bodies and for +p < 1 disc-shaped bodies. +The Perrin factor is defined through a multiplicative correction term to the friction coefficient +of a sphere: +f = f ′cor sphere · fP (B.1) +f ′sphere is the friction constant obtained for a sphere of equivalent volume of the spheroid +body. +The factor fP is defined by +2σ2/3 +fP = (B.2) +S +where, +a +σ = +b (√ +arcta |σ +2−1|) +S = 2 · √n σ +|σ2−1| +σ +Hence, the diffusion constant for a spheroid reads as follow: +KBT +Dsp = ′ · +S +f 2σ(sphere 2/3) +diffusion constant for a torus The derivation of the translational diffusion +constant for a torus can be found in [193]. Assuming rotational and traslational diffusion as +decoupled, one obtains for the translational part: +KBT · ( (8a) 1)Dsp = log + +8πµa b 2 +where a and b are defined in Figure 65. µ is the viscosity. +165 +166 corrections to the stokes’ law for sphere diffusion. +Figure 65: Local coordinates of a Torus reprinted from reference [193] +❚♦r✉s ❝♦rr❡❝t✐♦♥ To perform the correction due to the toroidal shape of the protein I +estimated the values of a and b defined as in Figure 65. 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(Cité aux +pages xviii et 19.) diff --git a/examples/theses/smigaj.pdf b/examples/theses/smigaj.pdf new file mode 100644 index 00000000..ffc823b1 Binary files /dev/null and b/examples/theses/smigaj.pdf differ diff --git a/examples/theses/smigaj/fulltext.pdf b/examples/theses/smigaj/fulltext.pdf new file mode 100644 index 00000000..ffc823b1 Binary files /dev/null and b/examples/theses/smigaj/fulltext.pdf differ diff --git a/examples/theses/smigaj/fulltext.pdf.txt b/examples/theses/smigaj/fulltext.pdf.txt new file mode 100644 index 00000000..53effdd9 --- /dev/null +++ b/examples/theses/smigaj/fulltext.pdf.txt @@ -0,0 +1,6257 @@ +Design and numerical modelling of integrated optical +components +Wojciech S´migaj +To cite this version: +Wojciech S´migaj. Design and numerical modelling of integrated optical components. Mathe- +matical Physics. Universite´ Paul Ce´zanne - Aix-Marseille III, 2010. English. +HAL Id: tel-00567213 +https://tel.archives-ouvertes.fr/tel-00567213 +Submitted on 18 Feb 2011 +HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est +archive for the deposit and dissemination of sci- destine´e au de´poˆt et a` la diffusion de documents +entific research documents, whether they are pub- scientifiques de niveau recherche, publie´s ou non, +lished or not. The documents may come from e´manant des e´tablissements d’enseignement et de +teaching and research institutions in France or recherche franc¸ais ou e´trangers, des laboratoires +abroad, or from public or private research centers. publics ou prive´s. +Thèse presentée à l’Université Paul Cézanne (Aix-Marseille III) +pour obtenir le grade de docteur en sciences +Conception et modélisation numérique +de composants optiques en nanophotonique intégrée +Design and numerical modelling +of integrated optical components +Wojciech S´MIGAJ +22 septembre 2010 +Laboratoire d’accueil Institut Fresnel, équipe CLARTE +Formation doctorale physique théorique et mathématique +Membres du jury +Philippe LALANNE rapporteur +Andrey A. FEDYANIN rapporteur +Didier LIPPENS examinateur +Maciej KRAWCZYK examinateur +Mathias VANWOLLEGHEM examinateur +Stefan ENOCH directeur de thèse +Boris GRALAK tuteur de thèse + +Contents +Acknowledgements 5 +Résumé en français 7 +1 Preliminaries 15 +1.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 +1.2 Outline of the thesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 +1.3 Notational conventions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 +1.4 Maxwell’s equations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 +2 Effective-medium model of photonic crystals 21 +2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 +2.2 Definition of the effective parameters of photonic crystals . . . . . . . . . . . . . . . . . 22 +2.2.1 Preliminaries: the homogeneous-medium case . . . . . . . . . . . . . . . . . . 22 +2.2.2 Existing definitions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 +2.2.3 Proposed definition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 +2.3 Influence of symmetries on the effective parameters . . . . . . . . . . . . . . . . . . . . 27 +2.3.1 Real-valuedness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 +2.3.2 Continuity and boundedness . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 +2.4 Examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 +2.4.1 Hexagonal lattice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 +2.4.2 Square lattice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 +2.4.3 Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 +2.5 Validity of the single-mode approximation . . . . . . . . . . . . . . . . . . . . . . . . . 40 +2.6 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44 +3 Antireflection gratings for photonic crystals 45 +3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 +3.2 Types of antireflection structures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 +3.2.1 Antireflection structures for homogeneous media . . . . . . . . . . . . . . . . . 45 +3.2.2 Antireflection structures for photonic crystals . . . . . . . . . . . . . . . . . . . 46 +3.3 Design procedure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 +3.4 Examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 +3.4.1 A photonic-crystal flat lens . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 +3.4.2 A supercollimating photonic crystal . . . . . . . . . . . . . . . . . . . . . . . . 59 +3.4.3 A photonic-crystal superprism . . . . . . . . . . . . . . . . . . . . . . . . . . . 62 +3.5 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63 +3 +4 Contents +4 Magneto-optical circulators 65 +4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 +4.1.1 Basic characteristics of isolators and circulators . . . . . . . . . . . . . . . . . . 65 +4.1.2 Routes to nonreciprocity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66 +4.1.3 Experimental realisations of optical isolators and circulators . . . . . . . . . . . 67 +4.1.4 Outline of this chapter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72 +4.2 Extension of the coupled-wave model . . . . . . . . . . . . . . . . . . . . . . . . . . . 72 +4.2.1 Inclusion of direct coupling between waveguides . . . . . . . . . . . . . . . . . 72 +4.2.2 Inclusion of radiation loss . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77 +4.3 Cavities with circular symmetry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79 +4.4 Photonic-crystal-based circulators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82 +4.5 Rib-waveguide-based circulators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90 +4.5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90 +4.5.2 Numerical calculations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92 +4.5.3 Geometry optimisation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97 +4.5.4 Fabrication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101 +4.6 Simulations of three-dimensional axisymmetric cavities . . . . . . . . . . . . . . . . . . 101 +4.6.1 Evaluation of possible three-dimensional geometries . . . . . . . . . . . . . . . 101 +4.6.2 Towards cavities with higher quality factor . . . . . . . . . . . . . . . . . . . . 105 +4.7 Conclusions and perspectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111 +5 Numerical methods 115 +5.1 Multiple-scattering method for systems containing gyrotropic media . . . . . . . . . . . 115 +5.2 Calculation of photonic-crystal band structures with Fourier-Bessel expansions . . . . . 118 +5.2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118 +5.2.2 Formulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119 +5.2.3 Numerical examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123 +5.2.4 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 128 +5.3 Finite-element simulations of three-dimensional axisymmetric cavities . . . . . . . . . . 128 +5.3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 128 +5.3.2 Formulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129 +5.3.3 Numerical implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137 +5.3.4 Evaluation of accuracy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 138 +6 Conclusions and perspectives 143 +Bibliography 145 +Acknowledgements +I have been very privileged to have undoubtedly the most supportive, reliable and friendly advisor anyone +could ask for, namely Boris Gralak. While not hesitating to offer his advice and share his experience, he +let me enjoy a complete liberty in the pursuit of my scientific interests. I really appreciated his eye for +detail, his striving for clarity and precision (even as I am writing these words, Boris is still hunting for +the remaining mistakes in the French summary of this thesis), as well as his inextinguishable optimism. +In addition to being a mentor, he became a friend. I thank him and Mylène for all the evenings we spent +together. I am also indebted to Stefan Enoch, who agreed to act as the director of this thesis, in spite of +his numerous responsibilities as the associate director of Institut Fresnel. +My gratitude extends towards all the members of the CLARTE team in Institut Fresnel, who gave +me a warm welcome upon my arrival to Marseille three years ago and have ensured an excellent work- +ing environment ever since. Four persons deserve a special mention. Gérard Tayeb was always willing +to share his experience in the development of computational methods. On various occasions, he took +time to participate in rehearsals of my oral presentations, and his help and advice was invariably much +appreciated. I was also fortunate to be able to collaborate with Daniel Maystre, whose profound un- +derstanding of the mathematical foundations of numerical algorithms is unmatched by anyone I know. +Sebastién Guenneau and Javier Romero-Vivas took active part in the development of magneto-optical +circulators and performed numerous simulations that helped to optimise the devices. Besides, Javier and +I shared the joys and sorrows of a foreigner in France (« C’est Marseille. . . »). +This thesis owes also a lot to collaborations with several research groups from outside Marseille. +The work on antireflection gratings for photonic crystals was done in collaboration with teams from +Université de Lille I and Université de Bourgogne in Dijon. Maxence Hofman and Olivier Vanbésien +from the DOME team in Université de Lille I manufactured samples of photonic-crystal flat lens covered +with the antireflection gratings we had designed. Geoffroy Scherrer, Benoît Cluzel and Frédérique de +Fornel from the OCP team in Université de Bourgogne performed the near-field characterisation of these +samples. I would like to thank all of them for the interesting and fruitful meetings. Special thanks go to +Olivier for giving us all a taste of the delicious Flemish cuisine. I am also indebted to Didier Lippens, +director of the DOME team, for having accepted the invitation to act as a member of the examining board. +I greatly enjoyed the collaboration with the members of the MMS team in Institut d’Électronique +Fondamentale (IEF) in Orsay on magneto-optical circulators. I am particularly grateful to Mathias Van- +wolleghem, who introduced me to the fascinating topic of non-reciprocity in optics, infecting me with his +enthusiasm. Luba Magdenko and Béatrice Dagens devoted a lot of effort to the fabrication of prototypes +of the circulators, gradually taming the etch-resistant bismuth-iron-garnet substrates. Luba also took part +in the numerical modelling of the circulators. Always ready to ask inconvenient questions and to point +out the experimental constraints, she was fun to work with. Thanks are due to the whole team for the +innumerable discussions and e-mail interchanges we have had, as well as for inviting Boris and me to +spend a month at IEF. +I am no less indebted to Maciej Krawczyk from Adam Mickiewicz University in Poznan´, the advisor +for my Master’s thesis, who has also accepted to be a member of the examination board. Thanks to +5 +6 Acknowledgements +Maciej I have been able to keep in touch with my alma mater. I am grateful for his continuous support +and for his genuine interest in the progress of my research. I am also indebted to Henryk Puszkarski, +director of the Surface Physics Division in Poznan´, for his willingness to share his experience and advice. +I particularly want to thank all the members of Prof. Puszkarski’s group for the warm welcome they gave +me whenever I came back to Poznan´. +I would like to extend my sincere gratitude to Philippe Lalanne from Institut d’Optique in Palaiseau +and to Andrey A. Fedyanin from Lomonosov Moscow State University for accepting to write reviews of +this thesis. I also acknowledge the French Ministry of Higher Education and Research for providing its +funding. +Finally, I would like to thank all my friends and my family, whose presence has been absolutely +invaluable during these three years. I am deeply grateful to my parents and sister for their continuing +support, kindness and love. My fellow Ph.D. students from the CLARTE and HIPE teams in Institut Fres- +nel, Alexis, Fabien, Raphaël P., Raphaël L., Mohamed, Xiaoyun, Frédéric, Muamer and Guillaume con- +tributed to making the lab the great place it was. My special thanks go to all the members of Aumônerie +Jer’aum,? who made me feel at home in Marseille. I will miss you much when I leave! Lastly, I want to +thank all of my Polish friends, especially Kasia, Małgosia, Milena, Alicja, Marcin, Jacek, Wawrzyniec +and Karol. +Wojciech S´migaj, Marseille, 1 September 2010 +? Jean Pol and Jean, Louis and Paul, Jules Hervé and Estelle, Jeannette, Alexandra, Lucie, Marion, Alexis, Frédéric, Césaire, +Romuald, Matthieu, Descartes, Jean-François and Yen, Rakia, Chinh, Olga, Damien, Jean-Marie, Charles and Yvri, Katell, +Randy, Thibault, Priscilla, Melissa. . . +Résumé en français +Contexte historique +L’aube de la seconde moitié du XXème siècle a été marquée par l’invention des circuits électroniques +intégrés fabriqués dans des couches minces semiconductrices. En raison de leur faible coût et de leur +petite taille, les circuits intégrés ont rapidement presque supplanté les « gros » composants électroniques : +les bobines, les tubes électroniques etc. Ils ont fourni les moyens de la révolution technologique qui a +fait des appareils électroniques compacts une partie intégrante de la vie moderne. +Peu de temps après la première démonstration expérimentale du laser en 1960, le concept des cir- +cuits optiques intégrés est apparu. Par analogie avec leurs homologues électroniques, ils devaient ouvrir +la voie à la miniaturisation des dispositifs optiques. Depuis la découverte du laser, des progrès signifi- +catifs ont été accomplis : de nombreux composants photoniques intégrés, tels que coupleurs, filtres ou +multiplexeurs, sont couramment utilisés dans les dispositifs disponibles dans le commerce. Toutefois, +il faut admettre que le développement de la technologie des circuits optiques intégrés a été beaucoup +plus lent que celui des circuits électroniques. Pour preuve, si les processeurs modernes contiennent des +millions de transistors sur une seule puce, les circuits intégrés optiques les plus complexes réalisés à ce +jour se composent d’à peine quelques centaines de composants [1–4]. +Il semble y avoir deux raisons principales à cette différence. Premièrement, la longueur d’onde de +la lumière aux fréquences de télécommunications, qui est de l’ordre de 0.1–1 µm dans des matériaux +diélectriques typiques, est beaucoup plus grande que la longueur de l’onde de Broglie d’un électron au +niveau de Fermi d’un métal classique, 0.1–1 nm [5, p. 120]. Celle-ci est si petite que, jusqu’à récemment, +les propriétés ondulatoires des électrons pourraient être quasiment ignorées dans la conception de com- +posants électroniques, qui pourraient donc être miniaturisés sans encombre. Au contraire, la longueur +d’onde de la lumière constitue une vraie limite de la taille des composants optiques.? Deuxièmement, +pour des applications diverses, il est avantageux d’utiliser des substrats avec des propriétés physiques +particulières, présentant par exemple d’importants effets électro-, magnéto- ou acousto-optiques. Étant +donné que ces propriétés sont difficiles à obtenir simultanément dans un seul matériau, les premiers +circuits optiques intégrés ont été construits de la façon dite hybride, où tous les composants sont fabri- +qués séparément en utilisant des matériaux et technologies différents avant d’être assemblés sur un seul +substrat [7, p. 9]. Avec cette approche, chaque composant peut être optimisé séparément ; par contre, +l’alignement et le couplage des différents éléments constituent une difficulté de taille. Ainsi, les circuits +optiques intégrés hybrides ne comportent pas plus que quelques composants. Les circuits intégrés les +plus complexes sont donc fabriqués de façon monolithique, où tout le système est gravé dans un seul +substrat. Actuellement, la technologie de ce type la plus avancée est certainement celle qui est fondée sur +le phosphure d’indium. +L’introduction de la notion de cristaux photoniques à la fin des années 1980 [8, 9] a profondément +influencé la recherche sur les circuits optiques intégrés. Le cristal photonique est défini comme un sys- +? Les composants plasmoniques, qui constituent actuellement le sujet de recherches actives, pourraient néanmoins permettre +d’aller plus loin dans la miniaturisation des dispositifs optiques [6]. +7 +8 Résumé en français +tème dans lequel la permittivité et la perméabilité dépendent périodiquement de la variable d’espace : +ainsi, il peut être considéré comme un analogue électromagnétique d’un solide cristallin. La périodi- +cité de la permittivité et de la perméabilité peut donner lieu à des « gaps », c’est-à-dire, des bandes de +fréquences où aucun état propagatif (transportant de l’énergie) n’existe à l’intérieur du cristal. Rapide- +ment, pour des fréquences situées dans un gap, des défauts linéaires le long desquels des modes localisés +peuvent se propager ont été imaginés dans des cristaux photoniques ; de tels défauts peuvent donc ser- +vir de guides d’onde [10]. En même temps, on a démontré que les défauts ponctuels dans les cristaux +photoniques peuvent se comporter comme des résonateurs avec la valeur du ratio entre le facteur de +qualité et le volume du mode potentiellement très importante [10]. Toutefois, c’est une autre découverte +qui va révéler l’énorme intérêt envers les cristaux photoniques en tant que moyen de miniaturiser les +circuits optiques intégrés : les modes de guides d’onde à cristaux photoniques peuvent se propager le +long des coudes pratiquement sans pertes d’énergie [11]. En effet, les rayons de courbure des guides +d’onde standards doivent être de l’ordre de quelques millimètres afin de maintenir les pertes à un niveau +raisonnable [10]. En revanche, les guides à cristaux photoniques peuvent avoir des coudes avec un rayon +de courbure d’environ un micromètre. Jusqu’ici, de nombreux dispositifs optiques basés sur les guides +d’onde et résonateurs à cristaux photoniques ont été proposés, et plusieurs d’entre eux ont été réalisés +expérimentalement. Pour une revue relativement récente de l’état actuel de la recherche sur les cristaux +photoniques, le lecteur peut consulter la référence 12. +Alors que les premières études de cristaux photoniques ont porté principalement sur la recherche de +structures fournissant le gap le plus large et sur la conception de composants fonctionnant dans le gap, +la dernière décennie a vu la communauté porter une attention croissante aux propriétés inhabituelles des +cristaux photoniques en dehors des gaps. Contrairement aux diélectriques homogènes, dont la surface +d’isofréquence est une ellipsoïde, la forme de la surface d’isofréquence des cristaux photoniques peut +être très compliquée.? En outre, la vitesse de groupe dans un cristal photonique peut être orientée dans +n’importe quelle direction. Cette richesse de la relation de dispersion donne lieu à des phénomènes +inhabituels [13], comme la réfraction négative de la lumière [14], l’apparition de faisceaux autocollimatés +[15] ou l’effet « superprism » [16]. Ainsi, il a été reconnu que même les cristaux photoniques sans défauts +(la présence de surfaces exceptée) peuvent constituer des dispositifs utiles, par exemple des lentilles +planes [17, 18] ou des diviseurs de faisceau [19]. +Structure de la thèse +Cette thèse est consacrée à la conception et l’analyse théorique et numérique de certains composants +en cristaux photoniques. Dans le chapitre 1, nous donnons une brève introduction à la thématique de la +thèse, nous définissons les notations utilisées dans la suite, et nous rappelons quelques faits de base sur +les équations de Maxwell, fondement de tous les développements ultérieurs. L’essence de la thèse, les +chapitres 2 à 5, se divise naturellement en trois parties distinctes. Dans les chapitres 2 et 3, nous étudions +les cristaux photoniques bidimensionnels sans défauts, limités par une ou deux surfaces planes parallèles. +En particulier, nous nous intéressons à la dépendance des propriétés de tels cristaux à l’égard de la +structure des interfaces les séparant des milieux homogènes. Dans le chapitre 4, qui constitue la deuxième +partie essentielle de cette thèse, nous tournons notre attention vers un type de composants optiques plus +traditionnels, puisque basés sur les guides d’onde : les circulateurs magnéto-optiques. La troisième partie +de la thèse, le chapitre 5, est consacrée à la présentation de quelques méthodes numériques développées +pour les simulations des dispositifs analysés dans les chapitres précédents. La thèse se termine par le +chapitre 6, dans lequel nous mettons en évidence les résultats qui nous semblent les plus importants +? On observe la même chose dans la théorie de l’état solide : la surface de Fermi dans un gaz d’électrons libres est sphérique, +mais dans un solide réel, elle a souvent une forme très complexe, parfois appelée, judicieusement, un monstre. +Chapitre 2 : Modèle du milieu effectif pour les cristaux photoniques 9 +et nous indiquons les perspectives des futurs travaux sur certains sujets. Ci-dessous nous résumons le +contenu des chapitres qui constituent le corps de la thèse. +Chapitre 2 : Modèle du milieu effectif pour les cristaux photoniques +Comme mentionné ci-dessus, une caractéristique essentielle des cristaux photoniques réside dans la ri- +chesse de leur relation de dispersion. La forme des surfaces d’isofréquence des cristaux photoniques +peut être très complexe : ils contiennent parfois des changements de direction brutaux séparant des ré- +gions planes ou même concaves. Toutefois, à certaines fréquences, ils peuvent également atteindre une +forme ellipsoïdale, caractéristique pour des milieux homogènes. En conséquence, la question se pose si +les cristaux peuvent alors être correctement décrits par le modèle du milieu effectif, dans lequel ils sont +représentés par un matériau homogène avec une certaine permittivité  et perméabilité . Comme les +matériaux homogènes sont incomparablement plus faciles à analyser que les matériaux structurés, une +réponse affirmative simplifierait le développement de dispositifs à cristaux photoniques, en particulier de +ceux qui utilisent l’effet de la réfraction négative [14]. En effet, la plupart des composants basés sur ce +phénomène, comme les célèbres superlentilles [17], ont été conçus pour des matériaux à indice négatif +homogènes imaginés par Veselago [20]. +De nombreux documents traitant de ce sujet ont déjà été publiés [21–32], donnant lieu à plusieurs +définitions des paramètres effectifs des cristaux photoniques, reportées au paragraphe 2.2.2. Cependant, +ces définitions sont généralement introduites de façon heuristique et manquent de justification formelle. +En outre, pour toutes ces définitions, la confrontation du coefficient de réflexion du cristal calculé rigou- +reusement avec celui du milieu effectif correspondant n’a jusqu’alors été effectuée que pour l’incidence +normale [24–26] ou quasi-normale [28]. Pourtant, de nombreuses applications, y compris celles utilisant +la réfraction négative, s’appuient sur le comportement des ondes incidentes aux grands angles, voire des +ondes évanescentes. Le domaine de validité de l’approximation du milieu effectif est, par conséquent, +encore mal connu. +L’objectif du travail présenté dans le chapitre 2 est de remédier à ces lacunes. Dans la section 2.2, +nous adoptons l’hypothèse de l’approximation monomode pour fournir une justification mathématique +rigoureuse à une certaine définition des paramètres effectifs des cristaux photoniques bidimensionnels. +Dans la section 2.3, nous étudions l’influence de la symétrie du plan de troncature du cristal et celle des +modes propres du cristal sur le comportement de ses paramètres effectifs. En particulier, nous dérivons +les conditions dans lesquelles les paramètres effectifs sont réels et bornés pour tous les angles d’inci- +dence. Nous généralisons ainsi le résultat obtenu par Pierre and Gralak [27] dans le cas unidimensionnel. +Pour évaluer la précision du modèle du milieu effectif, nous comparons dans la section 2.4 les valeurs +du coefficient de la réflexion spéculaire prévu dans le cadre du modèle avec les résultats des calculs +numériques rigoureux. Ces tests, effectués pour deux cristaux différents à un nombre de fréquences et +dans tout le domaine d’angle d’incidence, indiquent que la précision du modèle est limitée par celle de +l’hypothèse de départ, l’approximation monomode. +Ces résultats ont imposé d’analyser de façon précise le domaine de validité de l’approximation mo- +nomode. Dans la section 2.5, nous établissons un lien entre les amplitudes relatives d’excitation des +modes propres d’un cristal et le spectre de Fourier des champs électrique et magnétique de ces modes sur +le plan de troncature du cristal. Ce lien est utilisé pour formuler un critère d’estimation de la précision de +l’approximation monomode : cette hypothèse est d’autant plus pertinente que la courbe d’isofréquence +du cristal photonique se rapproche de celle du milieu homogène avec l’indice de réfraction égal à la +moyenne de l’indice de réfraction du cristal. Enfin, nous considérons le cas particulier des modes en- +gendrant la réfraction négative. Nous observons que leur excitation par une onde plane est accompagnée +pour la plupart des angles d’incidence par une excitation simultanée d’autres modes (évanescents) avec +10 Résumé en français +une amplitude importante. Dans ce cas, l’approximation monomode d’un cristal photonique présentant +le phénomène de réfraction négative ne peut être considéré comme (relativement) précise que près de +l’incidence normale. Notre analyse montre qu’il hasardeux de traiter un tel cristal photonique comme +un matériau homogène pour des angles d’incidence importants ou dans le régime d’ondes évanescentes. +Finalement, le comportement de systèmes contenant des matériaux d’indice négatif homogènes peut +s’avérer considérablement différent lorsque ces matériaux sont remplacés par des cristaux photoniques, +même si les courbes d’isofréquence (et, par conséquent, les indices de réfraction définis par l’intermé- +diaire de la vitesse de phase) des deux milieux sont identiques. +Chapitre 3 : Réseaux antiréfléchissants pour des cristaux photoniques +Les courbes du coefficient de réflexion des cristaux photoniques étudiés dans le chapitre 2 (figures 2.5, +2.7, 2.10, 2.12 et 2.13) montrent que des ondes réfléchies d’amplitude importante sont souvent générées +sur la surface des cristaux photoniques. Dans de nombreuses applications, il est au contraire souhaitable +d’obtenir un transfert d’énergie parfait entre l’onde plane incidente et le mode propre propagatif du cristal +photoniques (ou, plus rarement, plusieurs modes propagatifs). Les ondes réfléchies de caractère propa- +gatif doivent donc être éliminées. Le chapitre 3 concerne la conception de structures antiréfléchissantes +qui, placées sur la surface d’un cristal photonique, diminuent significativement la fraction d’énergie per- +due dans les ondes réfléchies. Après avoir examiné les classes de telles structures proposées à ce jour +(section 3.2), dans la section 3.3, nous proposons une nouvelle méthode de conception de réseaux anti- +réfléchissants avec une tolérance angulaire importante. +L’algorithme de conception que nous proposons consiste en trois étapes. Premièrement, les para- +mètres d’une couche homogène antiréfléchissante sont calculés à partir d’un modèle du milieu effectif +du cristal photonique en question. Deuxièmement, une théorie analytique du milieu effectif des réseaux +lamellaires binaires est utilisée pour trouver les paramètres d’un réseau composé des seuls matériaux +constitutifs du cristal, et dont les propriétés sont proches de celles de la couche obtenue à l’étape pré- +cédente. Troisièmement, la forme de la grille est raffinée à l’aide d’une routine numérique de recherche +locale qui vise à minimiser la réflectance moyenne de la structure dans la gamme désirée d’angle ou de +la fréquence. Cette dernière étape est nécessaire en raison des approximations faites dans les dérivations +analytiques utilisées dans les deux premières étapes de la procédure. +Dans la section 3.4, nous appliquons la méthode proposée à trois cristaux dont les courbes d’iso- +fréquence sont de courbure différente : un cristal présentant le phénomène d’autocollimation, avec une +courbe isofréquence très plate ; un cristal présentant l’effet de réfraction négative, avec une courbe d’iso- +fréquence presque circulaire ; et un cristal photonique du type « superprism », dont la courbe isofréquence +a des cornes. Dans les deux premiers cas, nous réussissons à concevoir des réseaux antiréfléchissants ga- +rantissant une réflectance très faible dans une vaste gamme angulaire. Les structures obtenues sont très +compactes et paraissent simple à fabriquer ; en fait, l’amélioration apportée par ces réseaux antiréflé- +chissants à la transmission à travers une lentille plate de cristal photonique (basée sur l’effet de réfrac- +tion négative) a déjà été confirmée expérimentalement [33]. Cependant, dans le cas du cristal du type +« superprism », la procédure de conception échoue à cause de la violation de certaines contraintes sur +l’impédance effective du cristal, qui doivent être remplies pour que la couche antiréfléchissante géné- +rée dans la première étape puisse être approchée par un réseau binaire constitué de matériaux réalistes. +L’existence de ces contraintes est la limitation principale de la procédure présentée. +Chapitre 4 : Circulateurs magnéto-optiques 11 +Chapitre 4 : Circulateurs magnéto-optiques +Dans le chapitre 4, nous étudions le problème de la miniaturisation des circulateurs optiques, qui ap- +partiennent aux derniers composants optiques intégrés importants dont la version intégrée ne soit pas +encore disponible dans le commerce. Le circulateur est un dispositif reliant n  3 guides d’onde de telle +sorte que l’énergie entrant par le guide Wi (1  i < n) est entièrement transférée au guide WiC1 et +l’énergie entrant par le guide Wn est transférée au guide W1. Un dispositif apparenté, l’isolateur, relie +deux guides d’onde ainsi que le transfert d’énergie soit interdit dans un sens, mais autorisé dans l’autre. +Manifestement, le circulateur peut également faire fonction d’isolateur. +Ces deux composants ont plusieurs applications importantes. Ils peuvent servir à éliminer les ondes +réfléchies des composants d’impédance mal adaptée dans des circuits complexes ; la présence de telles +ondes peut donner lieu à des interférences indésirables et couplages parasites [34]. Les composants en +question sont également employés dans l’acheminement des signaux dans des dispositifs tels que les +multiplexeurs [35]. Dans le domaine optique, l’application la plus importante des isolateurs est sans +doute la protection des lasers de la lumière réfléchie, qui perturbe la configuration des ondes stationnaires +dans une cavité laser et peut entraîner le laser à devenir instable [36]. +Les circulateurs et les isolateurs sont dits des dispositifs non-réciproques. Cela signifie, en particu- +lier, qu’ils ne peuvent pas être réalisés en utilisant uniquement des matériaux linéaires, invariants dans le +temps et dont la permittivité et la perméabilité s’expriment par des tenseurs symétriques. La façon la plus +commune d’obtenir un système non-réciproque est d’y inclure un matériau présentant l’effet magnéto- +optique : par exemple, un grenat synthétique tel que le grenat de fer et bismuth. Traditionnellement, les +isolateurs sont constitués d’une plaque d’un matériau magnéto-optique placée entre deux polariseurs, P1 +et P , tournés de 45ı2 l’un par rapport à l’autre. Le fonctionnement d’un tel isolateur s’appuie sur l’effet +de Faraday, qui consiste en une rotation non-réciproque du plan de polarisation des ondes électromagné- +tiques traversant un matériau magnéto-optique dans la direction parallèle à celle d’un champ magnétique +statique externe. Grâce à cet effet, le plan de polarisation des ondes qui entrent dans l’isolateur par le +polariseur P1 (par exemple) s’aligne progressivement avec l’axe du polariseur P2 ; par conséquent, ces +ondes sont transmises à travers le dispositif. En revanche, le plan de polarisation des ondes entrant par le +polariseur P2 devient perpendiculaire à l’axe du polariseur P1, par lequel ils sont donc absorbées. +Malheureusement, en raison de leur structure non plane, les isolateurs décrits ci-dessus ne peuvent +être produits comme éléments d’un circuit optique intégré. En conséquence, dans les deux dernières +décennies, beaucoup d’efforts ont été faits pour concevoir des isolateurs et des circulateurs adaptés à la +fabrication sur puce (voir la référence 35 pour une revue de la littérature). Le fonctionnement de la plupart +des dispositifs proposés jusqu’à présent est basé sur la conversion non-réciproque des modes propres d’un +guide d’onde (un phénomène analogue à l’effet de Faraday) ou sur l’interférence des ondes se propageant +dans deux ou plusieurs guides d’onde placés dans un champ magnétique statique externe. Cependant, +l’effet magnéto-optique est généralement faible : il ne peut influencer sensiblement le comportement +de la lumière que si celle-ci interagit avec un matériau magnéto-optique sur un chemin optique très +long, typiquement 1000, où  est la longueur d’onde de la lumière. En conséquence, les isolateurs et +circulateurs basés sur des guides d’onde sont très longs (1mm), ce qui rend difficile leur intégration +avec d’autres composants optiques fondamentaux, beaucoup plus petits. +Une stratégie de miniaturisation potentielle consiste à employer des résonateurs optiques pour allon- +ger le temps de l’interaction de la lumière avec le matériau magnéto-optique, au prix d’une réduction de la +bande passante du composant. En 2005,Wang et Fan [34, 37] ont proposé un circulateur magnéto-optique +inspiré d’une classe de dispositifs couramment utilisés dans le domaine micro-ondes, où, cependant, les +effets induits par un champ magnétique statique externe sont beaucoup plus importants. Le circulateur +de Wang et Fan se compose de trois guides d’onde à cristal photonique couplés à une cavité à cristal +12 Résumé en français +photonique dans laquelle deux modes propres bien localisés peuvent être excités. Leurs fréquences sont +décalées l’une par rapport à l’autre en présence d’un champ magnétique statique externe, la matrice du +cristal photonique étant d’un matériau magnéto-optique. En utilisant le formalisme du couplage faible, +on peut montrer qu’un tel système fonctionne comme un circulateur. +Il faut noter, cependant, que la séparation des fréquences des deux modes de la cavité originale pré- +sentée dans les références 34 et 37 est négligeable dans un champ magnétique statique externe uniforme. +Elle ne devient acceptable que si le matériau magnéto-optique dans la cavité est divisé dans de nombreux +domaines magnétiques polarisés dans les sens contraires, chacun d’une superficie d’une fraction de µm2. +La réalisation de tels domaines est, en pratique, très difficile technologiquement, car elle nécessite un +contrôle précis – à l’échelle nanométrique – du champ magnétique statique externe appliqué. Pour cette +raison, le dispositif conçu par Wang et Fan n’a jamais été fabriqué. L’objectif de la recherche présentée +dans le chapitre 4 était d’élaborer la conception d’un circulateur s’appuyant sur un résonateur magnéto- +optique et capable de fonctionner dans un champ magnétique statique externe uniforme, c’est-à-dire, +avec tout le matériau magnéto-optique aimanté uniformément. +Nous commençons par étudier comment la géométrie d’une cavité magnéto-optique bidimension- +nelle placée dans un champ magnétique statique externe influence le décalage des fréquences de ses +deux modes propres (section 4.3). Afin de mieux comprendre le problème, nous nous concentrons sur +le modèle simplifié d’une cavité axisymétrique, c’est à dire composée d’une série d’anneaux concen- +triques. De telles structures peuvent être traitées analytiquement ; en particulier, nous sommes en mesure +de montrer que le décalage maximal des fréquences dans un champ magnétique statique externe uni- +forme est obtenu pour des cavités ayant la forme d’un miroir de Bragg annulaire. Nous obtenons ainsi +une procédure explicite pour la conception de cavités axisymétriques optimisées pour le fonctionnement +dans un champ magnétique statique externe uniforme, ce qui constitue le fondement de cette étude. +L’étape suivante de la conception du circulateur est de coupler efficacement la cavité avec les guides +d’onde d’entrée et de sortie. Dans les sections 4.4 et 4.5, deux classes de structures sont examinées : +les circulateurs à base de cristaux photoniques, semblables à ceux étudiés dans les références 34 et 37, +et les circulateurs dans lesquels le revêtement à cristal photonique est supprimé et la cavité est couplée +directement à des guides d’onde standards. Cette élimination du cristal photonique conduit à une simpli- +fication importante de la géométrie du dispositif. Néanmoins, l’analyse théorique de son fonctionnement +devient un peu plus compliqué, car on doit tenir compte des effets du couplage direct entre les guides +d’onde et des pertes d’énergie par le rayonnement dans le plan du dispositif, comme il est décrit dans la +section 4.2. Les performances des deux catégories de circulateurs sont évaluées à l’aide de simulations +numériques rigoureuses. Nous concluons que la simplification de géométrie résultant de l’élimination du +cristal photonique ne doit pas être accompagnée d’une détérioration de la performance du composant. +Par conséquent, dans la suite du chapitre 4 nous nous concentrons sur les circulateurs avec des guides +standards, c’est-à-dire sans cristaux photoniques. +A ce stade, il convient de résumer les résultats des tests expérimentaux de nos circulateurs, fabriqués +et caractérisés par L. Magdenko et B. Dagens (Institut d’Electronique Fondamentale, Orsay, France) dans +des hétérostructures composées des grenats de bismuth et fer et de gadolinium et gallium. Ces résultats +révèlent un problème significatif dans la conception originale des cavités : des pertes d’énergie impor- +tantes par rayonnement hors plan du dispositif. Elles sont une conséquence du fait que la conception +n’était originellement basée que sur des simulations bidimensionnelles (l’approximation d’indice effec- +tif utilisée dans certaines des simulations s’est avérée ne pas avoir été assez précise). C’est pourquoi, dans +la dernière partie du chapitre 4, nous présentons les premiers résultats des simulations tridimensionnelles +des cavités, obtenus avec la méthode des éléments finis décrite dans la section 5.3. Nous démontrons +que le problème des pertes hors-plan peut être surmonté par un ajustement approprié de la géométrie de +la cavité. Plus précisément, le facteur de qualité des modes propres peut être sensiblement amélioré en +Chapitre 5 : Méthodes numériques 13 +recouvrant la cavité avec un matériau ayant un indice de réfraction proche de celui du substrat et par +l’optimisation numérique des positions et des largeurs des anneaux constitutifs de la cavité. A ce jour, +ce raffinement de la conception basé sur des simulations tridimensionnelles demande à être confirmé +expérimentalement. +Chapitre 5 : Méthodes numériques +Dans le chapitre 5, nous présentons les méthodes de calcul développées au cours de cette thèse et utilisées +pour obtenir une partie des résultats présentés dans l’ensemble des chapitres. +La section 5.1 est consacrée à la méthode de diffusion multiple [38–40] pour la solution du problème +de la diffusion de lumière par des cristaux photoniques bidimensionnels composés de cylindres circu- +laires. Cette technique est reconnue depuis longtemps comme l’une des méthodes les plus efficaces pour +traiter ce type de problèmes. La raison en est double. D’une part, les fonctions de base utilisées pour +développer le champ électromagnétique (à savoir les séries de Fourier-Bessel) sont des solutions exactes +des équations de Maxwell, et donc elles sont bien adaptées pour représenter le champ électromagnétique +en présence de ces domaines. Deuxièmement, comme les fonctions de base sont séparables en coordon- +nées polaires, les conditions de continuité satisfaites par le champ électromagnétique sur les surfaces +des cylindres sont simples à exprimer et imposer. Dans la section 5.1, nous montrons que la méthode +en question peut être généralisée aisément au cas des cristaux photoniques contenant des milieux gyro- +tropiques qui respectent la même symétrie axiale que les tiges circulaires [les tenseurs de permittivité et +perméabilité ont alors la forme donnée par l’équation (5.5)]. Nous notons, toutefois, qu’une extension +similaire pour le cas des matériaux avec une anisotropie plus générale n’est pas possible, car la réduction +des équations de Maxwell à l’équation de Helmholtz n’est alors possible qu’au prix d’un changement de +coordonnées transformant des cercles en des ellipses, ce qui engendre des effets secondaires indésirables. +Compte tenu de l’efficacité et la simplicité de la méthode de diffusion multiple, cette méthode a été +également appliquée au calcul de la relation de dispersion des cristaux photoniques infinis composés +de cylindres ou de sphères [41–47]. Elle nécessite, pourtant, de calculer explicitement le champ produit +par un nombre infini de diffuseurs disposés sur un réseau périodique. Ce champ peut être exprimé par +une série dite « lattice sum». Malheureusement, des telles séries sont lentement convergentes, et les +techniques particulières nécessaires pour l’accélération de leur calcul compliquent considérablement la +mise en œuvre de la méthode par rapport au cas d’un système fini. +Dans la section 5.2, nous proposons une technique élégante de calcul de la relation de dispersion des +cristaux photoniques composés de cylindres circulaires. Comme la méthode de diffusion multiple, elle +s’appuie sur le développement du champ électromagnétique sur des solutions exactes des équations de +Maxwell (les séries de Fourier-Bessel), avec l’avantage d’éviter le calcul des « lattice sums ». L’idée de +base est très simple : le champ dans une maille d’un cristal photonique est développé sur des solutions +particulières de l’équation de Helmholtz, et les conditions de Bloch sur les limites de la maille sont im- +posées par collocation. Cette approche est en fait similaire à la technique utilisée dans les simulations +de réseaux avec la méthode de sources fictives afin d’éviter le calcul des fonctions de Green périodiques +[48]. La méthode proposée ici partage également de nombreuses caractéristiques avec la technique des +opérateurs de Dirichlet-Neumann, mise au point dans le groupe de Lu [49, 50]. Par rapport à cette tech- +nique, la présente méthode est plus directe et plus efficace, mais aussi moins générale (spécialement +adaptée aux calculs de la relation de dispersion). +La principale vertu de la méthode que nous proposons est sa grande efficacité : en raison de la +convergence exponentielle des résultats, il est possible d’atteindre une précision relative meilleure que +1010 avec un coût de calcul modeste, comme il est démontré dans plusieurs exemples étudiés dans le +paragraphe 5.2.3. Par conséquent, la technique en question peut fournir des valeurs de référence extrê- +14 Résumé en français +mement précises aux fins des tests d’autres méthodes numériques. La haute précision est aussi précieuse +dans les études avec des effets faibles, tels que la non-réciprocité entraînée par l’influence d’un champ +magnétique statique sur la propagation des ondes aux fréquences optiques. +Pour les cristaux photoniques dont la maille ne contient qu’une seule inclusion circulaire, la mise +en œuvre de cette méthode est directe. Cependant, si plusieurs inclusions sont présentes, la maille doit +être décomposée en sous-mailles englobant les inclusions individuelles, ce qui complique à un certain +degré la mise en œuvre de la méthode. Les inconvénients principales de la technique en question sont +(1) sa restriction à des systèmes contenant des inclusions circulaires et (2) la dégradation visible de sa +précision à la présence des sous-mailles dont la forme diffère nettement de celle d’un cercle centré sur +l’inclusion. +Dans la section 5.3, nous décrivons une variante de la méthode des éléments finis utilisée pour cal- +culer les modes propres de cavités axisymétriques tridimensionnelles ouvertes, contenant des matériaux +gyrotropiques. Cette technique a été employée pour obtenir les résultats présentés dans la section 4.6. +Elle combine des éléments de plusieurs approches décrites dans la littérature, en particulier celles pré- +sentées dans les références 51 et 52. L’apport original de ce travail consiste en l’extension de la méthode +au cas des systèmes contenant des milieux gyrotropiques. Jusqu’à présent, elle n’avait été formulée que +pour des matériaux avec des permittivité et perméabilité représentées par des tenseurs diagonaux, ce qui +est le niveau de généralité nécessaire pour la modélisation des couches absorbantes parfaitement adaptées +(PMLs) [51, 53, 54]. +Nous donnons ici une caractérisation concise de la méthode décrite dans la section 5.3. Nous pro- +fitons d’abord de la symétrie axiale du domaine tridimensionnel en réduisant le problème original à +un système dénombrable des problèmes propres découplés, posés sur un seul plan méridien (bidimen- +sionnel). Nous utilisons des éléments finis nodaux scalaires pour développer la composante azimutale +du champ électrique, et des éléments finis vectoriels pour développer une superposition particulière des +composantes azimutale et méridienne de ce champ. Ce choix d’inconnues permet d’exprimer simple- +ment les conditions de continuité sur l’axe de la cavité. Afin de supprimer les réflexions parasites sur les +limites du domaine de calcul, nous les revêtons de PMLs. La mise en œuvre de la méthode est facilitée +par la disponibilité de plusieurs outils d’open source, en particulier les bibliothèques Hermes (éléments +finis) [55, 56] et SLEPc [57–59] (solution des problèmes aux valeurs propres avec des matrices creuses). +Les tests de convergence présentés dans le paragraphe 5.3.4 montrent que la fréquence propre des +modes localisés d’une cavité magnéto-optique typique conçue de la manière décrite dans la section 4.6 +peut être déterminée avec la précision relative de 105 dans un délai raisonnable sur un ordinateur de +bureau. Nous montrons également que les résultats sont très peu sensibles aux changements des para- +mètres qui contrôlent la troncature du domaine. +Chapter 1 +Preliminaries +1.1 Introduction +The dawn of the second half of the 20. century was marked by the invention of electronic integrated cir- +cuits (ICs) fabricated in semiconductor thin films. Owing to their low cost and small size, ICs quickly all +but displaced older “bulk” electronic components: coils, glass tubes and so on. They provided the means +for the technological revolution that made compact electronic devices an integral part of modern life. +Shortly after the first experimental demonstration of the laser in 1960, the concept of optical ICs +appeared. In analogy to their electronic counterparts, they were to pave the way to the miniaturisation +of optical devices. Significant progress has been made from that time: numerous integrated photonic +components, such as splitters, couplers or multiplexers, are routinely used in commercially available +devices. However, it must be admitted that the development of the optical IC technology has been +incomparably slower than that of electronic ICs. Suffice it to say that while state-of-the-art processors +contain millions of transistors on a single chip, the most complex optical ICs realised to date consist of +barely several hundred components [1–4]. +There seem to be two principal reasons for this difference. First, the wavelength of light at telecom- +munication frequencies, which is on the order of 0.1–1 µm in typical dielectric materials, is much larger +than the de Broglie wavelength of an electron at the Fermi level of a typical metal, 0.1–1 nm [5, p. 120]. +The latter is so small that until recently the wave-like properties of electrons could be essentially ignored +in the design of electronic components, which could therefore be rather straightforwardly miniaturised. +In contrast, the wavelength of light is a real limit on the size of optical components.? Second, for specific +applications it is advantageous to use substrates having particular physical properties, for example ex- +hibiting strong electro-, magneto- or acousto-optical effects. Since these properties are difficult to obtain +simultaneously in a single material, the first optical ICs were built with the so-called hybrid approach: +their individual components were fabricated separately, possibly using different materials and technolo- +gies, and then bonded together to a single substrate [7, p. 9]. The advantage of this approach is that each +component can be optimised separately; the disadvantage lies in the inherent difficulty of aligning and +coupling the various elements. Thus, hybrid optical ICs hardly ever consist of more than a few compo- +nents. ICs of larger complexity can only be fabricated using the monolithic approach, where the whole +system is etched in a single substrate. Currently, the most advanced technology of this type seems to be +that based on indium phosphide. +A boost to the research on optical ICs was given by the introduction of the concept of photonic +crystals (PCs) in late 1980s [8, 9]. A PC is defined as a system in which the permittivity and permeability +are periodically dependent on the position; thus, it can be viewed as an electromagnetic analogue of a +? Plasmonic components, which are currently an area of active research, might enable further miniaturisation of optical +devices [6]. +15 +16 Chapter 1. Preliminaries +crystalline solid. The periodicity of the material properties can give rise to the appearance of band gaps, +i.e., frequency ranges in which no propagative (energy-carrying) states can exist in the crystal. It was +quickly recognised that linear defects in PCs can support localised eigenmodes with frequencies lying +in the band gaps, and thus they can serve as waveguides [10]. Simultaneously, point defects in PCs +were shown to act as resonant cavities with potentially very large quality factor–mode volume ratios +[10]. However, it was the discovery that modes in PC waveguides can propagate around extremely sharp +bends essentially without scattering losses [11] that led to an enormous increase of the interest in PCs as +a possible means for further miniaturisation of optical ICs. Indeed, the bending radii of standard rib or +ridge waveguides need be on the order of millimetres in order to keep the losses at a reasonable level [10]. +Since then, an overwhelming number of optical components made of interconnected PC waveguides and +cavities have been proposed, and several of them have seen experimental realisation. For a relatively +recent review of the current state of research on PCs, see ref. 12. +While the early studies of PCs were focused primarily on the quest for structures providing the +widest band gap and on the design of components operating within band gaps, in the last decade more +and more attention has been devoted to the unusual properties of PCs outside band gaps. In contrast +to homogeneous dielectrics, in which the equifrequency surfaces (EFSs) have the form of ellipsoids, +the shape of the EFSs of PCs can be very complicated.? They can contain flat or even concave areas +separated by sharp corners or edges. In addition, the group velocity need not point away from the origin +of the reciprocal space. This richness of the dispersion relation gives rise to unusual phenomena [13], +such as negative refraction of light [14], appearance of supercollimated beams [15] and the superprism +effect [16]. Thus, it has been recognised that even defect-free (except for the presence of surfaces) PCs +can constitute useful devices, for instance flat lenses [17, 18] or beam splitters [19]. +1.2 Outline of the thesis +This thesis naturally splits into three parts. In chapters 2 and 3 we study defect-free two-dimensional +(2D) PCs limited by one or two parallel surfaces. In particular, we are interested in the dependence of +their properties on the structure of the interfaces separating them from the adjacent homogeneous media. +In chapter 2 we introduce the single-mode approximation and use it as a mathematical foundation +for an effective-medium model of 2D PCs. In contrast to most previous work, we do not restrict our +considerations to the case of waves impinging perpendicularly to the PC surface. We show that our +model allows to reproduce the strong dependence of the effective material properties of a PC on the +position of its truncation plane, observed by previous authors [21]. In particular, we demonstrate that +the effective permittivity and permeability derived in the framework of the model are guaranteed to be +real and continuous only if the truncation plane is chosen in certain particular ways. We test the validity +of the model by comparing the values of the specular reflection coefficient it predicts for some specific +PCs against results of rigorous numerical calculations. Since there has been a lot of interest in using +PCs exhibiting the negative-refraction effect as lossless replacements of metamaterials, we pay particular +attention to the accuracy of the effective-index description of bands with negative group velocity. We find, +however, that it leaves much to be desired, especially for large incidence angles and in the evanescent- +wave region. By means of a qualitative theoretical analysis, we argue that this behaviour is not restricted +to the particular PC under study; instead, the low accuracy of the effective-index approximation is due to +the inherent structure of the field of PC modes responsible for negative refraction. +In chapter 3 we consider the problem of reducing the reflection losses occurring at an interface +between a semi-infinite PC and a homogeneous medium. This is an important issue, severely limiting +? This is analogous to what happens in solid-state theory: the Fermi’s surface in a free electron gas is spherical, but in a real +solid it can have a very complex form, sometimes called, fittingly, a monster. +1.3. Notational conventions 17 +the performance of practical PC devices, especially those using “bulk” PCs (as opposed to components +based on PC waveguides). We propose to minimise these losses by superposing an additional structure— +antireflection (AR) grating—on the PC surface, and present in detail an algorithm for the design of +compact, wide-angle AR gratings for general 2D PCs. To assess its strengths and limitations, we apply +it to three specific PCs, exhibiting the negative refraction, beam supercollimation, and superprism effect, +respectively. In the first two cases, we obtain gratings ensuring a very significant decrease of the reflection +loss; in the last case, however, the design procedure fails due to the violation of certain assumptions +made in the derivation of our algorithm. The improvement brought by the proposed AR gratings to +the transmission through a PC flat lens (based on the negative-refraction effect) has been confirmed +experimentally [33]. +In chapter 4, which constitutes the second major part of this thesis, we shift our attention to more +traditional, waveguide-based optical devices. We study the problem of miniaturisation of optical circula- +tors, one of the last important components whose integrated versions are not yet commercially available. +We build on the design of a magneto-optical PC-based circulator proposed in 2005 by Wang and Fan +[34, 37]. It consists of three PC waveguides coupled to a special PC cavity supporting a pair of modes +whose frequencies are split in the presence of a static external magnetic field (SEMF). The mode fre- +quency splitting of the original cavity from refs. 34 and 37 is negligible in a uniform SEMF; it can only be +augmented if the magneto-optical material in the cavity is divided into many oppositely polarised mag- +netic domains, each having the area of a fraction of µm2. Fabrication of such domains presents serious +experimental difficulties, as it requires a precise control of the applied SEMF on the nanometre scale. +Here, using an analytical model of an axisymmetric resonant cavity, we show how to design cavities +exhibiting maximum frequency splitting in a uniform SEMF. We present 2D numerical simulations of +two classes of circulators containing the proposed cavities: PC-based circulators, similar to those studied +in refs. 34 and 37, and circulators in which the PC coating is dispensed with and the cavity is coupled +directly to rib waveguides. This elimination of the PC lattice leads to a significant simplification of the +device geometry, without any deterioration of its performance. Subsequently, we comment briefly on the +results of the experimental tests of the proposed devices that have been done in Institut d’Electronique +Fondamentale (Orsay, France). They reveal a significant problem with the original design of the resonant +cavities: large out-of-plane radiation losses. In the final part of chapter 4 we report on the initial results +of full three-dimensional (3D) simulations of the cavities, which show that the above problem may be +overcome by an appropriate adjustment of the geometry of the cavity. +In the last part of this thesis, chapter 5, we present several numerical methods developed for the sake +of simulating some of the devices analysed in the earlier chapters. We start by discussing the extension +of the multiple-scattering method, widely used to handle the problem of light scattering by finite PCs, +to the case of 2D PCs containing gyrotropic materials. Next, we show how the band structures of 2D +PCs composed of circular cylinders can be calculated to great accuracy using Fourier-Bessel expansions; +remarkably, no lattice sum computations are necessary. Finally, we describe the implementation of the +finite-element method for the calculation of eigenmodes of open, axisymmetric, 3D cavities containing +gyrotropic materials. +1.3 Notational conventions +Throughout this thesis, symbols embellished with arrows (e.g., aE) will denote column vectors; with +bars (aN), row vectors; and with hats (aO), matrices, tensors or operators. Complex conjugation will be +indicated by an asterisk (), transposition by the symbol T, and Hermitian conjugation by a dagger (Ž). +A unit vector in a given direction  will be written as eE . In particular, the unit vectors directed along the +axes of a Cartesian coordinate system will be denoted by eEx , eEy and eEz , and of a cylindrical coordinate +18 Chapter 1. Preliminaries +system, by eE, eE and eEz . Vector operators will be written using the nabla symbol; thus, rEa, rE  aE +and rE  aE will denote the gradient, divergence and curl of a or aE. Finally, unless otherwise noted, the +terms permittivity, permeability, impedance, admittance and immittancewill refer to relative permittivity, +permeability etc. +1.4 Maxwell’s equations +The electromagnetic fields in PCs and other optical systems are governed by Maxwell’s equations [60, +61]. For convenience, we shall gather here the forms of these equations that will be most often refer- +enced in later chapters of this manuscript. Since we shall only be concerned with the propagation of +electromagnetic waves with wavelength much larger than the atomic dimensions (typically  > 1 µm), +we shall be using the macroscopic (phenomenological) Maxwell’s equations, in which the effects of +light-matter interaction are taken into account by help of so-called material parameters. +The most general differential form of macroscopic Maxwell’s equations is [61, eq. (I.1a)] +rE  E @B +E +E = E ; (1.1a)@t +rE  E @D +E +H = E C J +E; (1.1b) +@t +rE DE = ; (1.1c) +rE  BE = 0; (1.1d) +where EE denotes the electric field, HE the magnetic field, DE the electric displacement field, BE the mag- +netic induction,  the free charge density and JE the free current density. All quantities are, in general, +functions of the position rE and time t ; for conciseness, this dependence has not been written explicitly. +Throughout this thesis we shall assume all fields to be time-harmonic, i.e., to depend on time as ei!t , +where i is the imaginary unit and ! the (angular) frequency. In this case, differentiation over t reduces +to multiplication by .i!/ and hence eqs. (1.1) become +rE EE = i!BE; (1.2a) +rE HE = i!DE C JE; (1.2b) +rE DE = ; (1.2c) +rE  BE = 0: (1.2d) +The fields DE and BE are related to EE and HE by so-called constitutive relations. We shall be dealing only +with linear media, in which these relations take the form +E O  E Cp O˛  pD =   E   H and BE =   Oˇ0 0 0 0 0 E C 0O HE; (1.3) +where 0 and 0 denote the (absolute) permittivity and permeability of free space, O and O are the +dimensionless (relative) position-dependent permittivity and permeability tensors of the system under +study, and O˛ and Oˇ describe the strength of the magneto-electric coupling in this system. In the vast +majority of materials used in practice, the elements of the two latter tensors are very small and can be +neglected, as we shall do in the following. We shall also usually consider situations in which no free +1.4. Maxwell’s equations 19 +charges or currents are present. Using all the above assumptions, eqs. (1.1) can be brought into the form +rE EE = i!0O HE; (1.4a) +rE HE = i!0O EE; (1.4b) +rE  .O EE/ = 0; (1.4c) +rE  .O HE / = 0: (1.4d) +It should be noted that owing to the identityrE .rE FE/ = 0, valid for any vector field FE [60, eq. (A1.17)], +eqs. (1.4c)–(1.4d) follow automatically from eqs. (1.4a)–(1.4b) as soon as the field is not static (! ¤ 0), +and therefore can be omitted. +In a large part of this manuscript we shall analyse 2D systems, in which the material properties O +and O are invariant with respect to translations along a privileged axis, called  in the following. Under +the additional conditions that (i) the fields EE and HE are also independent from  (the case of in-plane +propagation) and (ii) the tensors O and O have the block form +" # " # +O 0E O 0E +O = tN and O = +t +N (1.5)0  0  ; +eqs. (1.4a)–(1.4b) split into a pair of uncoupled systems of equations. Specifically, denoting by EEt, HEt +and rE t the components of the vectors EE,HE and rE perpendicular to  , we obtain +rE t HEt = i!0E ; (1.6a) +rE t  .EeE/ = i!0O t HEt (1.6b) +and +rE t EEt = i!0H ; (1.7a) +rE t  .HeE/ = i!0Ot EEt: (1.7b) +It can be easily seen that eqs. (1.6) contain only the E and HEt field components, whereas eqs. (1.7) +contain solely EEt and H . A field satisfying eqs. (1.6) and having EEt = 0 and H = 0 will be called +s-polarised. Conversely, a field satisfying eqs. (1.7) and having E = 0 and HEt = 0 will be called +p-polarised. + +Chapter 2 +Effective-medium model of photonic crystals +2.1 Introduction +As mentioned in section 1.1, a crucial feature of photonic crystals (PCs) is the richness of their disper- +sion relation. The shape of PC equifrequency surfaces can be very complex: they can contain sharp +corners or edges separating flat or even concave areas. However, at specific frequencies, they can also +attain ellipsoidal shape, characteristic for homogeneous media. In consequence, the question arises if +the crystals can then be successfully described by the effective-medium model, in which they are ap- +proximated by a homogeneous material with specific values of permittivity  and permeability —or, +equivalently, refractive index n = ./1=2 and impedance  = .=/1=2. Since homogeneous materials +are incomparably easier to analyse than structured ones, an answer in the affirmative would facilitate the +development of PC devices, especially those using the negative-refraction effect [14]. Indeed, most com- +ponents employing this phenomenon, like the famous superlenses [17], have been designed essentially +with homogeneous negative-index materials, first analysed by Veselago [20], in mind. +Numerous papers dealing with this subject have already been published [21–32], giving rise to sev- +eral competing definitions of the effective parameters of PCs, which will be reviewed in subsection 2.2.2. +Unfortunately, as a rule, these definitions have been only heuristically motivated and lack a formal justifi- +cation. Moreover, the ultimate verification of each such a definition, the comparison of the true reflection +coefficient of the crystal with that of the corresponding effective medium, has so far been performed only +for normal [24–26] or near-normal [28] incidence. Yet many applications, including those involving neg- +ative refraction, rely on waves incident at large angles, as well as evanescent ones. The range of validity +of the effective-medium approximation is, therefore, still poorly known. +The aim of the work presented in this chapter is to address these shortcomings. In section 2.2 the +concept of the single-mode approximation is used to provide a mathematical justification for a particular +definition of the effective parameters of two-dimensional (2D) PCs. In section 2.3 we study the influence +of the symmetry of the crystal’s truncation plane and of the electromagnetic fields of its eigenmodes on +the behaviour of its effective parameters, generalising the theorems obtained by Pierre and Gralak [27] +in the one-dimensional (1D) case. To assess the accuracy of the effective-medium model, in section 2.4 +we compare the values of the specular reflection coefficient predicted within the model’s framework with +the results of rigorous numerical calculations. These tests are done for two different crystals at a number +of frequencies and in the full range of incidence angles. This leads to a detailed discussion of the appli- +cability conditions of the single-mode approximation itself (section 2.5). We conclude that as far as the +bands responsible for negative refraction are concerned, the single-mode approximation is (moderately) +accurate only close to normal incidence. Thus, it does not make much sense to treat a PC exhibiting neg- +ative refraction as a homogeneous material for large incidence angles or in the evanescent-wave regime. +In consequence, the behaviour of systems containing homogeneous negative-index materials can change +21 +22 Chapter 2. Effective-medium model of photonic crystals +z z +refracted excited +wave eigenmodes +O2; O 2 +z0 z0 +1; 1 +diffracted +incident reflected incident waves +wave wave wave +x x +(a) (b) +Figure 2.1 Schematic diagrams of the fields generated by an s- or p-polarised plane wave incident from an +isotropic homogeneous medium on the surface of (a) another homogeneous medium and (b) a photonic crystal. +significantly if these materials are replaced with PCs, even if the equifrequency surfaces (and so the +phase refractive indices) of both media are the same. +A substantial part of the results presented in this chapter has previously been published in refs. 62 +and 63. +2.2 Definition of the effective parameters of photonic crystals +2.2.1 Preliminaries: the homogeneous-medium case +In the effective-medium approximation, a lossless 2D PC is modelled by a lossless, homogeneous, pos- +sibly anisotropic medium with one optical axis oriented along the invariant direction of the PC, hereafter +taken to lie along the y axis. We shall begin with a brief analysis of the refraction of a plane wave inci- +dent on the interface between an isotropic medium, labelled 1, with permittivity 1 and permeability 1, +occupying the z < z0 half-space, and this anisotropic material, labelled 2, characterised by tensorial O2 +and O 2, lying in the z > z0 half-space [fig. 2.1(a)]. The wave is taken to propagate in the xz plane. +For the sake of simplicity, we shall restrict our attention to PCs whose point group includes a mirror +plane perpendicular to the x or z axis or a three-fold rotation axis parallel to the y axis. In these cases, +by Neumann’s principle (“the symmetry elements of a physical property of a crystal must include the +symmetry elements of the crystal point group” [64, p. 14]), the tensors O2 and O 2 become diagonal in the +chosen coordinate system, +2 3 2 3 +2x 0 0 2x 0 0 +O2 = 4 0  5 42y 0 ; O 2 = 0 2y 0 5 : (2.1) +0 0 2z 0 0 2z +Maxwell’s equations (1.6) can then be used to derive the dispersion relation of, say, s-polarised plane +waves (with electric field perpendicular to the propagation plane) with wave vector kE = kxeEx C kzeEz +propagating in medium 2, +k2 k2 !2 2x C z = 1 with K2    and K2 !x 2y 2z z  2y2x ; (2.2)K2 K2 c2 c2x z +2.2. Definition of the effective parameters of photonic crystals 23 + pwhere ! denotes the frequency and c 1= 00 the speed of light defined in terms of the (absolute) +permittivity 0 and permeability 0 of free space. Thus, the equifrequency curve (EFC) of material 2 is +an ellipse with principal axes of length 2Kx and 2Kz . +When a plane wave with wave vector kE1 = kxeEx C k1zeEz falls on the interface separating media 1 +and 2, reflected and refracted waves, with wave vectors kE01 = kxeEx k1zeEz and kE2 = kxeEx C k2zeEz , +respectively, are generated. By imposing the continuity conditions at z = z0 on the field components par- +allel to the interface, the well-known Fresnel’s formulas for the amplitude of the reflected and refracted +waves can be derived: +2x=k2z 1=k= 1zr C ; (2.3a)2x=k2z 1=k1z +22x=k= 2zt C : (2.3b)2x=k2z 1=k1z +These formulas can be written in a concise way by introducing the notion of transverse impedance of a +material, defined as +E += j tZj .j = 1; 2/; (2.4) +p +Z0Hj t +where Z0 0=0 denotes the (absolute) impedance of free space, and Ej t (Hj t) is the amplitude of +the transverse, i.e., parallel to the interface, component of the electric (magnetic) field of a plane wave +E 0 Epropagating in the j th material in the given direction k . Since in our case E = E = E eikj rEj j t jy jy , +H = H = .i!  /11t 1x 0 1 @E1y=@z = .k1z=!01/E1y , andH2t = .k2z=!02x/E2y , we obtain +!  += jxZj (2.5) +c kjz +and +Z2 Z1 2Z +r = 2C ; t = C : (2.6)Z2 Z1 Z2 Z1 +By the duality theorem [65, p. 72–73], analogous results for p-polarised waves can be obtained by +substituting HE , EE, O and O for EE,HE , O and O , respectively. Equations (2.6) must then be replaced by +Y2 Y1 2Y +r = 2C ; t = C ; (2.7)Y2 Y1 Y2 Y1 +where +!  += jxYj (2.8) +c kjz +is the transverse admittance of j th material. Introduction of the notion of transverse immittance  of a +medium, defined as its transverse impedanceZ in the s-polarisation case and its transverse admittance Y +in the p-polarisation case, lets us write the Fresnel’s formulas (2.6) and (2.7) in a unified way: +2 1 2 +r = 2C ; t = C : (2.9)2 1 2 1 +2.2.2 Existing definitions +Several authors [24–26, 28, 66] have attempted to generalise the concept of transverse immittance to non- +homogeneous media, the main obstacle being, obviously, that in such media the ratio Et=Ht is spatially +dependent. The most straightforward is to define  as the ratio of the spatial field averages over the +24 Chapter 2. Effective-medium model of photonic crystals +surface unit cell, as proposed by Lu and Prather [26]; while this might seem an oversimplification, in +subsection 2.2.3 we shall show that this approach is in fact rigorous if the single-mode approximation, +defined in the same subsection, is valid. In an attempt to preserve more information from the detailed +field structure, other authors [24, 25, 28, 66] suggested empirical definitions of the transverse impedance, +expressed in terms of the average electromagnetic energy and Poynting vector of the dominant crystal +eigenmode. However, no mathematical justification of these definitions has been given. +Efros and Pokrovsky [23] and later Decoopman et al. [21] proposed an entirely different procedure. +They considered the perturbation of the incident electromagnetic field caused by a PC slab embedded in +a homogeneous medium whose permittivity  and permeability  were varied. The values of  and  +corresponding to minimum perturbation were taken as the effective parameters of the crystal. Contrary +to the approaches cited in the previous paragraph, this method is based on a full rigorous solution of +Maxwell’s equations. On the other hand, it requires a significant computational effort since, for each +value of the frequency and angle of incidence, simulations need to be performed for multiple, possibly +complex, values of  and  of the homogeneous medium. Therefore, it is not well-suited to the analysis +of the general behaviour of the effective parameters, for which an—even approximate—semianalytical +approach would be useful. +Finally, some authors [29–32] proposed definitions of effective parameters based on the extended +Maxwell’s-Garnett theory, where the crystal unit cell is replaced by a coated cylinder (or sphere) embed- +ded in a homogeneous host medium whose parameters are determined from the condition of vanishing +scattering, calculated by the Mie theory. This approach enabled them to reproduce the band structure +of PCs, usually composed of dispersive (e.g., polaritonic) materials, with good accuracy. Nevertheless, +the effective parameters they obtained are independent from the choice of the crystal truncation plane, +whereas one of the key observations of Decoopman et al. [21] was the strong variability of effective  +and  with the position of the crystal surface. Thus, the parameters introduced in refs. 29–32 could not +be used to determine accurately the reflection coefficient of a truncated PC. +2.2.3 Proposed definition +To arrive at the proper definition of the effective parameters of PCs, let us consider a semi-infinite 2D +PC invariant along the y axis, on whose surface, z = z0, an s- or p-polarised plane wave with wave +vector kE = kxeEx C kzeEz is incident [fig. 2.1(b)]. Owing to the system’s periodicity in the x direction, +the reflected field will comprise infinitely many diffraction orders. Similarly, the transmitted field will +be a superposition of infinitely many crystal eigenmodes (propagative and evanescent) characterised by +different wave vectors. In contrast, as we have seen in subsection 2.2.1, if the crystal were replaced +by a homogeneous material, only one transmitted plane wave would be excited. The effective-medium +approximation can therefore be reasonably expected to give a good picture of reality only when some +crystal eigenmode is excited with an amplitude significantly greater than the others. In other words, the +validity of the effective-medium approximation is constrained by that of the single-mode approximation, +which consists in neglecting all crystal eigenstates but the dominant one. We shall now show how this +approximation leads to a natural definition of the crystal’s effective parameters. +In the remaining part of this chapter we shall focus on s-polarised waves; formulas corresponding to +p polarisation can be derived using the duality theorem and will be omitted for brevity. For the chosen +polarisation, the electric field reduces to its component along the y axis, and Maxwell’s equations (1.6) +take the form +@Ey = i!0Hz; (2.10a) +@x +@Ey = i!0Hx; (2.10b) +@z +2.2. Definition of the effective parameters of photonic crystals 25 +@Hz @Hx = i!0Ey : (2.10c) +@x @z +We shall solve these equations separately in the homogeneous region and in the PC, and then match the +solutions at the crystal surface by imposing the continuity of the Ey andHx components, in accordance +with Maxwell’s boundary conditions. +We assume the PC to be oriented so that a (not necessarily primitive) rectangular unit cell .ax; az/ +can be defined. The whole system is periodic with respect to the variable x, so it is possible to perform +a Floquet-Bloch transform [13, 67] of the Maxwell’s equations (2.10). After this transform, as is well +known from grating theory, the solution of the Maxwell’s equations in the homogeneous region is given +by the Rayleigh’s expansion [68, 69] +Eh.x; z/ = eiŒkxxCˇ0.z +X +z0/C r eiŒ.kxCGxn/xˇn.zz0/y n ; (2.11) +n2Z +whereG  2 n=a and ˇ  Œ  .!=c/2.k CG /21=2xn x n 1 1 x xn with the sign of the square root chosen +so that ReˇnCImˇn  0. In the crystal, we can expand the field in terms of the PC eigenmodes with the +x component of the Bloch vector equal to kx , taking into account (i) propagative modes carrying energy +in theCz direction and (ii) evanescent modes decaying in the same direction [13, 41–43, 70–72]. These +modes can be determined by several methods, most of which utilise some variant of the scattering-matrix +algorithm [73]; in the numerical calculations presented later in this chapter we have used the differential +method [69, 74–76]. The electric field of themth eigenmode with Bloch vector Em = kxeEx C mzeEz can +be written as a 2D Fourier expansion w npXith cXoefficients .um /n;p2Z: +E .x; z/ = unp eiŒ.kxCGxn/xC.mzCGzp/zmy m ; (2.12) +n2Z p2Z +where G  2 p=a .?zp z Thus, the total electric fiXeld in the crystal will be +Ecy.x; z/ = tmEmy.x; z/ (2.13) +m2N +with “transmission coefficients” tm denoting the amplitudes of individual modes. +The requirement of continuity of E andH = .i! /1y x 0 @Ey=@z at z = z0 leads to +X +eikxxC r ei.kxCGxn/xn +X n XX C C C (2.14a)= t np iŒ.kx Gxn/x .mz Gzp/z0m um e ; +m +iˇ X +n p +0 ik x iˇe x n r ei.kxCGxn/xn +1 X X n X1 (2.14b) += tm i. +np iŒ.kxCGxn/xC.mzCGzp/z0 +mz CGzp/um e : +m n p +R +Using the identity 1 e2 inx0 dx = ın0, where ınm equals 1 if n = m and 0 otherwise, we arrive at the +? Since we shall be studying the influence of shifting the surface of the crystal with respect to the origin of its unit cell, it is +convenient to expand the field in the PC [eq. (2.12)] about the fixed point .0; 0/ rather than the point .0; z0/ anchored on +the surface. +26 Chapter 2. Effective-medium model of photonic crystals +following inhomogeneous system of linear equatioXns with unknowns .rn/n2Z and .tm/m2N: +ı C r = unn0 n mtm; (2.15a) +iˇ Xmn +.ın0 rn/ = vnmtm; n 2 Z; (2.15b)1 m +with the coefficient n nXs um and vm defined as X +un  unp ei.mzCGzp/z0 ; vn  i. CG /unp ei.mzCGzp/z0m m m mz zp m : (2.16) +p p +This system can be written in the matrix form +" O #" # " #I uO rE aE +Oˇ O E = E0 ; (2.17)i =1 v t a +where IO denotes the identity matrix, uO and vO are matrices with elements un and vn (the row and column +indices being denoted by super- and subscripts, respectively), Oˇ +m m +is the diagonal matrix of the coeffi- +cients ˇ , rE and tE are column vectors of the coefficients r and t , and the vectors aE and aE0n n m , whose +elements are given by +a  ı ; a0n n0 n  iˇ0ın0=1; (2.18) +represent the incident field. +If the crystal were replaced by a homogeneous medium, the only nonzero reflection coefficient would +be the specular one, r0. Using eqs. (2.15) corresponding to n = 0, the following relation between r0 and +the transmission coefficients of individual modes can be derived: +r0 = P +P +0 0 +mŒum .1=iˇ0/vmtm +C : (2.19)Œu0m m .1=iˇ0/v0mtm +As we have already seen, the effective-medium approximation relies on the assumption that the trans- +mission coefficient of a particular (dominant) mode is much larger than of all others; without loss of +generality, we can denote this mode with the index 1, so that our assumption reads jt1j  jt2j; jt3j; : : : +If it holds, expression (2.19) reduces to + iu +0 +1=v +0 +1 1=ˇ0r0 C : (2.20)iu01=v01 1=ˇ0 +Comparing eq. (2.20) to the Fresnel’s formula (2.3a) and noting that ˇ0 and k1z denote the same +physical quantity—the z component of the wave vector of the incident plane wave—we conclude that +iu0=v01 1 in eq. (2.20) corresponds to 2x=k2z in eq. (2.3a). In the homogeneous-medium case, k2z +is the z component of the wave vector of the refracted wave. Assuming that the EFC of the crystal +at the considered frequency can be approximated by an ellipse with semiaxes Kx and Kz and centre +KE0  .K0x; K0z/, as shown in fig. 2.2, it is natural to identify k2z in the PC case with the z component +of the Bloch vector of mode 1 measured from the centre of this ellipse, i.e., 01z  1z K0z . In this +way, we arrive at the following definition of the effective x of the crystal: +0 u0 = i 1x 1z : (2.21) +v01 +2.3. Influence of symmetries on the effective parameters 27 +kz +E0 +1 +Kx +E1 +Kz +KE0 +kx +Figure 2.2 Relationship between the vectors KE , E and E00 1 1. +The dispersion relation (2.2) provides then the formulas for the effective z and y , +K2x 1 K +2 +z =  ;  = +z +x y ; (2.22) +K2  !2 2z x =c +and eq. (2.5), for the effective transverse impedance, +! iu0 +Z = 1 : (2.23) +c v01 +Thus, within the framework of the single-mode approximation the PC produces the same reflected wave +as the homogeneous medium with material parameters given by eqs. (2.21) and (2.22). +Finally, we note that the definition (2.23) of the effective transverse impedance agrees with that +given by Lu and Prather [26, section 3], since from eqs. (2.10b), (2.12) and (2.16) it follows that u01 +and v01=.i!0/ are the average periodic parts of the Ey and Hx fields of mode 1 on the PC surface; +substituting these values to eq. (2.4), we arrive at the expression (2.23). +2.3 Influence of symmetries on the effective parameters +“Standard” lossless homogeneous materials are characterised by purely real ,  and Z. From the +Fresnel’s formula (2.3a) it follows that the reflection coefficient of a plane wave incident on the interface +separating two such materials will also be purely real provided that both the incident and the transmitted +wave are propagative, i.e., k1z and k2z are real. These properties do not always carry over to the PC case. +Indeed, Pierre and Gralak [27] proved that for 1D PCs they are guaranteed to hold only if the crystal is +truncated along one of its mirror symmetry planes; otherwise, the effective material properties and the +reflection coefficient may take complex values. +Since the effective-medium description of PCs is an approximation, one might expect their effective +material properties to have some kx-dependence. This does no harm as long as the variation with kx is +fairly small. However, ref. 27 demonstrates that the effective parameters of a 1D PC cut elsewhere than +along a mirror symmetry plane may diverge at the value of kx where the crystal eigenmode turns from +propagative to evanescent. In consequence, the usefulness of the effective-medium model in this case is +rather limited. +In this section we shall extend the results from ref. 27 to the 2D case. It should be noted that in 1D +systems mirror planes are in fact identical with inversion centres and two-fold rotation axes, so that a +priori it is not obvious which of them turn out to be crucial in 2D. +28 Chapter 2. Effective-medium model of photonic crystals +2.3.1 Real-valuedness +We shall now prove the following sufficient condition for the real-valuedness of the effective parameters +and the specular reflection coefficient of 2D PCs. +The reflection coefficient r0 and the effective parameters x , z , y , and Z of a 2D PC are real if: +(i) both the incident wave and the dominant eigenmode are propagative, i.e., ˇ0 and 1z are real, +(ii) the truncation plane z = z0 contains an inversion centre of the infinite crystal, +(iii) the single-mode approximation is valid. +Simple inspection of eqs. (2.20)–(2.23) shows that if the assumptions (i) and (iii) are fulfilled, the +proposition is true provided the ratio i 0 0 is real. This expression involves the Fourier coefficients npu1=v1 u1 +of the electric field of the dominant PC mode. By assumption (i), this mode is propagative, and therefore +the coefficients in question can be obtained with the standard plane-wave method as described in ref. 77. +Now, if the crystal is centrosymmetric with respect to a point .x0; z0/, the electric field of the mode can +be written as XX +E .x; z/ = uQnp eiŒ.kxCGxn/.xx0/C.z1CGzp/.zz0/1y 1 ; (2.24) +n p +where Qnpu1 are the elements of a vector equal to the product of a real diagonal matrix and an eigenvector +of a real symmetric matrix [77]; hence, they can be taken to be real. Comparing eq. (2.24) with the +general formula (2.13), we obtain +np = Qnpu u eiŒ.kxCGxn/x0C.z1CGzp/z01 1 ; (2.25) +and, using eqs. (2.16), we arrive at +P +0 P Q0piu u1 = p 1 : (2.26) +v0 0p1 p.1z CGzp/uQ1 +Owing to the real-valuedness of Qnpu1 and 1z , the above expression is real, and the proposition follows. +On the contrary, if the interface contains no symmetry centres, a complex Hermitian eigenvalue +problem is solved in the plane-wave method, so that the eigenvector elements Qnpu1 need not be real, and +neither does iu0=v01 1 . +2.3.2 Continuity and boundedness +Preliminaries We proceed to the investigation of the behaviour of the effective permittivity and per- +meability of a 2D PC near a value of kx at which its dominant eigenmode turns from propagative to +evanescent, i.e., near a vertex KE = .K ˙ K ;K / of the elliptical EFC. At such a point, 0v˙ 0x x 0z 1z is +zero; according to eqs. (2.21) and (2.22), this implies  =  = 0 and j j ! 1 unless v0x z y 1 is zero at +the same time. In this subsection we shall study the circumstances in which this necessary condition for +the continuity and boundedness of y at the transition point is guaranteed to be met. The considerations +are necessarily somewhat technical; the reader not interested in mathematical details can skip to the last +paragraph of this subsection, where the obtained results are summarised. +We shall limit the discussion to PCs whose geometry is described by one of the symmorphic space +groups.? Eigenmodes with a given Bloch vector kE can then be classified in terms of the irreducible +? A symmorphic space group is a space group that contains all elements of its point group [78, p. 18]. This means, in +particular, that the set of its generators must consist solely of pure rotations and mirror reflections (no screw rotation axes +and glide planes are allowed). +2.3. Influence of symmetries on the effective parameters 29 +representations of the largest common subgroup of the PC’s point group and the group of kE, i.e., the +group of symmetry operations leaving kE invariant or transforming it to a Bloch vector kE0 differing from +kE by a reciprocal-lattice vector [79, chap. 3; 80, chap. 8]. +If a vertex KEv˙ is located at a general reciprocal-space point, whose group consists solely of the +identity operation I , no constraints on the symmetry of the corresponding eigenmode can be obtained. +However, if K0z = 0 or K0z =  =az—as, in practice, is very often the case—the group of KEv˙ contains +additionally the operation of mirror reflection with respect to the x axis,  .?x It follows that if the crystal +itself has mirror planes parallel to x, the electric field of an eigenmode with Bloch vector KEv˙ is either +symmetric or antisymmetric with respect to reflection about each of these planes. We shall assume the +origin of the coordinate system to be chosen so that the mirror planes lie at z = 1qaz for all q 2 Z (it2 +is easy to see that there are always two parallel planes per a rectangular unit cell). Let us now consider +separately the cases of K0z = 0 and K0z =  =az . +The case of K 0 Setting 0 to K = 0 in the definition (2.16) of v00z = 1z 0z 1 and using the definition of +Gzp, we get +2 i X +v0 = 0ppu e2 ipz0=az1 1 : (2.27)az +p2Z +Consider first the case of an eigenmode whose electric field E1y.x; z/ is symmetric with respect to +reflection about the plane z = 0, i.e., E1y.x; z/ = E1y.x;z/. Expression (2.13) for E1y.x; z/ and the +orthogonality of the Fourier basis yield +n;p = npu1 u1 for all n; p 2 Z: (2.28) +It is easy to check that the above condition guarantees also the symmetry of E1y.x; z/ with respect to all +the other mirror planes z = 1qaz . Substituting eq. (2.28) into eq. (2.27), we obtain2 +0 4  +X += 0p +2 pz +v1 pu1 sin +0 +: (2.29) +az az +p>0 +Without further constraints on 0pu , the coefficient v01 1 is guaranteed to be null only if 2 z0=az is an +integral multiple of  , so that all the sine factors vanish. With z0 restricted to the first unit cell (0  z0 < +a ), this is equivalent to z = 0 or z = 1z 0 0 az . Thus, the crystal should be truncated along one of its mirror2 +planes. +If the PC is based on a hexagonal or centred rectangular Bravais lattice, its primitive cell is two times +smaller than the rectangular unit cell .ax; az/ we are using. It can then be shown that half of the Fourier +coefficients npu1 , namely those with nC p odd, vanish. As a result, eq. (2.29) becomes +8  X0 = 0;2p 4 pzv1 pu1 sin 0 : (2.30)az az +p>0 +It follows that all the sine factors, and hence the total sum too, will vanish on two more planes per unit +cell: z = 10 az and z0 = 3az .4 4 +Let us now proceed to the case of electric field antisymmetric with respect to the plane z = 0. Instead +of eq. (2.28) we have then +n;p = npu1 u1 for all n; p 2 Z: (2.31) +? Note in particular that the vector x.K0x ˙Kx ;  =az/ = .K0x ˙Kx ; =az/ is equivalent to .K0x ˙Kx ;  =az/, since +they differ by the reciprocal-lattice vector .2 =az/eEz . +30 Chapter 2. Effective-medium model of photonic crystals +and the sines in eq. (2.29) are replaced by cosines. To ensure that 0 vanishes for all sequences 0pv1 .u1 /p2N, +to each p must correspond a q 2 such that 2 pz =a = .q C 1Z 0 z / . It is easy to see that this condition2 +cannot be fulfilled for any value of z0. For a PC based on a hexagonal or centred rectangular Bravais +lattice, the condition becomes 4 pz =a = .q C 10 z / , which has no solutions, either.2 +The case of K0z = pi/az Instead of eq. (2.27), we have + i X0 = 0pv .2p C 1/u e i.2pC1/z0=az1 1 : (2.32)az +p2Z +Substitution of the expression (2.13) for E1y.x; z/ to the condition of symmetry/antisymmetry with +respXectXto plane z = 0, E1y.x; z/ = ˙E1y.x;z/, yields +unp eiŒ.kxC +XX +2n =ax/xC.2pC1/ z=az = ˙ unp eiŒ.kxC2n =ax/x.2pC1/ z=azm m ; (2.33) +n p n p +so that from the orthogonality of the Fourier basis we obtain +unp = ˙un;p1m m for all n; p 2 Z: (2.34) +It can also be shown that a mode with kz =  =a that is symmetric with respect to the plane z = 0 must +be antisymmetric with respect to the plane z = 1az and vice versa; thus, without loss of generality, we2 +can take the plus sign in the above equation. Substituting it into eq. (2.32), we get + i X +v0 = .2p C 0p1/u Œei.2pC1/ z0=az ei.2pC1/ z0=az1 1 az +p0X C (2.35)2 i .2p 1/ z= C 0p.2p 1/u1 sin 0 :az  azp 0 +Vanishing of v01 is thus ensured if sinŒ.2p C 1/ z0=az = 0 for all integer p  0, which is equivalent +to z0 = qaz with q 2 Z. This corresponds to placing the truncation plane along a symmetry plane of +the electric field of the crystal’s dominant eigenmode. The situation is the same if the PC is based on +a hexagonal or centred rectangular Bravais lattice: the condition for vanishing v01 takes then the form +sinŒ.4p C 1/ z0=az = 0 for all integer p  0, which is again equivalent to z0 = qaz with q 2 Z. +Conclusions From the above considerations we can establish the following rule: +The effective parameters x , z and y are continuous and bounded at the point of the propagative-to- +evanescent transition of the dominant PC eigenmode in the two following cases: +(i)  the transition occurs at kE = kxeEx , + the crystal has mirror planes parallel to x, + the electric field of the dominant mode is symmetric with respect to these planes, and + the crystal is truncated along one of these planes or, provided it is based on a hexagonal or +centred rectangular Bravais lattice, midway between these planes; +(ii)  the transition occurs at kE = kxeEx C  =azeEz , + the crystal has mirror planes parallel to x, and + the crystal is truncated along a symmetry plane of the electric field of its dominant eigen- +mode. +2.4. Examples 31 +a +0:5 +0:4 +0:3 +plane 3 p +3a 3=8 0:2 +plane 2 p +a 3=4 +plane 1 0:1 +0 + M K +(a) (b) +Figure 2.3 (a) Geometry of the hexagonal-lattice PC analysed in the text. Horizontal lines mark the position of +truncation planes 1, 2, and 3; inversion centres of the PC located at these planes are marked with crosses. (b) Band +structure of the crystal shown in part (a). Horizontal lines mark the frequency values ! = 0:14  2 c=a and +0:259  2 c=a. +This rule is not a rigorous theorem. First, the sufficiency of the above conditions has not been proved. +Assuming that the Taylor expansions of u01. +0 +1z/ and v +0 0 +1.1z/ about  +0 +1z = 0 exist, the formula (2.21) +for x can be written as +0  +0 u01z 1.0/C .0 2 0 0 01z/ .du1=d1z/ C    + . / = i 1z +=0 +x 1z C 0 0 C    : (2.36)v01.0/ 1z.dv01=d /01z 1z=0 +The effective permeability x is then finite and different from zero if and only if exactly q 1 lowest +derivatives of u01 and q lowest derivatives of v +0 +1 , where q 2 N, vanish at 01z = 0. We have proved that +in the two cases listed above v01.0/ vanishes; it can also be shown that in these cases u +0 +1.0/ is in general +non-zero. However, the proof that .dv0 0 01=d1z/ =0 does not vanish is missing.1z +Second, the above conditions have not been proved to be strictly necessary. Indeed, the coefficients +0p +u1 can accidentally take such values that v +0 +1 will vanish for some “random” truncation. This does not +seem to be a major problem, though, and one should probably treat these situations like, for instance, +accidental degeneracies in group theory. +These reservations notwithstanding, in the following section it will be shown that the effective pa- +rameters of two typical PCs at several distinct frequencies behave exactly as predicted by the above rule. +So far, the author has not found any counterexample to it. +2.4 Examples +In this section we shall apply the theory presented above to the cases of two specific PCs, one with a +hexagonal and one with a square lattice. In particular, the predictions of the effective-medium model will +be compared with the results of numerical calculations made with the differential method [69, 74–76]. +2.4.1 Hexagonal lattice +To begin with, we consider the crystal shown in fig. 2.3(a): the hexagonal lattice of air holes of radius +0:35a, a being the lattice constant, embedded in a dielectric matrix with  = 16. Figure 2.3(b) presents +its Brillouin diagram. At the frequency ! = 0:14 2 c=a, the EFC of the single s-polarised propagative +crystal eigenmode has the shape of a circle centred at the = .0; 0/ point [fig. 2.4(a), middle diagram, +solid line]. In figs. 2.5(a), (d) and (g) the specular reflection coefficient of this crystal at the quoted +!a=2 c +32 Chapter 2. Effective-medium model of photonic crystals +1:50 +(a) (b) +1:25 n D 2 +n D 2 +1:00 +0:75 +n D 1 +0:50 n D 1 +0:25 D 4 + D 2 + D 1 +0:50 n D 0 +nD1 +0:25 +n D 0 +0:00 +0:25 +0:00 0:25 0:50 0:00 0:25 0:50 +kxa=2  kxa=2  +Figure 2.4 The EFCs at frequency (a) ! = 0:14  2 c=a andp(b) ! = 0:259  2 c=a of three PCs of the +type shown inpfig.p2.3(a) with the same average refractive index h i = 2:67, but different values of the index +contrast = b= h between the background and the holes: b = 16, h = 1, = 4 (solid lines), b = 11:76, +h = 2:94, = 2 (dotted lines), and b = h = 7:11, = 1 (dashed lines). The middle part of the graphs shows +the EFCs of the real bands (Re kz ¤ 0, Im kz = 0), the bottom one, of the imaginary bands of thpe first kind [81] +(Re kz = 0, Im kz ¤ 0), and the top one, of the imaginary bands of the second kind (Re kz = 2 =a 3, Im kz ¤ 0, +i.e., lying on the edge of the first Brillouin zone). Only the three bands with lowest values of Im kz are shown in +each case. The bands of the empty lattice ( = 1) are labelled with the index n of the harmonic Gxn to which they +correspond. For each mode with wave vector kE visible in the graph, the crystal supports three additional modes +with wave vectors kE, kE, and kE [81]. +Im kza=2  Re kza=2  Im kza=2  +2.4. Examples 33 +1 0:06 1 0:10 +(a) Im r0 (g) +0:04 +0 ! 0 0:05 +rel. error +Re 0:02 r0 +1 0:00 1 0:00 +4 4 +(b) (h) +2 2 +0 0 +1:0 14 20  =2 +(c) (i) +0:9 y ! 13 +10 0 +0:8 12 10jx j jy jx +argx arg y +0:7 11 0  =2 +0:0 0:1 0:2 0:3 0:4 0:5 0:0 0:1 0:2 0:3 0:4 0:5 +kxa=2  kxa=2  +1 0:15 +(d) +0:10 +0 +0:05 +1 0:00 +4 +(e) +2 +0 +1:5 10 +(f) +1:4 +9 +1:3 +8 +1:2 +1:1 7 +0:0 0:1 0:2 0:3 0:4 0:5 +kxa=2  +Figure 2.5 (a) The kx-dependence of the specular reflection coefficient r0 of the crystal from fig. 2.3(a) trun- +cated along plane 1, at ! = 0:14  2 c=a. Solid lines: results of rigorous calculations, rn0 ; circles: results of +calculations made in the single-mode approximation, rsm0 ; dashed line: relative error  of the single-mode approx- +imation. The vertical lines at kx = 0:14  2 =a and 0:447  2 =a mark where the incident wave and the single +propagating crystal eigenmode, respectively, turn from propagating to evanescent. (b) Amplitudes of the three +most slowly decaying crystal eigenmodes excited in the above conditions (solid, dashed, and dotted line, in order +of increasing Im kz). (c) Effective x (dark lines) and y (light lines) of the crystal. (d)–(f) and (g)–(i) The same +for planes 2 and 3. +x j j Re r0, Im r0, xtm j j Re r0, Im r0,tm +10jx j, jy j j j Re r0, Im r0,tm +argx , arg y +Relative error +Relative error Relative error +y y +34 Chapter 2. Effective-medium model of photonic crystals +1 +0 +1 +(a) (b) +Figure 2.6 Real part of the electric field Ey of the modes of the crystal shown in fig. 2.3(a) with (a) ! = +0:14 2 c=a, kx = 0:447 2 =a, and kz = 0, (b) ! = 0:259 2 c=a, kx = 0:259 2 =a, and kz = 0. A mirror +plane of the crystal parallel to its surface is marked with a horizontal line. +1 1:5 2 2 +(a) rel.!error +(d) +1:0 + Im r0 +0 0 1 + Re r 0:50 +1 0:0 2 0 +4 10 +(b) (e) +2 5 +0 0 +0:2 50 0:1 50 +(c) (f) +0:0 +0:0 +y ! 0 0:1 0 +0:2 x 0:2 +0:4 50 0:3 50 +0:0 0:1 0:2 0:3 0:4 0:5 0:0 0:1 0:2 0:3 0:4 0:5 +kxa=2  kxa=2  +Figure 2.7 Same as fig. 2.5, at frequency ! = 0:259 2 c=a and for truncation planes (a)–(c) 1 and (d)–(f) 2. +Discontinuities in the plots of rsm0 appear at kx = 0:33  2 =a, because at this value of kx the two most slowly +decaying crystal eigenstates “swap places”, and the calculations of rsm0 are always done assuming the mode with +the smallest Im ky to be dominant. The domain of the plots of effective parameters has been restricted to the range +of kx in which the relative error of the single-mode approximation is less than 25%. +frequency is plotted against the x component of the wave vector of the incident plane wave for three +different positions, marked with horizontal lines in fig. 2.3(a), of the interface between the crystal and +the homogeneous medium, taken to be vacuum (1 = 1 = 1). In these graphs, the results of rigorous +numerical calculations (rn0 , solid lines) are juxtaposed with the values obtained from eq. (2.20) derived +in the framework of the single-mode approximation (rsm0 , circles). Evidently, for surfaces containing +inversion centres Im rn0 is very small in the whole range kx < 0:14  2 =a, in which the incident wave +is propagative [figs. 2.5(a) and (d)]. On the contrary, when the termination is chosen in an arbitrary way, +r0 acquires an appreciable imaginary part [fig. 2.5(g)]. This is in agreement with the rule formulated in +subsection 2.3.1. +x +j j Re r0, Im r0,tm +x jtmj Re r0, Im r0, +y +Relative error + +Relati yve error +2.4. Examples 35 +In all the three graphs, the relative error of the single-mode approximation, defined as   jrsm0 +rnj=jrn0 0 j, is plotted with a dashed line. It is clear that at the chosen frequency (corresponding to the mid- +dle of the first band of the crystal) the single-mode approximation is very accurate for kx corresponding +to propagative incoming waves (kx < !=c); for larger kx , the accuracy degrades slightly, but the relative +error seldom exceeds 10%. +Figures 2.5(c), (f) and (i) present the kx-dependence of the effective x and y at ! = 0:14 2 c=a +for the three different termination planes of the crystal. As shown in fig. 2.6(a), at the chosen frequency +(and in the whole first band) the electric field of the mode with kx = 0:447  2 =a and kz = 0 is +symmetric with respect to the horizontal mirror planes of the crystal. Thus, the conditions enumerated +in point (i) of the rule from subsection 2.3.2 are satisfied for truncation planes 1 and 2, and indeed, as +shown in figs. 2.5(c) and (f), the effective permittivity y is continuous and bounded for these truncation +planes. In contrast, y diverges at kx = 0:447  2 =a when the crystal is truncated along the arbitrarily +chosen plane 3 [fig. 2.5(i)]. +It should be noted that shifting the truncation plane has a large influence on the numerical values +of the effective parameters. For instance, at normal incidence, the crystal truncated along plane 1 has +y = 14:0 and x = 0:73, whereas for the truncation plane 2 these values are y = 7:1 and x = 1:43—a +difference of a factor of two. This corroborates the earlier observations of Decoopman et al. [21]. +As demonstrated above, at a frequency lying in the first band of the crystal under study the single- +mode approximation works well, and so the effective-medium model is well-founded. In the second +band, however, this approximation becomes much less accurate. We shall consider specifically the fre- +quency ! = 0:259  2 c=a, at which the EFC of the crystal is, again, centred at , approximately +circular, and its radius corresponds to the effective index n  1 [fig. 2.4(b), middle diagram, solid +line]. In figs. 2.7(a) and (d) the rigorous value of the specular reflection coefficient of the crystal at this +frequency is juxtaposed with that calculated from eq. (2.20). The relative error grows with kx and is +usually greater than 20% (plane 1) and 10% (plane 2). In the evanescent region, the single-mode ap- +proximation is clearly irrelevant. The graphs of the amplitudes of the three most slowly decaying crystal +eigenmodes [figs. 2.7(b) and (e)] clearly show that the influence of the second mode is nonnegligible +in the whole range of kx , and for the first truncation plane even the third mode plays a significant part. +Close inspection reveals that the ratios jt2=t1j and jt3=t1j tend to grow with the incidence angle; thus, +the effective-medium model is a better approximation at near-normal than at grazing incidence (except +for the immediate neighbourhood of kx = !=c, where r0 becomes exactly 1). +In addition, as shown in fig. 2.6(b), the electric field of the mode with ! = 0:259  2 c=a, kx = +0:259  2 =a and kz = 0 is antisymmetric with respect to the mirror planes of the crystal. Thus, y is +divergent at kx = 0:259  2 =a regardless of the choice of the truncation plane [figs. 2.7(c) and (f)]. +2.4.2 Square lattice +The second structure to be studied is the square lattice of air holes of radius 0:35a, where a is the lattice +constant, drilled in a dielectric matrix with  = 11:56 [fig. 2.8(a)]. Its Brillouin diagram is plotted in fig. +2.8(b). The analysis will be conducted at three discrete frequencies, ! = 0:13  2 a=c, 0:22  2 a=c +and 0:31  2 a=c, at which the EFCs of the crystal have an approximately circular or ellipsoidal shape, +as demonstrated in fig. 2.9. +Figures 2.10(a), (d) and (g) show the kx-dependence of the reflection coefficient r0 at the frequency +! = 0:13  2 a=c for the three positions of the truncation plane marked in fig. 2.8(a). Planes 1 and 2 +contain inversion centres of the PC, while plane 3 does not. According to the theorem from subsec- +tion 2.3.1, for the former planes r0 should be real as long as both the incident wave and the dom- +inant crystal eigenstate are propagative, which is the case for kx < !=c = 0:13  2 =a. Figures +36 Chapter 2. Effective-medium model of photonic crystals +a +0:5 +0:4 +plane 3 0:3 +3a=4 +plane 2 0:2 +a=2 +plane 1 0:1 +0 + X M +(a) (b) +Figure 2.8 (a) Geometry of the square-lattice PC analysed in the text. Horizontal lines mark the position of +truncation planes 1, 2 and 3; inversion centres of the infinite PC located at these planes are marked with crosses. +(b) Band structure of the crystal shown in part (a). Horizontal lines mark the frequency values ! = 0:13 2 c=a, +0:22  2 c=a and 0:31  2 c=a. +0:50 +(a) (b) (c) +0:25 +0:00 +0:25 +0:50 +0:5 0:0 0:5 0:5 0:0 0:5 0:5 0:0 0:5 +kxa=2  kxa=2  kxa=2  +Figure 2.9 The EFCs at frequency (a) ! = 0:13  2 c=a, (b) 0:22  2 c=a, and (c) 0:31  2 c=a of the PC +shown in fig. 2.8(a) (solid lines) and the corresponding “empty lattice”, i.e., the homogeneous medium of refractive +index 2:476 (dashed and dotted lines). The empty-lattice bands corresponding to the n = 0 harmonics are plotted +with dashed lines, the rest with dotted lines. +2.10(a) and (d) confirm that this is fulfilled with a very good accuracy. In fact, Im rn0 does not exceed +0.002, that is, 0.3% of the magnitude of rn0 ; this tiny imaginary part stems from the excitation of sec- +ondary crystal eigenmodes, which are neglected in the single-mode approximation. In turn, when the +PC is truncated along plane 3, r0 retains a large imaginary part also in the propagative-wave region +[fig. 2.10(g)]. +The plots of the relative error show that when the incident wave is propagative, the single-mode +approximation is extremely accurate at the frequency in question (the relative error is less than 0.3%). +For larger kx , the error slowly grows, reaching   0:6–0:8 (planes 1 and 3) and   0:2 (plane 2) +at the Brillouin zone edge. However, it does not exceed 10% until kx = 0:43  2 =a for planes +1 and 3 and kx = 0:475  2 =a for plane 2, so that the single-mode approximation is still rele- +vant at kx = 0:39  2 =a, where 1z vanishes and the dominant eigenmode becomes evanescent. +We may then proceed to the analysis of the behaviour of the effective parameters at this value of kx . +The EFC of the dominant eigenmode is centred at , and its electric field at kx = 0:39  2 =a +and kz = 0 is symmetric with respect to the horizontal mirror planes of the crystal, as evidenced by +fig. 2.11(a). In consequence, the effective parameters x = z and y are continuous and bounded +kza=2  +!a=2 c +2.4. Examples 37 +1 0:75 1 1:0 +(a) (g) + 0:50 +Im r0 +0 0 0:5 +R e r0 0:25 +! +rel. error +1 0:00 1 0:0 +4 4 +(b) (h) +2 2 +0 0 +0:95 11 20  =2 +(c) (i) +0:90 +y ! 10 arg y +0:85 10 jy j 0 +9 arg + x0:80 x jx j +0:75 8 0  =2 +0:0 0:1 0:2 0:3 0:4 0:5 0:0 0:1 0:2 0:3 0:4 0:5 +kxa=2  kxa=2  +1 0:3 +(d) +0:2 +0 +0:1 +1 0:0 +4 +(e) +2 +0 +1:4 7:5 +(f) 7:0 +1:2 6:5 +6:0 +1:0 5:5 +0:0 0:1 0:2 0:3 0:4 0:5 +kxa=2  +Figure 2.10 (a) The kx-dependence of the specular reflection coefficient r0 of the crystal from fig. 2.8(a) trun- +cated along plane 1, at ! = 0:13  2 c=a. Solid lines: results of rigorous calculations, rn0 ; circles: results of +calculations made in the single-mode approximation, rsm0 ; dashed line: relative error  of the single-mode approx- +imation. The vertical lines at kx = 0:13  2 =a and 0:367  2 =a mark where the incident wave and the single +propagating crystal eigenmode, respectively, turn from propagating to evanescent. (b) Amplitudes of the three +most slowly decaying crystal eigenmodes excited in the above conditions (solid, dashed and dotted line, in order +of increasing Im kz). (c) Effective x (dark lines) and y (light lines) of the crystal. (d)–(f) and (g)–(i) The same +for planes 2 and 3. + + xx j j Re r0, Im r0, j j Re r0, Im r0,tm tm +jx j, jy j j Re r0, Im r0,tmj +argx , arg y +Relative error +Relative error +y Relative error y +38 Chapter 2. Effective-medium model of photonic crystals +1 +0 +1 +(a) (b) (c) +Figure 2.11 Real part of the electric field Ey of the modes of the crystal shown in fig. 2.8(a) with (a) ! = +0:13  2 c=a, kx = 0:367  2 =a and kz = 0, (b) ! = 0:22  2 c=a, kx = 0:264  2 =a and kz =  =a, +(c) ! = 0:31  2 c=a, kx = 0:078  2 =a and kz = 0. Two nonequivalent mirror planes of the crystal parallel to +its surface are marked with horizontal lines. +1 1:0 1 0:2 +(a) (d) + 0 +Im r0 +0 0:5 1 0:1 + Re r0 2 + rel. error!1 0:0 3 0:0 +4 2 +(b) (e) +2 1 +0 0 +3 1 50 +(c) (f) +z +2 +0 0 +1 y +x +0 1 50 +0:0 0:1 0:2 0:3 0:0 0:1 0:2 0:3 +kxa=2  kxa=2  +Figure 2.12 Same as fig. 2.10, at frequency ! = 0:222 c=a and for truncation planes (a)–(c) 1 and (d)–(f) 2. +The vertical lines at kx = 0:22 2 =a and 0:264 2 =a mark where the incident wave and the single propagating +crystal eigenmode, respectively, turn from propagating to evanescent. +in the whole range of kx for the cuts 1 and 2, which coincide with mirror planes of the PC [figs. +2.10(c) and (f)]. In contrast, truncating the crystal along plane 3 leads to divergence of y at kx = +0:39  2 a=c. +We turn now to the study of the system at the frequency ! = 0:22  2 a=c. The EFC, shown in fig. +2.9(b), consists of two elliptical “branches” encircling the points X = .0;  =a/ and X 0 = . =a; 0/. In the +effective-medium model, we focus on the neighbourhood of the first EFC branch (jkxj < 0:39  2 =a) +and use the dimensions of the ellipse encircling the X point to calculate the effective parameters. The +electric field of the mode corresponding to the right vertex of this ellipse is plotted in fig. 2.11(b). It is +symmetric with respect to plane 1, which passes through the cylinder centres, and antisymmetric with +respect to plane 2, passing midway between the cylinders. +j j Re r0, Im r0,x , z , y tm +x , z j j Re r0, Im r0,tm + +Relati yve error +Relative error +2.4. Examples 39 +1 2 1 2 +(a) (d) + +Im r0 +0 1 0 1 + Re r0 +rel. error! +1 0 1 0 +20 +(b) 20 (e) +10 +0 0 +0:08 0:5 0:100 0:4 +(c)  ! (f)y + 0:60:10 0:125 0:5 +0:7 +0:12 0:150 0:6x 0:8 +0:14 0:9 0:175 0:7 +0:00 0:02 0:04 0:06 0:08 0:00 0:02 0:04 0:06 0:08 +kxa=2  kxa=2  +Figure 2.13 Same as fig. 2.10, at frequency ! = 0:31  2 c=a and for truncation planes (a)–(c) 1 and (d)– +(f) 2. The vertical line at kx = 0:0782 =a marks where the propagating crystal eigenmode turns evanescent (the +incident wave is propagating throughout the kx range presented on the plot). +Figures 2.12(a) and (d) show the kx-dependence of the reflection coefficient r0 for these two crystal +terminations. As for ! = 0:13  2 c=a, the approximation accuracy is visibly better for plane 2 than 1: +in the former case, r0 is rendered faithfully well beyond the propagative-wave region. The superior +performance achieved for plane 2 is probably due to the uniformity of the crystal permittivity on this +plane, which leads to smaller spatial field variations, making fewer Fourier harmonics necessary to match +the field in the crystal with that in free space. However, the antisymmetry of the eigenmode’s electric +field with respect to plane 2 implies that the effective permittivity y diverges at kx = 0:26  2 =a [fig. +2.12(f)]. In contrast, if the other truncation plane is chosen, all effective parameters are continuous and +bounded [fig. 2.12(c)], but at the cost of a significant single-mode approximation error:   17% close +to normal incidence. (This time, the relative error is not very meaningful in the evanescent-wave region, +since the rigorous reflection coefficient passes through zero at kx = 0:29  2 =a, so that  blows up.) +Finally, we move on to the case of ! = 0:31  2 c=a. The EFC diagram shown in fig. 2.9(c) +comprises an approximately circular part located at the centre of the Brillouin zone and four curves +of irregular shape, together forming a closed path encircling the point M = . =a;  =a/. The circular +EFC represents a negative-refraction band. As seen from fig. 2.11(c), the electric field of the mode +with kx = 0:078  2 =a and kz = 0 is symmetric with respect to planes 1 and 2, which assures the +continuity of the effective parameters at kx = 0:078  2 =a, where the mode turns from propagating to +evanescent. This is in contrast to the negative-refraction band of the hexagonal crystal analysed in the +previous subsection, whose symmetry properties made y diverge at the transition point. However, there +is no improvement in the accuracy of the single-mode approximation: the comparison of the values of r0 +calculated rigorously and from eq. (2.20) [figs. 2.13(a) and (d)] reveals that the approximation introduces +a significant error (above 33% for plane 1 and 11% for plane 2) due to the large excitation amplitude of +secondary crystal eigenmodes [figs. 2.13(b) and (e)]. +x +jtmj Re r0, Im r0, +x +jtmj Re r0, Im r0, +y +Relative error +y +Relative error +40 Chapter 2. Effective-medium model of photonic crystals +2.4.3 Remarks +In the context of metamaterials containing resonant components, such as metallic split rings, it has been +observed that inside band gaps, the effective permittivity and permeability of these structures (defined at +normal incidence) have large imaginary parts of opposite sign, regardless of the location of the truncation +plane [82–85]. This is not in contradiction with our theory, since one of the assumptions of the condition +for real-valuedness of  and formulated in subsection 2.3.1 is the propagative nature of the fundamental +crystal eigenstate (real 1z). Of course, inside band gaps all modes are evanescent, and so the condition +in question is not applicable. +On the other hand, our results show that in general the effective parameters of a lossless PC can attain +complex values even outside band gaps, if the truncation plane does not exhibit certain symmetries. In +this case, the product  is real (due to the absence of losses), and either  or  has a negative imaginary +part. This is visible, for example, in fig. 2.5(i) showing the kx-dependence of the effective parameters +for the low-symmetric truncation plane 3 of the PC from fig. 2.3(a): it is clear that arg 2 Œ x ; 0, so2 +that Imx < 0. Only at specific truncation planes are effective  and  real. (It must be noted, though, +that precisely these special truncation planes have usually been chosen in previous calculations of the +effective parameters of PCs and metamaterials.) +2.5 Validity of the single-mode approximation +We have seen that the accuracy of the single-mode approximation for a given PC varies strongly with +frequency and incidence angle. In some cases, one of the crystal modes is clearly dominant; in others, +several eigenstates are excited with similar magnitude. In the following, we offer a qualitative argument +relating the ratios jtm=t1j of the excitation coefficients of the individual modes to the Fourier spectrum of +their electromagnetic fields on the crystal surface. This leads us to conclusions regarding, in particular, +the viability of the effective-medium description of negative-refraction bands. +Let us begin by writing the system (2.17) in a partitioned form, emphasising the rows corresponding +to the nonzero elements of the vectors representing the incident field, a and a00 0, as well as the columns +corresponding to the unknowns r0 and tk: +2 32 3 2 3 +666 +IO 0E 0O uO<0 uE<0 uO<07766rE<077 66 0Ek6 0N 1 0N +7 +uN0 u0 uN0 r 76 k7766 066 0O 0E IO uO>0 uE>0 uO>076rE 7 +77 666 1 7770E +6 k777666 >0777 = 6Oˇ E O E 66 77E 7 : (2.37)6i = 0 0 vO<0 vE<0 vO<06 <0 1 tk7766 k k 0 15 +0O 0E i Oˇ>0= vO>01 vE>0 vO>0 tE>k 0Ek +We remind the reader that the symbols embellished with arrows, bars and hats are column vectors, row +vectors and matrices, respectively, while those without any embellishment are scalars (see section 1.3). +The meaning of the indices should be clear; for example, uO<0 stands for the submatrix of the uO matrix +l +ˇˇˇ 0O IO uO +ˇˇˇ +>0 uO>0 +l +Oˇ O O<0 O<0 ˇˇˇ +ˇˇˇˇ +i <0=1 0 v vl +>0 >0ˇ +tl = .1/l 0 +O i Oˇ +k >0 +=1 vO vOl ˇˇˇ : (2.38) +tk ˇˇˇ IO 0O uO<0 uO<0k +ˇˇˇ 0O O O +ˇˇˇ +I u>0 uO>0 +k +ˇi Oˇ = 0O +<0 <0 ˇˇˇ +<0 1 vO vOk +0O i Oˇ>0= vO>0 vO>0ˇ1 k +By means of the Laplace expansion [86, p. 259] of the determinants in the numerator and denominator +along the columns containing uEk and uEl , respectively, the ratio tl=tk can be written as the ratio of two +sums of terms proportional to the components of the Fourier expansion of the electric and magnetic fields +at the crystal surface of, respectively, the kth and l th eigenmode: +P +P ¤ .a un C b vntl = n 0 n n /k kn C n ; (2.39)tk n¤0.anu bnv /l l +where an and bn denote the appropriate coefficients resulting from the Laplace expansion. It is crucial +to observe that these sums do not contain the zeroth Fourier component of either field. +The PC bands can be treated as mixtures of the eigenstates of the empty lattice with “average”  +and ; for a fipxed kx , these eigenstates are the plane waves Eyn.x; z/ = expŒi.kx C Gxn/x C ikznz, +where k = .!=c/2 .k CG /2zn x xn . When the index contrast of the PC is low enough, in some +regions of the .!; kx/ space each of the PC eigenstates comprises a single dominant plane wave, the +perturbative components having low amplitude. This means that each of the sets of coefficients .unm/n2Z +corresponding to different modes m contains a single dominant component. From eq. (2.39) it follows +that, in general, the mode whose dominant component is the zeroth one (n = 0) is then excited the +most strongly. Indeed, labelling this mode with index m = 1, we see that in the expression (2.39) for +the ratio t =t (l ¤ 1) the sum in the numerator does not contain terms proportional to u0 and v0l 1 1 1 , +which, by assumption, are the largest ones. On the contrary, the sum in the denominator contains two +terms proportional to the dominant components of the th mode, say, nl and nl u v l , since nl is necessarilyl l +different from zero. Thus, we see that the fraction tl=t1 is a ratio of a “small” and a “large” quantity—and +so jtl j  jt1j for all l ¤ 1, that is, the defining assumption of the single-mode approximation is fulfilled. +Conversely, if there is strong coupling between the zeroth harmonic and plane waves corresponding +to different values of n, so that no mode with highly dominant zeroth component exists, the numerator in +(2.39) for k = 1 is no longer a small quantity, and multiple eigenmodes can be excited with comparable +amplitude. +We conclude that the single-mode approximation should work best at those values of ! and kx for +which the mode originating from the n = 0 harmonic—the plane wave exp.ikxx C ikz0z/—does not +contain significant contributions of other plane waves. In practice, this usually means that when we +consider the transition from the empty lattice to the final PC, the fragment of the EFC of the PC around +a given value of kx should form mainly from the circle corresponding to the n = 0 harmonic of the +empty lattice. For example, as can be seen in fig. 2.4(a), the EFC of the single propagating mode of +the hexagonal-lattice PC at frequency ! = 0:14  2 c=a (solid line, middle diagram) is very similar to +the original EFC of the n = 0 harmonic of the empty lattice (dashed line). In addition, the imaginary +bands corresponding to n = 1 and n = 2 are very weakly perturbed (top diagram). We infer that the +42 Chapter 2. Effective-medium model of photonic crystals +1:0 +(a) (b) +0:5 +0:0 +0:5 +1 +(c) (d) +0 + u +n +1=u +0 +1 1 +vn=v0 + 1 12 +2 1 0 1 2 2 1 0 1 2 +n n +Figure 2.14 Values of the harmonics .un/2 and .vn 21 n=2 1 /n=2 of the propagative eigenmode of the crystal from +fig. 2.3(a) on the truncation plane 1 and at (a) ! = 0:14  2 c=a, kx = 0:10  2 =a, (b) ! = 0:14  2 c=a, +kx = 0:40  2 =a, (c) ! = 0:259  2 c=a, kx = 0:05  2 =a, (d) ! = 0:259  2 c=a, kx = 0:20  2 =a. +individual plane waves couple weakly, so that the zeroth harmonic of the field of the propagating crystal +eigenmode should be dominant, and the eigenmode itself should be strongly excited. These claims are +corroborated by figs. 2.14(a)–(b), where the amplitudes of several harmonics un n1 and v1 of this mode +at the truncation plane 1 are shown for two values of kx , and fig. 2.5(b), where the amplitudes jtmj of +individual eigenstates are juxtaposed. +Now let us turn our attention to fig. 2.4(b), where the evolution of the EFCs at the frequency ! = +0:259  2 a=c is shown; this frequency lies in the second band, which exhibits negative group velocity. +We can see that in this case the plotted quarter of the circular EFC of the single propagating crystal +eigenstate is formed by merging of the n = 0 and n = 1 harmonics of the empty lattice. Their strong +coupling is further indicated by the substantial alteration of the shape of the imaginary bands. We can +expect the contribution of the zeroth harmonic to be strongest at small values of kx , and so the accuracy +of the single-mode approximation to be highest near normal incidence and deteriorate with increasing kx . +This is again confirmed by figs. 2.14(c)–(d) and 2.7(b). +To help establish a broader picture of the single-mode approximation’s performance for the hexagonal- +lattice PC, in fig. 2.15(b) the relative error of the reflection coefficient r0 calculated in this approximation +is plotted for a mesh of 101  100 points of the .kx; !/ space. In turn, figs. 2.15(c) and (d) present the +amplitude variations of the zeroth harmonic of the electric and magnetic field, respectively, of the most +slowly decaying crystal mode (on the truncation plane 1). It can be seen that, although there is no one-to- +one correspondence, the areas of significant error generally match those in which the n = 0 component +of either the electric or magnetic field, or both, of the least-evanescent eigenmode has small amplitude. +(In fact, the dependence of the approximation’s accuracy on the Fourier spectrum of the magnetic field +seems more pronounced than that on the electric field.) +Finally, it should be noted that the EFC from fig. 2.4(b) is in fact typical for negative-refraction +bands. Indeed, the EFCs of the empty lattice are circular, with group velocity directed outwards, and the +negative bands arise from convex figures formed by arcs of three, four or six such intersecting circles, +necessarily including those corresponding to harmonics with nonzero Gxn (see fig. 2.16). Thus, the +resulting bands do not fulfil the validity condition of the single-mode approximation, or do it only in the +restricted range of kx close to zero. Consequently, attribution of effective permittivity and permeability +to negative-refraction bands makes sense at most for near-normal incidence, while in the evanescent +regime the effective-medium description is definitely inappropriate. +Normalized value +Normalized value +2.5. Validity of the single-mode approximation 43 +0:5 +0:4 +0:3 +0:2 +0:1 +(a) +0:0 +0:5 1:00 +0:4 +0:75 +0:3 +0:50 +0:2 +0:25 +0:1 +(b) +0:0 0:00 +0:5 1:00 +0:4 +0:75 +0:3 +0:50 +0:2 +0:25 +0:1 +(c) +0:0 0:00 +0:5 1:00 +0:4 +0:75 +0:3 +0:50 +0:2 +0:25 +0:1 +(d) +0:0 0:00 +0:0 0:2 0:4 +kxa=2  +Figure 2.15 (a) Projection of the band structure of the PC shown in fig. 2.3(a) on the .kx ; !/ plane. Grey and +white areas denote photonic bands and gaps, respectively. The arrows mark the frequency values ! = 0:14  +2 c=a and 0:259  2 c=a. (b) The dependence of the relative error of the single-mode approximation of this +crystalP’s reflection coefficient on kx andP! for the truncation plane 1. (c) The corresponding dependence ofj 1=2 1=2u01j= njunj21 . (d) Same for jv0 n 21 j= njv1 j . +!a=2 c !a=2 c !a=2 c !a=2 c +0 0 +Relative error Normalized ju1j Normalized jv1 j +44 Chapter 2. Effective-medium model of photonic crystals +(a) (b) +(c) (d) +Figure 2.16 Typical configurations of empty-lattice EFCs leading to formation of negative-refraction bands +after introducing sufficient lattice modulation. In each case, the direction of normal incidence is from the bottom; +circles corresponding to harmonics with Gxn = 0 are drawn in darker blue. Thin lines mark the boundaries of +the first Brillouin zone of each lattice, and black dots denote reciprocal lattice points. Top row: square lattice, +bands encircling (a) theM point of the first Brillouin zone, (b) the point; bottom row: hexagonal lattice, bands +encircling (c) the K point, (d) the point. +2.6 Conclusions +In this chapter, we have analysed in detail the effective-medium description of 2D PCs. Its validity has +been shown to be restricted by the accuracy of the single-mode approximation, and a definition of the +effective permittivity, permeability and transverse impedance, rigorous under this approximation, has +been given. In the framework of the single-mode approximation, we have studied the dependence of +the specular reflection coefficient r0 of the crystal on the position of the truncation plane, deriving the +conditions assuring r0, and consequently the effective parameters, to be real-valued. Continuity and +boundedness of the latter have been shown to depend on the symmetry of the dominant eigenmode of the +crystal. +Subsequently, the conditions of validity of the single-mode approximation have been studied. We +have established a link between the relative excitation amplitudes of individual crystal eigenmodes and +the Fourier spectrum of the electric and magnetic fields of these modes on the crystal truncation plane. +This link has been employed to formulate a criterion for estimating the accuracy of the single-mode +approximation by comparing the equifrequency diagrams of the PC and of the homogeneous medium +with refractive index equal to the average refractive index of the PC. Finally, we discussed the special +case of negative-refraction bands; we concluded that the effective-medium description of these bands is, +quite generally, inaccurate, since their Fourier-space structure entails simultaneous excitation of other +bands by plane waves incident at most angles, and so attributing a definite effective permittivity and +permeability to these bands is not physically meaningful. +Chapter 3 +Antireflection gratings for photonic crystals +3.1 Introduction +As can be seen from the plots of the reflection coefficient of PCs presented in chapter 2 (figs. 2.5, 2.7, +2.10, 2.12, and 2.13), reflected waves of significant amplitude are often generated at PC surfaces. In +many applications, one strives after a perfect energy transfer between the incident plane wave and the +propagative PC eigenmode (or, more rarely, several such modes). Propagative reflected waves should +then be eliminated. This chapter concerns the design of antireflection (AR) structures that, placed on +a PC surface, significantly diminish the fraction of energy lost to reflected waves. After reviewing the +classes of these structures proposed to date (section 3.2), in section 3.3 we put forward a new method of +designing AR gratings operating in a wide range of angles of incidence. This algorithm is illustrated in +section 3.4 by means of several examples. We summarise the advantages and limitations of the proposed +approach in section 3.5. +3.2 Types of antireflection structures +3.2.1 Antireflection structures for homogeneous media +Since the design of AR structures for PCs is often guided by the experience gained from the long- +standing study of methods for eliminating reflections from interfaces separating homogeneous media, +we shall begin with a brief review of the AR structures employed in this simpler case. +They can be divided into two broad classes. The refractive index n of AR coatings depends only on +the coordinate z perpendicular to the interface; depending on whether n.z/ is piecewise-constant or not, +we speak of homogeneous-layer or inhomogeneous-layer AR coatings [87]. In turn, the refractive index +of AR gratings is also a function of the coordinates parallel to the interface. Figure 3.1 shows example +AR structures belonging to these three classes. +The simplest homogeneous-layer AR coating consists of a single thin film with refractive index n and +thickness d chosen so as to ensure destructive interference of waves reflected from its top and bottom +surfaces, excited by a plane wave with a certain frequency ! and angle of incidence  . The values of +n and d can be obtained analytically. In order to improve the angular and frequency tolerance of the +coating, one can increase the number of layers to make the transition between the refractive index of the +super- and substrate more gradual [87], thus reducing the amplitude of waves reflected on the individual +discontinuities of n.z/. In the limit of an infinite number of layers, one arrives at an inhomogeneous- +layer coating with a continuous monotonic profile n.z/. Several specific profiles have been proposed in +the literature (see ref. 88 for a review). Unfortunately, these “ideal” AR coatings, even the single-layer +one, cannot usually be realised because of the lack of suitable materials with the required values of n. +This is the case, in particular, for air-solid interfaces, where thin films with refractive index close to unity +45 +46 Chapter 3. Antireflection gratings for photonic crystals +z z z +medium 2 medium 2 medium 2 +AR +AR coating AR coating grat- +ing +medium 1 medium 1 medium 1 +x x x +(a) (b) (c) +Figure 3.1 Example AR structures belonging to the three principal classes described in the text. Darker areas +denote regions with higher refractive index. (a) A homogeneous-layer AR coating. (b) An inhomogeneous-layer +AR coating. (c) A (binary lamellar) AR grating. +are needed. Short of using special ultra-low-index media, such as so-called Reststrahlen materials [87], +there are two basic ways of circumventing this problem. +One of them consists in abandoning completely the structures based on a “continuous transition” +between the super- and substrate refractive indices in favour of interference-based coatings [87]. In +these systems, the total reflected wave vanishes thanks to the destructive interference of partial waves +generated at interfaces between layers with contrasting values of n. For instance, so-called v-coatings +consist of two layers with prescribed refractive indices n1 and n2 (corresponding to realistic materials) +and thicknesses d1 and d2 adjusted so as to eliminate reflection at the desired values of ! and  . Note +that n1 and n2 must satisfy certain conditions in order that appropriate d1 and d2 can be found [89, +p. 96]. A disadvantage of v-type AR coatings is that their angular and frequency tolerance are usually +inferior even to those of the corresponding ideal single-layer coatings [89, p. 97; 90, p. 188]. +The other solution consists in using subwavelength gratings to simulate AR coatings with arbitrary +n.z/ profiles. In many cases, the effective-medium theory of gratings can be employed to calculate +the grating profile mimicking the desired n.z/ dependence [88]. Several types of gratings, such as the +lamellar, trapezoidal, sinusoidal, triangular and pyramidal ones, have been studied in the literature and +shown to have good AR properties [88, 91–93]. A review of the experimental methods used to fabricate +such AR structures can be found in ref. 94. +3.2.2 Antireflection structures for photonic crystals +As pointed out in chapter 2, a distinguishing feature of PCs is the dependence of their reflection coeffi- +cient on the position of their truncation plane. One could hope then that a significant reduction of a PC’s +reflectance could be achieved without adding any AR structure, but simply by choosing an appropriate +cut. For some crystals, this has indeed proved to be possible [95, 96]. In particular, Botten et al. [96] have +shown that very low reflectance is a rather general feature of rod-type PCs truncated midway between +successive layers of rods. For many crystals, however, no truncation plane provides a sufficiently small +value of reflectance (see fig. 3.2). This method of reducing reflection is therefore not general enough, +and one often has to resort to introducing some AR structure. Several types of them have been proposed +in the literature. More often than not, they have much in common with one of the solutions developed +with homogeneous materials in mind, reviewed in the previous subsection. +3.2. Types of antireflection structures 47 +0:4 +z a +0:3 +p +a 3 +0:2 +2 +0 +0:1 +0:0 0:1 0:2 0:3 0:4 0:5 +p +z0=.a 3/ +(a) (b) +Figure 3.2 (a) The dependence of the reflectance jr 20j of the PC shown in part (b), placed in air, on the location +of the truncation plane z = z0. The impinging wave is normally incident, s-polarised and has frequency ! = +0:311  2 c=a. It can be seen that jr 20j does not fall under 0.13 for any truncation plane. (b) Geometry of the +PC under study: a hexagonal lattice of air holes with radius 0:365a, where a is the lattice constant, etched in a +dielectric matrix with permittivity  = 10:6. +The simplest approach has been proposed by Li et al. [97]. It consists in placing in front of the +crystal a v-type AR coating composed of two layers made of constituent materials of the crystal, usually +air and a dielectric. Their thicknesses can be determined analytically or graphically as soon as the +reflection coefficient of the semi-infinite uncoated PC at the selected operation frequency is known. This +frequency is assumed to be low enough that only the zeroth diffraction order be propagative in the layer +closest to the PC surface, so that all higher orders reflected by the crystal decay before reaching the +boundary between the two layers. If it is not the case, the structure may still work, but the optimum layer +thicknesses will not in general be given by the analytical formulas derived from the thin-film theory. The +basic disadvantage of this otherwise very attractive approach is the relatively low angular and frequency +tolerance of v-type AR coatings. +Another group has studied a similar approach, in which one of the homogeneous layers is replaced +by a grating of rods or holes [98, 99]. The performance of the resulting AR gratings was shown to be +similar to that of v-type coatings [99]. Related structures, albeit with only a single degree of freedom +(the radius of the outermost rods of a rod-type PC), were also analysed by Jin and He [100]. In turn, +Zhang and Li [101] proposed a more complex wide-angle AR grating for the interface between air and +a PC flat lens, whose fabrication would be seriously hindered, though, by the presence of extremely thin +air slits and dielectric veins. +In contrast to the above works, which concentrated on the low-frequency regime, the authors of refs. +102–104 endeavoured to eliminate the reflection from an interface between a PC and a semiconductor at +a frequency where multiple propagative diffraction orders existed in the latter medium. They proposed +an AR grating consisting of elongated drop-shaped air holes, this nonstandard form being motivated +by the desire of ensuring a gradual transition between the two media. In fact, the shape of the resulting +structure resembles closely the classical trapezoidal AR gratings studied, e.g., by Raguin andMorris [92]. +The improvement brought about by these gratings has subsequently been demonstrated experimentally +[105]. Unfortunately, Baba et al. did not provide any analytical guidelines regarding the choice of the +geometrical parameters of the gratings, resorting instead to a time-consuming scan of the parameter space +in order to find the optimum structure [102, 103]. +A very important contribution was made by Lawrence et al. [106, 107], who introduced the concept +of generalised matrix-valued effective immittance O of gratings and showed that their effective-medium +jr j20 +48 Chapter 3. Antireflection gratings for photonic crystals +description can be made arbitrarily accurate by allowing O to have sufficiently large dimensions. Such +matrix-valued immittance cannot serve as a drop-in replacement of the corresponding scalar quantity in +standard formulas derived for homogeneous media [107]. Therefore, for instance, analytical determi- +nation of the optimum parameters of an AR structure for a given PC composed of layers described by +a matrix O is not possible. However, Lawrence et al. derived equations corresponding to the Fresnel +formulas (2.9) involving the generalised immittances of two adjacent gratings, and showed that the im- +mittance matrix of typical gratings can be truncated to 5 5 elements or less without a substantial loss in +accuracy. Since numerical calculations involving such small matrices are very fast, it becomes feasible +to design optimum AR gratings by performing a full scan of the available parameter space. Example AR +structures presented in ref. 107 include, for instance, a relatively wide-band AR coating of a superprism- +type PC at a frequency where multiple propagative diffraction orders exist in the adjacent dielectric. A +slight limitation of the approach of Lawrence et al. is that the generalised immittance has only been +defined for 2D gratings symmetrical with respect to a two-fold rotation axis parallel to the direction of +invariance. Therefore, it does not cover, for instance, triangular or trapezoidal gratings. +All the AR structures discussed so far are relatively compact, with thickness rarely exceeding one +or two lattice constants of the underlying PC. Some authors have advocated sacrificing compactness in +favour of potentially larger frequency and angular tolerance offered by thick stacks of gratings, whose +geometry changes gradually so as to ensure a smooth transition of the electromagnetic field of the in- +cident plane wave towards the Bloch mode of the semi-infinite PC. Several design principles for such +gratings have been proposed [108, 109]. In this work, we shall focus on compact AR structures, and +therefore we do not consider adiabatic AR gratings in detail. +3.3 Design procedure +We shall now present an alternative method of designing AR gratings for PCs. Compared to the ap- +proaches reviewed in subsection 3.2.2, it has the following distinguishing features: +1. Instead of performing a potentially time-consuming global scan of possible geometries, we use an +effective-medium model of PCs to calculate analytically the geometrical parameters of a “tenta- +tive” AR grating; then, if necessary, these parameters are refined with a numerical local-minimisa- +tion procedure. The end result of our procedure is a trapezoidal AR grating. +2. The resulting AR structures have good angular tolerance, which in some important applications +of PCs is more significant than the frequency tolerance. For instance, the quality of the image +produced by a PC flat lens with effective refractive index n  1 depends in the first place on +the angular range of incident propagative plane waves which are transmitted through the lens with +little or no energy loss. On the other hand, frequency tolerance is not vital since n can be close +to 1 only in a narrow frequency band. +We draw on the results of Raguin and Morris [92], who demonstrated that triangular and trapezoidal +gratings allow a significant reduction of reflectance at interfaces between homogeneous media in a wide +range of incidence angles. Let us now proceed to detailing the three constituent steps of the algorithm. +Step 1 We begin by using the classical theory of AR coatings to calculate the refractive index and +thickness of a single-layer coating that should minimise the reflection from the PC surface at a fixed +angle of incidence  and frequency !. The value of  should lie approximately midway the desired +angular operation range of the final AR structure. +Consider the system shown in fig. 3.3, in which a propagative plane wave with frequency ! = ck0 +and wave vector kE1 = .kx; kz1/ = .n1k0 sin ; n1k0 cos / impinges from the dielectric 1 with refractive +3.3. Design procedure 49 +z +medium 3 +d2 medium 2 +n2 +E  +medium 1 +k1 +n1 +x +Figure 3.3 System considered in step 1 of the AR grating design procedure. +index n1 on the surface of the homogeneous film 2 with thickness d2 and refractive index n2 coating the +PC 3. Let us assume that medium 2 supports exactly one propagative diffraction order and is sufficiently +thick for all the evanescent orders reflected from the PC surface to vanish at the interface between media +1 and 2. We can calculate the total amplitude of the reflected plane wave, r , by summing up all the +multiple reflections occurring in the system: +hX1 i 2 += C n r12 C .t12t21 r12r21/r= 23˚r r12 t12˚r23˚ .r21˚r23˚/ t21 ; (3.1)1 r 221r23˚ +n=0 +where rij and tij denote the amplitudes of the waves reflected from the interface between media i and j +and transmitted through it, respectively, and˚  eikz2d2 with k  .n2k2k2/1=2z2 2 0 x . From the Fresnel’s +formulas [cf. (2.9)] +j i 2 +rij = +j +C ; tij = C (3.2)j i j i +it immediately follows that r21 = r12 and t12t21 r12r21 = 1, hence +r C r ˚2 += 12 23r C : (3.3)1 r 212r23˚ +The parameters of the antireflection coating, n2 and d2, can now be obtained by requiring the numerator +of the fraction in the above equation to vanish. If the coating is lossless, so that j˚ j = 1, the numerator +vanishes if and only if (i) the moduli of r12 and r23 are equal and (ii) the thickness d2 is such that +arg r23 C 2kz2d2 = arg r12 C .2mC 1/ ; (3.4) +where m 2 Z and arg z stands for the argument of the complex number z. Solving for d2, we get +arg r12 arg r23 C .2mC 1/  +d2 = : (3.5) +2kz2 +It is usually best to choose the value of m corresponding to the smallest positive admissible value of d2; +otherwise, internal resonances in the coating layer can spoil its antireflective properties for some angles +of incidence. +50 Chapter 3. Antireflection gratings for photonic crystals +We shall now use condition (i) to determine the refractive index n2 of the AR coating. Substituting +the Fresnel’s formulas (3.2) into the condition jr j2 = jr j212 23 , we obtain +.  /22 1 .3 2/. 2/ +C = +3 +C  C : (3.6).  /22 1 .3 2/.3 2/ +Straightforward algebra leads to +Re C j j22 = 3 3 =1 22 1 : (3.7)Re3 1 +The s- and p-polarisation cases need now to be considered separately. Assuming materials 1 and 2 to be +nonmagnetic (1 = 2 = 1), in the s-polarisation case we have 2 = Z2 and eq. (2.5) gives +k0 k +Z2 = = q 0 ; (3.8) +kz2 n2 2 2 2 22k0 n1k0 sin  +hence +2 2 2 C 1n2 = n1 sin  : (3.9) +Z22 +It can be seen that Z22 must be non-negative in order that kz2 be real, as we have assumed. +For p polarisation, 2 = Y2 and eq. (2.8) yields +n22k0 n +2 +Y = = q 2k02 : (3.10) +kz2 n22k +2 n20 1k2 sin20  +This leads to the quadratic equation for n22, +n4 Y 2n2 C Y 2n2 sin22 2 2 2 1  = 0; (3.11) +which has real solutions  q  +1 +n2 2 4 2 2 22 = Y2 ˙ Y2 4Y2 n1 sin  (3.12)2 +provided that Y 4 4Y 2n2 sin22 2 1   0. It can be shown that this condition, together with the condition of +real-valuedness of kz2 [for both solutions of eq. (3.12)], is fulfilled if and only if +Y 2  4n2 sin22 1 : (3.13) +In practice, there are further constraints on the choice of the constituent material of the coating. Other +experimental issues aside, n2 is bounded from below by the refractive index of air, and from above, by +the index at which a second propagative diffraction order appears at the given value of kx . We shall now +show how such constraints of the general form +n2  n2  n2min 2 max (3.14) +can be transformed into equivalent constraints on the immittance of the PC, 3. +We begin by noting that the conditions (3.14) can always be rewritten in the form +2  2  2min 2 max (3.15) +3.3. Design procedure 51 +Range of n2 , n2 and n2 Y 2 Y 2 +min max x min max +2  n +2 +2  2 n +4 4 +0 < n min +n +; n n min maxx 2 min max n2 n2 n2 n2 +min x max x +n2 4 +min 2 2  2  2 n4 n< n < n n 2n max min +2 x min max x n2 n2 n2 n2max x min x +n2 22 2 2 2  n n2 n +4 +min < n < n ; 2n < n min x 4n2 min +2 x min x max n2 n2 x n2 n2 +min x min x +n2 n2 n2 4 +min < n2 < n2 ; min x +n +< n2 4n2 max +2 x min n2 n2 max x n2 n2 +min x max x +n2  n2 < n2  2 n42n maxx max x 2 2 1min nmax nx +n2  n2 ; 2n2 < n2x x max 4n2x 1min +Table 3.1 Minimum and maximum bounds on Y 22 sufficient and necessary for fulfilment of the condition (3.14) +together with the constraint (3.13) for at least one of the solutions (3.12) of eq. (3.11). The symbol n2x denotes +n2 sin21  . +with appropriate  and  . Specifically, for s polarisation, the formulas for Z2 and Z2min max min max +follow readily from eq. (3.9): +2 1 1Zmin = ; Z +2 +max = : (3.16)n2max n2 21 sin  n2 n21 sin2 min +For p polarisation, due to the more complex form of eq. (3.12) and the presence of the supplementary +condition (3.13), several cases must be considered. The final formulas for Y 2 and Y 2max are given inmin +table 3.1. +To arrive at the form of the constraints on 3, we substitute eq. (3.7) into inequality (3.15) and +introduce reduced immittances Q i  i=1 (i = 3, min, max), obtaining +Q ReQ C jQ j22  3 3Q  Q +2 +min max: (3.17)Re3 1 +This expres"sion can be rewritten as Q   Q  #2 2 2 2 +ReQ3 +1C 1  +min C .ImQ3/2 min .ReQ3 1/  0; (3.18a) +" 2 2Q   Q  #2 2 2 2 +ReQ 1Cmax C 1 .ImQ /2 max .ReQ3 3 3 1/  0: (3.18b) +2 2 +It follows that the constraints (3.14) are equivalent to the following conditions on Q3: +.Q3 2 extP and Q3 2 extCmin and Q3 2 intCmax/ +Q 2 Q 2 Q 2 (3.19)or .3 intP and 3 intCmin and 3 extCmax/; +where P +Q  + +stands for the half-plane ReQ3 < 1, C 1 Q 2 1min, the circle ofradius j1  j centred at .1C2 min 2 +2 /; 0 , and C , the circle of radius 1 j1 Q 2 j centred at 1max max .1C Q 2max/; 0 . The symbols intAmin 2 2 +and extA denote the interior and exterior of a region A, and the overbar denotes set closure. Thus, for +instance, intA stands for the interior of the set A together with its boundary. +To illustrate various possible geometries of the region of the complex Q3 plane determined by the +constraints (3.14) transformed into the form (3.19), fig. 3.4 shows the shape of this region for s polarisa- +tion and three distinct choices of the parameters nmin, nmax, n1 and  . +52 Chapter 3. Antireflection gratings for photonic crystals +1 +(a) (b) (c) +Cmax +Cmin Cmin Cmin +Cmax +0 Cmax +1 +0 1 2 0 1 2 0 1 2 3 +ReZQ Q3 ReZ3 ReZQ 3 +Figure 3.4 Regions of the complex ZQ 3 plane determined by the condition (3.19) equivalent to the constraint +(3.14) for s polarisation and (a) n1 = 1, nmin = 1:5, nmax = 3,  = 0, (b) n1 = 1, nmin = 1, nmax = 3,  = 30ı, (c) +n1 = 1:5, nmin = 1, nmax = 3,  = 0. The circles Cmin and Cmax are defined in the text after eq. (3.19); note that +in the case (b) Cmax degenerates into the point .1; 0/. +Step 2 The coating obtained in step 1 is not practical, since its fabrication would call for integration +of the PC with a completely different solid; moreover, a suitable material with the required value of +refractive index might not be easily available. However, as noted in subsection 3.2.1, a homogeneous +thin film can often be replaced without adverse effects by a subwavelength grating. Such a grating could +be easily etched in the same process as the underlying PC; it would then naturally be composed of the +same materials as the PC, with permittivities, say, l and h (l < h). +In order to calculate the fill factor of a binary lamellar grating mimicking a layer with refractive +index n2 obtained in the previous step, one can resort to the classical second-order effective-medium +theory of gratings due to Rytov, described in ref. 92. According to this theory, the effective permittivity Qs +of a binary grating with period a and fill factor f (0  f  1), composed of materials with permittivities +l and h, and operating in the s polarisation is + 2 +   +Q N C k0a +2 +2 2 .h l/ +2 +s = s 1 f .1 f / N ; (3.20)3 2  s +where +Ns = fh C .1 f /l: (3.21) +For p polarisation, the effective permittivity Qp is + 2 2  2 +Q = N C   k0a 2 2 2 N Npp p 1 f .1 f / .h l/ s ; (3.22) +3 2  hl +where   +N f C 1 f +1 +p = (3.23) +h l +and Ns is given by eq. (3.21). Thus, the required fill factor can be obtained by setting Qs or Qp to n22 in eq. +(3.20) or (3.22) and solving it numerically for f . +It should be noted that in the domain of validity of Rytov’s theory (small k0a=2 ) the functions Qs.f / +and Qp.f / are monotonically increasing from l to h. Thus, a binary grating cannot simulate a material +with permittivity outside the range delimited by the permittivities of the grating’s constituent materials. +As a result, the bounds n2 and n2max mentioned in step 1 must fulfil n +2  l and n2min min max  h, +respectively. +ImZQ 3 +3.4. Examples 53 +0:50 +PC +air +0:25 +0:00 +0:25 +0:50 +0:5 0:0 0:5 +kxa=2  +Figure 3.5 Solid line: EFC of the PC considered in subsection 3.4.1 at frequency ! = 0:311  2 c=a and for +s polarisation. Dashed line: EFC of air at the same frequency. +Step 3 The structure obtained at this stage should, in principle, ensure low reflectance for incidence +angles close to  . Nevertheless, owing to the applied approximations—neglect of higher diffraction +orders excited by the PC and the AR grating—its geometrical parameters might not be precisely optimal. +In addition, it is well known [91, 92] that trapezoidal and triangular AR gratings have larger angular +and frequency tolerance than lamellar ones. Therefore, it is advisable to apply a numerical optimisation +procedure to adjust the geometry of the grating, described by some small number of parameters, so as +to minimise a given objective function . The geometry obtained in step 2 can be expected to provide a +good starting point for a local search algorithm, such as the Nelder-Mead simplex method [110, section +10.4]. +3.4 Examples +3.4.1 A photonic-crystal flat lens +Preliminaries The first PC we shall consider is a hexagonal lattice of air holes of radius r = 0:365a, +where a is the lattice constant, etched in a dielectric matrix of permittivity  = 10:6. These parameters +correspond to the structure whose fabrication was reported in ref. 18. For s polarisation, at frequency +! = 0:311  2 c=a, the effective refractive index n = 1 can be attributed to the crystal, since its +EFC takes an approximately circular shape (fig. 3.5) with radius K  !=c and group velocity directed +inwards. (Unless otherwise noted, all calculations whose results are presented in this subsection have +been made with the differential method [69, 74–76].) +Veselago [20] predicted that a slab of material with n = 1 should act as a flat lens: an image of +an object placed near one of the surfaces of the slab should be produced on the other side of the slab. +Figure 3.6 shows the map of the modulus of the electric field generated by a wire source with current +1A (ampere) located above a slab of the PC in question.? The parts (a) and (b) refer to slabs truncated +in the ways shown in figs. 3.7(a) and (b), respectively; from now on, these two structures will be referred +to as S1 and S2. In accordance with the theoretical predictions, images are formed below the slabs. +? The field maps shown in figs. 3.6 and 3.12 have been produced with the finite-element method using the RF module of +the COMSOL program. The computational domains were rectangles of width 55a and height 30a surrounded by perfectly +matched layers of thickness 3a. The meshes consisted of about 225,000 second-order triangular Lagrangian elements +of maximum size 0:2a (refined further in the neighbourhood of the point source). Numerical convergence was tested by +comparing the results of a representative calculation against those obtained after refining the mesh by dividing each element +into four. This produced no visible changes in the field map and the maximum amplitude of the image produced by the +lens changed by less than 1%. +kza=2  +54 Chapter 3. Antireflection gratings for photonic crystals +200 +(a) +10 +150 +0 100 +50 +10 +0 +200 +(b) +10 +150 +0 100 +50 +10 +0 +20 10 0 10 20 +x=a +Figure 3.6 Modulus of the electric field generated by an s-polarised wire source with current 1A located above +a slab of the PC studied in subsection 3.4.1 truncated along a plane (a) lying midway between two neighbouring +rows of holes, (b) crossing the centres of holes. +However, their amplitude is low (67 and 79V=m for structures S1 and S2, respectively) and intense +beams reflected from the top of the lenses are visible in the upper part of the plots. This suggests that +only a small fraction of energy is transmitted through the lenses. Indeed, as shown in fig. 3.7(a), the +reflectance of structure S1, jr 20./j , where r0 is the specular reflection coefficient, exceeds 29% for all +angles of incidence. Structure S2 performs better for low incidence angles, but degrades quickly with +increasing  . We shall now apply the algorithm presented in section 3.3 to design an AR grating for +this PC. +Step 1 We have seen in section 2.4 that the effective-medium model of PCs tends to be more accurate +for crystals truncated along a plane with constant permittivity profile, as is the case, for instance, for +structure S1. Therefore in the first step of the design procedure we shall calculate the effective transverse +impedance Z3 of this structure. We consider two ways of obtaining this quantity. First, we calculate it +from eq. (2.23), derived in the framework of the model presented in chapter 2. At frequency ! = 0:311 +2 c=a and angle of incidence  = 45ı (corresponding to kx = 0:220  2 =a) we get Z1 = 1:414 and +Z3 = 0:319. We should now check whether ZQ 3  Z3=Z1 = 0:225 lies within the region determined by +the conditions (3.19) equivalent to the constraints (3.14) with nmin = 1 and nmax = 2:51 (the maximum +index of a medium in which only a single propagative diffraction order exists). Figure 3.8, in which +z=a z=a +jEy j (V=m) jEy j (V=m) +3.4. Examples 55 +1:00 +S1 +0:75 S2 +0:50 +(a) S1 +0:25 +0:00 +0 30 60 90 +Angle of incidence  (deg) +(b) S2 +(c) +Figure 3.7 Geometry of the PC studied in subsection 3.4.1 truncated along a plane (a) lying midway between +two neighbouring rows of holes, (b) crossing the centres of holes. (c) Angular dependence of the reflectance of +the structures shown in parts (a) and (b). +1 +Cmin +B +0 C +A max +1 +0 1 2 +ReZQ 3 +Figure 3.8 Shaded circle: region of the complex ZQ 3 plane determined by the condition (3.19) equivalent to the +constraint (3.14) for s polarisation, n1 = nmin = 1 and nmax = 2:51. Points A and B: reduced impedances ZQ 3 of +structure S1 calculated in two different ways described in the text. +the value of ZQ 3 cited above is marked with point A, shows that this is indeed the case. Therefore eqs. +(3.5) and (3.9) can be used to calculate the parameters of the AR coating of the crystal: refractive index +n2 = 1:649 and thickness d2 = 0:540a. The geometry of this structure, called S3 from now on, is shown +in fig. 3.9(a) and its reflectance is plotted in fig. 3.9(e) with a solid black line. It can be seen that the +application of the coating reduces significantly the reflectance of the crystal, especially for small angles +of incidence. However, the parameters of S3 are certainly not optimal, since its reflectance at the “design +angle”  = 45ı is as large as 9%. This is due to the relatively large error introduced by the single-mode +approximation for negative-refraction PC bands, as pointed out in chapter 2. +We shall evaluate, therefore, an alternative method of obtaining Z3, which consists in calculating +it directly from the rigorous specular reflection coefficient r0 of the uncoated crystal at the chosen ! +and kx . In other words, we assume that r0 can be expressed in the form r0 = .Z3 Z1/=.Z3CZ1/ [cf. +eq. (3.2)] and invert this formula to obtainZ3 = Z1.1Cr0/=.1r0/. Of course, the effective impedance +defined in this way depends on the material properties of medium 1. Nevertheless, at least for the PC in +question, this dependence is weak for sufficiently small n1: we obtain Z3 = 0:258C 0:175i for n1 = 1 +and the effective impedance does not change by more than 10% up to n1 = 2:25. As shown in fig. 3.8, the +reduced impedance ZQ 3 = 0:182C 0:124i corresponding to the above value of Z3 (marked with point B) +also lies within the allowed region of the ZQ 3 plane. Taking this value of Z3, from eqs. (3.5) and (3.9) +ImZQ 3 +Reflectance jr j20 +56 Chapter 3. Antireflection gratings for photonic crystals +n2 = 1:649 +d2 = 0:540a +(a) S3 +1:00 +S3 +n2 = 1:884 0:75 S4 +d2 = 0:565a S5 +0:50 S6 +(b) S4 +0:25 +f = 0:192 0:00 +d 0 30 60 902 = 0:565a +Angle of incidence  (deg) +(c) S5 +(e) +f = 0:192 +d2 = 0:565a +(d) S6 +Figure 3.9 (a)–(b) Geometry of AR coatings S3 and S4, characterised by refractive index n2 and thickness d2 +specified next to the drawings. (c)–(d) Geometry of binary lamellar AR gratings S5 and S6, characterised by +fill factor f and thickness d2 specified next to the drawings. (e) Angular dependence of the reflectance of the +structures shown in parts (a)–(d). +we get n2 = 1:884 and d2 = 0:565a. The angular dependence of the reflectance of the PC covered with +this coating, shown in fig. 3.9(b) and called S4 in the following, is plotted in fig. 3.9(e) with a solid grey +line. It is evident that this structure has much better angular tolerance than S3; moreover, its reflectance +at  = 45ı is only 0.05%. Therefore we choose S4 as a basis for the further steps of the algorithm. +Step 2 Numerical inversion of eq. (3.20) gives the fill factor f = 0:192 of the binary grating mimick- +ing a medium with n = 1:884. Since we would like the angular dependence of r0 to be symmetric with +respect to  = 0, the grating should be positioned so as to preserve the vertical mirror symmetry axes of +the underlying PC. This can be done in two possible ways, shown in figs. 3.9(c) and (d). The reflectance +of these two structures, called S5 and S6, is plotted in fig. 3.9(e). Clearly, grating S5 reproduces fairly +faithfully the original reflectance curve of the AR coating S4. On the other hand, grating S6 behaves +better in the high- region. +Step 3 The lamellar gratings obtained in step 2 provide already a remarkable improvement over the +uncoated PC and, in contrast to the AR coatings from step 1, should be manufacturable. Nevertheless, +their geometry can be further ameliorated. To this end, as mentioned in the last paragraph of section 3.3, +we use the Nelder-Mead simplex algorithm to find the optimum values of the dimensions wi, wo, hi, and +ho parametrising the trapezoidal grating shown in fig. 3.10. The objective function  is defined as the +average of the numerically calculated reflectance of the given structure over the desired angular tolerance +Reflectance jr j20 +3.4. Examples 57 +a +p +a 3=4 +hi +ho +wo +wi +Figure 3.10 Definition of the geometrical parameters wi, wo, hi, and ho of a trapezoidal grating superposed on +the surface of structure S1. +interval Œmin; max, Z +1 max + = jr0./j +2 d: (3.24) +max min min +The integral in eq. (3.24) is calculated with the 20-point Gauss-Legendre quadrature algorithm [110, +section 4.5], whose typical relative accuracy, 105, is better than that of the reflectance calculations, +103. The initial shape of the grating is taken to correspond to one of the lamellar gratings obtained in +step 2, i.e., wi = wo = fa, hi = 0, and ho = d2. The search routine is terminated when the size of the +simplex, defined as the average distance of its vertices from its geometric centre, falls below 105. The +final values of the geometrical parameters of the grating are determined by selecting the best among the +16 structures obtained by rounding each of the parameters delivered by the simplex algorithm upwards +or downwards to a multiple of 0:01a. +Application of this procedure with  = 0ı,  = 90ımin max to grating S5 yields grating S7 shown in +fig. 3.11(a). The plot in fig. 3.11(e) (solid black line) demonstrates the excellent antireflective properties +of this structure (note the scale of the vertical axis). Its average reflectance is as low as 2.8%; in fact, +jr ./j2 does not exceed 5.5% until  = 87ı0 . The structure does not seem to present special fabrication +difficulties—e.g., acute angles—except possibly for the relatively thin dielectric veins separating the +circular holes from the surface. Should this pose a real experimental difficulty, one can increase the +value of hi at the expense of a slight performance deterioration. For example, grating S8 with hi = 0:08a +has average reflectance of 4.8%. +Figure 3.12 shows the map of the modulus of the electric field produced by a point source placed +above a PC slab coated with AR gratings of type S7 from above and below. The comparison with fig. 3.6 +reveals the significant improvement brought about by the AR grating: not only are the reflected beams +prominent in the upper part of the latter figure suppressed, but the amplitude of the image formed by the +lens grows to 159V=m, which is two times better than in the situation from fig. 3.6(b). +Optimisation of structure S6 leads to gratings with average reflectance comparable to that of S7 and +S8 but composed of “narrower” trapezoids (wiCwo  0:2a), thus less suitable for fabrication. Therefore +we omit the detailed discussion of these structures. +Other structures In refs. 111 and 112 two other trapezoidal AR gratings, here denoted S9 and S10, +were presented. Their geometrical parameters, shown in figs. 3.11(c) and (d), were obtained by minimis- +58 Chapter 3. Antireflection gratings for photonic crystals +wi = 0:40a +wo = 0:16a +hi = 0:05a +ho = 0:55a +(a) S7 +0:20 +wi = 0:28a S7 +wo = 0:28a 0:15 S8 +hi = 0:08a S9 +ho = 0:50a 0:10 S10 +(b) S8 +0:05 +wi = 0:50a +wo = 0 0:00 +hi = 0:01a 0 30 60 90 +ho = 0:69a Angle of incidence  (deg) +(c) S9 +(e) +wi = 0:29a +wo = 0:22a +hi = 0:08a +ho = 0:53a +(d) S10 +Figure 3.11 (a)–(d) Geometry of AR gratings S7–S10 characterised by parameters wi, wo, hi, and ho specified +next to the drawings. (e) Angular dependence of the reflectance of the structures shown in parts (a)–(d). To help +visualise the details of the jr 20./j dependence, the y axis has been truncated at jr 20j = 0:2. +200 +10 +150 +0 100 +50 +10 +0 +20 10 0 10 20 +x=a +Figure 3.12 Modulus of the electric field generated by an s-polarised wire source with current 1A located above +a slab of the PC studied in subsection 3.4.1 with S7-type gratings placed on its horizontal surfaces. +z=a +Reflectance jr j20 +jEy j (V=m) +3.4. Examples 59 +max wi wo hi ho +90ı 0:378–0:424a ( 22 nm) 0:151–0:170a ( 9 nm) 0:045–0:055a ( 5 nm) 0:543–0:557a ( 7 nm) +80ı 0:330–0:463a ( 63 nm) 0:132–0:186a (26 nm) 0:033–0:062a (14 nm) 0:530–0:569a (19 nm) +60ı 0:192–0:533a (162 nm) 0:084–0:208a (59 nm) 0 –0:082a (39 nm) 0:497–0:586a (42 nm) +Table 3.2 Ranges of geometrical parameters of grating S7 for which its average reflectance at frequency 0:311 +2 c=a in the angular range 0    max does not exceed 5%. The numbers in parentheses are the lengths of the +tolerance intervals for a = 476 nm, which corresponds to operation wavelength  = a=0:311 = 1530 nm. Note that +the tolerance intervals correspond to perturbations of one parameter at a time (not all parameters simultaneously). +R +ing the objective function 2  =20 jr0./j d (average modulus of the specular reflection coefficient r0)  +calculated with a less accurate quadrature algorithm. The average reflectance of structure S9 in the full +0ı–90ı range, 2.8%, matches that of S7; in a more restricted range, say, 0ı–80ı, the performance of +grating S9 is even slightly better. Nonetheless, its disadvantage lies in the presence of very thin dielectric +veins at the surface. Grating S10, with hi = 0:08a, is devoid of this problem. However, it is superseded +by structure S8 with identical hi, which has somewhat lower average reflectance. +Tolerance to fabrication imperfections A fabrication process invariably perturbs the geometrical +parameters of the manufactured structure. To assess the sensitivity of the proposed gratings to fabrication +errors, we have determined the maximum perturbation of each of the four geometrical parameters of +grating S7 for which the grating’s average reflectance in the angular range 0    max did not exceed +5%. Three values of  were considered: 90ı, 80ı, and 60ımax . The results of this test are summarised +in table 3.2. It can be seen that the grating is more sensitive to variations of the height of the trapezoids +(via the h and h parameters) than of their width (w and w ). The constraints for  = 90ıo i o i max and + = 80ımax are rather stringent and unlikely to be met in practice. In contrast, fabrication of a structure +satisfying the constraints for  = 60ımax seems well within reach of current technology. +We have also tested the frequency tolerance of grating S7, finding that the its average reflectance stays +below 5% for 0:3094  !a=2 c  0:3113 ( = 90ı), 0:3048  !a=2 c  0:3122 ( = 80ımax max ), +and 0:2511  !a=2 c  0:3173 ( = 60ımax ). This tolerance seems quite sufficient for applications +related to lensing. +3.4.2 A supercollimating photonic crystal +Preliminaries The second example to be considered is a PC composed of a square lattice of air +holes of radius r = 0:3a, where a is the lattice constant, etched in a dielectric matrix of permittivity + = 12:25. Near the frequency ! = 0:265  2 c=a its EFCs for p polarisation take a square-like +shape (cf. fig. 3.13. In consequence, supercollimated beams [16, 113] can propagate in the crystal. +All calculations reported in this subsection have been made with a frequency-domain finite-difference +method with subpixel smoothing implemented along the lines of ref. 114. +Figure 3.14(c) shows the angular dependence of the reflectance of this PC at ! = 0:265  2 c=a; +two different truncation planes, shown in figs. 3.14(a)–(b) and called S11 and S12 in the following, are +considered. It is seen that the crystal cut through hole centres has fairly low reflectance: about 10% at +normal incidence and decreasing for larger angles up to   65ı. This level of power losses might in +fact be already sufficient for practical applications. Nevertheless, for the sake of illustration, we shall +present the design procedure of AR gratings that help to decrease even further the reflectance of the PC +in question. +60 Chapter 3. Antireflection gratings for photonic crystals +0:50 +0:25 +0:00 +0:25 +0:50 +0:5 0:0 0:5 +kxa=2  +Figure 3.13 EFC of the PC studied in subsection 3.4.2 at frequency ! = 0:265  2 c=a. The shaded region +corresponds to the range   45ı (jkxj  0:187  2 =a), where the EFC is approximately flat and for which the +minimisation of the PC’s reflectance is made. +1:00 +S11 +0:75 S12 +0:50 +(a) S11 +0:25 +0:00 +0 30 60 90 +Angle of incidence  (deg) +(b) S12 +(c) +Figure 3.14 Geometry of the PC studied in subsection 3.4.2 truncated along a plane (a) lying midway between +two neighbouring rows of holes, (b) crossing the centres of holes. (c) Angular dependence of the reflectance of +the structures shown in parts (a) and (b). +Step 1 We are mostly interested in coupling the incoming light to modes lying on the flat horizontal +part of the PC’s EFC. As shown in fig. 3.13, at frequency ! = 0:265  2 c=a this corresponds roughly +to the range j j  45ı, i.e., jkxj  0:187  2 =a. Therefore we choose  = 22:5ı as the design +angle of the AR coating. As in the previous subsection, we test two different ways of calculating the +effective immittance (in this case, admittance) of the crystal cut along a constant-permittivity plane, i.e., +structure S11. The effective-medium model presented in chapter 2 yields Y3 = 6:138. In turn, the +effective admittance calculated from the rigorous reflection coefficient of structure S11 embedded in air +is Y3 = 6:075 1:191i. Figure 3.15 shows that the reduced admittances corresponding to both these +values lie within the region of the complex YQ3 plane determined by the conditions (3.19) equivalent to +the constraints (3.14) with n1 = nmin = 1, nmax = 3:391 (the refractive index for which the second +propagative diffraction order appears) and  = 22:5ı. The parameters of the AR coatings determined +from these two values of Y3 are (n2 = 2:548, d2 = 0:374) and (n2 = 2:595, d2 = 0:391), respectively. +Figure 3.16 shows the geometry of these coatings, henceforth referred to as S13 and S14, and the angular +dependence of their reflectance. As in the PC lens case, the AR coating S14 designed using the value of +Y3 obtained from the rigorous reflection coefficient of the crystal performs slightly better than the other +one. Therefore structure S14 shall be used in the subsequent design step. +kza=2  +Reflectance jr j20 +3.4. Examples 61 +5 Cmax +0 Cmin A +B +5 +0 5 10 +ReYQ3 +Figure 3.15 Shaded circle: region of the complex YQ3 plane determined by the condition (3.19) equivalent to the +constraint (3.14) for p polarisation, n1 = nmin = 1 and nmax = 3:391. Points A and B: reduced admittances YQ3 of +structure S11 calculated in two different ways described in the text. +1:00 += S13n2 2:548 +0:75 S14 +d2 = 0:374a +0:50 +(a) S13 +0:25 +n2 = 2:595 0:00 +d = 0:391a 0 30 60 902 +Angle of incidence  (deg) +(b) S14 (c) +Figure 3.16 (a)–(b) Geometry of AR coatings S13 and S14, characterised by refractive index n2 and thick- +ness d2 specified next to the drawings. (c) Angular dependence of the reflectance of the structures shown in parts +(a) and (b). +Step 2 From numerical inversion of eq. (3.22) it follows that the fill factor of the binary grating mim- +icking a medium with n = 2:595 for p polarisation is f = 0:812. Figures 3.17(a)–(b) show the geometry +of the two gratings, called S15 and S16, with this fill factor and a mirror symmetry plane perpendicular to +the direction of periodicity. From the juxtaposition of their reflectance curves [fig. 3.17(c)] it follows that +structure S15 has somewhat better performance than S16. Incidentally, there is some similarity between +the geometry of grating S15 and the truncated crystal S12, which also exhibited fairly low reflectance: +The surface of both these structures contains “teeth” shifted by 1a in the horizontal direction with re- +2 +spect to the positions of the circular holes. Therefore, one could view the crystal S12 as an imperfect +realisation of the AR grating S15. +Step 3 The lamellar grating S15 can be further ameliorated by adjusting its thickness d2 and fill +factor f to minimise the objective function  defined in eq. (3.24). We take min = 0, max = 45 +ı and, +as before, perform the optimisation with the Nelder-Mead simplex algorithm. This leads to structure S17 +with d2 = 0:37a and f = 0:73, shown in fig. 3.17(c). Its reflectance curve is plotted in fig. 3.17(d) (solid +line). In the angular range 0    45ı, the reflectance never exceeds 0.6%, on average amounting +to only 0.12%. The structure does not seem to present any special fabrication problems. It is possible +to continue the grating’s optimisation by allowing it to take a trapezoidal rather than a lamellar shape; +however, in view of its already very good AR properties, this appears unnecessary. +ImYQ3 +Reflectance jr j20 +62 Chapter 3. Antireflection gratings for photonic crystals +f = 0:812 +d2 = 0:391a 1:00 +S15 +(a) S15 0:75 S16 +S17 +0:50 +f = 0:812 +d2 = 0:391a 0:25 +(b) S16 0:00 +0 30 60 90 +Angle of incidence  (deg) +f = 0:730 +(d) +d2 = 0:370a +(c) S17 +Figure 3.17 (a)–(c) Geometry of binary lamellar AR gratings S15, S16 and S17 characterised by fill factor f +and thickness d2 specified next to the drawings. (d) Angular dependence of the reflectance of the structures shown +in parts (a)–(c). +3.4.3 A photonic-crystal superprism +We have also attempted to design an AR grating for the unidirectional mirror proposed by Vanwolleghem +et al. [115]. This device, which will be analysed in some more detail in subsection 5.2.3, is slab of the PC +shown in fig. 3.18(a). The PC consists of a hexagonal lattice of triples of adjacent circular holes etched +in a magneto-optical (MO) matrix characterised by a gyrotropic permittivity tensor +2 3 +O = 4.2:5/ +2 0 0:1i +0 .2:5/2 0 5 : (3.25) +0:1i 0 .2:5/2 +The presence of this MO material lifts the time-reversal symmetry of Maxwell’s equations; the spatial +inversion symmetry is also broken owing to the particular choice of the motif. As a result, the crystal +becomes nonreciprocal, i.e., the usual property of the dispersion relation, !.kE/ = !.kE/ [79, pp. 22–23], +no longer holds. The p-polarisation EFC of this crystal at frequency ! = 0:3915  2 c=a, calculated +with the method described in section 5.2, is shown in fig. 3.18(b). It can be seen that a plane wave +impinging at the angle of about 58ı (corresponding to kx   =3a) on the top surface of a slab made +from this PC will be coupled to its propagative mode, and thus will be partially transmitted. However, +a wave travelling in the opposite direction, incident from the bottom, will be totally reflected, since the +crystal has no propagative modes with kx   =3a. This behaviour justifies the name unidirectional +mirror. +The problem with the presented device is its large forward loss: even waves propagating in the +“allowed” direction undergo a significant reflection on the surfaces of the slab. Currently we do not +have a reliable code allowing to calculate accurately the reflection coefficient of the MO PC from fig. +3.18(a) in p polarisation. Therefore we shall study instead the non-MO crystal in which the original motif +composed of three circles is replaced by three overlapping squares, as shown in shown in fig. 3.19(a). The +permittivity of the matrix is taken as  = .2:5/2. [This modified geometry is due to K. Postava (Technical +Reflectance jr j20 +3.5. Conclusions 63 +(b) +(a) 0:50 +a a 0:25 +r +0:00 +0:25 +0:50 +a +0:5 0:0 0:5 +kxa=2  +Figure 3.18 (a) Geometry of the PC composed of a hexagonal lattice of groups of three adjacent circular holes +with radius r = 0:20a, where a is the lattice constant, etched in a magneto-optical matrix. (b) p-polarisation EFC +of this crystal at frequency ! = 0:3915  2 c=a. +University of Ostrava, Czech Republic).] The EFC of this crystal at frequency ! = 0:4548  2 c=a, +calculated with the differential method, is shown in fig. 3.19(b). Clearly, its shape in the regions marked +by dashed circles is similar to that seen in fig. 3.18(b). Fig. 3.19(c) shows a magnification of this EFC +near its inflection point kx = 0:309 2 =a, together with the kx-dependence of the crystal’s reflectance. +It can be seen that the latter is very high. Therefore, to be useful in practice, the unidirectional mirror +would need to be coated with some AR structure. +Unfortunately, the design of an appropriate AR grating using the procedure described in section 3.3 +turns out to be impossible. For instance, at the inflection point of the EFC, the reflection coefficient of +the uncoated PC is r0 = 0:969 0:086i, which corresponds to YQ3 = 6:50 20:5i. As evidenced by +fig. 3.19(d), this lies far outside the region of the complex YQ3 plane determined by the conditions (3.19) +equivalent to the constraints (3.14) with n1 = nmin = 1 and nmax = 1:52 (the refractive index of the +least optically dense coating in which the second propagative diffraction order would appear). In fact, if +we blindly apply eqs. (3.7) and (3.12) to calculate the refractive index of the optimum AR coating, we +obtain n2 = 12:4 or 0:68. It is obvious that none of these indices can be simulated by any binary grating +composed of the constituent materials of the PC. Therefore, an AR structure for the unidirectional mirror +will probably need to be designed with some purely numerical method. In particular, Lawrence et al. +[107] have shown their approach to give good results for a superprism that, uncoated, has an extremely +high reflectance (jr j20 = 0:996). +3.5 Conclusions +In this chapter we have presented a new method of designing gratings that, superimposed on surfaces +of PCs crystals, will minimise their reflectance. The design algorithm consists of three steps. First, the +parameters of a homogeneous-layer AR coating are calculated from an effective-medium approximation +of the PC in question. Second, an analytical effective-medium theory of gratings is used to find the +parameters of a binary lamellar grating composed solely of the constituent materials of the crystal and +approximating the coating obtained in the previous step. Third, the shape of the grating is refined with +a numerical local-search routine so as to minimise the reflectance of the structure in the desired angular +kya=2  +64 Chapter 3. Antireflection gratings for photonic crystals +a 0:746a +(a) (b) +0:4a 0:50 +0:25 +0:00 +0:3a +0:4a 0:25 +p +p 3 +3 a 0:50 +a 2 +2 +truncation plane 0:5 0:0 0:5 +kxa=2  +1:0 0:60 1:0 +(c) (d) +0:9 0:55 0:5 +Cmax +0:8 0:50 0:0 Cmin +0:7 jr0j2 0:45 0:5 +kza=2  +0:6 0:40 1:0 +0:250 0:275 0:300 0:325 0:350 0:0 0:5 1:0 1:5 2:0 +kxa=2  ReYQ3 +Figure 3.19 (a) Geometry of the PC composed of a hexagonal lattice of non-centrosymmetric motifs etched +in a dielectric matrix. (b) p-polarisation EFC of this crystal at frequency ! = 0:4548  2 c=a. (c) Solid line: +kx-dependence of the reflectance jr 20j of this crystal, placed in air and truncated in the way indicated in part (a). +Dashed line: a fragment of the EFC from part (b). (d) Shaded circle: region of the complex YQ3 plane determined +by the condition (3.19) equivalent to the constraint (3.14) for p polarisation, n1 = nmin = 1 and nmax = 1:52. The +reduced admittance of the crystal, YQ3 = 6:50 20:5i, lies far beyond the range of the graph. +or frequency range. This last step is necessary owing to the approximations made in the analytical +derivations used in the first two steps of the procedure. +This algorithm of AR grating design can be viewed as complementary to the method proposed by +Lawrence et al. [106, 107]. While their approach is based on an exhaustive scan of the whole parameter +space (made very efficient by the application of the matrix-valued effective immittance of gratings), ours +rests on approximate analytical considerations used to find a starting point for a local search procedure. +In section 3.4 the proposed method has been applied to three example crystals with EFCs of different +curvature: a supercollimating crystal with a very flat EFC, a crystal exhibiting negative refraction, with +almost circular EFC, and a PC superprism, whose EFC has a kink. In the two first cases, the design +process succeeded in producing AR gratings ensuring very low reflectance in a wide angular range. +The obtained structures are quite compact and apparently rather straightforward to fabricate. In the +last case, the procedure broke down owing to the violation of the constraints (3.19) on the effective +immittance of the crystal that must be satisfied in order that the AR coating produced in the first step can +be approximated with a binary grating made of realistic materials. The existence of these constraints is +the basic limitation of the presented procedure. +jr 20j +kza=2  +ImYQ3 +kza=2  +Chapter 4 +Magneto-optical circulators +4.1 Introduction +4.1.1 Basic characteristics of isolators and circulators +This chapter will be devoted to the design of magneto-optical circulators optimised for operation at in- +frared frequencies in a uniform static external magnetic field (SEMF). Circulators and (closely related) +isolators are devices widely used both in the optical and microwave domain. Their operation can be +most easily explained with the formalism of scattering matrices. Consider the junction of waveguides +W1, W2; : : : , Wn shown in fig. 4.1. On any cross-section Pj (called a port) of waveguide Wj located +sufficiently far from the junction, the field can be represented solely in terms of the waveguide’s prop- +agative eigenmodes. Let us assume all the waveguides to be single-mode and denote the amplitudes of +the incoming and outgoing mode of Wj on the port Pj by sj;in and sj;out. If the system under study +is linear, the amplitudes of the outgoing modes can be linked with those of the incoming ones by the +scattering matrix SO of the junction [116, p. 249]: +sEout = SOsEin; (4.1) +where sE = Œs ; s ; : : : ; s T and sE = Œs ; s ; : : : ; s Tin 1;in 2;in n;in out 1;out 2;out n;out . An ideal isolator is a two- +port device that passes a wave coming from waveguideW1 to waveguideW2, but blocks the transmission +in the opposite direction. It is described by the scattering matrix [117, p. 523] +  +0 0 +SO = : (4.2) +1 0 +In turn, a circulator is an n-port device that couples a wave coming from waveguideW1 to waveguideW2 +only, a wave coming from W2 to W3 only, and so on [116, p. 468]. The simplest, 3-port circulator is +described by the scattering matrix [117, p. 536] +2 3 +0 0 1 +SO = 41 0 05 : (4.3) +0 1 0 +It is worth noting that a circulator can be used as a replacement of an isolator if we ensure that no +incoming waves ever reach one of its ports. This can be easily achieved by connecting that port to a +matched load, which does not generate reflected waves. +The above devices have several important applications. They can be used to eliminate waves reflected +from imperfectly matched components of complex circuits; the presence of such waves can give rise to +undesired interferences and parasitic couplings [34]. They are also employed in signal routing in devices +65 +66 Chapter 4. Magneto-optical circulators +Wn +Pn +: : : +P1 +W1 +P2 +W2 +Figure 4.1 An n-port device. +such as multiplexers [35]. In the optical domain, possibly the most important application of isolators +is the protection of lasers from back-reflected light, which disturbs the standing-wave pattern in a laser +cavity and may cause the device to become unstable [36]. +From the Lorentz reciprocity theorem it follows that the scattering matrix of a reciprocal system is +symmetric provided that the amplitudes sj;in and sj;out are normalised so that any mode with unitary +amplitude carries unitary power [116, pp. 235–236 and 249]. By a reciprocal system, we understand +a system consisting of time-invariant, linear media whose material properties [cf. eq. (1.3)] satisfy the +relations [118, p. 10] +O = OT; O = OT and O˛ = OˇT: (4.4) +Since the scattering matrices from eqs. (4.2) and (4.3) are not symmetric, isolators and circulators must +by necessity contain nonreciprocal materials. +4.1.2 Routes to nonreciprocity +Among the possible ways of building nonreciprocal systems, by far the most common is the introduc- +tion of ferro- and ferrimagnetic materials. The propagation of low-amplitude microwaves in these media +placed in a sufficiently strong SEMF is usually described by considering them to have a tensorial perme- +ability of the form 2 C C 3 +O = 41 y z iz iyi 5z 1C x C z ix ; (4.5) +iy ix 1C x C y +where i and i (i = x; y; z) are proportional to the i th component of the magnetisationME induced by +the SEMF [119, p. 92; 117, p. 503]. For lossless media, O is Hermitian, so that all the parameters i and +i are purely real. Therefore the diagonal part of the tensor defined in eq. (4.5) is real and (obviously) +symmetric, while its off-diagonal part is imaginary and antisymmetric. Tensors with these properties are +called gyrotropic. +Near the ferromagnetic resonance frequency, which for sub-tesla SEMFs falls in the microwave +range, the magnitude of the off-diagonal components of O is comparable to that of the diagonal ones. +This can lead to very strong nonreciprocal effects. +4.1. Introduction 67 +At optical frequencies, the propagation of electromagnetic waves in ferro- and ferrimagnetic media +is more commonly handled by attributing them an anisotropic permittivity +2 3 igz igy +O = 4ig 5z  igx ; (4.6) +igy igx  +where gi = KMi and the parameter K describes the magneto-optical (MO) properties of the material +[35; 119, p. 236]. MO effects are usually weak; therefore the SEMF-induced perturbation of the diagonal +elements of O is commonly neglected. The real part of K is related to the specific Faraday rotation F +by +F = p +  +Ms ReK; (4.7) +  +where  is the free-space wavelength and Ms denotes the characteristic saturation magnetisation of the +medium. The imaginary part ofK, in turn, is responsible for the effect of circular dichroism. In low-loss +ferrimagnetic materials this imaginary part is often small and therefore in the rest of this chapter we shall +assume K to be real. We shall also introduce the symbol g MsK. +The most commonly used MO materials are (ferrimagnetic) synthetic garnets, of which the most +well-known is yttrium iron garnet (YIG). It is usually grown on substrates made of gadolinium gallium +garnet (GGG). The atoms of yttrium can be substituted by other elements, including bismuth and cerium. +The specific Faraday rotation of partially cerium-substituted yttrium iron garnet (Ce:YIG) at  = 1550 nm +has been measured to be 0:45ı=µm, which corresponds to g = 0:01 [120]. Bismuth iron garnet +(BIG), which is reputed to outperform Ce:YIG [121], has been found to have as large as 30ıF =µm at + = 540 nm, i.e., g = 0:22 [122]. Unfortunately Vertruyen et al. [122] do not report on measurements +of the specific Faraday rotation of BIG in the infrared range. The available data indicate that F of +this material diminishes with increasing wavelength, but the effect of this decrease on g is partially +compensated by the growth of . It seems realistic to expect that g  0:05–0:1 can be obtained at +infrared frequencies. It is also worth noting that another (non-garnet) material, europium oxide, has been +reported to have g = 0:4 in this frequency range [123]; however, its magneto-optical properties disappear +above the Curie temperature of 69K [124]. +There are a few other methods of obtaining nonreciprocal behaviour. In the microwave domain it +is possible to introduce off-diagonal imaginary components to the permittivity tensor of standard non- +magnetic metals, such as gold, by placing them in a strong SEMF. Unfortunately, this method cannot be +applied easily to optical systems because the strength of the necessary SEMF increases with frequency, +reaching several teslas in the optical range; another obstacle consists in the relatively large losses ex- +hibited by metals in this segment of the electromagnetic spectrum. Another possibility consists in using +so-called Tellegen’s media, in which the relation O˛ = OˇT does not hold; however, in known materials +of this type the magnitude of the real component of the tensors O˛ and Oˇ is very small, and therefore this +method of inducing nonreciprocal behaviour remains so far largely unexplored. Finally, instead of using +materials whose parameters do not meet conditions (4.4), one can violate the other conditions of valid- +ity of the standard Lorentz reciprocity theorem: introduce a time-dependent modulation of the material +properties of the system or employ nonlinear effects. +4.1.3 Experimental realisations of optical isolators and circulators +Bulk magneto-optical isolators A basic feature of MO materials is the phase velocity difference +between right- and left-circularly polarised plane waves propagating parallel to the magnetisation direc- +tion. As a result of this difference, the polarisation plane of a linearly polarised plane wave propagating +68 Chapter 4. Magneto-optical circulators +along the direction ofME gradually rotates; moreover, the direction of this rotation (clockwise or counter- +clockwise), when viewed in the laboratory frame, does not depend on whether the wave propagates par- +allel or antiparallel to ME [116, p. 460–464]. This phenomenon, known as Faraday’s effect, is the basis +of the operation of the archetypical “bulk” optical isolator, shown schematically in fig. 4.2(a). It consists +of a slab of a MO material sandwiched between two polarisers rotated by 45ı with respect to each other +[35]. The slab, magnetised perpendicularly to the planes of the polarisers, has thickness d such that the +polarisation plane of waves traversing the medium rotates by 45ı. Let us assume that this happens in +the clockwise direction. Then a wave coming in through polariser 1 will eventually find its polarisation +plane aligned with the axis of polariser 2. In contrast, the polarisation plane of a wave coming in through +polariser 2 will become perpendicular to the axis of polariser 1. As a consequence, the former wave will +be transmitted, whereas the latter will be absorbed. +As noted in subsection 4.1.2, the specific Faraday rotation (rotation angle per unit length) of com- +monly used MO materials is small. Therefore, optical isolators built in the way presented in the previous +paragraph need to be rather thick (d  0:1–1mm). It is, however, possible to reduce d to tens of mi- +crometres by replacing the single MO layer by a Fabry-Perot resonator composed of a stack of dielectric +and MO thin films, at the cost of a reduced operation bandwidth [125]. +Another way of reducing the thickness of a bulk isolator consists in the application of PCs. As +noted first by Figotin and Vitebsky [126], a PC with both the spatial inversion symmetry and the time- +reversal symmetry broken has a dispersion diagram that lacks inversion symmetry. From this it follows +in particular that at a given frequency a band gap can exist for waves propagating in a direction kE, but +not for those propagating in the direction kE; thus, at such a frequency the PC behaves as an isolator. An +example 1D PC of this type was presented in ref. 127. In this structure, the spatial inversion symmetry +was lifted by the presence of MO layers polarised in opposite directions (but always parallel to the layers, +unlike in Faraday rotators). Since fabrication of such layers might be difficult, Khanikaev and Steel +[128] proposed to break the inversion symmetry by the introduction of a third material into the periodic +lattice. They showed also an alternative resonator-type design, in which a single MO layer is sandwiched +between two different dielectric Bragg mirrors. In turn, the isolator proposed by Vanwolleghem et al. +[115] consists of a 2D PC composed of a lattice of holes drilled in a MO matrix magnetised in the +out-of-plane direction. The shape of holes is chosen so that the system’s spatial inversion symmetry is +lifted. +Owing to their large lateral dimensions, bulk, non-planar structures are difficult to combine with +integrated optical circuits. Therefore, in the last two decades there has been a lot of activity devoted to +the design of isolators and circulators suitable for on-chip manufacturing. Most of these structures are +intended for fabrication in MO garnet layers grown on GGG substrates, although methods of bonding +garnet layers to semiconductor (e.g., silicon) substrates have also been developed. With respect to their +geometry, the proposed devices can be divided into two broad classes: waveguide- and resonator-type +components. +Waveguide-type devices The operation of the earliest waveguide-type isolators was based on the +nonreciprocal conversion between quasi-TE and quasi-TMmodes of rib waveguides, induced by a SEMF +parallel to the waveguide axis. This phenomenon is analogous to Faraday’s effect [35]. However, it +must be noted that in this case the conversion occurs between states whose polarisation planes differ by +90ı rather than 45ı. Therefore, a 45ı-long nonreciprocal Faraday rotator must be connected in series +with a 45ı-long reciprocal rotator. The presence of this additional element, together with the necessary +polarisers at the input and output ports, complicates the fabrication procedure. The main deficiency of the +design based on Faraday’s effect, though, is that while in a bulk MO material the phase velocities of all +plane waves polarised perpendicularly toME are identical, the effective indices of quasi-TE and quasi-TM +4.1. Introduction 69 +W3 +P2 +P1 +W1 cavity +P3 +W2 +(a) (b) +ME +P nonreciprocal section2 P1 +(c) +P2 P4 +ME +nonreciprocal section +P1 P3 +(d) +Figure 4.2 Selected types of optical isolators and circulators. (a) Bulk isolator based on Faraday rotation (after +ref. 35). (b) Three-way resonator-type circulator. (c) Mach-Zehnder interferometer with one nonreciprocal arm. +(d) Nonreciprocal coupler acting as a four-port circulator. The arrows indicate the directions of energy transfer. +70 Chapter 4. Magneto-optical circulators +waveguide modes are, in general, different. For high isolation, the waveguide geometry should therefore +be adjusted to force a close match of these indices. In practice, this is not easy to obtain without post- +fabrication etch-tuning or deposition of an additional dielectric layer [129, 130]. It is worth mentioning, +however, that Dammann et al. [131] showed that the stringent requirements for index matching can be +somewhat relaxed, at the cost of incurring a modest additional forward loss, if the polarisation plane of +the input mode is rotated by 22:5ı from the vertical direction. +The drawbacks listed in the previous paragraph are eliminated in devices exploiting the difference +in the phase velocity of forward- and backward-propagating modes of MO waveguides lacking a mirror +symmetry plane parallel to their axis and placed in a SEMF perpendicular to that axis. The simplest +isolator based on this effect has the form of a Mach-Zehnder interferometer [fig. 4.2(c)] with its two +arms designed so as to introduce a nonreciprocal phase shift of 90ı and a reciprocal shift of the same +value [120, 132, 133]. For a forward-propagating wave, these shifts cancel out, so that the waves coming +from the two arms interfere constructively at the output; for a backward-propagating wave, the shifts add +up, which leads to a destructive interference. Analogous structures based on PC waveguides have also +been investigated [134]. In a different scheme, so-called nonreciprocal multi-mode imaging, a single +multi-mode waveguide is used instead of two single-mode ones [135]. +A related type of device is a four-port circulator composed of two coupled MO waveguides [fig. +4.2(d)], whose parameters are chosen so that the phase velocities of forward-propagating modes differ, +while those of backward-propagating ones match. This leads to a difference in the coupling strength of +the two pairs of modes. As a result, a forward-propagating mode stays in the original waveguide, while +a backward-propagating one gradually leaks to the neighbouring waveguide. Both rib-waveguide-based +[136] and PC-waveguide-based [137] designs have been proposed. +Another way of achieving isolation is to employ nonreciprocal absorption. This phenomenon occurs +primarily in ferromagnetic metals, which are usually highly lossy at optical frequencies. The concept +of an isolator based on the difference of the decay rates of forward- and backward-propagating waves +was originally proposed by Zaets and Ando [138] and Takenaka and Nakano [139]. The first success- +ful demonstration of such a device was made by Vanwolleghem et al. [140], who fabricated a system +containing a layer of a cobalt-iron alloy embedded in indium phosphide. Improved version of this iso- +lator were reported on in refs. 141 and 142 (the latter authors used manganese arsenide instead of the +cobalt-iron alloy). In turn, Takeda and John [123] proposed the device consisting of a MO PC waveguide +designed so that its forward- and backward-propagating eigenmodes have significantly different group +velocities. Since the slower mode experiences a longer effective optical path, in the presence of absorp- +tion its decay rate exceeds that of the faster mode. In all these designs current injection is normally used +to compensate for the undesired absorption of the forward-propagating mode. +Certain MO waveguides are characterised by a difference in the cut-off frequency of forward- and +backward-propagating modes. Therefore, in the range between these two frequencies guided-wave prop- +agation is possible in one direction only. As pointed out by the authors of refs. 143, 144 and 145, this +effect can also be used for the construction of an isolator. +Wang et al. [146] have shown that a SEMF can lift degeneracies in the band structure of high- +symmetry PCs containing materials with gyrotropic permittivity or permeability, thus leading to the +creation of band gaps. They also predicted that unidirectional waveguide modes with frequencies lying +within such band gaps can propagate along interfaces separating the just described PCs from dielectric +PCs or metals. This has been subsequently confirmed experimentally [147]. However, these effects have +so far been demonstrated only at microwave frequencies, where the permeability tensor can have off- +diagonal components with magnitude comparable with that of the diagonal ones. The MO effects are +much weaker, and it is not certain whether the band gaps generated in the optical regime will be robust +against disorder [147]. +4.1. Introduction 71 +Resonator-type devices More suitable for integration than their bulk counterparts, waveguide-type +MO devices must still be rather long in order to provide a satisfactory isolation. For instance, arm lengths +of 1mm are used in the state-of-the-art Mach-Zehnder interferometers whose fabrication was reported +on in ref. 120. According to the review of Dötsch et al. [35], this value is typical. Isolators are thus +much larger than other standard components used in integrated circuits. A possible way of miniaturising +them consists in employing resonant cavities to lengthen the time during which light interacts with the +MO material. Of course, a drawback of this approach is the reduction of the operation bandwidth of the +devices. +Circulators based on resonant cavities are commonly used in the microwave domain [117]. A typical +device of this type is composed of three identical reciprocal waveguides Wi (i = 1; 2; 3) coupled to a +single resonant cavity containing a ferrimagnetic material and, in the absence of SEMF, supporting two +degenerate localised modes of frequency !0 [fig. 4.2(b)]. In a SEMF perpendicular to the plane of the +system, this degeneracy is lifted: the modes couple and form two linear combinations corresponding to +left- and right-rotating modes with frequencies ! and !C [34, 148]. At the frequency 1.! C !C/, a2 +wave incoming from, say, waveguideW1 excites such a superposition of these two eigenmodes that they +interfere constructively in front of one output waveguide (say,W2), and destructively in front of the other +(W3). As a result, an outgoing mode with a significant amplitude appears only in waveguide W2, while +W3 is isolated from the incoming power. Analogously, owing to the three-fold rotational symmetry of +the device, energy transfer occurs in the directions W2 ! W3 and W3 ! W1. The scattering matrix +of the system is then given by eq. (4.3). If the SEMF polarisation is flipped, the direction of the energy +transfer reverses, too. +In 2005 Wang and Fan [34, 37] proposed an analogous device intended for operation at optical +frequencies, composed of a 2D PC cavity coupled to three PC waveguides. Using a model based on +the coupled-wave theory [149], they showed the bandwidth of the circulator to grow with the frequency +splitting !  j!C !j. This frequency splitting, in turn, was demonstrated to be proportional to +the integral of the out-of-plane component of the cross product of the electric fields of the cavity modes, +weighted with g, over the area of the cavity. +The authors of ref. 34 observed that in a typical PC cavity the sign of the cross product mentioned +above oscillates rapidly, leading, as a result, to a severe diminution of !. To remedy this, they pro- +posed to divide the MO material in the cavity into several domains polarised in opposite directions, thus +flipping locally the sign of g and forcing the overall sign of the integrand to be constant everywhere. +Unfortunately, the resulting structure is almost impossible to manufacture with the current technology, +since the creation of the necessary magnetic subdomains would require the application of a SEMF inho- +mogeneous on the scale of hundreds of nanometres, with the inhomogeneities precisely aligned with the +geometric structure of the cavity. +In a follow-up paper [150] the same authors presented a design of a four-port circulator composed of +two straight PC waveguides coupled to a single MO cavity with a subdomain structure determined along +analogous principles. In turn, Kono and Koshiba proposed a rib-waveguide-based circulator consisting of +a Mach-Zehnder interferometer coupled to an exterior ring [151], and, subsequently, a device similar to +that from ref. 150, but built from rib waveguides coupled to a MO microdisk [152]. Another contribution +of the latter paper was the introduction of a method of increasing the circulator’s bandwidth by including +several coupled resonators instead of just one. In all these designs, however, division of the MO material +into oppositely-polarised domains is still required. +It is worth noting that in ref. 34 a solution alternative to the introduction of magnetic domains was +also considered, namely the inclusion of a single MO rod in an standard dielectric PC. In principle, it +is possible, but it would also pose serious technological problems related to the growth of two different +materials on a single substrate and the necessity of aligning precisely the structures obtained in two +72 Chapter 4. Magneto-optical circulators +etching processes. In any case, to the best of our knowledge, none of the devices proposed in refs. +34, 37, 150, 151 and 152 has ever been fabricated. +Non-magneto-optical devices As has been noted before, introduction of ferro- and ferrimagnetic +materials is not the only method of making a system nonreciprocal. Therefore a number of isolator and +circulator designs based on the alternative approaches have also appeared in the literature. For instance, +Gallo et al. [153] described optical analogues of diodes employing nonlinear optical processes. Yu and +Fan [154] proposed an isolator based on a time-dependent modulation of the refractive index of parts of +a dielectric waveguide. In turn, Yu et al. [155] showed that the SEMF-induced gyrotropy of metals in the +microwave domain can lead to the creation of unidirectional waveguide modes at the interfaces of these +metals and dielectric PCs. +4.1.4 Outline of this chapter +The aim of the research reported on in this chapter was to design a three-port MO circulator of the +type shown schematically in fig. 4.2(b), suitable for operation in a uniform SEMF, i.e., with all the MO +material magnetised in the same direction. The plan of the text is as follows. In section 4.2 we set the +stage by extending the coupling-wave model of the device in question, introduced by Wang and Fan [34], +to include the influence of direct coupling between the three waveguides and the effect of radiation loss. +These results are used later. In section 4.3 we derive an analytical axisymmetric model of a 2D MO PC +cavity and use it to formulate a design principle of cavities exhibiting maximum frequency splitting in +the presence of a uniform SEMF. This is the key result of this chapter. +Section 4.4 is devoted to PC-based circulators. Having shown how to convert an axisymmetric cavity +designed along the rules established in section 4.3 to a component liable for integration with a periodic +lattice, we demonstrate numerical simulations of a complete circulator embedded in a 2D PC. In sec- +tion 4.5 we investigate rib-waveguide-based devices, which should be simpler to fabricate than PC-based +ones, but present design problems of their own due to imperfect in-plane light confinement. We begin by +detailing the design process of a rib-waveguide-based circulator intended for fabrication in a GGG-BIG +heterostructure. This design is based on 2D finite-element simulations with the influence of the third di- +mension taken into account by help of the effective-index approximation. In subsection 4.5.4 we report +briefly on the outcome of the first attempts to manufacture and characterise this device, made at Institut +d’Electronique Fondamentale (Orsay, France). The measurements indicate that the vertical confinement +provided by the cavity is insufficient. Therefore, in section 4.6 we describe the results of rigorous three- +dimensional (3D) simulations of axisymmetric cavities designed by the method presented in section 4.3 +and discuss various methods of improving the vertical confinement. Finally, in section 4.7 we summarise +the results of our work on MO devices. +Some of the results presented in sections 4.3 and 4.4 have appeared previously in ref. 148. +4.2 Extension of the coupled-wave model +4.2.1 Inclusion of direct coupling between waveguides +Let us consider a circulator composed of three identical single-mode waveguides, W1, W2, and W3, +weakly coupled with a resonant cavity and arranged so that the whole system has C symmetry,?3v as +shown schematically in fig. 4.2(b). We assume that in the absence of SEMF the cavity supports a pair of +degenerate orthonormal eigenmodes belonging to the unique two-dimensional irreducible representation +? The symmetry elements of the group C3v are a three-fold rotation axis and three mirror planes intersecting each other at +the angle of 120ı along this axis [80, p. 325]. +4.2. Extension of the coupled-wave model 73 +of the C3v point group and having frequency !0. They can be classified as even or odd, according to +their symmetry with respect to reflection about the axis of waveguide W1, which is assumed to lie along +the x axis. The circulator’s operation at frequency ! is described by the coupled-mode equations [149] +i!aE = .i O˝ C O /aE CDO TsEin; (4.8a) +sEout = CO sEin CDO aE; (4.8b) +where the vector aE = .a ; a /T contains the cavity mode amplitudes, sE = .s ; s ; s /Te o in 1;in 2;in 3;in and sEout = +.s ; s ; s /T1;out 2;out 3;out , the amplitudes of the in- and outgoing waveguide modes, the matrix CO describes +the direct coupling between waveguides,DO the cavity-waveguide coupling, O˝ the mode eigenfrequencies +and their coupling, and O their decay. These matrices are subject to the fundamental constraints [149] +DO ŽDO = 2O; (4.9a) +CODO  = DO : (4.9b) +Together with those following from the system’s symmetry, these constraints can be used to reduce the +number of independent parameters necessary for the characterisation of the device. We shall now con- +sider each of the matrices occurring in eqs. (4.8) in turn. +Owing to the three-fold symmetry of the circ O2ulator, the3C matrix must have the form +r t t +CO = 4t r t5 ; (4.10) +t t r +where t  jt j ei and r  jr j ei.C/ are the transmission and reflection coefficients of waveguide modes +in the absence of the cavity. If the system is lossless, as we shall assume in this subsection, we can use +the condition of unitarity of CO to express t and r as +2 cos ei i.C/ +t = p C ; r = p +e +C : (4.11)1 8 cos2 1 8 cos2 +Note that the case of no direct coupling, considered in ref. 34, corresponds to  =   and  =   . +2 2 +TheDO matrix has the general form 2 3 +d1e d1o +DO = 4d d 52e 2o ; (4.12) +d3e d3o +where dim (i = 1; 2; 3; m = e; o) describes the coupling of mth cavity mode with i th waveguide. These +coupling parameters are proportional to the values of the electromagnetic field of the modes along the +waveguide axes. Making use of the assumed symmetry of the mode fields, it can be shown that these six +parameters can be expressed in terms of a single complex co iı2 3upling constant d  jd j e : +1 0 +DO = 46 p 7d 1 3p 5 : (4.13)2 2 +1 3 +2 2 +Substituting this formula into eq. (4.9a),we obtain +1 0 +O = ; where  3 jd j2: (4.14) +0 1 4 +74 Chapter 4. Magneto-optical circulators +The second constraint, eq. (4.9b), yields +.t r/d = d: (4.15) +Noting that from eq. (4.11) we have + p2 cos e +i +i 3 cosC i sint r = e = ei. C/ = eiŒ CCarg.3 cosCi sin/C j C j (4.16)1 8 cos2 3 cos i sin +and writing d in its polar form, we obtain the expression for ı: +ı = 1 Œ.2nC 1/ C  C arg.3 cosC i sin/; (4.17) +2 +where n is an integer. Lastly, since the coupling between the cavity modes is assumed to result solely +from their interaction with the SEMF, the O˝ matrix takes the form [34] + j jO˝ !0 i V= j j ; (4.18)i V !0 +where V is the mode coupling strength. The eigenvalues of this matrix, !˙  !0 ˙ jV j, are the +frequencies of the eigenmodes of the cavity in isolation (uncoupled to waveguides). The frequency +splitting!  !C! = 2jV j is proportional to the mode coupling strength. As noted in ref. 148, it is +often convenient to write jV j as jV j = g!0v, where g is the magnitude of the off-diagonal component of +the permittivity tensor of the MO constitutive material of the cavity, and v, called reduced mode coupling +strength, depends solely on the geometry of the cavity. +Substituting eqs. (4.10), (4.11), (4.13), (4.14), (4.17), and (4.18) to the coupled-mode equations (4.8), +taking W to be the input waveguide by setting sE = .1; 0; 0/T1 in , and solving for sEout, we obtain +i   +p e i4.3 cosC i sin/ Œ i.! ! /s1;out = C e +0 + C j j ; (4.19a)1 8 cos2 3 Œ i.! ! /2 V 20 +p +i  C j j p 2 e 3 cos i sin Œ V 3 i.! !0/s2;out = +1C cosC ; (4.19b)8 cos2 2 2 3 Œ i.! !0/ C jV jpi  +p 2 e C 3 cosC i sin Œ C jV j 3 i.! !0/s3;out = C cos C j j : (4.19c)1 8 cos2 3 Œ i.! ! /2 V 20 +This solution is valid provided that the matrix i. O˝ !IO/CO , where IO denotes the 22 identity matrix, +is invertible. This is the case if +! ¤ !0 ˙ jV j and ¤ 0: (4.20) +It is easily seen than the reflectance R  js j2 and transmittances T  js j21;out i i;out (i = 2; 3) are +independent of  and  -periodic in . Moreover, +jsE .; !/j2 = jsE .  ; 2! !/j2i;out i;out 0 for i = 1; 2; 3: (4.21) +Therefore it is sufficient to study the properties of R and T in the interval  2 Œ0;  i .2 +We are primarily interested in the behaviour of the isolation factor of the circulator, defined as I  +T3=T2. Figure 4.3 shows the dependence of I on the frequency shift .! !0/ and the waveguide- +cavity coupling parameter for a few representative values of  and a fixed mode coupling strength +4.2. Extension of the coupled-wave model 75 +log10I for D = 0 log10I for D = А4 +0.2 0.2 +1 +1 +0.1 01 0.1 0 +2 -1- +0.0 -34 0.0- +-2 +-3-4 +-0.1 -111 0 -0.1 +0 +-0.2 -0.2 +0.00 0.05 0.10 0.15 0.20 0.00 0.05 0.10 0.15 0.20 +Γ Γ +log10I for D = А3 log10I for D = А2 +0.2 0.2 +1 +1 +0.1 02 0.1 +0.0 -1 0.0 4 +3 +2 +-2 +-0.1 -0.1 +-0.2 0 -0.2 +0.00 0.05 0.10 0.15 0.20 0.00 0.05 0.10 0.15 0.20 +Γ Γ +Figure 4.3 Isolation I as a function of and ! ! for  = 0,   ,  0 and   (logarithmic scale).4 3 2 +jV j = 0:1. It can be conjectured that for any ¤   infinite isolation factor can be obtained for a specific +3 +value of ! and . However, in practice one is more concerned with the maximum bandwidth B.Imin/, +defined as the maximum range of frequencies for which the isolation factor or its inverse exceeds a +predetermined threshold Imin. Figure 4.3 shows that this bandwidth is particularly large for vanishing +( =   ) and maximum ( = 0) direct waveguide-to-waveguide coupling. In these cases,pthe isolation2 +factor is anpeven function of .! !0/, and infinite isolation occurs at ! = !0 and = jV j 3 ( =   )2 +or = jV j= 3 ( = 0). It is also at these “optimum” values of that maximum bandwidth is obtained. +Figure 4.4 illustrates the frequency dependence of the transmittances and the isolation factor for + =   and 0, with set to the respective “optimum” values cited above. In the first case, I > 1 every- +2 +where: for the chosen SEMF polarisation, waveguide W3 receives more power than W2 at all operation +frequencies. In contrast, the device with  = 0 acts as a switch: transmission occurs preferentially to +Ω-Ω0 Ω-Ω0 +Ω-Ω0 Ω-Ω0 +76 Chapter 4. Magneto-optical circulators +1:00 +(a) T2 ( D  =2) +0:75 T3 ( D  =2) +0:50 +0:25 +0:00 +1:00 +(b) T2 ( D 0) +0:75 T3 ( D 0) +0:50 +0:25 +0:00 +104 +3 (c) I ( D  =2)10 +1=I ( D 0) +102 +101 +100 +101 +0:50 0:25 0:00 0:25 0:50 +! !0 +Figpure 4.4 (a) Frequency dependence of the transmittapnces T2 and T3 for a circulator with  =   and =2jV j 3. (b) Same for a circulator with  = 0 and = jV j= 3. (c) Frequency dependence of the isolation factor I +of the two circulators. In both cases jV j = 0:1. +waveguide W2 for j! !0j < jV j and to W3 outside this frequency range. In consequence, the band- +width of the system with maximum coupling ( = 0) is inferior to that of the one with no direct coupling +( =   ) regardless of the chosen threshold Imin. However, fig. 4.4(c) shows that the difference in band-2 +width becomes less and less pronounced as Imin grows: for very high isolation factors, the bandwidths +of both structures are virtually indistinguishable. +The conclusions from the previous two paragraphs, based in part on an analysis of plots made for +several specific cases, can also be reached in a rigorous manner. We shall first derive the values of +! and at which the isolation factor or its inverse becomes infinite. By definition of I , this will be +the case provided that exactly one of s2;out and s3;out vanishes. Rewriting the condition s2;out = 0 as +(Re s2;out = 0 and Im s2;out = 0) and using assumption (4.20), we obtain +p +3ŒjV j2 C jV j 3 .! ! 20/  cos .! p!0/ sin = 0; (4.22a) + Œ3.! !0/ cosC . jV j 3/ sin = 0: (4.22b) +One solution of these equations, ! = !0 ˙ jV j and = 0, is obviously incompatible with assumption +(4.20). The other can be obtained by solving eq. (4.22b) for ! and substituting the result into eq. (4.22a). +Isolation factor Transmittance Transmittance +4.2. Extension of the coupled-wave model 77 +This yields +C 2 sin.2/ +p +j j 1 4 cos +2 p +! = !0 C V 3 and = C jV j 3: (4.23)1 8 cos2 1 8 cos2 +Comparing the expressions (4.19b) and (4.19c) for s2;out and s3;out, one immediately sees that the con- +dition for s3;out = 0 is given by formula (4.23) with jV j replaced by jV j. Noting further that, by +definition (4.14), cannot be negative, we arrive at the following conclusion. +The isolation factor I of a lossless circulator is infinite if and only if +j j 1 C 2 sin.2/ +p +j j 1 4 cos +2 p +cos < ; ! = !0 C V 3 and = C jV j 3: (4.24a)2 1 8 cos2 1 8 cos2 +The factor I is zero if and only if +j j 1 2 sin.2/ +p +j j 4 cos +2 1 p +cos > ; ! = !0 C V 3 and = C jV j 3: (4.24b)2 1 8 cos2 1 8 cos2 +Restricting to the interval Œ0;   , we see that jcosj < 1> if and only if <>   . It should be noted that2 2 3 +for  =   there exist no solutions of eq. (4.22) compatible with assumption (4.20). +3 +It is convenient to introduce the reduced frequency +Q  ! !0 ˙ 2 sin.2/ +p 1 +! 3 for jcosj > N 3. The spirit of this approach is similar to that advocated in ref. 160. In contrast to the +method based on Poynting flux integration, it allows to calculate not only the transmittances T 2j  jtj j +(j = 2; 3), but also the reflectance R  jr j2 and the amount of power lost to non-guided modes, +1 .RC T2 C T3/. +Figure 4.11 shows a juxtaposition of the values of the isolation coefficient I  T2=T3 obtained with +the two above methods for the circulator from fig. 4.10. Clearly, there is an excellent match between the +two sets of data. Therefore in the following we shall limit our discussion to the results obtained with the +second, more powerful approach. +Figure 4.12(a) presents the frequency dependence of the transmittances T2 and T3 of the same cir- +culator, along with the total power passed to guided modes, P  R C T2 C T3. It can be seen that in +the neighbourhood of !0 the amount of power not accounted for by the guided modes increases to about +10%. We believe this power deficit to be primarily a consequence of radiation occurring from the cavity, +and possibly also from the waveguides, into free space. These losses might conceivably be reduced if the +thickness of the cladding were increased. +!a=2 c +4.4. Photonic-crystal-based circulators 87 +dclad +P3 +2r +Waveguide W h3 +: : Q +3 +: N +: : +: : : : +: : :: : : +a .N 1/a +Q3 +2 +Q3 +: : : 1 +: : : +: : : +: : : +: : : +Q1 Q1 Q1   +1 2 : : : N +: : : +: : : +: : : +: : : +Q2 +1 +Q2Waveguide W1 2 +: : :: : : +: : : : +Point source : : +: : : +Q2 +N +Waveguide W2 P2 +p  +3 + dw a2 +Figure 4.10 Schematic of the PC circulator described in the text. +: : : +: : : +: : : +: : : + + +: : :  +: : : +: : : +: : : +: : : +: : : + + + +88 Chapter 4. Magneto-optical circulators +100 +Method 1 +Method 2 +10 +1 +0:3110 0:3115 0:3120 0:3125 0:3130 +!a=2 c +Figure 4.11 Comparison of the isolation I of the circulator from fig. 4.10 calculated by integrating the Poynt- +ing fluxes through ports P2 and P3 (“method 1”, crosses) and by fitting the data obtained in multiple-scattering +simulations with formulas (4.45) (“method 2”, circles). +1:00 100 +(a) +0:75 +T2 +T3 +0:50 10 +P +I +0:25 +0:00 1 +0:3110 0:3115 0:3120 0:3125 0:3130 +!a=2 c +1:00 10000 +(b) +0:75 1000 +T2 +T3 +0:50 100 +P +I +0:25 10 +0:00 1 +0:3115 0:3120 0:3125 0:3130 0:3135 +!a=2 c +Figure 4.12 Frequency dependence of the transmittances T2 and T3, isolation I , and the sum P  RCT2CT3 +of the circulator shown in fig. 4.10 with the vertically hatched holes shifted by (a) dh = 0 and (b) dh = 0:038a +in the radial direction with respect to their original position. All the quantities were calculated by fitting the data +obtained in multiple-scattering simulations with formulas (4.45). +T2, T3, P T2, T3, P +Isolation I +I +I +4.4. Photonic-crystal-based circulators 89 +# x=a y=a r=a # x=a y=a r=a # x=a y=a r=a +1 0.000 0.000 0.92 32 5.922 8.705 0.30 63 8.422 13.035 0.30 +2 0.810 1.403 0.40 33 6.000 0.000 0.30 64 8.500 6.062 0.30 +3 1.403 0.810 0.40 34 6.000 1.732 0.30 65 8.500 7.794 0.30 +4 1.620 0.000 0.40 35 6.000 3.464 0.30 66 8.500 9.526 0.30 +5 1.965 1.702 0.30 36 6.000 5.196 0.30 67 8.500 11.258 0.30 +6 2.452 2.548 0.30 37 6.000 6.928 0.30 68 8.922 13.901 0.30 +7 2.457 0.851 0.30 38 6.422 9.571 0.30 69 9.000 6.928 0.30 +8 2.600 0.000 0.30 39 6.500 0.866 0.30 70 9.000 8.660 0.30 +9 2.967 3.426 0.30 40 6.500 2.598 0.30 71 9.000 10.392 0.30 +10 3.001 1.733 0.30 41 6.500 4.330 0.30 72 9.000 12.124 0.30 +11 3.422 4.375 0.30 42 6.500 6.062 0.30 73 9.500 7.794 0.30 +12 3.433 0.849 0.30 43 6.500 7.794 0.30 74 9.500 9.526 0.30 +13 3.496 2.595 0.30 44 6.922 10.437 0.30 75 9.500 11.258 0.30 +14 3.733 0.000 0.30 45 7.000 0.000 0.30 76 9.500 12.990 0.30 +15 3.922 5.241 0.30 46 7.000 1.732 0.30 77 10.000 8.660 0.30 +16 3.995 1.730 0.30 47 7.000 3.464 0.30 78 10.000 10.392 0.30 +17 4.000 3.464 0.30 48 7.000 5.196 0.30 79 10.000 12.124 0.30 +18 4.422 6.107 0.30 49 7.000 6.928 0.30 80 10.000 13.856 0.30 +19 4.451 0.857 0.30 50 7.000 8.660 0.30 81 10.500 9.526 0.30 +20 4.500 2.598 0.30 51 7.422 11.303 0.30 82 10.500 11.258 0.30 +21 4.500 4.330 0.30 52 7.500 0.866 0.30 83 10.500 12.990 0.30 +22 4.867 0.000 0.30 53 7.500 2.598 0.30 84 10.500 14.722 0.30 +23 4.922 6.973 0.30 54 7.500 4.330 0.30 85 11.000 10.392 0.30 +24 5.000 1.732 0.30 55 7.500 6.062 0.30 86 11.000 12.124 0.30 +25 5.000 3.464 0.30 56 7.500 7.794 0.30 87 11.000 13.856 0.30 +26 5.000 5.196 0.30 57 7.500 9.526 0.30 88 11.500 11.258 0.30 +27 5.422 7.839 0.30 58 7.922 12.169 0.30 89 11.500 12.990 0.30 +28 5.500 0.866 0.30 59 8.000 5.196 0.30 90 12.000 12.124 0.30 +29 5.500 2.598 0.30 60 8.000 6.928 0.30 91 12.000 13.856 0.30 +30 5.500 4.330 0.30 61 8.000 8.660 0.30 92 12.500 12.990 0.30 +31 5.500 6.062 0.30 62 8.000 10.392 0.30 93 9.422 14.767 0.17 +Table 4.3 Cartesian coordinates .x; y/ and radii r of the circular air holes making up the optimised circulator +shown in fig. 4.13. For brevity, only the holes lying in the sector 0    60ı are included. +The maximum isolation obtained with the circulator from fig. 4.10, I  50, is somewhat unsatis- +factory. According to the coupled-wave model from section 4.2, low maximum I may be caused by +a suboptimal coupling level between the cavity and the waveguides. This level can be controlled by +fine-tuning the positions of the holes in the neighbourhood of the cavity. We have found that by shifting +the holes hatched vertically in fig. 4.10 by dh = 0:038a in the radial direction, the maximum isolation +can be boosted to about 2600, as shown in fig. 4.12(b). The isolation I stays above 100 in a frequency +band of width B.100/ = 0:00011  2 c=a, which corresponds to 81GHz for the operation wavelength + = 1300 nm. The level of power losses to radiative modes, 1 P , does not change appreciably with +respect to the case from fig. 4.12(a). Figure 4.13 shows the map of the magnetic field excited by a point +source placed close to the entrance of waveguideW1 of the “optimised” circulator with dh = 0:038a at +frequency ! = 0:3124  2 c=a, where maximum isolation is obtained. The standing-wave ratio in the +input waveguide is very small, which reflects the good quality of the match between the waveguides and +the cavity. Table 4.3 lists the positions and radii of the air holes making up the optimised circulator. +90 Chapter 4. Magneto-optical circulators +1:0 +20 +0:8 +10 +0:6 +0 +0:4 +10 +0:2 +20 +0:0 +20 10 0 10 +x=a +Figure 4.13 Magnitude of the magnetic fieldHz in the circulator with dh = 0:038a, excited by a point source +of frequency ! = 0:3124  2 c=a. +4.5 Rib-waveguide-based circulators +4.5.1 Introduction +In section 4.4 we have shown how an axisymmetric cavity designed along the rules derived in section 4.3 +can be adapted for embedding in a PC lattice and coupling with PC waveguides. One could well ask, +however, whether the introduction of a periodic lattice is strictly necessary. At first sight, the answer is +no. Having the form of a circular Bragg grating, the cavity is by itself well isolated from the surrounding +medium (at least in-plane), so there is little to be gained by embedding it additionally in a PC exhibiting +a band gap. The PC waveguides can also be straightforwardly replaced by rib waveguides with constant +cross-section, whose operation is based on the index-guiding mechanism. To obtain a working circulator, +however, one needs also to ensure the appropriate level of coupling between the localised cavity and +waveguide modes and to minimise the power lost to free space during the energy transfer between these +two families of modes. The latter objective is much easier to fulfil in a PC-based circulator, which +operates in the band gap of the periodic lattice surrounding all the functional elements. Nevertheless, in +this section we shall study a class of non-PC-based systems that allow to achieve the two goals mentioned +above, at least to a certain degree. +The general geometry of the structured to be considered is shown in fig. 4.14. The depicted circulator +consists of a resonant cavity, composed of nf full and ns split rings with inner and outer radii determined +by the procedure described in section 4.3, and three identical waveguides of width dwg. The distance +from the centre of the cavity to the ends of the waveguides is wg, while the widths of the slits in the split +rings are denoted by dn with n = nfC 1, nfC 2, : : : , nfC ns. The rings and waveguides are made of a +y=a +jHz j +4.5. Rib-waveguide-based circulators 91 +dwg +d6 d5 d4 d3 +rwg +Figure 4.14 Geometry of an example rib-waveguide-based circulator with nf = 2 full and ns = 4 split rings. +MO material with permittivity 2 3 +h ig 0 +O = 4 5h ig h 0 (4.46) +0 0 h +and are embedded in an isotropic medium with permittivity l. +The level of coupling between the cavity and waveguide modes, and hence the circulator’s perfor- +mance, will of course depend on the values of all the geometrical parameters, which should therefore +be optimised. The space spanned by them is rather large, and it is not possible to scan it exhaustively. +Therefore our optimisation of the presented structure has been somewhat heuristic. We have chosen the +material parameters as  = .2:25/2h = 5:0625, l = 1 and g = 0:1; the quoted value of h corresponds +approximately to the effective index of the fundamental s-polarised guided mode of a planar waveguide +composed of a BIG layer of thickness 340 nm sandwiched between GGG and air. The waveguide width +dwg was fixed to 250 nm. The radii of the rings, listed in table 4.4, were determined with the procedure +described in section 4.3 to ensure the existence of a pair of cavity modes with the azimuthal order l = 1 +at the wavelength  = 1300 nm. +92 Chapter 4. Magneto-optical circulators +Ring number Inner radius (nm) Outer radius (nm) +1 381 539 +2 847 998 +3 1309 1457 +4 1772 1919 +5 2236 2382 +6 2700 2846 +7 3165 3310 +Table 4.4 Radii of the high-index rings of the cavity with  = .2:25/2h = 5:0625 and l = 1 supporting a +resonant mode with azimuthal order l = 1 at wavelength  = 1300 nm. +With the chosen value of g, the relative frequency splitting of the cavity is!=!0 = 2gv = 0:00175. +From eq. (4.27), in the absence of losses the optimum value of =!0 is 0.00151, i.e., the quality factor +Q  !0=.2 / describing the cavity-waveguide coupling should be Q = 330. The quality factors of +the chosen cavity with 3 and 4 rings are 163 and 829, respectively. Therefore one can expect that the +waveguides of an optimally designed circulator should end somewhere close to the third innermost ring— +or possibly even inside it, since the coupling to waveguides is doubtlessly less efficient that to the whole +surrounding free space. +The total number of rings necessary for ensuring a prescribed level of peak transmission Tmin could +in principle be estimated from eq. (4.30): for instance, for Tmin = 0:9 the quality factor Ql describing +radiation loss should be greater than 6430. This is already ensured by a cavity composed of 6 rings, +whose quality factor reaches 21,140. However, the quality factors of cavities with split outer rings will +necessarily be smaller than of those with full rings; therefore, a larger number of rings might be necessary +to ensure a 90-percent efficiency. In our calculations, we restricted our attention to systems with at most +7 rings. +The results of the optimisation process will be reported on in subsection 4.5.3. In the meantime, +we shall describe the numerical method used to analyse these systems and evaluate the accuracy of +calculations. +4.5.2 Numerical calculations +The calculations of the transmission through the circulators studied in this section, and shown schemati- +cally in fig. 4.14, have been performed with the finite-element method (FEM) using the RF module of the +COMSOL program. In contrast to the multiple-scattering method used to analyse PC-based circulators in +ref. 148, FEM can easily handle structures composed of scatterers with complex (especially elongated) +shapes. On the other hand, unlike that method, it requires a finite computational domain. Since the +system shown in fig. 4.14 is, in principle, infinite, it must be truncated for the sake of FEM calculations. +Problems involving light scattering by finite objects are routinely handled with FEM by letting the +computational domain consist of a finite region enclosing the objects in question and surrounded by +a perfectly matched layer (PML) of finite thickness, which ideally behaves as a perfect non-reflecting +absorber [53]. In our case, the situation is complicated by the presence of infinite waveguides; the +scatterer to be modelled obviously cannot fit within any finite contour. To circumvent this problem, we +construct the computational domain in the way shown in fig. 4.15. The region surrounded by the dashed +line is a fragment of the physical system shown in fig. 4.14. The parts of its boundary lying “far” from +the waveguide ends are covered with PMLs of thickness dPML. We have used standard PMLs adapted +4.5. Rib-waveguide-based circulators 93 +Circulator n n  (nm) d (nm)  (ıf s wg  cone ) +C1 3 3 1250 1570 — +C2 3 4 1240 1770 — +C3 3 4 1210 — 35.1 +Table 4.5 Geometrical parameters of the circulators analysed in the text. The ring radii are listed in the first +.nf C ns/ rows of table 4.4. +for cylindrical coordinates, implemented in COMSOL by means of the coordinate transform? +!7  in sPML.1 i/; (4.47) +dPML +where  is the radial coordinate measured form the centre of the cavity, in denotes the radius of the +inner PML boundary, and sPML, called the PML strength, influences the field decay rate inside the PML +[161, p. 44]. On the other hand, the electromagnetic fields on the segments Pn (n = 1; 2; 3) perpendicu- +lar to the waveguides are constrained to be a superposition of the incoming and outgoing guided modes +of the corresponding waveguides, which are assumed to be single-mode. The profile of these modes is +calculated analytically and normalised to unitary power, and the amplitude of the incoming mode is set +to unity on P1 and to zero on P2 and P3. Physically, these constraints correspond to the assumption +that all the radiative waveguide modes excited by the cavity decay before reaching the ports Pn. Math- +ematically, they reduce to Robin’s boundary conditions and are implemented as COMSOL’s matched +boundary conditions. On the remaining part of the computational domain’s boundary (solid line in fig. +4.15) perfect-electric-conductor boundary conditions are imposed. The domain is divided into triangular +Lagrangian elements of order p. The mesh density is controlled by fixing the mpaximum allowed size +of individual elements in each subdomain with constant permittivity  to hmax= , where hmax is a +constant. The mesh in areas with higher permittivity is made finer, since the fields is these regions are +expected to vary faster. +In our calculations we are primarily interested in the isolation factor I = T2=T3, where T2 and T3 +are the powers transmitted through ports P2 and P3. We can see that the numerically calculated value +of I of a given circulator at a fixed free-space wavelength  depends on the following six parameters: + maximum element size in air, hmax, + element order, p, + PML thickness, dPML, + PML strength, sPML, + length of the part of the waveguides extending past the outermost ring, dsep, + port height, dport. +To determine the values of these parameters sufficient for obtaining satisfactory accuracy, we have stud- +ied the influence of their variation on the isolation I of a particular circulator, denoted henceforth as C1, +whose parameters are listed in the first row of table 4.5. +We tested first the dependence of I on hmax and p for fixed values of the remaining parameters. +Figure 4.16(a) shows the values of I obtained for p = 2 and five different values of hmax, whereas +fig. 4.16(b) presents the dependence of I on the element order p with hmax fixed to 500 nm. We see +that the convergence with increasing p is much faster than with decreasing hmax. Therefore in future +calculations we have taken hmax = 500 nm and p = 5. +? In COMSOL simulations the ei!t convention for time-harmonic dependence is used, opposite to that employed here. +94 Chapter 4. Magneto-optical circulators +PML +P3 +PML +dsep dPML +dport P1 +P2 +PML +Figure 4.15 Geometry of the domain used in FEM calculations. +400 +(a) (b) +300 +200 +100 +0 +500 250 125 62:5 2 3 4 5 +hmax (nm) p +Figure 4.16 Influence of the finite-element expansion parameters, hmax and p, on the calculated value of the +isolation I of circulator C1. The parameters related to the truncation of the computational domain are fixed to +dsep = 5000 nm, dPML = 600 nm, sPML =  and dport = 2250 nm. The wavelength  = 1299:5 nm was chosen to +lie in the proximity of the maximum of I./, but not exactly at it. (a) Convergence of I with decreasing maximum +element size in air, hmax, at fixed element order p = 2. (b) Convergence of I with increasing element order p at +fixed hmax = 500 nm. +I +4.5. Rib-waveguide-based circulators 95 +86 +84 +82 +sPML D  +sPML D 2 +80 +0 250 500 750 1000 +dPML (nm) +Figure 4.17 Convergence of the isolation I of circulator C1 with increasing PML thickness dPML. Two PML +strengths, sPML =  and 2, are considered; the wavelength  = 1299:5 nm. The other parameters are fixed as +hmax = 500 nm, p = 5, dsep = 5000 nm and dport = 2250 nm. +(a) (b) +Figure 4.18 Change of the mesh structure in the PML with dPML increasing from (a) 400 nm to (b) 500 nm. +Note that in the former case the mesh of the PML consists of two interleaving rows of triangles, whereas in the +latter case the number of rows increases to four. +We proceeded to the study of the influence of the PML parameters, dPML and sPML. Figure 4.17 +shows the dependence of I on the PML thickness for two different PML strengths, sPML =  and 2. +It can be seen that the values obtained with sPML =  (which is COMSOL’s default) are very stable +with respect to dPML: the difference between the maximum and minimum value of I does not exceed +0.15%. On the other hand, the I.dPML/ curve corresponding to sPML = 2 has a noticeable jump +between dPML = 400 and 500 nm. This jump is due to a change in the mesh structure: as illustrated in +fig. 4.18, for dPML = 400 nm the mesh in the PML region consists of two rows of triangles, while for +dPML = 500 nm two more rows appear. For dPML  600 nm the isolation factor obtained with both +PML strengths are very similar; moreover, the subsequent appearance of another pair of rows, occurring +between dPML = 800 and 900 nm, does not have any discernible effect on the I.dPML/ curves. All +in all, the detailed choice of the PML parameters does not seem very important for the accuracy of the +calculations. Therefore, we continue to take dPML = 600 nm and sPML = . +We studied next the sensitivity of I to dsep. The I.dsep/ curves shown in fig. 4.19, corresponding +to two different wavelengths, exhibit irregular oscillations of amplitude roughly equal to 3% of the mean +value. We interpret them as stemming mainly from the interference of the fundamental waveguide mode +with slowly decaying radiative modes excited by the cavity. Another culprit might be the mesh modifi- +cations induced by changes of the location of the domain’s boundary. Elimination of these oscillations +would be difficult without considerable enlargement of the computational domain, which would neces- +I +96 Chapter 4. Magneto-optical circulators +88 +(a)  D 1299:5 nm (b)  D 1300:5 nm +21:0 +87 +86 +20:5 +85 +84 20:0 +3000 4000 5000 6000 7000 8000 3000 4000 5000 6000 7000 8000 +dsep (nm) dsep (nm) +Figure 4.19 Dependence of the isolation I of circulator C1 on the value of dsep for two different wavelengths  +located in the neighbourhood of a maximum of I./. The other parameters are fixed as hmax = 500 nm, p = 5, +dPML = 600 nm, sPML =  and dport = 2250 nm. +sarily lead to a drastic increase of the time of calculations. Therefore, we decide to leave unchanged the +value dsep = 5000 nm taken previously. +The choice of dport is definitely the most difficult. In principle, the value of dport=2 should corre- +spond to the distance from the waveguide axis at which the magnitude of the field of the guided mode +becomes comparable to that of the radiative modes excited by the cavity. Unfortunately, it is not easy to +determine this distance a priori. The value dport = 2250 nm taken so far corresponds to the width of a +port at whose ends the magnetic field of the waveguide mode with  = 1300 nm decays to 1% of its +maximum value. +Figure 4.20 shows the dependence of I on dport at four different wavelengths. For ease of compar- +ison, the plots have been normalised to the values of I obtained for dport = 3000 nm. The curves have +several interesting features. First, the isolation factor varies very rapidly for small values of dport. This +is not surprising: for such small port lengths, the incident field is not represented accurately, since the +profile of the waveguide mode is severely truncated in the direction perpendicular to the waveguide axis. +Second, for large port lengths we observe a steady, seemingly linear decay of I . In fact, a look on the +plots of the field excited on these long ports reveals that in the port regions lying far from the waveguide +axis the field shape does not resemble that of the guided mode any more; this effect is especially pro- +nounced in the isolated waveguideW3. This indicates that the optimum port length might be close to the +value of dport at which the linear decay emerges; however, this value varies with the wavelength. Third, +the dependence of I on dport is visibly strongest at  = 1300:0 nm, which is the wavelength closest to +the peak of I./. This indicates that the maximum value of I./ observed for a given circulator might +be strongly influenced by the choice of dport. Unfortunately, this proves to be the case: the maximum +isolation factors of circulator C1 obtained for dport = 1700, 2000 and 2250 nm are 2130, 3560 and 6140, +respectively. The extreme values differ, then, by nearly a factor of three. On a more positive note, the +bandwidth B.Imin/, a quantity much more important from the experimental point of view, turns out to +be significantly less sensitive to the choice of port length, as long as Imin is not too large. For instance, +the range of wavelengths in which C1 provides an isolation factor better than 100 has width 0:610, 0:615 +and 0:618 nm according to simulations performed with the three values of dport quoted previously. We +conclude that while the maximum isolation factors calculated with the present technique do not have +absolute significance, and can at most be used for the purposes of comparison between different struc- +tures, the bandwidths are robust against changes of the domain truncation parameters. Lacking reliable +guidelines on the selection of the optimum port length, we stick to the value chosen previously, i.e., +dport = 2250 nm. +I +I +4.5. Rib-waveguide-based circulators 97 +2:0 +1:5 +1:0 + D 1299:0 nm + D 1299:5 nm +0:5 + D 1300:0 nm + D 1300:5 nm +0:0 +0 1000 2000 3000 +dport (nm) +Figure 4.20 Dependence of the isolation I of circulator C1 on the value of dport for four different wavelengths  +located in the neighbourhood of a maximum of I./. The other parameters are fixed as hmax = 500 nm, p = 5, +dPML = 600 nm, sPML =  and dsep = 5000 nm. +It is worth noting that some authors [137, 162] have proposed a different method of handling infinite +waveguides in FEM calculations. In their approach, PMLs surround the whole computational domain, +including the waveguide outlets, and the incident waveguide mode is introduced into the system by im- +posing special boundary conditions on a cross-section of the input waveguide lying inside the domain. +As an alternative, one could also divide the system under study in two parts: one comprising the input +waveguide, and the other, the cavity with the output waveguides. In the latter, the finite-element expan- +sion would continue to stand for the total electromagnetic field. In the former, however, the expansion +would represent only the scattered field, i.e., the total field minus the incident waveguide mode. The +latter could be introduced into the system by means of appropriate boundary conditions imposed on the +junction of the two subdomains. The combined structure could then be completely surrounded in PMLs, +as shown in fig. 4.21. +We have not tested any of these solutions, mostly owing to time constraints. However, they could be +implemented in future if the accuracy limits of the approach followed so far become a serious issue. +4.5.3 Geometry optimisation +Having fixed most of the geometrical parameters of the circulator in the way described at the end of +subsection 4.5.1, we were essentially left with the problem of optimising the values of dn and wg. +For the sake of simplicity, we initially focused on structures with dn independent from n, i.e., with +waveguides enclosed in rectangular “slits” of width d . The bandwidth proved a rather cumbersome +objective function, since it is nonzero only for structures already rather close to optimum. Therefore, +the reservations from subsection 4.5.2 notwithstanding, we chose the maximum isolation factor as the +objective function, hoping that circulators with large values of this parameter would also be characterised +by a large bandwidth. +Figure 4.22(a) shows the geometry of the best structure that we have found, called C2 in the follow- +ing. It has 3 full and 4 split rings. The slit width d = 1770 nm and the waveguide ends are located at +wg = 1240 nm from the cavity centre, so that the waveguides cross the outermost full ring. For ease +of reference, the values of all the geometrical parameters of C2 are listed in table 4.5. This circulator +offers maximum isolation of 3590, and the wavelength dependences of T2, T3 and I are shown in fig. +4.22(b). Clearly, the curves are fairly symmetric with respect to the central wavelength  = 1300:0 nm, +which indicates that the direct coupling between waveguides is insignificant. Figure 4.22(c) shows the +map of the magnetic field at  = 1300:0 nm. At this wavelength, 88% of the input power is transmitted +I=I.dport D 3000 nm/ +98 Chapter 4. Magneto-optical circulators +PML +Subdomain 2 +Subdomain 1 +Figure 4.21 Alternative technique of domain truncation. In subdomain 1, the electromagnetic field is repre- +sented by the sum of the field of the incident waveguide mode (assumed known) and the scattered field expanded +on a finite-element basis. In subdomain 2, the finite-element basis is used to expand the total field. Electromagnetic +continuity conditions are imposed on the interface separating the two subdomains (dashed line). +to waveguide 2; the rest is not reflected, but mainly lost to the surrounding free space. Far from the +peak, the amount of these losses can exceed 50%. This behaviour contrasts with that of the PC circu- +lator, where almost 100% of the input power remains in the waveguide system due to the quasi-perfect +isolation provided by the surrounding periodic lattice. The 20-dB bandwidth B.100/ of circulator C2 is +0.729 nm. +The grey curves in fig. 4.22(b) show the transmittance curves of circulator C2 as predicted by the +coupled-wave model with radiation losses taken into account, presented in subsection 4.2.2. The values +of the parameters !0, !, and l were found by fitting the expressions for T2 and T3 obtained from +eqs. (4.26) to the values calculated numerically. The Levenberg-Marquardt algorithm was used as the +fitting procedure. The best fit was obtained for parameters corresponding to 0  2 c=!0 = 1299:9 nm, +  2 c!=!20 = 2:3 nm,Q  !0=.2 / = 370 andQl  !0=.2 l/ = 5730. Clearly, there is a good +match between the theoretical and numerical curves; its quality would probably be further improved by +taking into account the direct coupling between waveguides, which causes the slight asymmetry of the +numerical plots. The quality factor related to losses, Ql, is significantly lower than that of an isolated +cavity with 7 full rings, which is as large as 107,000. This is obviously due to the presence of slits. On +4.5. Rib-waveguide-based circulators 99 +1:00 10000 +T2 +0:75 T 10003 +T2 (fit) +0:50 T 1003 (fit) +I +0:25 10 +0:00 1 +1295:0 1297:5 1300:0 1302:5 1305:0 + (nm) +(a) (b) +(c) +Figure 4.22 (a) Geometry of circulator C2. (b) Wavelength dependence of the transmission (left axis) and +isolation (right axis) of this circulator. (c) Magnitude of the magnetic field in the circulator at the wavelength + = 1300:0 nm, corresponding to the maximum isolation. The waveguide mode is incident from the left. +the other hand, the position of the ends of the waveguides (just inside the third innermost ring) is in good +accord with the predictions made at the end of subsection 4.5.1. +We have found this device fairly tolerant to variations of the slit width d ; figs. 4.23(a)–(b) show the +plot of the maximum isolation and bandwidth of C2 when this parameter is varied. It can be seen that the +bandwidth stays above 0.5 nm in a 300-nm-wide range of d . The constraints on wg are more stringent: +as shown in fig. 4.23(c), the corresponding range of wg is only about 40 nm wide. +The performance of this structure changes rather abruptly when the number of rings is modified. For +instance, if the seventh ring is removed, the maximum isolation decreases to only 140 and the bandwidth +to 0.386 nm. However, it is possible to improve these figures by readjusting the slit widths and the +Transmission T2, T3 +Isolation I +100 Chapter 4. Magneto-optical circulators +0:75 +(a) (c) +0:50 +0:25 +0:00 +10000 +(b) (d) +1000 +100 +10 +1200 1400 1600 1800 2000 1200 1220 1240 1260 1280 +d (nm) rwg (nm) +Figure 4.23 Tolerance of the maximum isolation Imax and the bandwidth B.100/ of circulator C2 to perturba- +tions of the parameters (a)–(b) d and (c)–(d) wg. +1:00 10000 +T2 +0:75 T 10003 +I +0:50 100 +cone 0:25 10 +0:00 1 +1295:0 1297:5 1300:0 1302:5 1305:0 + (nm) +(a) (b) +Figure 4.24 (a) Geometry of a circulator with conical slits surrounding the waveguides. The values of the vari- +ous parameters have been chosen to match those of circulator C3. (b)Wavelength dependence of the transmission +(left axis) and isolation (right axis) of this circulator. +position of the waveguide ends: for wg = 1250 nm and d = 1570 nm (10% less than in the 7-ring case) +Imax reaches 2140 and the bandwidth 0.603 nm. +It is interesting to note that both for 6 and 7 rings the optimum angular length of the removed sectors +of the outermost ring is almost the same: 34ı. This led us to test the performance of a second class +of structures, in which the outer rings are truncated along radial lines instead of ones parallel to the +waveguides, so that the latter are enclosed by conical rather than rectangular air slits, as illustrated in fig. +4.24(a). We found the optimum cone aperture  ıcone to be 35:1 , which is close to the value obtained +in the simulations of the first class of structures (with dn independent from n). The optimum position +of the waveguide end, wg = 1210 nm, is also only slightly different from the original one. More +importantly, the maximum isolation and bandwidth decrease much less (from 3300 to 700 and from +0.770 to 0.708 nm, respectively) when the seventh ring is removed. This relative insensitivity to the +details of the geometrical structure of the exterior region of the device is the behaviour that one would +intuitively expect from a well-designed circulator; therefore, structures with conical slits seem closer to +the ideal that those with rectangular ones. Figure 4.24(b) shows the wavelength dependence of T2, T3 +and I of the optimum 7-ring circulator with conical slits, referred to as C3. Its parameters are listed in +table 4.5. +Max. isolation Bandwidth (nm) +Transmission T2, T3 +Isolation I +4.6. Simulations of three-dimensional axisymmetric cavities 101 +(a) (b) +Figure 4.25 Microphotographs of a rib-waveguide-based circulator etched in a BIG layer grown on a GGG sub- +strate (courtesy of L. Magdenko and B. Dagens, Institut d’Électronique Fondamentale, Orsay, France). (a) Tung- +sten mask before etching. (b) Complete circulator after etching. +4.5.4 Fabrication +Our collaborators from Institut d’Électronique Fondamentale (Orsay, France) have developed a tech- +nique of fabricating magnetophotonic structures in BIG thin films [163]. The films used in experiments, +supplied by the GEMAC team from Versailles, France, were grown on GGG substrates by pulse layer +deposition. The circulators were fabricated by inductively coupled plasma ion etching the BIG layer in a +mixture of boron trichloride and argon, with a nanostructured tungsten layer used as a mask. An example +circulator fabricated in this way is shown in fig. 4.25. +To evaluate the optical properties of the manufactured structures, a series of measurements of the +power transmitted to the two output waveguides was made. The transmittances to the two output branches +were found not to be completely equal. However, reversal of the polarisation of the applied SEMF +brought no discernible change of the transmission levels. Apparently, then, the observed difference +between T2 and T3 was due to fabrication imperfections rather than to nonreciprocal effects. +4.6 Simulations of three-dimensional axisymmetric cavities +4.6.1 Evaluation of possible three-dimensional geometries +Motivation We strongly suspected that the incorrect operation of the fabricated circulators was due to +the fact that their design had been based solely on two-dimensional simulations. While we had attempted +to take the three-dimensional (3D) nature of the true physical system into account by using the effective- +index model to find the material properties of the high- and low-index regions of the simulated structures, +this was evidently not enough. Indeed, the effective-index description is known to give erroneous results +for high-contrast systems, such as those considered in this chapter [164]. In any case, its accuracy can +only be evaluated by comparing its predictions with results of rigorous 3D calculations. +Owing to the time requirements of full-blown 3D simulations, which would be necessary to anal- +yse complete circulators consisting of a cavity coupled to waveguides, we decided to implement first a +method allowing to calculate the eigenmodes of axisymmetric 3D cavities. In this case it is possible to +profit from the knowledge of the azimuthal dependence of the eigenmodes to restrict the computational +mesh to a single meridional (z) plane of the cavity. Our calculations were made with the finite-element +method, described in detail in section 5.3. +High-contrast cavities We began by considering the simplest type of structures, in which the rings +are etched in a layer of BIG with thickness dBIG, sandwiched between a GGG substrate and air, as shown +102 Chapter 4. Magneto-optical circulators +in fig. 4.26(a). We set dBIG = 340 nm and took the refractive indices of BIG and GGG to be nBIG = 2:51 +and nGGG = 1:97. The effective index of the unetched areas was calculated to be 2.25, while that of +the etched rings was set to the index of air, nair = 1. The radii of the rings were determined with the +procedure described in section 4.3, with the target wavelength  = 1300 nm. For future reference, we +shall denote this just described geometry with the symbol G1. +Very soon it became apparent that cavities of type G1 behaved very badly in 3D. In fact, they do +not seem to support any well-localised modes near the design wavelength  = 1300 nm. This turns +out to be easily explicable: sufficiently far from the cavity centre, a circular Bragg grating can be well +approximated by a linear grating with period d = 1.n1Cn10 1 /, where n0 and n1 denote the refractive4 +indices of etched and unetched areas. If d is larger than =.2nGGG/, all Bloch eigenmodes of the grating +will leak into the GGG substrate [165, p. 203]. Unfortunately, this is the case with G1-type structures: +d = 469 nm > =.2nGGG/ = 330 nm. +Low-contrast cavities In view of the failure of the effective-index description of structures of type +G1, we have studied a handful of geometries liable to be approximated better by the effective-index +model. They were proposed by L. Magdenko and B. Dagens (Institut d’Electronique Fondamentale, +Orsay, France). +The first structure that was considered is shown in fig. 4.26(b). In this case, the BIG layer is left +unetched, and the necessary effective-index contrast between successive rings is introduced by etching +an additional high-index layer deposited on top of BIG. This geometry has distinct theoretical and ex- +perimental advantages. First, owing to the continuity of the BIG layer, it supports everywhere a locally +guided mode. This lets us avoid the problem that the effective index, defined with the help of the prop- +agation constant of the fundamental guided mode of a given region, is in fact undetermined for regions +where no guided modes exist. Conventionally, these areas are attributed the index of the sub- or super- +strate but, as noted by Hammer and Ivanova [164], this choice is not based on any rigorous arguments. +In the case of the geometry from fig. 4.26(b), the effective index is well-defined everywhere and one can +hope that this will improve the accuracy of the effective-index description. +From the experimental point of view, the structure in question has the advantage that it does away +with the necessity of etching the BIG layer. This process, while already successfully demonstrated [163], +remains less well developed than the nanostructuration of materials such as silicon or indium phosphide. +On the other hand, the presence of a MO material both in the high- and low-index rings will necessarily +diminish the SEMF-induced mode coupling strength, owing to the cancellation effect described in ref. +148. A possible solution consists in depriving the uncovered areas of BIG of their MO properties, which +can be experimentally achieved by ion implantation. +The structure shown in fig. 4.26(b) is characterised by the refractive index nspl of the supplemen- +tary layer, its thickness dspl, and the thickness of the BIG layer, dBIG. We have taken nspl = 3:50, +corresponding to the index of amorphous silicon around the wavelength  = 1300 nm. The choice of +dspl and dBIG was motivated by two competing goals. On one hand, the supplementary layer had to +be sufficiently thick to provide an appreciable contrast of the effective index of the etched and unetched +areas. On the other hand, dspl could not be chosen too large for fear of generating a second s-polarised +guided mode in the unetched region and of displacing too large a fraction of the guided mode’s energy +away from the BIG layer, which would diminish the MO properties of the system. As a compromise, +the two thicknesses were taken as dspl = 80 nm and dBIG = 280 nm. The effective indices of the etched +and unetched regions were then calculated as 2.19 and 2.50, and the fraction of energy of the guided +mode of the unetched region contained in BIG was found to be 0.48. For convenience, the just described +geometry will henceforth be referred to as G2. +In another type of structures, shown in fig. 4.26(c), the etched BIG layer of thickness dBIG is covered +4.6. Simulations of three-dimensional axisymmetric cavities 103 +z +nair +nBIG dBIG + +nGGG +(a) +z +nair +nspl dspl +nBIG dBIG + +nGGG +(b) +z +nsup +nBIG dBIG + +nGGG +(c) +Figure 4.26 Schematics of 3D structures of types (a) G1, (b) G2, and (c) G3 and G4 (which differ only with +the value of nsup). +with a solid superstrate with refractive index nsup close to that of GGG. In this way, the index contrast +between the etched and unetched areas is lessened and one can expect the effective-index approximation +to be more accurate. We considered mainly systems with nsup = 1:97 (exactly equal to the refractive in- +dex of GGG) or nsup = 1:90 (refractive index of silicon nitride) and chose dBIG to be 330 nm. Structures +with these parameters will be called G3 and G4 in the following. The effective indices of their unetched +regions were calculated to be 2.275 and 2.282, respectively, whereas those of the etched areas were set +to min.nGGG; nsup/, i.e., 1.97 and 1.90. +Table 4.6 summarises the results obtained for a handful of structures. Three cavities, designed for +azimuthal orders l = 1, 4 and 10, were tested for each of the geometry types G2, G3 and G4. In addition, +for cavities of type G2 two distributions of the MO coefficient g were investigated. In one series of +simulations, the whole BIG layer was assumed to be uniformly magnetised, so that g was taken to be +0.1 throughout that layer. In the other, the areas of BIG not covered with silicon were assumed to be +deprived of their MO properties and, consequently, attributed g = 0. For ease of reference, these two +variants of geometry G2 will be called G2(a) and G2(b). +The magnitude the relative frequency splitting !=!0 obtained in 3D simulations does not differ +drastically from that predicted by 2D ones. The observed deviation is easily explicable by the fact that +not the whole vertical profile of the unetched areas has MO properties. Anyway, the coupling strength +of the eigenmodes of most of the cavities listed in table 4.6 exceeds that of the 2D high-contrast cavity +104 Chapter 4. Magneto-optical circulators +Type l C  !=!0 (3D) !=!0 (2D) QC Q Qavg +G2(a) 1 1:27779C 0:00618i 1:27833C 0:00617i 0:00042 — 103 104 103 +4 1:27546C 0:00607i 1:27633C 0:00611i 0:00068 — 105 104 105 +10 1:27564C 0:00582i 1:27666C 0:00588i 0:00080 — 110 109 109 +G2(b) 1 1:27892C 0:00616i 1:27727C 0:00618i 0:00129 0:00166 104 103 104 +4 1:27722C 0:00603i 1:27466C 0:00615i 0:00200 0:00286 106 104 105 +10 1:27764C 0:00570i 1:27475C 0:00600i 0:00227 0:00342 112 106 109 +G3 1 1:28103C 0:00461i 1:27926C 0:00498i 0:00138 0:00224 139 128 134 +4 1:28102C 0:00355i 1:27829C 0:00391i 0:00213 0:00356 180 164 172 +10 1:28032C 0:00179i 1:27724C 0:00206i 0:00241 0:00408 357 310 334 +G4 1 1:28550C 0:00722i 1:28366C 0:00773i 0:00143 0:00207 89 83 86 +4 1:28675C 0:00606i 1:28403C 0:00662i 0:00212 0:00348 106 97 102 +10 1:28710C 0:00401i 1:28415C 0:00454i 0:00229 0:00411 160 141 151 +Table 4.6 Results of 3D calculations of the eigenmodes of cavities with geometries G2(a), G2(b), G3 and G4. +The symbols  and C denote the wavelengths of the modes with azimuthal order l and l . In addition to the +relative frequency splitting !=!0 of the modes of the 3D cavities, calculated as .ReC Re/=Œ.ReC C +Re/=2, the values obtained for the corresponding infinite 2D cavities are also given; they are calculated as in +section 4.3. The symbolsQ˙ = .Re˙/=.2 Im˙/ stand for the quality factors of the modes with order l and l . +Finally,Qavg is defined as .QC CQ/=2. +presented at the end of section 4.3. This can be attributed to the decrease of the effective-index contrast +between etched and unetched areas, and is in accord with the observation from ref. 148 that the reduced +coupling strength of a 2D high-contrast cavity can be augmented three times by making its core of +demagnetised BIG instead of air. +As opposed to the values of!=!0, well preserved in the 2D-to-3D transition, the quality factors of +the 3D cavities are on average ten times smaller than the quality factors obtained with 2D calculations +(related only to the in-plane confinement). The geometry that fares best, G3, provides barely Q = 334. +In addition, even the small deviation from symmetry induced by changing the superstrate’s refractive +index from 1.97 to 1.90 decreases the quality factor by about 50%. +Figures 4.27, 4.28 and 4.29 show the maps of the z components of the magnetic field and the cross +product EEe  EEo of the electric fields of the even and odd eigenmodes of the G2-, G3- and G4-type +cavities designed for the azimuthal order l = 10, in the absence of SEMF. Comparison of figs. 4.28(a) and +4.29(a) gives testimony to the substantial increase of out-of-plane radiation losses in the cavity of type +G4 with respect to that of type G3: the field in the asymmetric cavity features a prominent beam directed +into the substrate, which is absent from that of the symmetric cavity’s eigenmode. The field in the G2- +type cavity from fig. 4.27 is well localised in the vertical direction, and the low quality factor of this +mode seems to stem from the excitation of the fundamental p-polarised mode of the highly asymmetric +GGG-BIG-air multilayer, as evidenced by the relatively large amplitude of the Ez field component on +the plot from fig. 4.27(b). +Both !=!0 and Q typically increase with l (the exception is the geometry G2, for which little +change ofQ is observed). This effect is further illustrated in fig. 4.30(a), which shows the l-dependence +of !=!0 and Q of circulators of type G3. Figure 4.30(b), in turn, presents the dependence of these +parameters on the number of high-index rings, N , with l fixed to 10. It can be seen that !=!0 and Q +reach their asymptotic values around N = 25. +To sum up, the results listed in table 4.6 attest that the SEMF-induced coupling strength of the +eigenmodes of structures G2, G3 and G4 is sufficient to cause a substantial frequency splitting; even in +4.6. Simulations of three-dimensional axisymmetric cavities 105 +1:00 +(a) jHz j +1000 0:75 +0:50 +0 +0:25 +1000 +0:00 +1:00 +(b) jEz j=Z0 +1000 0:75 +0:50 +0 +0:25 +1000 +0:00 +1:0 +(c) eEz  .EEe EEo/ +1000 0:5 +0:0 +0 +0:5 +1000 +1:0 +0 2000 4000 6000 + (nm) +Figure 4.27 (a) Magnitude of the z component of the magnetic field of the eigenmodes of the G2-type cavity +designed for l = 10, in the absence of SEMF. (b) Magnitude of the z component of the electric field divided +by Z0. The colour scale is the same for parts (a) and (b). (c) The z component of the cross product EE Ee  Eo of +the electric fields of the even and odd modes of the same cavity, which occurs as the integrand in the expression +for the SEMF-induced mode coupling strength [34]. +the unfavourable case of geometry G2 with uniformly MO BIG the frequency splitting of high-l modes +is fairly large. However, the quality factor of these cavities is unsatisfactory. The cavity design must +clearly be further improved to make the resulting devices usable in practice. +4.6.2 Towards cavities with higher quality factor +There are several routes that might potentially lead to an increase ofQ. First, one could augment further +the azimuthal order of the cavity mode; fig. 4.30(b) lets us expect that this will lead to a rise of Q. +Indeed, we have verified that the G3-type cavity designed for l = 40 has Q = 1760. This growth of Q +is achieved, however, at the expense of a significant enlargement of the cavity volume, which may not +always be desirable. +z (nm) z (nm) z (nm) +106 Chapter 4. Magneto-optical circulators +1:00 +(a) jHz j +1000 0:75 +0:50 +0 +0:25 +1000 +0:00 +1:0 +(b) eE z  .EEe EEo/ +1000 0:5 +0:0 +0 +0:5 +1000 +1:0 +0 2000 4000 6000 8000 + (nm) +Figure 4.28 (a) Magnitude of the z component of the magnetic field of the eigenmodes of the G3-type cavity +designed for l = 10, in the absence of SEMF. (b) The z component of the cross product EE  EEe o of the electric +fields of the even and odd modes of the same cavity. The plot of jEzj=Z0 has been omitted because this field +component is very small. +1:00 +(a) jHz j +1000 0:75 +0:50 +0 +0:25 +1000 +0:00 +1:0 +(b) eE z  .EE EEe o/ +1000 0:5 +0:0 +0 +0:5 +1000 +1:0 +0 2000 4000 6000 8000 + (nm) +Figure 4.29 Same as fig. 4.28, but for the G4-type cavity. +z (nm) z (nm) z (nm) z (nm) +4.6. Simulations of three-dimensional axisymmetric cavities 107 +600 0:0025 +(a) +400 0:0020 +200 0:0015 +Q +!=!0 +0 0:0010 +0 5 10 15 +Bessel order l +400 0:002500 +(b) +0:002475 +300 +Q +0:002450 +!=!0 +200 +0:002425 +100 0:002400 +10 15 20 25 30 +Number of rings N +Figure 4.30 Dependence of the relative frequency splitting !=!0 and quality factor Q of G3-type cavities +(a) on the azimuthal order l with fixed number of high-index rings N = 20 and (b) on the number of rings N with +fixed l = 10. +Second, one might look for ways of improving the accuracy of the effective-index approximation. As +we have mentioned before, the effective index of regions supporting no guided modes is not rigorously +defined. We have tested the influence of changing the value taken for the effective index of the etched +areas of G4-type cavities from 1.90 to 1.97 and found that it brought about a 20-percent growth of Q. +However, the wavelength of the cavity modes shifted by 2.5 nm further away from the design value of +1300 nm, which indicates that the increase of Q was not due to an improvement in the accuracy of +the effective-index description. We have also tried the variational effective-index method proposed by +Hammer and Ivanova [164], but found it to degrade both the quality factor and the match between the +predicted and true value of the frequency of cavity modes. +Third, one should certainly profit from the extensive research on the optimisation of PC cavities done +in the course of the last decade. As discussed in the review by Lalanne et al. [166], the approaches to this +subject proposed so far can be divided into two large classes. +Some authors [167, 168] treat a PC cavity as a system consisting of many “elementary” cells of size +comparable to the lattice constant of the surrounding PC. In each such cell, they expand the field in the +basis of the cell’s Bloch eigenstates. Often, each cell supports only one guided mode (one that does not +radiate energy in the vertical direction). The radiation loss from the cavity is then regarded as resulting +from the scattering of the guided modes into radiative ones at the intercell boundaries. To reduce this +loss, the geometry of each cell must then be adjusted so as to improve the match between the profiles of +the guided modes of successive cells. +Unfortunately, this approach cannot be directly applied to axisymmetric structures, since it relies +on the idea of expanding the field in each cell in its Bloch basis. Maxwell’s equations in cylindrical +Quality factor Q Quality factor Q +Relative shift !=!0 +Relative shift !=!0 +108 Chapter 4. Magneto-optical circulators +coordinates are not invariant with respect to translations in the radial direction, however, even if the +permittivity and permeability are; therefore the Bloch’s theorem does not carry over to systems periodic +in the radial direction. On the other hand, sufficiently far from the z axis, an approximate version of +the Bloch’s theorem can certainly be formulated. The results from a recent paper [169] indicate that this +approximate formalism is fairly accurate even in small distances from the axis. Thus, it might be possible +to apply the ideas from refs. 167 and 168 to axisymmetric systems. This will be the subject of future +work. +Other researchers [170–173] base their cavity optimisation procedures on the link between the cav- +ity’s radiation pattern and the Fourier transform of its electromagnetic field. The quality factor Q of a +cavity mode can be written asQ = .Re!/U=P , where ! is the mode’s frequency, U stands for the time- +averaged energy stored in its electromagnetic fields, and P is the rate of energy loss [166, 172]. Treating +the cavity as an aperture antenna, one can relate the out-of-plane energy loss rate P? to the 2D Fourier +transforms of the  and  field components on two planes, one lying in the substrate and the other in +the superstrate of the cavity [174, 175]. Englund et al. [172] have gone one step further, rewriting P? in +terms of the z components of EE andHE : +X Z qZ k k2 k2 C k2    x y 1 +P? = dkx dky C jE +Q .k 2 Q 2z x; ky/j C jHz .kx; ky/j ; +8 2 2C 2 2 k2 k2 Z2k k +=sub;sup x y +k x y  +(4.48) +where Z + p  +p +.0 /=.0 / is the (absolute) impedance of medium  (substrate or superstrate), +k k0  and Z Z +Q 1 1 1F .k ; k /  dx dy F .x; y; z / ei.kxxCkyy/z x y z  (4.49) +2  1 1 +denotes the 2D Fourier transform of the field Fz on the plane z = z . The plane z = zsub can be taken +to lie just below the interface of the substrate and the guiding layer, and the plane z = zsup, just above +the boundary between the guiding layer and the superstrate. It is important to note that the integrals in +eq. (4.48) run only over the light cones. One concludes that to obtain a high-Q cavity it is necessary to +sweep all the peaks of the Fourier transforms EQ andHQ away from the circle k2 C k2  k2z z x y  [171]. +In the axisymmetric case it is possible to simplify eq. (4.48). It can be shown [176, section 9.3] that +the 2D Fourier transform of a function f .; /  f ./ eill is +fQ.k ; /  fQ .k / eil l  ; (4.50a) +where Z +Q 1fl.k/  d  fl./Jl.k/ (4.50b) +0 +is the l th-order Hankel transform of f ./. The symbols .; / and .k; / denote the polar coordinates +in the direct and reciprocal space. Using eqs. (4.50) one can bring eq. (4.48) into the form +X Z qk k2 k2 Z k    1 +P? = +  dk jEQz .k 2/j C jHQ 2z .k/j : (4.51) +4  k Z20  +=sub;sup  +Figure 4.31(a) shows the squared norms of the Hankel transforms Z1 EQz;sub.k/ and HQz;sub.k/sub +of the clockwise-rotating eigenmode of a G2-type cavity designed for l = 10 and comprising as much +as 40 high-index rings (to eliminate border effects related to insufficient lateral size). The plane zsub is +4.6. Simulations of three-dimensional axisymmetric cavities 109 +taken to lie 1 nm below the top boundary of the substrate. The curves obtained with 3D FEM simulations +are juxtaposed with that stemming from Hankel-transforming theHz field of the eigenmode of the corre- +sponding 2D cavity (this mode is purely p-polarised, so the Ez component vanishes). Clearly, the peaks +of all the curves are fairly well localised outside the light cone, whose boundary, k = 1:97k0, is marked +with a vertical line. Remarkably, the areas under the curves Z2 jEQ .k /j2z;sub  and jHQz;sub.k/j2 ob-sub +tained with 3D calculations are roughly equal, while the Ez component should vanish according to 2D +simulations. This confirms our earlier conclusions that the low quality factor of the eigenmodes of G2- +type cavities stems from the excitation of a p-polarised guided mode of the multilayer rather than from +radiation losses. +The corresponding plots obtained for G3- and G4-type cavities are shown in figs. 4.31(b) and (c). +While the transforms calculated in the 2D case are virtually indistinguishable, there is a marked differ- +ence in the 3D case: the transform ofHz of the mode of the G4-type cavity extends considerably further +into the light cone than that corresponding to the G3-type structure. This is reflected in the lower quality +factor of the mode of the former cavity, as evidenced in table 4.6. In contrast to what we saw in the +previous paragraph, for G3- and G4-type cavities the part played by the Ez component is completely +negligible. +In all the three systems considered here, the refractive index of the substrate is at least equal to that +of the superstrate. Hence, radiation loss into the substrate dominates over that into the superstrate and, +for brevity, we omit the discussion of the Hankel transforms of the fields on z = zsup. +Advocates of the Fourier-transform-based optimisation of PC cavities have demonstrated that the +quality factor–mode volume ratio of an eigenmode of a given structure can be increased by adjusting its +geometry so as to lessen the decay rate of the mode field near the centre of the cavity. This narrows the +peak of the Fourier transform, so that, provided that the centre of the peak lies outside the light cone, the +integral of the squared norm of the Fourier transform over the light cone diminishes. This design rule +has been summarised as “light should be confined gently in order to be confined strongly” [173]. +Unfortunately, it is not easy to establish a link between the geometry of the cavity and the shape of its +eigenmode field. Englund et al. [172] have derived an approximate formula for the permittivity profile of +a cavity supporting a mode with a prescribed spatial dependence. However, they assumed that the field +near the centre of the cavity could be approximated by that of a PC waveguide mode close to cut-off, +i.e., with a very flat dispersion curve. For axisymmetric structures, this assumption is not met: near the +z axis, the cavity mode could possibly be approximated with a guided mode of the multilayer, whose +dispersion relation is in general not flat. Moreover, the formula derived by Englund et al. is based on the +application of the perturbation theory rather far from its domain of validity—to describe discontinuous +high-amplitude perturbations of permittivity. Therefore, its predictions might conceivably be not always +accurate. +The last method that can be tried is the adjustment of ring dimensions based on a purely numerical +optimisation algorithm. We have made some limited attempts at this sort of optimisation, parametrising +the cavity geometry by the seven variables rc, ah, bh, ch, al, bl and cl, defined as follows. The symbol +rc denotes the radius of the central low-index hole. The widths of the high-index rings are taken to be +C bh C cwh;n = hah with n = 1; 2; : : : ; (4.52a) +n n2 +whereas these of the low-index rings are set to +b += C lwl;n al C C +cl +C with n = 1; 2; : : : : (4.52b)n 1 .n 1/2 +These particular functional forms were chosen because of their ability of approximating well the ring +width distributions generated by the procedure from section 4.3. As the optimisation routine, we used +110 Chapter 4. Magneto-optical circulators +10:0 +(a) +7:5 +5:0 jHQ 2z j , 2D calc. +jHQ j2z , 3D calc. +2:5 +Z2jEQ j20 z , 3D calc. +0:0 +10:0 +(b) +7:5 +5:0 jHQ j2z , 2D calc. +jHQ 2z j , 3D calc. +2:5 +Z2jEQ j20 z , 3D calc. +0:0 +10:0 +(c) +7:5 +5:0 jHQ j2z , 2D calc. +jHQz j2, 3D calc. +2:5 +Z2 Q 20 jEz j , 3D calc. +0:0 +0 1 2 3 +k=k0 +Figure 4.31 Squared norms of the Hankel transforms of the eigenmode fields of the cavities of types (a) G2, +(b) G3 and (c) G4 designed to support modes with l = 10 at wavelength  = 1300 nm. In each plot, the Hankel +transforms ofHz and Ez of the eigenmodes of the respective 3D cavities, calculated at the plane lying 1 nm below +the substrate-BIG interface, are juxtaposed with the Hankel transform of the Hz field of the eigenmode of the +corresponding 2D cavity. The vertical line at k = 1:97k0 marks the boundary of the light cone of the substrate. +the trust-region-based gradient-free NEWUOA algorithm by Powell [177]. The objective function was +initially taken as   +! ˛ ˇ +  Qavg (4.53) +!0 +with the exponents ˛ and ˇ chosen heuristically as ˛ = 2 and ˇ = 1 to favour cavities with a large +frequency splitting. Later it was found necessary to prevent a drift of the wavelength of the cavity +eigenmodes far away from the design value of  = 1300 nm; this was done by multiplying  by an +additional penalty factor + 1 1p +1C e . (4.54)min/ 1C e .max/ +with = 0:2 nm1, min = 1250 nm and max = 1350 nm. At the start of the optimisation algorithm, +the seven parameters were set so as to mimic the ring width distribution obtained with the procedure +described in section 4.3. +jHQ j2 Z2jEQ j2 jHQ j2 Z2jEQ j2 jHQ j2 Z2jEQ j2z , 0 z z , 0 z z , 0 z +4.7. Conclusions and perspectives 111 +0:5 (a) +0 +0:5 (b) +0 +0 2 4 6 8 + (nm) +Figure 4.32 Geometry of (a) the original and (b) the numerically optimised cavity G3-type cavity designed for +the azimuthal order l = 10. The shaded areas are the cross-sections of BIG rings, which are immersed in a material +with refractive index 1.97. +We have not yet tested extensively the above optimisation algorithm, applying it so far only to a few +special cases. One of them was the 20-ring G3-type cavity designed to support a mode with l = 10 +at the wavelength  = 1300 nm, whose geometry is shown in fig. 4.33(a). According to table 4.6 the +average quality factor of the counter-propagating modes of this cavity is 334 and the relative frequency +splitting, 0.00241. Using the just described procedure to optimise the radii of the rings, we arrived at +the geometry shown in fig. 4.32(b). The average Q factor of the resonant mode of this structure is as +large as 2630. One can suspect this Q factor to be limited by in-plane rather than out-of-plane losses, +since it is already higher than the Q factor of the corresponding 20-ring 2D cavity, 2156. Remarkably, +the observed improvement of the mode confinement does not occur at a cost of deterioration of the MO +properties of the cavity, whose relative frequency splitting, 0.00260, is even slightly larger than that of +the original structure. Figure 4.33 shows the map of the z components of the magnetic field and of the +cross product EE Ee  Eo of the eigenmodes of this cavity, as well as the squared norms of the Hankel +transformsZ1 EQz;sub.k/ andHQz;sub.k/. Comparing these curves with those from fig. 4.31(b), it cansub +be seen that the peak of jHQ 2z;sub.k/j of the optimised structure is indeed more tightly localised outside +the light cone of GGG. +4.7 Conclusions and perspectives +The research presented in this chapter was founded on the algorithm for the design of z-invariant axi- +symmetric MO cavities that in the presence of a uniform SEMF exhibit maximum frequency splitting +(section 4.3). In sections 4.4 and 4.5 we put forth a number of designs of three-port circulators incorpo- +rating such cavities and operating according to the model presented in section 4.2. Lastly, in section 4.6, +we studied the properties of the proposed cavities in a 3D setting, using full 3D simulations. +In the course of this work, we increasingly tried to take into account the 3D nature of real integrated +systems, in which the components are etched in BIG thin layers grown on GGG substrates. Initially, +we performed purely 2D calculations, using bulk indices of the constituent materials. To some extent, +this approach was justified: the algorithm from section 4.3 was based on 2D considerations, and it was +necessary to compare the performance of the cavities designed by its help against those proposed before +[34, 37, 150], which were also evaluated in a purely 2D setting. +At the next stage, we attempted to take into account the multilayer structure of the experimental sys- +tem with the effective-index approximation, which is fairly widely used to bring the results of 2D simu- +lations of, in particular, PC-slab-based devices closer to reality. The design of the rib-waveguide-based +circulators, reported on in section 4.5, was done in this way. However, measurements of the transmittance +z (nm) z (nm) +112 Chapter 4. Magneto-optical circulators +1:00 +(a) jHz j +1000 0:75 +0:50 +0 +0:25 +1000 +0:00 +1:0 +(b) eE z  .EEe EEo/ +1000 0:5 +0:0 +0 +0:5 +1000 +1:0 +0 2000 4000 6000 8000 + (nm) +7:5 +(c) +5:0 +2:5 jHQ j2z , 3D calc. +Z2jEQ j20 z , 3D calc. +0:0 +0 1 2 3 +k=k0 +Figure 4.33 (a) Magnitude of the z component of the magnetic field of the eigenmodes of the optimised G3- +type cavity designed for l = 10, in the absence of SEMF. (b) The z component of the cross product EEe  EEo of +the electric fields of the even and odd modes of the same cavity. (c) Squared norms of the Hankel transforms of +the eigenmode fieldsHz and Ez at the plane located 1 nm below the surface of the substrate. +through fabricated components of this type revealed that the behaviour of the 3D cavity differed strongly +from the predictions of the 2D model. It became apparent that full 3D simulations were inevitable. +The results of these calculations, summarised in section 4.6, proved that resonant cavities designed by +help of the effective-index approximation do have good MO properties: the SEMF-induced splitting of +the frequencies of their eigenmodes is indeed spectacular. However, the cavities suffer from substantial +radiation losses in the vertical direction. The outcome of the various attempts at increasing the quality +factor of these cavities, presented in subsection 4.6.2, points to the conclusion that 3D simulations are, +unfortunately, all but unavoidable. They are required not only in the somewhat “brute-force” numerical +optimisation of ring widths described at the end of subsection 4.6.2, but also in the approach based on +Bloch’s theorem, which we have not tested, but which definitely looks promising. +Regardless of the way in which a cavity is designed, it must still be integrated with waveguides. The +results from section 4.5, while based on the effective-index approximation and therefore inaccurate, do +z (nm) z (nm) +jHQ j2 Z2jEQ j2z , 0 z +4.7. Conclusions and perspectives 113 +provide some insight into the problem of cavity–rib-waveguide coupling. In particular, they confirm that +the optimum location of the waveguide ends can be approximately determined by analysing the quality +factors of cavities with a varying number of rings. Therefore, if the distance from the cavity centre to +the ends of 3D waveguides is figured out with this method, some nonreciprocal isolation should be ob- +servable in experiment. Clearly, though, some numerical fine-tuning of this distance will be necessary +to optimise the maximum isolation and the operation bandwidth of the device. Three-dimensional sim- +ulations of a complete circulator would be prohibitively slow. However, as a workaround one might try +the method of Andreani and Gerace [178], who successfully calculated the diffraction losses of eigen- +modes of PC slabs by expanding the fields in terms of a few lowest guided modes of a specific multilayer +(dependent on the structure of the slab) and including the radiation losses in a perturbative way. + +Chapter 5 +Numerical methods +5.1 Multiple-scattering method for systems containing gyrotropic media +In section 4.4 we presented results of numerical simulations of the scattering of electromagnetic waves +by 2D PCs composed of circular cylinders etched in a MO, and thus anisotropic, matrix. The multiple- +scattering method used to make these calculations was originally derived for isotropic materials [38]. +Here we show that it can be extended with very little effort to the case of gyrotropic media. +The most important assumption of the method, which is described in detail in refs. 38, 39 and 40, +is that the field Fz (standing for Ez for s-polarised waves and Hz for p-polarised ones) in the medium +surrounding the scatterers is governed by the Helmholtz equation +r2F C k2n2z 0 Fz = 0; (5.1) +where k0  !=c, ! denotes the frequency, and n is the refractive index of the medium in question. +It can be shown that in each circular annulus surrounding a particular scatterer Si and intersecting no +other scatterers the field F can be decomposed into three parts: F srcz zi , the incident field coming directly +from the source, F inc, the field scattered towards S by other scatterers, and F scattzi i zi , the field scattered +by Si itself. Each of these fields can be writtenXin the form of a Fourier-Bessel series: +F src. ;  / = asrcJ .k n / eimizi i i im m 0 i ; (5.2a) +mX2Z +F inc. ;  / = aincJ .k n / eimizi i i im m 0 i ; (5.2b) +mX2Z +F scatt. ;  / = b H .1/.k n / eimizi i i im m 0 i ; (5.2c) +m2Z +where src, inc and are constant coefficients, and .1/aim aim bim Jm.x/ Hm .x/ denote the Bessel and Hankel +functions of the first kind, and .i ; i / are polar coordinates defined with respect to the centre of the +annulus. With the so-called Graf’s theorem, a link can be established between the series (5.2) expressed +in coordinate systems associated with different scatterers. This makes it possible to write F inczi in terms +of F scattzj for all j ¤ i . Moreover, a linear relation exists between the Fourier-Bessel coefficients of the +sum F src C F inc and those of F scattzi zi zi . With aEi and bEi denoting the column vectors of the coefficients +.asrc C aincim im / and bim, respectively, this relation can be expressed as +bEi = SOiaEi ; (5.3) +where SOi is conventionally called the scattering matrix of Si . Its entries can be obtained by imposing +the electromagnetic boundary conditions on the inner surface of the annulus mentioned above. Their +115 +116 Chapter 5. Numerical methods +derivation is particularly simple for a homogeneous isotropic circular scatterer with refractive index ni ; +in this case, the total field Fz inside Si can alsoXbe written as a Fourier-Bessel series, +F int. ;  / = c J .k n  / eimizi i i im m 0 i i ; (5.4) +m2Z +and since the surface of Si coincides with a constant coordinate line of the polar coordinate system +anchored at the centre of Si , field matching can be done analytically and in fact the matrix SOi becomes +diagonal. +We shall now show that Maxwell’s equations describing wave propagation in a homogeneous medium +can also be reduced to a Helmholtz equation if the medium has gyrotropic permittivity and permeability +of the form 2 3 2 3 +t ig 0 t ig 0 +O  4i  05 and O  4i  0 5g t g t : (5.5) +0 0 z 0 0 z +We shall focus on p polarisation; the results for s polarisation can be obtained from the duality principle +[65, p. 72–73]. Substituting eqs. (5.5) into Maxwell’s equations for p polarisation, eqs. (1.7), and writing +the differential operators explicitly in Cartesian coordinates, we get +@Ey @Ex = i!0zHz; (5.6a) +@x @y +@Hz = i!0.tEx C igEy/; (5.6b) +@y +@Hz = i!0.igEx C tEy/: (5.6c) +@x +Solving the two last equations for the components of EE, we obtain +  +1 @H += i z +@Hz +Ex g C t ; (5.7a)i! .20 g 2t / @x @y  +1 @Hz +Ey = t C +@H +i zg : (5.7b) +i! 2 20.g  / @x @yt +Substitution of these expressions into eq. (5.6a) yields +2 2  2@ Hz C @ Hz C k20 t g zHz = 0: (5.8)@x2 @y2 t +Thus, the fieldHz fulfils a Helmholtz equation with an “effective refractive index” +n0  Œ. 2= / 1=2t g t z : (5.9) +It is also possible to derive analytically the expression for the entries of the scattering matrix SO of a +homogeneous gyrotropic cylinder S of radiusR embedded in a gyrotropic matrix. We need to impose the +conditions of continuity of the components of the electric and magnetic fields tangential to the surface +of S , i.e.,Hz and E . The fieldHzXon the exterior side of the surface of S is given by +H ext.R; / = Œa J .k n0 R/C b H .1/.k n0 R/ eimz n m 0 ext n m 0 ext ; (5.10a) +m2Z +5.1. Multiple-scattering method for systems containing gyrotropic media 117 +and on the interior side, X +H int.R; / = c J .k n0 R/ eimz n m 0 int I (5.10b) +m2Z +in these formulas, the subscripts “int” and “ext” label quantities measured on the interior and exterior +side of the surface of S . Equations (5.7) imply that +  +1 @Hz +E = t C +ig @Hz +; (5.11) +i!0.2 2g / @r r @t +hence +X +ext 1 .mg;ext=R/Jm.k0n +0 R/C  k 0 0 0ext t;ext 0nextJm.k0nextR/E .R; / = ami! 2 20 +m2Z g;ext t;ext +.1/ 0 C 0 .1/0 0 C .mg;ext=R/Hm .k0nextR/ t;extk0nextHm .k0n R/b ext imm e ; (5.12a)2 2g;ext t;ext + 1 +X .mg;int=R/J 0m.k0n R/C  0t;intk0n J 0 .k n0 R/ +Eint +m 0 +.R; / = c int int int im m e ; (5.12b)i! 2 20 +m2Z g;int t;int +where the symbols 0 and .1/0Jm.x/ Hm .x/ denote the derivatives of the Bessel and Hankel functions at x. +To condense the notation, we can rewrite eqs. (5.10) and (5.12) in the form +X X +H ext.R; / = .AHa C BHb / eim ; H intz m m m m z .R; / = CH c imm m e ; (5.13a) +mX2Z mX2Z +Eext.R; / = .AEa C BEb / eim ; Eint m m m m  .R; / = CE imm cm e ; (5.13b) +m2Z m2Z +where the definitions of the constant coefficients AHm etc. can be obtained straightforwardly by com- +paring the above expressions with eqs. (5.10) and (5.12). Imposing now the conditions H extz .R; / = +H int.R; / and Eext.R; / = Eintz   .R; / for all  2 Œ0; 2 / and noting that, owing to the orthogonality +of the functions eim (m 2 Z) on this interval, the sums over m can be dropped, we arrive finally at the +formulas +H E +AmCm A +E +mC +H +b = mm am; (5.14a)BH E Em Cm BmCHm +H E +AmBm A +E +mB +H +c = mm am: (5.14b)BH E Em Cm BmCHm +Thus, by virtue of eq. (5.14a), we conclude that the scattering matrix SO of a gyrotropic cylinder embedded +in a gyrotropic matrix is diagonal and its elements are given by +H E +AmCm A +E H +S = m +Cm +mn ımn: (5.15)BH E Em Cm BmCHm +We have thus demonstrated that only minor modifications of the multiple-scattering method are nec- +essary to make it able to tackle gyrotropic materials. First, the refractive index n supplied to the argument +of Bessel functions must be replaced by the “effective refractive index” n0 defined in eq. (5.9). Second, +118 Chapter 5. Numerical methods +the formulas for the entries of the scattering matrix of a cylinder acquire additional terms proportional to +the off-diagonal elements of the material property tensors. +It is natural to ask whether these steps suffice for different classes of anisotropic materials. The +answer is, unfortunately, negative. For instance, consider the case of a medium with permittivity O  +diag.x; y ; z/ with x ¤ y . The transformation of Maxwell’s equations into the Helmholtz equation +comes now at the price of the change of coordinates +r +sx y +.x; y/!7 .sxx; syy/ with = ¤ 1: (5.16) +sy x +An unwelcome side-effect of this change of coordinates is the mapping of circles into ellipses. This has +two consequences. First, the elements of the scattering matrix of a circular cylinder cease to be diagonal +and have to be determined in a more complicated way than that presented above, since after the mapping +the cylinder’s surface does not coincide any more with a line of constant polar coordinates. Second, if +it is the matrix (rather than the scatterer) that is anisotropic, the mapping (5.16) may cause the circles +circumscribing the scatterers to overlap. It is well known that if this overlap is sufficiently large, the +Fourier-Bessel expansion (5.6c) of the scattered field becomes invalid and the multiple-scattering theory +in it classical form cannot be applied [179, 180]. +5.2 Calculation of photonic-crystal band structures +with Fourier-Bessel expansions +5.2.1 Introduction +The multiple-scattering method, whose extension to MO materials we have presented in the previous +section, has long been recognised as one of the most efficient techniques of modelling finite PCs com- +posed of circular cylinders. The reason for this is twofold: first, the basis functions used to expand the +fields are exact solutions of Maxwell’s equations, and hence they are well-adapted for the representation +of these fields; second, since the basis functions are separable in polar coordinates, it is easy to apply the +electromagnetic boundary conditions at the surfaces of the cylinders. +In view of these advantages of the multiple-scattering method, it is tempting to extend its domain of +application to the calculation of band structures of infinite PCs. Such an extension has indeed been made +both for PCs composed of cylinders and spheres [41–47]. In this approach it is necessary to calculate ex- +plicitly the field produced by an infinite number of scatterers arranged on a periodic lattice, which can be +expressed by a series termed a lattice sum. Unfortunately, lattice sums are slowly convergent, and special +techniques needed for acceleration of their computation complicate significantly the implementation of +the method with respect to the finite-system case. +Here we propose a much simpler technique of calculating band structures of PCs composed of cir- +cular cylinders. Like the multiple-scattering method, it relies on Fourier-Bessel field expansions, but it +dispenses with the calculation of lattice sums. The underlying idea is very simple: the field in a unit cell +of a PC is expanded in terms of particular solutions of the Helmholtz equation, and the Bloch conditions +on the boundaries of the cell are imposed by collocation (point matching). This approach is actually +similar to the technique used in the fictitious-sources method to avoid the calculation of periodic Green’s +functions in simulations of gratings [48]. The method is easy in implementation and it leads to expo- +nential convergence of the band structure, potentially yielding very high relative accuracy, as will be +demonstrated in the following. +The proposed method shares many features with the technique of Dirichlet-to-Neumann mappings +developed in the group of Lu [49, 50]. In their approach, a field expansion in particular solutions of the +5.2. Calculation of photonic-crystal band structures with Fourier-Bessel expansions 119 +Helmholtz equation is used to calculate a finite-dimensional approximation of the Dirichlet-to-Neumann +operator that maps the distribution of the field on the unit cell’s boundary to that of the normal derivative +of this field. The resulting operator can then be used to calculate the band structure of the PC. Our method +is more direct and more efficient, since it does not require the construction of the Dirichlet-to-Neumann +matrix, and hence dispenses with the need of performing a matrix inversion. On the other hand, it is +also less powerful, since a Dirichlet-to-Neumann operator can be used for the sake of computing not +only a band structure, but also, for instance, the transmission and reflection coefficients of a finite or +semi-infinite PC [50]. One could say that while the method of Lu et al. is more general, ours has been +specifically tailored to band-structure calculations. +In the next subsection we shall present the formulation of the proposed technique. Some concrete +numerical examples of its application will be given in subsection 5.2.3, and the obtained results will be +briefly discussed in subsection 5.2.4. +5.2.2 Formulation +Let us consider a 2D PC whose unit cell, shown in fig. 5.1(a), is composed ofM nonoverlapping circular +inclusions of radius rm, permittivity Om and permeability Om (m = 1; 2; : : : ;M ), embedded in a matrix +with permittivity O0 and permeability O 0. The tensors Om and Om (m = 0; 1; : : : ;M ) are assumed to +have the (gyrotropic2) form 3 2 3 +tm igm 0 tm igm 0 +Om  4i  0 5 and O  4i  0 5gm tm m gm tm : (5.17) +0 0 zm 0 0 zm +As we have shown in section 5.1, for p polarisation, the Maxwell’s equations in a homogeneous region +with permittivity Om and permeability Om reduce to the Helmholtz equation for the z component of the +magnetic field,Hz: +r2H C k2z mHz = 0; (5.18) +where  2 1=2 +km  ! +gm +tm : (5.19) +c tm +The corresponding equation for s polarisation can be obtained simply from the duality principle [65, p. +72–73]. Vekua [181, section 22] showed that every regular solution of the Helmholtz equation (5.18) in +a multi-connected domain D  D0n.C1 [ C2 [    [ CM /, where D0, C1, C2, : : : , CM are simply- +connected domains and C1; C2; : : : ; CM  D0, can be approximated uniformly by a linear combination +of the functions +J .k / eil and Y .k  / eilml m l m m for l 2 Z and m = 1; 2; : : : ;M; (5.20) +where .; / are standard polar coordinates and .m; m/ are the polar coordinates defined with respect +to the point Om 2 Cm [see fig. 5.1(b)]. +We shall use Vekua’s theorem to determine the representation of the field in the PC unit cell shown +in fig. 5.1(a). We divide it into M 0  M polygonal subcells, each containing exactly one circular +inclusion. (For numerical purposes it can be advantageous to introduce subcells containing no “physical” +inclusions; these can be treated as if they contained an inclusion with permittivity O0, permeability O 0 +and a sufficiently small radius.) Inside the inclusion of the mth subcell, the solution of the Helmholtz +equation can be approximated by the series +XL +.L/  .L/H .m; m/ c Jl.kmm/ eilm ; (5.21)z;in ml +l=L +120 Chapter 5. Numerical methods +D0 +P +C1 +1 +1 + 2 +O1 +  +C +2 2 +O O2 +(a) (b) +Figure 5.1 (a)Geometry of a PC’s unit cell that containsM = 3 circular inclusions embedded in a homogeneous +matrix. It is subsequently divided into M 0 = 4 quadrilateral subcells. (b) Schema of the domain D referred to in +Vekua’s theorem. Note that the symbol D0 denotes the whole interior of the large contour, whereas D stands for +the shaded region. +with the polar coordinates .m; m/ defined with respect to the origin Om lying in the centre of the +inclusion. In turn, the field outside the inclusion can be approximated by +XL +.L/  .L/ .L/H . ;  / Œa J .k  /C b Y .k  / eilmz;out m m l 0 m l 0 m : (5.22)ml ml +l=L +The superscripts .L/ in the above formulas stress that, according to Vekua’s theorem, the system +(5.20) is complete, but need not be a basis. In other words, it is not guaranteed, for instance, that there +exist coefficients aml and bml (Xl 2 Z) such that the series +Œa J .k  /C b Y .k  / eilmml l 0 m ml l 0 m (5.23) +l2Z +converges to the true solution Hz;out.m; m/. What is guaranteed is that a finite superposition of the +functions (5.20) can be found that approximates Hz;out.m; m/ to any desired accuracy  > 0. This is +quite sufficient for practical purposes. An example illustrating clearly the difference between a basis and +a complete set is given by Christensen [182, pp. 98–99]. For compactness of notation, the superscripts +.L/ will be dropped from now on. +At the present stage, to each subcell correspond three families of unknown coefficients: aml , bml +and cml . The former two can be easily expressed in terms of the latter one by imposing analytically the +electromagnetic boundary conditions at the surfaces of the circular inclusions. This is done exactly in +the same way as in the multiple-scattering method, and has been detailed in ref. 40 for the isotropic case +and in section 5.1 of this thesis for the gyrotropic case. Therefore, we do not describe it again here. In +any case, this procedure leads to expressions of the form +aml = Amlcml and bml = Bmlcml ; (5.24) +where Aml and Bml are known. Substituting them to eq. (5.22), we get +XL +H . ;  /  c ŒA J .k  /C B Y .k  / eilmz;out m m ml ml l 0 m ml l 0 m : (5.25) +l=L +To determine the values of cml , we impose appropriate boundary conditions at discrete collocation points +distributed on the inter-subcell boundaries, which can be divided into two classes. On an interface of two +5.2. Calculation of photonic-crystal band structures with Fourier-Bessel expansions 121 +subcells belonging to the same unit cell, we impose the continuity of Hz and its derivative normal to +that interface. (The continuity of the tangential derivative should follow, in the limit of infinitely many +collocation points, from the continuity of Hz itself.) On an external boundary of a unit cell, in turn, +we impose Bloch conditions on Hz and its normal derivative. Assuming that the number of collocation +points is equal to half the number of unknowns cml , the above procedure leads to a homogeneous system +of linear equations, whose matrix is square and depends on the Bloch vector kE. This system is subse- +quently transformed into a generalised eigenvalue problem for one of the components of kE, as will be +demonstrated on an example later in this section. +In the meantime, there is a technical difficulty to be resolved. As we have seen, we have always an +even number of boundary conditions. However, the expansion (5.25) contains an odd number (2LC 1) +of coefficients cml . In order to match the number of equations and that of unknowns, it is necessary +to dispense with one coefficient. To this end, we follow a procedure used in spectral Fourier-expansion +techniques [183, subsection 2.2.1]. We rewrite the exponential functions eilm in eq. (5.25) in terms of +the trigonometric functions cos.l / and sin.l /, and use the relations J .x/ = .1/lm m l Jl.x/, Yl.x/ = +.1/lYl.x/, Am;l = Aml and Bm;l = Bml to convert the series from eq. (5.25) to the form +XL +Hz;out.m; m/  ŒAmlJl.k0m/C BmlYl.k0m/Œd cml cos.lm/C d sml sin.lm/; (5.26) +l=0 +where +d c  c C .1/lc and d s  iŒc .1/lml ml m; l ml ml cm;l : (5.27) +We set now d smL = 0, obtaining +XL +Hz;out.m; m/  d cml ŒAmlJl.k0m/C BmlYl.k0m/ cos.lm/ +l=0 +X (5.28)L 1 +C d sml ŒAmlJl.k0m/C BmlYl.k0m/ sin.lm/ +l=1 +and reducing the total number of unknowns to 2L. +We shall now present in detail the conversion of the square system of linear equations resulting from +the collocation procedure to an eigenvalue problem, considering the example case of a PC composed +of a hexagonal lattice of cylinders, shown in fig. 5.2(a). Its unit cell can be chosen as the Wigner-Seitz +cell delimited by the segments ˙i (i = 1; 2; : : : ; 6). Since it contains only a single inclusion, it is not +necessary to divide it into subcells. Let us assume that on each segment ˙i L=3 collocation points with +polar coordinates .1;ij ; 1;ij / (j = 1; 2; : : : ; L=3) are distributed so that the positions of the points lying +on opposite sides of the cell differ by a lattice vector. Let us denote by HO i the matrix of size .L=3; 2L/ +that, right-multiplied by the vector of unknowns dE  Œd c ; d c ; : : : ; d c ; d s ; d s ; : : : ; d s T1;0 1;1 1;L 1;1 1;2 1;L1 , +will produce the vector of values of the fieldHz at the collocation points lying on the segment˙i . From +eq. (5.28), the elements ofHO i are given by ( +O C  cos.l1;ij / for l = 0; 1; : : : ; L;.Hi /jl = ŒA1lJl.k01;ij / B1lYl.k01;ij / C C (5.29)sin.l1;ij / for l = L 1;L 2; : : : ; 2L: +The analogous matrix that, right-multiplied by dE, will produce the vector of derivatives of Hz taken in +the direction normal to ˙ will be denoted byHO 0i i . +122 Chapter 5. Numerical methods +bE2 +aE2 +a ˙3 ˙2 +M +˙ r4 ˙1 +0 +aE K M1 +collocation ˙5 ˙6 +E +points b1 +(a) (b) +Figure 5.2 (a) Geometry of a hexagonal-lattice PC composed of circular air holes etched in a dielectric matrix. +A Wigner-Seitz unit cell is marked by shading. (b) Reciprocal space of this PC. Large dots mark the positions +of reciprocal lattice points. The hexagonal first Brillouin zone is also shown; its irreducible part MK has been +shaded. +In this matrix notation, the equations resulting from imposition of the Bloch boundary conditions at +all the collocation points take then the form +O E ikEH d = e aE1 HO dE; HO 0dE = eikEaE1 HO 01 4 1 4dE; +O E ikEaE O E O 0 E ikEH d = e 2 H d; H d = e aE2 HO 0dE2 5 ; (5.30)2 5 +HO dE = eikE.aE2aE / E13 HO6dE; HO 03dE = eik.aE2aE1/HO 06dE; +p +where aE 1 31  .a; 0/ and aE2  . a; a/ denote the basis vectors of the hexagonal lattice show2 2 pn in fig. +5.2(a). The Blo +E  p +ch vector kE can be expressed as kE = k E E E 2 1b1 C k2b2, where b1  .1;1= 3/ anda +b 2 2 .0; 2= 3/ are the basis vectors of the reciprocal lattice of the PC in question, shown in fig.a +5.2(b), and have the property aEi  bEj = 2 ıij . Consequently, eqs. (5.30) can be rewritten as +.HO e2 ik1 HO /dE = 0; .HO 0 C e2 ik1 HO 01 4 1 4/dE = 0; +.HO e2 ik2 HO /dE = 0; .HO 0 C e2 ik22 5 HO 0 /dE = 0; (5.31)2 5 +.e2 ik1 HO 2 ik2 O E 2 ik1 O 0 2 ik2 O 0 E3 e H6/d = 0; .e H3 C e H6/d = 0: +To bring this system into the form of an eigenvalue problem, we can fix the value of some linear combi- +nation of k1 and k2. For instance, calculations of the band structure of the hexagonal-lattice PC from fig. +5.2(a) are most often done along the boundaries of the irreducible fragment of its first Brillouin zone, the +triangle MK, shown in fig. 5.2(b). On the segment M , the Bloch vector kE has the form kE = bE1CbE2 +with 0    1 . Thus, setting k1 = k2   in eq. (5.31) and reordering terms, we obtain the linear2 +eigenvalue problem 2 O 3 2 36 H HO666 +1 4 +HO 0 7 6 O 07 +O1 +7 +6 77 6 +6 +H 7 E 6 +H 7 +6 HO +47 +6 2 7 d = e2 i6 O 0 7 6 +57 E +6 O 0777 d: (5.32)4 HHO 2HO3 65 4 H50O 5 +HO 03 CHO 0 0O6 +5.2. Calculation of photonic-crystal band structures with Fourier-Bessel expansions 123 +Since the matrices HO and HO 0i i have dimensions .L=3; 2L/, it can be easily verified that the matrices in +the above equation are square. +Things are slightly more complex for the segment K. There, the Bloch vector kE = 2bE1 C bE2 +with 0    1 , and eqs. +3 2(5.313) reduce to thO 2 +e quad3ratic eigenva2lue pro3blem +H 0O HO +6 1 466HO 0777 666 0O 777 666 HO 076 17 76HO 7 O O +47 +6 26 O 077 +E C e2 i 666H57d O 077 dE6 7 C e +4 i +66 +66 0 7O 77 dE7 = 0: (5.33)4HO25 4 HO5H6 H35 4 00O 5 +HO 0 HO 06 3 0O +This problem can be solved in a number of ways [184]. The most popular of them, which we employ +here, is linearisation: given an equation of the form .AO C BO C 2CO /xE = 0, one defines yE  xE and +solves a linear eigenvalue problem"of doub#leO O " +siz#e, e."g.,O O #" #A B xE 0 C xE +O O E = O O E ; (5.34)0 I y I 0 y +where IO denotes the identity matrix. Alternative linearisations are also possible, but they are advanta- +geous primarily if the original quadratic eigenvalue problem has a particular structure—for instance, is +symmetric—which is not the case here. +The band structure on the KM segment could be calculated by solving a third eigenvalue problem +obtained from eq. (5.31) by imposing the constraint k1 C k2 = 1. However, owing to the six-fold +rotational symmetry of the PC from fig. 5.2(a), its dispersion diagram on KM is identical with that on +the segmentKM 0, shown in fig. 5.2(b), which is collinear with K. Thus, the band structure on K and +KM 0 can be obtained simultaneously by solving the eigenvalue problem (5.33); values of  belonging +to the intervals Œ0; 1  and Œ1 ; 1  will then correspond to Bloch vectors lying on the segments K and +KM 0 +3 3 2 +, respectively. +5.2.3 Numerical examples +We shall now apply the method introduced in the previous subsections to the determination of the band +structure of several example PCs. The results obtained with this technique will be compared to those +produced by another, well-tested code. We shall also examine the convergence rate of Fourier-Bessel +expansions and discuss some technical details of the implementation of the proposed method. +We begin with the simple case of a PC composed of a hexagonal lattice of air holes of radius r = +0:3a, where a is the lattice constant, etched in a dielectric matrix with refractive index 2.5, as shown +schematically in fig. 5.2(a); this is in fact the PC introduced in section 4.4. First, it is necessary to check +whether the proposed method yields results convergent with increasing truncation order L. We shall +therefore study how the changes in L influence the magnitude of the Bloch vector kE of the state located +on the M segment and having frequency ! = 0:40  2 c=a (chosen arbitrarily). In practice, the +determination of the error of a calculated value of k is complicated by the fact that the exact magnitude +of kE is not known. As a workaround, given a series of values ki (i = 1; 2; : : : ; NL) obtained at several +monotonically increasing truncation orders Li , we shall take as a reference the value ki for which the +expression .jki ki1j C jki kiC1j/=jki j is smallest. +The collocation points on all boundaries ˙i (i = 1; 2; : : : ; 6) of the unit cell will be initially placed +at the Gauss-Legendre quadrature points, i.e., at the roots of the Legendre polynomial of order L=3C 1 +[183, p. 252]. This choice will be later demonstrated to be near-optimal. +124 Chapter 5. Numerical methods +100 +(a) (b) Equidistant + Chebyshev10 5 Legendre +1010 No bal. +Bal. (1) +1015 Bal. (2) +0 50 100 150 200 0 50 100 150 200 +L L +Figure 5.3 (a) Convergence of the magnitude of the Bloch vector kE of the state located on the M seg- +ment in the first Brillouin zone of the hexagonal-lattice PC shown in fig. 5.2(a). The frequency was fixed to +! = 0:40  2 c=a. The different data series refer to results obtained with different levels of eigenvalue-problem +balancing. Crosses: no balancing. Black circles: out-of-the-box balancing as provided by LAPACK. White cir- +cles: balancing preceded by elimination of nonzero matrix entries due to round-off error, as described in the text. +(b) Convergence of k with three different distributions of collocation points: equidistant points (crosses), Gauss- +Chebyshev quadrature points (black circles), Gauss-Legendre quadrature points (white circles). +Since Bessel functions of different orders vary greatly in magnitude for a fixed argument, the eigen- +value problems (5.32) and (5.33) very quickly become numerically close to singular if no rescaling of +the basis functions is done. This leads to erroneous results. As a remedy, it is possible to scale the +basis functions manually, e.g., by normalising them to the value they attain at a typical (in some sense) +distance from the collocation points to the origin of the coordinate system. However, we found it more +convenient to rely on the matrix-pair balancing algorithm due to Ward [185], which can be invoked auto- +matically by the generalised non-symmetric eigensolver routine ggevx from the LAPACK library [186]. +In fig. 5.3 the points marked with black circles show the convergence of k calculated in this way with +the truncation order L. Clearly, relative accuracy of 107 is achieved in a fairly wide range of trunca- +tion orders. However, there is still room for improvement, since the machine precision is much higher +(1016/. +The performance of the balancing algorithm of Ward [185] is degraded by the presence of small +matrix elements due to round-off error [187, balance function]. Such entries do occur in our case; they +correspond to collocation points located on nodal lines of trigonometric functions cos.lm/ and sin.lm/ +of various orders l [cf. eq. (5.29)]. It is impractical to locate such points by hand. Therefore we have +used instead a heuristic procedure that looks for matrix entries smaller than a given fraction of the +average magnitude of the elements of the column they lie in. These entries are subsequently replaced +with zeros. The value = 1010 seems to work well. As demonstrated by the series marked with white +circles in fig. 5.3(a), introduction of this procedure leads to a significant increase of the attainable relative +accuracy, which reaches 1014. +We have also studied the dependence of the convergence rate on the placement of collocation points. +Three distributions were considered: Gauss-Legendre, Gauss-Chebyshev and equispaced. As shown in +fig. 5.3(b), the former two yield approximately the same convergence rate of k (the Gauss-Legendre +distribution performing marginally better), while the equispaced points fare distinctly worse. These +tendencies have also been observed for other frequencies and PC geometries. Thus, in the remaining +examples we use the Gauss-Legendre distribution. +In figs. 5.4(a) and (b) the band structures of the crystal from fig. 5.2 computed for p and s polarisa- +tions with the method under study are compared with the data obtained using the MPB library [188]. For +both polarisations, a perfect visual agreement can be seen. +Relative error +5.2. Calculation of photonic-crystal band structures with Fourier-Bessel expansions 125 +0:4 (a) (b) +0:2 +0:0 + M K M K +Figure 5.4 Comparison of the (a) p-polarisation and (b) s-polarisation band structure of the hexagonal-lattice +crystal from fig. 5.2, calculated with the method described here (points) and with the MPB library (lines). +aE bE2 2 +M +r +aE X1 bE1 +a +a +(a) (b) +Figure 5.5 (a) Geometry of a square-lattice PC composed of circular air holes etched in a dielectric matrix. A +Wigner-Seitz unit cell is marked by shading. (b) Reciprocal space of this PC. Large dots mark the positions of +reciprocal lattice points. The square first Brillouin zone is also shown; its irreducible part MX has been shaded. +We shall now move on to the analysis of the square-lattice PC shown in fig. 5.5(a), composed of air +holes of radius r etched in a dielectric matrix with refractive index 3.4. We shall focus on the case of +large r (close top1a). Without Vekua’s theory, one could have doubts about the validity of the method2 +for r > a.1 2/=2  0:29a, since in this case the circumscribed circle of a unit cell crosses the +inclusions from the neighbouring cells, and hence it is not clear whether a Fourier-Bessel representation +of the field near the cell corners is valid. We shall show that even for r  1a the method still produces +2 +correct results, in accordance with Vekua’s assertion. +Figure 5.6 shows the juxtaposition of the band structures of the PC from fig. 5.5(a) with r = 0:49a +obtained with the present technique and with MPB. As before, a perfect visual agreement in apparent. +In turn, in fig. 5.7 we compare the convergence of the magnitude of the vector kE of a Bloch state lying +on the M segment for the two polarisations and three values of r : 0:45a, 0:49a and 0:50a. In each +case, the frequency is fixed so as to correspond to k roughly equal to 0:25a. It can be seen that in the +p polarisation case the convergence slows down distinctly as r approaches 0:50a; this is probably related +to the occurrence of field singularities at the points of contact of neighbouring holes. Such singular fields +cannot be represented efficiently with a regular function basis. Even so, a relative accuracy of 104 is +attainable with a reasonable number of basis functions. +Comparison of figs. 5.3(a) and 5.7 shows that the ultimate relative error of the calculations done for +!a=2 c +126 Chapter 5. Numerical methods +0:4 (a) (b) +0:2 +0:0 + X M X M +Figure 5.6 Comparison of the (a) p-polarisation and (b) s-polarisation band structure of the square-lattice +crystal from fig. 5.5, calculated with the method described here (points) and with the MPB library (lines). +100 +(a) p pol. (b) s pol. r D 0:45a +r D 0:49a +105 r D 0:50a +1010 r D 0:45a +r D 0:49a +r D 0:50a +1015 +0 50 100 150 200 0 50 100 150 200 +L L +Figure 5.7 Convergence of the magnitude of the Bloch vector kE of the state located on the M segment in +the first Brillouin zone of the square-lattice PC shown in fig. 5.5(a) for (a) p polarisation and (b) s polarisation. +The frequency was fixed to: (a) ! = 0:38  2 c=a for r = 0:45a; ! = 0:40  2 c=a for r = 0:49a; and +! = 0:47  2 c=a for r = 0:50a; (b) ! = 0:35  2 c=a for r = 0:45a; ! = 0:40  2 c=a for r = 0:49a; and +! = 0:40  2 c=a for r = 0:50a. In all these cases, k  0:25  2 =a. +the square-lattice PC is slightly larger than in the hexagonal-lattice case. This is probably caused by the +fact that the spread of the radial coordinates of the collocation points placed on a square is greater than +on a hexagon. Therefore the range of values taken by any given basis function at different collocation +points is larger in the former case, and this reduces the efficiency of the balancing algorithm. +The third example to be studied is the PC composed of a hexagonal lattice of “shamrocks”, i.e., +patterns of three adjacent circular air holes of radius 0:2a, shown in fig. 5.8(a). The PC matrix is assumed +to be magneto-optical, with a tensorial permittivity of the form (4.31) with  = .2:5/2 and g = 0:1; these +parameters correspond roughly to those of BIG in the infrared range (see section 4.4). In this structure, +which has already been discussed briefly in section 3.4.3, both the spatial inversion symmetry and the +time-reversal symmetry of Maxwell’s equation are broken; therefore, it is nonreciprocal and its band +structure has no centre of symmetry. A particularly striking consequence of this fact is the existence +of unidirectional band gaps. Such a band gap appears, for instance, in the neighbourhood of frequency +! = 0:3915  2 c=a. Figure 5.8(b) shows the equifrequency curve at this value of !. Clearly, there +exist propagative bands at kx =  =.3a/ (close to theK points), whereas there are none at kx =  =.3a/ +(close to the K 0 points). As noted in ref. 115, a slab of such a PC can be used as an isolator.? +? As a historical note, we mention that the unidirectional-mirror effect caused by the lifting of the spatial inversion symmetry, +described in ref. 115, had originally been discovered in the PC shown in fig. 5.8(a). However, it was subsequently found +that a PC composed of triples of slightly overlapping holes provides a larger unidirectional gap and would be easier to +manufacture. Such a system cannot be directly handled by the method presented here; therefore, calculations of its band +Relative error +!a=2 c +5.2. Calculation of photonic-crystal band structures with Fourier-Bessel expansions 127 +(a) +(b) K +0 M K +0:50 +a a +0:25 M M +r +0:00 + +K K0 +0:25 +M M +0:50 +K0 M K +0:5 0:0 0:5 +a +kxa=2  +100 (c) +103 +106 +0 50 100 150 200 +L +Figure 5.8 (a) Geometry of the PC composed of a hexagonal lattice of groups of three adjacent circular holes +etched in a magneto-optical matrix. The shaded region is the unit cell composed of four hexagonal subcells +that was used in calculations. (b) p-polarisation equifrequency curve of this crystal at ! = 0:3915  2 c=a. +(c) Convergence of the magnitude of the Bloch vector kE of the state located on the M segment in the first +Brillouin zone of this crystal at the same frequency. +The calculations of the equifrequency curve shown in fig. 5.8(b) were made by dividing the PC’s unit +cell into four hexagonal subcells outlined in fig. 5.8(a), one of them empty. Owing to the presence of +field singularities at the cylinder junction points and the offset of the inclusion centres with respect to the +hexagon centres, which causes a wider spread of the radial coordinates of different collocation points, +only a moderate relative accuracy of105 was attained in simulations, as evidenced by the convergence +plot from fig. 5.8(c). For very large truncation orders (L  150) round-off error increasingly corrupts +the results. +In section 4.4 another class of PC systems was studied with the method proposed here: waveguides +embedded in the hexagonal-lattice crystal from fig. 5.2. The band structures of two such waveguides +are plotted in fig. 4.9. These calculation were done using the supercell technique, with artificial quasi- +periodic boundary conditions imposed on the segments ˙1–˙4 of the supercell shown schematically in +fig. 5.9. +structure reported in ref. 115 were performed with the MPB library [188]. +Relative error +kya=2  +128 Chapter 5. Numerical methods +dw +˙3 +˙2 ˙4 +˙1 +Figure 5.9 Geometry of the supercell used for the calculation of the waveguide dispersion relations shown in +fig. 4.9. +5.2.4 Conclusions +In this section we have presented a method of calculating band structures of 2D PCs composed of circular +cylinders by help of Fourier-Bessel expansions. Its cardinal virtue is its high efficiency: owing to the +exponential convergence of the method, it is possible to achieve a relative accuracy better than 1010 at a +modest computational cost. Therefore the proposed technique can provide extremely accurate reference +values for the purposes of testing other numerical methods. High accuracy is also invaluable in studies +of tiny effects, such as the nonreciprocity induced by a static magnetic field at optical frequencies. +For PCs whose unit cell need not be divided into subcells, the method has an extremely simple imple- +mentation. On the other hand, if multiple subcells are present, the necessary bookkeeping can be tricky; +however, it should be possible to automatise the imposition of the appropriate boundary conditions to +a certain degree. Disadvantages of the technique in question lie primarily in its restriction to systems +containing circular inclusions and in the degradation of its accuracy for subcells whose shape deviates +markedly from that of a circle concentric with the embedded inclusion. This latter problem might pos- +sibly be alleviated with more advanced matrix-pair balancing algorithms, such as those presented in +ref. 189. +5.3 Finite-element simulations of three-dimensional axisymmetric cavities +5.3.1 Introduction +In this section we shall describe the finite-element (FE) method used to calculate the eigenmodes of open +3D axisymmetric cavities containing gyrotropic materials. This technique was used to obtain the results +presented in section 4.6. +There are two major approaches to FE simulations of axisymmetric systems [60, p. 912–913]. Early +researchers [190, 191] made use of the possibility of expressing all the components of the electromag- +netic fields EE and HE in such systems in terms of the so-called coupled azimuthal potentials E and +H , which were subsequently discretised with standard nodal FEs. However, Maxwell’s equations +written in terms of these potentials have nonphysical singularities at certain radii, whose presence affects +adversely the accuracy of calculations. +In 1993, Lee et al. [192] proposed an alternative approach to the problem of finding the eigenmodes +of a closed axisymmetric cavity. He formulated the equations in terms of the two meridional ( and z) +components of the electric fields, expanded into curl-conforming vector elements, and the electric az- +imuthal potential E , expanded into nodal elements. The boundary conditions on the z axis were not +yet treated in a sophisticated way. Therefore, the expressions for the elements of the matrices repre- +senting the discretised equations contained singular integrals, whose computation can be numerically +demanding. Later, Chinellato [193] established a solid mathematical foundation for this approach, intro- +ducing also a set of carefully crafted techniques for the calculation of the singular integrals. Combined +with a PML-based truncation of the computational domains, this method was used for the determina- +tion of the eigenmodes of open dielectric axisymmetric resonators [194]. Hiptmair and Ledger [195] +5.3. Finite-element simulations of three-dimensional axisymmetric cavities 129 +extended it to FEs of arbitrary order, so-called hp FEs, which allow to obtain exponential convergence, +even if field singularities are present, by combining mesh refinement with an increase of the element +order. +In the meantime, however, it had been shown that the enforcement of the boundary conditions on +the z axis is facilitated if a particular change of variables is made so that the vector FEs are used to +expand a specific combination of the azimuthal and meridional components of EE rather than the “pure” +meridional part [196, 197]. This change of variables removes also all singular integrals. Greenwood and +Jin applied this idea to simulations of wave scattering [51] and radiation [198] by axisymmetric bodies, +using PMLs to truncate the computational domain. Finally, Venkatarayalu [52] proposed an algorithm +of elimination of unwanted static (zero-frequency) cavity eigenmodes from the FE approximation space, +which is reputed to accelerate the convergence of iterative eigenvalue solvers. +The particular variant of the axisymmetric FE method implemented during this thesis combines el- +ements of several works cited above. It is probably closest to that of Greenwood and Jin [51]: vector +FEs are used to expand a superposition of the azimuthal and meridional components of EE; exponential +Fourier expansions in the azimuthal direction are used rather than trigonometric ones; and the computa- +tional domain is truncated with PMLs. On the other hand, unlike Greenwood and Jin, we look for the +eigenmodes of the modelled system rather than its response to an incident field; thus, in a manner similar +to that of Venkatarayalu [52], we derive an eigenvalue problem rather than an inhomogeneous system of +equations. Finally, like Hiptmair and Ledger [195], we use relatively high-order FE expansions is order +to improve the efficiency of calculations. The original contribution of our work is the extension of the +method to the case of media with gyrotropic material properties. Before, it had been formulated only for +diagonal permittivity and permeability tensors, which are used to represent PMLs adapted to cylindrical +coordinates [51, 53, 54]. +In the next subsection we present the derivation of our algorithm. Some issues, in particular the +manner of boundary condition enforcement on the z axis, are discussed in rather more detail than it has +been done in literature [51, 52, 196].? We hope that their pedagogical derivation here will be useful for +future researchers intending to use or program the FE method for axisymmetric structures. Subsection +5.3.3 is devoted to the numerical implementation of the proposed technique. Finally, in subsection 5.3.4 +we evaluate its accuracy. +Several examples of the application of the method to the calculation of the eigenmodes of specific +cavities can be found in section 4.6. +5.3.2 Formulation +Axisymmetric systems We begin by defining precisely what we mean by an axisymmetric structure. +A system characterised by position-dependent permittivity and permeability tensors is said to be axisym- +metric if the representations of these tensors in cylindrical coordinates .; ; z/ are independent from +the azimuthal coordinate . It is instructive to check in what circumstances a tensor field whose Carte- +sian components are constant in some area of space stays independent from  when it is transformed to +cylindrical coordinates. Consider, for instance, the permittivity tensor O. Its Cartesian components are +defined by the relation 2 3 2 32 3 +4Dx5 4xx xy xz54ExDy =   5yx yy yz Ey ; (5.35) +Dz zx zy zz Ez +? We have not had access to ref. 197, in which this topic is probably also considered. +130 Chapter 5. Numerical methods +where EE  .E ;E ;E /T is the electric field and DE  .D ;D ;D /Tx y z x y z the electric displacement. +Since the Cartesian components of a vector FE are related to the cylindrical ones by +2 3 2 32 34Fx5 4cos sin 0F = sin cos 054FF 5y  ; (5.36) +Fz 0 0 1 Fz +the tensor O in cylindrical coordinates will take the form +2 312 32 34cos sin 05 4xx xy xz54cos sin 0O.cyl/ = sin cos 0 yx yy yz sin cos 05 +20 0 1 zx zy 3zzC 2 +0 0 3 1 +1 += 4 xx yy xy yx 0 5 4 0 0 xz.xy yx/  5xx C yy 0 C 0 0 yz cos +2 +2 0 30 2z2z zx zy 0 3 (5.37) +4 0 0 yz xx yy xy C yx 0C 10 0  5 sin C 4xz xy C yx .xx yy/ 05 cos 2 +2 +2zy zx 0 30 0 0 +4 1 xy C yx .xx yy/ 0C . 5xx yy/ .xy C yx/ 0 sin 2: +2 +0 0 0 +Obviously, in order that .cyl/ be independent of , all the terms proportional to trigonometric functions +of  in the above expression must vanish. This is the case if and only if xx = yy , xy = yx and +xz = yz = zx = zy = 0. Thus, a permittivity tensor field having a locally constant Cartesian +representation will be independent from  after transformation to cylindrical coordinates if and only if it +has the form 2 3 +t ig 0 +O.Cart/ = 4i 5g t 0 (5.38) +0 0 z +(the imaginary unit has been introduced into the off-diagonal components purely for future convenience +and for consistency with other parts of this manuscript). It is worth noting that from eq. (5.37) it follows +that in this case O.cyl/ = O.Cart/. Obviously, the above reasoning can be repeated for the permeability +tensor O . +In this way we have shown that axisymmetric systems may not contain physical? materials whose +permittivity or permeability tensors have a form other than (5.38). +Statement of the problem We seek the (leaky) eigenmodes of an open axisymmetric cavity with +the given permittivity O.; z/ and permeability O .; z/ (in the rest of this section, components of material +property tensors will be assumed to be given in cylindrical coordinates unless mentioned otherwise), ful- +filling the Sommerfeld’s boundary conditions [60, p. 294] at infinity. Since it is not possible to discretise +the whole space 3R with FEs, simulations will be done on the finite cylindrical domain +˝0  f.; ; z/j0    R and 0   < 2  and Z  z  ZCg : (5.39) +? This conclusion does not apply to “numerical” media such a PMLs, which need not have piecewise-constant Cartesian +representations of the permittivity and permeability tensors. +5.3. Finite-element simulations of three-dimensional axisymmetric cavities 131 +In order to suppress spurious reflections on the boundaries of ˝0, its surface will be coated with PMLs, +treated numerically as special anisotropic media, whose nature will be specified later in this section. On +the whole surface of ˝0 perfect-electric-conductor boundary conditions will be imposed. +Wave equation We shall now demonstrate that the independence of O and O from  allows to convert +the vector wave equation for the electric field EE in ˝0 into an infinite set of decoupled equations for the +restriction of EE to a single meridional plane of ˝0. +Eliminating the magnetic field HE from the time-harmonic source-free Maxwell’s equations (1.4a)– +(1.4b), we get +rE  ŒO1  .rE EE/ = k20O EE; (5.40) +where k0  !=c is the free-space wave number. The electric field EE can be expanded in a Fourier series +with respect to : +E XE.; ; z/ = EE .; z/ eill ; (5.41) +l2Z +so that eq. (5.40) becomes +X E E E Xr  fŒO .; z/ 1  Œr E .; z/ eil g = k2 O.; z/ EE .; z/ eill 0 l : (5.42) +l l +In cylindrical coordinates, +rE = rE C eE 1t  @ ; where rE t  eE@ C eEz@z : (5.43) +Since all functions in eq. (5.42) depend on  only through factors eil , differentiation over  reduces to +multiplication by il . As a result, eq. (5.42) can be rewritten as +X +rE  fŒO .; z/ +X +1  ŒrE EE .; z/g eil = k2 O.; z/ EE .; z/ eill l l 0 l ; (5.44) +l l +where +rE  rE C eE il1l t  : (5.45) +From the linear independence of the functions eil (l 2 Z) on the interval Œ0; 2  it follows that eq. (5.44) +is equivalent to a system of decoupled equations on individual Fourier coefficients EEl.; z/: +rE  fŒO .; z/1  ŒrE EE .; z/g = k2l l l 0O.; z/ EEl.; z/ for each l 2 Z: (5.46) +Thus, the eigenmodes of an axisymmetric system can be classified according to their azimuthal order l +and found by solving separately each of the equations (5.46) for the field EEl.; z/ defined on the 2D +domain +˝  f.; z/j0    R and Z  z  ZCg : (5.47) +Needless to say, this brings substantial savings in computational time in comparison to the solution of +the original equation (5.40) defined on the 3D domain ˝0. The geometry of the domain ˝ is shown +schematically in fig. 5.10. +132 Chapter 5. Numerical methods +z +1 eEn +ZC +PML +0 1 +˝ +R  +PML +Z +1 +Figure 5.10 Geometry of the domain ˝. Regions filled with PMLs are hatched. +Weak form The FE method is based on the Galerkin’s technique, itself a representative of the class of +weighted-residual methods for solving differential equations. In these methods, a generalised differential +eigenvalue problem [like the one from eq. (5.46)] of the general form A u = Bu, where A and B are +differential operators, u is the unknown function, and  is the eigenvalue, is converted into a system of +algebraic linear equations by (i) expanding u in a series of known basis functions un and (ii) requiring +that an appropriately defined inner product .vn;Ru/ of a number of test functions vn with the residual +Ru  A u Bu vanish. In the Galerkin’s method the set of test functions is chosen to be identical +with that of basis functions [199, section 3.1]. +Boundary conditions can be incorporated into the equation .vn;Ru/ = 0 using integration by parts. +This leads to the weak form of a differential equation, in which the original equation and its associated +boundary conditions are merged in a single formula. +We shall now derive the weak form of eq. (5.46). We define the inner product in the usual way, +“ +.vE; uE/  vE.; z/  uE.; z/ d˝: (5.48) +˝ +The condition that the inner product of an arbitrary test function vE with the residual of eq. (5.46) vanish +takes then the form (henceforth we omit the superscript l in EEl ) +“ “ +vE  frE  ŒO1  .rE EE/g d˝ = k2 vE  O EEl l 0 d˝ (5.49) +˝ ˝ +It can be shown that the following integration-by-parts formula is valid: +“ “ I +vE  .rE  uE/ d˝ = .rE  vE/l l  uE d˝ .vE  uE/  eEn dl I (5.50) +˝ ˝ @˝ +here, vE and uE are arbitrary sufficiently regular functions, @˝ is the boundary of ˝, and eEn denotes the +unit vector normal to @˝ and directed outwards. Applying this formula to eq. (5.49), we get +“ I “ +.rE  vE/ O1  .rE EE/ d˝ fvE  ŒO1  .rE EE/g  eE dl = k2 vE  O EEl l l n 0 d˝: (5.51) +˝ @˝ ˝ +Later in this subsection we shall use the boundary conditions to dispense with the contour integral in the +above equation. +5.3. Finite-element simulations of three-dimensional axisymmetric cavities 133 +Boundary conditions The contour @˝ can be divided into two parts: that lying on the z axis, denoted +henceforth 0, and the rest, denoted 1 (see fig. 5.10). The segment 1 is a subset of the surface of the +original 3D domain ˝0. Therefore the boundary condition imposed on it has already been specified to +be of the perfect-electric-conductor type. In contrast, the segment 0 does not belong to the surface +of˝0, and the boundary conditions on it have still to be determined. They will follow from the physical +requirement that the limits lim!0EE.; ; z/ and lim!0HE.; ; z/ exist and be independent from  +for all z 2 ŒZ; ZC. +For an eigenmode of a given order l , EE.; ; z/ = EE.; z/ eil . Using eq. (5.36) and rewriting cos +and sin in terms of the exponential functions e˙i , we obtain that +E .; ; z/ = 1fŒE .; z/C iE .; z/ ei.lC1/ C ŒE .; z/ iE .; z/ ei.l1/x     g; (5.52a)2 +E .; ; z/ = 1 fŒE .; z/C iE .; z/ ei.lC1/ ŒE .; z/ iE .; z/ ei.l1/y     g; (5.52b)2i +E .; ; z/ = E .; z/ eilz z : (5.52c) +Thus the lim8ˆits of these expressions with ! 0 exist and are independent from  only if< for l = 0; (a) E.0; z/ = 0 and (b) E.0; z/ = 0; (5.53) +:ˆ for jl j = 1; (a) E.0; z/C ilE.0; z/ = 0 and (b) Ez.0; z/ = 0; (5.54) +for jl j > 1; (a) E.0; z/ = 0; (b) E.0; z/ = 0 and (c) Ez.0; z/ = 0: (5.55) +Turning now to the magnetic field, from eq. (1.4a) we get +HE.; ; z/ = Œi! O .; z/10  ŒrE EE.; ; z/ +O  rE  E (5.56)= Œi!0.; z/ 1 Œ l E.; z/ eil : +R8ˆˆˆeasoning analogously as in the case of the electric field, we obtain the conditions +ˆˆˆ for l = 0; (a) ŒO1  .rE l EE/.0; z/ = 0 and (b) ŒO1  .rE El E/.0; z/ = 0; (5.57)< for jl j = 1; (a) ŒO1  .rE EE/ .0; z/C il ŒO1  .rE EEl  l /.0; z/ = 0 and (5.58) +ˆˆˆˆˆ (b) ŒO1  .rE l EE/z.0; z/ = 0; +:ˆ for jl j > 1; (a) ŒO1  .rE EE/ .0; z/ = 0; (b) ŒO1l   .rE l EE/.0; z/ = 0 and (5.59) +(c) ŒO1  .rE l EE/z.0; z/ = 0: +Finite-element expansions From now on we restrict our attention to the case jl j  1. The deriva- +tions go slightly differently for modes with order l = 0, and such modes are less interesting for us, since +they do not exhibit the twofold degeneracy required in a cavity forming part of a circulator. Following +refs. 51, 196, 197 and 52, we introduce the following change of variables: +EE  eE E C eE E = .il/1.eE E EE 0t   z z   t/: (5.60) +We expand the azimuthal component of EE into nodal FE basis functions u0n.; z/ (n = 1; 2; : : : ; N): +XN +E = E +0 +nun; (5.61) +n=1 +and the new field EE 0t, tangential to the meridional plane z, into curl-conforming vector FE basis func- +tions uE0tn.; z/ (n = 1; 2; : : : ; Nt): +E 0 XNtEt = E 0 0tnuEtn: (5.62) +n=1 +134 Chapter 5. Numerical methods +The coefficients E and E 0n tn are the unknowns to be determined. The restrictions of the functions +u0 and of both components of uE0 to any element are polynomials in  and z. The functions u0n tn n are +continuous on ˝, whereas uE0tn have the property that their tangential components are continuous across +element borders; as a result, rE  uE0t tn is finite everywhere. +Gathering together eqs. (5.60)–(5.62), we obtain thus the following FE expansion of the electric +field EE, XN XNt +EE = ŒeE C .il/1eEE .il/1EE 0t = EnuEn C E 0tnuEtn; (5.63) +n=1 n=1 +in terms of the azimuthal basis functions +uE  ŒeE C .il/1eE u0n   n .n = 1; 2; : : : ; N/ (5.64) +and the meridional basis functions +uE  .il/1uE0tn tn .n = 1; 2; : : : ; Nt/: (5.65) +Imposition of boundary conditions We shall now demonstrate that the chosen form of FE ex- +pansions allows to impose conditions (5.53) and (5.57) in a simple way, as well as to remove from the +integrals in eq. (5.51) all singular weights, stemming from the presence of the term eE il1 in definition +(5.45) of rE l . We shall assume that close to the z axis the tensor O has the gyrotropic form2 3 +t ig 0 +O = 4i 5g t 0 (5.66) +0 0 z +As will be shown in section 5.3.3, this is the case even if PMLs are present. +We begin by expressing E , E and all the components of rE EE in terms of E and EE 0 z l  t. Using eq. +(5.60), after some straightforward algebra we obtain +E = .il/1.E E 0  /; (5.67a) +E = .il/1E 0z z; (5.67b) +.rE EE/ = @ E E 0l  z  z; (5.67c) +.rE EE/ = .il/1Œ@ E CE 0 .@ E 0 @ E 0l  z  z z   z; (5.67d) +.rE EE/ = @ E CE 0l z   : (5.67e) +Owing to the regularity properties of the basis functions used to expand the fields E and EE 0 t, discussed +above, the limits of expressions (5.67) with ! 0 exist and are equal to +E .0; z/ = .il/1 E.0; z/; (5.68a) +Ez.0; z/ = 0; (5.68b) +.rE EE/ .0; z/ = .@ E /.0; z/ E 0l  z  z.0; z/; (5.68c) +.rE EE/ .0; z/ = .il/1Œ.@ E /.0; z/CE 0l  z  z.0; z/; (5.68d) +.rE EE/ .0; z/ = .@ E /.0; z/CE 0l z   .0; z/: (5.68e) +Let us now study the cases jl j = 1 and jl j > 1 in turn. +For jl j = 1, conditions (5.54) on the electric field on the z axis are satisfied automatically: the +fulfilment of condition (5.54b) follows directly from eq. (5.68b), while that of condition (5.54a) is the +5.3. Finite-element simulations of three-dimensional axisymmetric cavities 135 +consequence of eq. (5.68a) and the observation that l = l1 if jl j = 1. The satisfaction of condition +(5.58a) also follows from eqs. (5.68c) and (5.68d), as can be verified by hand (the assumption that O is +gyrotropic on the z axis is crucial here). In contrast, condition (5.58b) is not met automatically, and it +will need to be imposed weakly by help of the contour-integral term in eq. (5.51), as will be demonstrated +below. +For jl j > 1, only condition (5.55c) is automatically fulfilled, by virtue of eq. (5.68b). To satisfy +conditions (5.55a), (5.55b), (5.59a) and (5.55b), homogeneous Dirichlet boundary conditions on E and +E 0z on 0 must explicitly be imposed by removing from the series (5.63) the functions uEn and uEtn +whose  or z components are nonzero on 0. As in the case jl j = 1, the remaining condition (5.59c) will +be imposed weakly. +For all values of l , of course, the perfect-electric-conductor boundary conditions eEn  EE = 0 on 1 +must also be imposed; this can be done in the manner described in the previous paragraph, by removing +appropriate terms from expansion (5.63). +We are now ready to tackle the contour integral from eq. (5.51). The integration path @˝ is the sum +of 0 and 1; let us consider first the latter part of this contour. From the identity .aE  bE/  cE = .cEaE/  bE, +where aE, bE and cE are arbitrary vectors, we get +Z Z +fvE  ŒO1  .rE EEl /g  eEn dl = .vE  eE n/  O1  .rE l EE/ dl: (5.69) +1 1 +But since in the Galerkin’s method the set of test functions is identical with that of basis functions and, +as we have said above, the latter will be chosen so as to fulfil the perfect-electric-conductor boundary +conditions on 1, the cross product vE  eEn will vanish on 1 and this part of the integration path will +bring no contribution to the integral. Integration over 0 is more interesting. Using the aforementioned +identity one more time, we convert the integral to the form +Z Z +fvE  ŒO1  .rE l EE/g  eEn dl = vE  fŒO1  .rE El E/  eEng dl: (5.70) +0 0 +Since on 0 the unit vector eEn = eE, +Z Z Z +fvE ŒO1  .rE l EE/g  eEn dl = ŒO1  .rE l EE/ zv dlC ŒO1  .rE El E/ vz dl: (5.71) +0 0 0 +By conditions (5.58b) and (5.59c), for all l  1 the z component of O1  .rE l EE/ should vanish on 0; +hence, the first term on the right-hand side of eq. (5.71) will approach zero as the FE approximation of a +given cavity eigenmode tends to the true solution. Therefore, we shall omit this term from the discretised +equation (5.51). On the other hand, the second term will vanish because, as we have said above, the +chosen FE expansions satisfy automatically the condition that Ez = 0 on 0 [conditions (5.54b) and +(5.55c)]; hence, vz will disappear on this part of the integration contour. +In this way we have shown that the contour integral can be dropped from the weak form (5.51) of the +vector wave equation of an axisymmetric system. We arrive thus at the final form of this equation: +“ “ +.rE  vE/  O1  .rE EE/ d˝ = k2 vEl l 0  O EE d˝: (5.72) +˝ ˝ +Conversion into algebraic eigenvalue problem In order to convert eq. (5.72) into a system of +algebraic equations, we write it separately for each test function vE = uEn (n = 1; 2; : : : ; N) and vE = uEtn +136 Chapter 5. Numerical methods +(n = 1; 2; : : : ; Nt), substituting for EE expansion (5.63). We assume the cylindrical representation of the +permittivity tensor to have the form 2 3 + ig 0 +O = 4i 5g  0 ; (5.73) +0 0 z +and the permeability tensor to be diagonal, 2 3 + 0 0 +O = 4 0  5 0 ; (5.74) +0 0 z +with the additional constraint that  =  close to the z axis, which is necessary for the boundary con- +ditions on that axis to be met.? The reader will certainly have noted that we have let the tensors O and O +take a more general form than the gyrotropic one from eq. (5.38). This is because we allow for the pres- +ence of PMLs, whose material properties need not have a piecewise-constant Cartesian representation. +After some algebra, we obta"in the following generalised eigenvalueO O #" E # " O O # +p"roble#m: +A At E E 2 B Bt E +O O NE 0 = k0 O O NE 0 ; (5.75)At Att EN Bt t Btt EN t +where EE and EE 0 denote the column vectors of coefficients E and E 0 t n tn, respectively (the underbars +have beNen addedNto distinguish these symbols from those denoting components ofEE), whereas the entries +of matrices AO O˛ˇ“and B˛ˇ (˛; ˇ = ; t) are given by +.AO / = .1@ u0 @ u0 C 1@ u0 @ u0 C l21@ u0 @ u0 mn   z z z z /  d dz; (5.76a) +“ z m n  m n  m n˝ +.AO / = f1@ u0 u0 C 1@ u0 u0t mn z  m n  z m zn +˝ +C l21@ u0 Œu0 .rE  uE0 z m zn t tn/zg  d dz; (5.76b) +.AOt/mn =“.AOt/nm; (5.76c) +.AO / = f1u0 u0 C 1u0 u0tt mn z m n  zm zn +˝ +“C l21 0 E 0 0 E 0 Œuzm .rt  uEtm/zŒuzn .rt  uEtn/zg  d dz; (5.76d) +.BO / = Œ.l2 2l1 mn  g C /u0 u0   d dz; (5.76e) +“ m n˝ +.BO / = Œ.l2 C l1 /u0 u0  2t mn  g m n d dz; (5.76f) +˝ +.BOt/mn = .“BOt/nm; (5.76g) +.BO / = l2. u0 u0 C  u0 u0 / 3tt mn  m n z zm zn d dz: (5.76h) +˝ +In these formulas u0 and u0 denote the  and z components of the basis function uE0n zn tn. It has been +assumed that all the functions u0 and uE0n tn are real-valued. +? It is equally possible to handle the slightly more general case with  =  ¤ 0, at the cost of more complicated +formulas. +5.3. Finite-element simulations of three-dimensional axisymmetric cavities 137 +5.3.3 Numerical implementation +Software We have implemented the method presented in the previous subsection using the Hermes +C++ library [55, 56], which significantly facilitates the development of FE-method-based codes. First, +it provides ready-made implementations of commonly used classes of FEs, including standard nodal +FEs and vector curl-conforming FEs, up to the polynomial order 10. Both triangular and quadrilateral, +recti- and curvilinear elements are available. Second, the library completely automatises the matrix +assembly, allowing also to impose Dirichlet and Neumann boundary conditions on selected portions +of the computational domain’s boundary. In principle, a user of Hermes needs only to write functions +calculating the integrals occurring in the weak form of the differential equation at hand and to specify +the geometry of the computational domain along with the boundary conditions. +Meshing A characteristic feature of axisymmetric cavities produced by etching multilayer structures +is that the material interfaces in any meridional plane are almost always parallel to the  or z axis. This +is the case with all the structures studied in section 4.6. Therefore we have meshed the domain ˝ with +rectangular FEs with sides parallel to eE and eEz . The process of mesh generation for a typical cavity goes +as follows. In the first step,˝ is divided into as many conforming elements as are necessary to ensure that +each interface between two different materials coincides with an interelemental boundary. The elements +created in this way are subsequently subdivided into smaller ones with side lengths approximately equal +to a predefined constant hideal. If desired, the resulting mesh is further uniformly refined by splitting +each element into quarters. This step can be repeated as many times as necessary. +FE expansions The unknown fields E and EE 0 t are expanded into hierarchical polynomial bases pro- +vided by Hermes. The expansion order p, defined as the maximum degree of the polynomials included +in these expansions, is taken to be the same in all elements. +Quadratures All the matrix entries (5.76) are calculated with Gauss-Legendre quadratures. In ele- +ments containing materials with constant O and O , we employ quadratures of the minimum order neces- +sary to ensure their exactness (for the given expansion order p). In elements containing PMLs, whose +material properties depend on the position in a non-polynomial way (see below), the quadrature order is +chosen as greater by ten than that which would ensure exact integration for constant O and O . +Eigenvalue problem solving To solve the complex sparse non-symmetric generalised eigenvalue +problem (5.75), we have used the Krylov-Schur iterative sparse eigenvalue solver implemented in the +SLEPc library [57–59]. Hermes provides interfaces to several popular sparse linear equation solvers; +unfortunately, at present it does not offer integration with any eigenvalue solvers. Therefore we have +written a custom interface between Hermes and SLEPc. +The vector wave equation (5.40) incorporates Gauss’s law rE .O EE/ = 0, but only if k0 ¤ 0 [200]. As +a result, eq. (5.75), derived from (5.40), possesses a large cluster of spurious static solutions that do not +obey Gauss’s law. Therefore even if the lowest-frequency eigenmodes of a given cavity are desired, they +cannot be found by using an iterative eigenvalue solver to find a few lowest-magnitude eigenvalues of +(5.75). Rather, a shift-and-invert transformation of (5.75) must be used to bring the part of its spectrum +closest to a prescribed shift  into the neighbourhood of zero, so that the eigenmodes belonging to this +part of the spectrum may be found by the iterative algorithm [59]. Such spectral transformations are +handled transparently by SLEPc. +It is possible to modify the bases used for field expansions so as to eliminate altogether the spuri- +ous static solutions [201]. Another possibility consists in modifying an iterative eigenvalue solver so +as to prevent it from converging to a solution violating Gauss’s law. This technique has recently been +demonstrated by Venkatarayalu [52]. Although these approaches probably improve the efficiency of +138 Chapter 5. Numerical methods +z +1 +ZC +PML dPML +0 dsup 1 +dsep dPML +R +d sub +PML dPML +Z +1 +Figure 5.11 Geometry of an example domain ˝. Darker regions have larger permittivity. PMLs are hatched. +calculations—in particular, a sparse matrix inversion required by a shift-and-invert transformation is +avoided—their implementation is quite non-trivial. We have therefore stuck to shift-and-invert transfor- +mations, which we found to work very reliably. +Perfectly matched layers As mentioned in the previous subsection, to suppress spurious reflections +due to the finite size of the computational domain, the boundary 1 is coated from inside by PMLs +of thickness dPML, as shown in fig. 5.11. We use standard PMLs adapted for cylindrical coordinates, +which can be interpreted as anisotropic materials with diagonal permittivity tensors O = O and O = O, +where  and  are the material parameters of the “real” media adjacent to PMLs and the diagonal tensor +O  diag.;  ; z/ is responsible for the absorbing properties of the PML. Its elements are given by +[51, 54] + SzQ  SzS ;  Q and z  +SQ +; (5.77) +S  Sz +where   2 +S./  1C  .R dPML/isPML U ; (5.78a) +  dPMLC 2    C .Z dPML/ z z .ZC d / 2PMLSz.z/ 1 isPML U C isPML U ; (5.78b) +dPML dPML +ŒU. .R d //3 +Q PML./  C isPML (5.78c) +3d2 +PML +and U.x/ is x if x > 0 and zero otherwise. The real parameter sPML is called the PML strength. It is +worth noting that for   R dPML we have S./ = Q./ = 1; hence,  =  = Sz , in accord with +our earlier assumption that the tensor O should be gyrotropic close to the z axis. +5.3.4 Evaluation of accuracy +The accuracy of calculations made with the proposed technique is affected by a number of factors, which +can be divided into two groups. The first of them includes the parameters of the FE expansion itself: + typical element size h, + expansion order p. +5.3. Finite-element simulations of three-dimensional axisymmetric cavities 139 +# rin (nm) rout (nm) # rin (nm) rout (nm) +1 1236 1443 11 4618 4765 +2 1656 1828 12 4933 5079 +3 2019 2181 13 5246 5392 +4 2363 2519 14 5559 5705 +5 2696 2849 15 5872 6017 +6 3023 3174 16 6184 6329 +7 3346 3496 17 6495 6640 +8 3667 3816 18 6806 6951 +9 3986 4134 19 7117 7262 +10 4303 4450 20 7428 7572 +Table 5.1 Radii of the high-index rings of the G4-type cavity used to test the accuracy of calculations. The +symbols rin and rout denote the inner and outer radius of a ring, respectively. +nref p C  +0 1 1:25199C 0:00612i 1:25194C 0:00610i +0 2 1:24329C 0:00367i 1:24022C 0:00419i +0 3 1:25691C 0:00340i 1:25384C 0:00387i +0 4 1:26034C 0:00333i 1:25728C 0:00379i +1 1 1:25900C 0:00362i 1:25597C 0:00411i +1 2 1:26133C 0:00333i 1:25827C 0:00378i +1 3 1:26148C 0:00331i 1:25842C 0:00376i +2 1 1:26145C 0:00331i 1:25839C 0:00376i +2 2 1:26149C 0:00331i 1:25843C 0:00376i +Table 5.2 Influence of the number of mesh refinements, nref, and the expansion order p on the calculated values +of the wavelengths ˙ of the counter-rotating modes of the cavity described in the text. The remaining parameters +were chosen as dsub = dsup = 600 nm, dsep = dPML = 500 nm and sPML = 6. +The second is formed by the domain truncation parameters: + substrate thickness dsub, + superstrate thickness dsup, + distance from the outermost inhomogeneity in the multilayer to the inner boundary of the radial +PML, dsep, + PML thickness, dPML, + PML strength, sPML. +In fig. 5.11 graphical definitions of the first four items from the above list are shown. +To determine the values of the above parameters required to get a reasonable accuracy, we have +studied the influence of their variation of the calculated values of the wavelengths C and  of the +modes with azimuthal order l = 10 and 10 of a particular G4-type cavity (see section 4.6) containing +20 high-index rings, whose radii are listed in table 5.1. +We began by testing the dependence of ˙ on h and p. The former was varied as follows: first, in the +way described in subsection 5.3.3, we generated an initial mesh composed of rectangular elements with +side lengths roughly equal to hideal = 150 nm, and subsequently we refined it uniformly nref times. Table +5.2 lists the values of ˙ obtained for a number of combinations .nref; p/; the values of the remaining +parameters are specified in the caption of that table. Clearly, at least one level of refinement is necessary +to get accurate results. This is probably related to the occurrence of field singularities at the edges of +140 Chapter 5. Numerical methods +nsub = nsup C  +0:1 1:26135C 0:00311i 1:25831C 0:00354i +0:2 1:26146C 0:00319i 1:25842C 0:00364i +0:3 1:26150C 0:00325i 1:25845C 0:00370i +0:4 1:26150C 0:00329i 1:25845C 0:00374i +0:5 1:26150C 0:00330i 1:25844C 0:00376i +0:6 1:26149C 0:00331i 1:25843C 0:00376i +0:7 1:26148C 0:00331i 1:25843C 0:00376i +0:8 1:26148C 0:00331i 1:25843C 0:00376i +0:9 1:26148C 0:00331i 1:25842C 0:00376i +1:0 1:26148C 0:00331i 1:25842C 0:00376i +Table 5.3 Influence of the substrate and superstrate thicknesses, dsub and dsup (taken equal to each other) on +the calculated values of the wavelengths ˙ of the counter-rotating modes of the cavity described in the text. The +remaining parameters were chosen as nref = 1, p = 3, dsep = dPML = 500 nm and sPML = 6. +rings; these singularities can be clearly seen on plots of the meridional components ofEE. It is well known +[202, section 3.3] that the convergence of a FE expansion can be accelerated by an additional refinement +of the elements at whose corners singularities occur. +In any case, the data in table 5.2 show that the wavelengths obtained for .nref; p/ = .1; 3/, .2; 1/ +and .2; 2/ differ only with the sixth significant digit. Therefore, one can expect them to have absolute +accuracy of at least 0.1 nm. This is enough for the purposes of the evaluation of the wavelength splitting +  C  between the counter-rotating modes, which is typically on the level on 2–3 nm. For the +remaining calculations we fixed nref = 1 and p = 3. +We studied next the sensitivity of ˙ to the changes of dsub and dsup, for simplicity taking them +to be equal. The results, listed in table 5.3, indicate that the influence of these parameters is negligible +(˙ does not change by more than 0.03 nm) as soon as they are chosen larger than 100 nm. We decided +therefore to stay with the originally assigned values, dsub = dsup = 600 nm. We have also calculated ˙ +as a function of dsep ranging from 100 nm to 800 nm, and found all the obtained values to be identical to +six significant digits. In future calculations we continue to take dsep = 500 nm. +Lastly, we evaluated the dependence of ˙ on the PML parameters, dPML and sPML. We made two +series of calculations, in which the PML strength was fixed to 6 and 12, respectively, while its thickness +was varied from 100 to 800 nm. The results are given in table 5.4. Clearly, for both PML strengths the +wavelengths ˙ converge quickly to practically the same values (˙0:01 nm). +To sum up, the parameters related to the truncation of ˝ have been found to affect little the results +of calculations. Thus, one can be reasonably confident that the data presented in section 4.6, which were +obtained with nref = 1, p = 3, dsub = dsup = 600 nm, dsep = dPML = 500 nm and sPML = 6, are +accurate to about˙0:05 nm, which corresponds to a relative error of 4  105. +5.3. Finite-element simulations of three-dimensional axisymmetric cavities 141 +sPML = 6 sPML = 12 +dPML C  C  +0:1 1:25945C 0:00388i 1:25617C 0:00423i 1:26114C 0:00439i 1:25796C 0:00488i +0:2 1:26107C 0:00385i 1:25793C 0:00430i 1:26163C 0:00331i 1:25858C 0:00378i +0:3 1:26148C 0:00350i 1:25841C 0:00396i 1:26147C 0:00330i 1:25842C 0:00375i +0:4 1:26151C 0:00334i 1:25845C 0:00380i 1:26148C 0:00330i 1:25842C 0:00376i +0:5 1:26149C 0:00331i 1:25843C 0:00376i 1:26148C 0:00331i 1:25842C 0:00376i +0:6 1:26148C 0:00331i 1:25843C 0:00376i 1:26148C 0:00331i 1:25842C 0:00376i +0:7 1:26148C 0:00331i 1:25843C 0:00376i 1:26148C 0:00331i 1:25843C 0:00376i +0:8 1:26148C 0:00331i 1:25842C 0:00376i 1:26148C 0:00331i 1:25843C 0:00376i +Table 5.4 Influence of the PML thickness dPML and PML strength sPML on the calculated values of the wave- +lengths ˙ of the counter-rotating modes of the cavity described in the text. The remaining parameters were chosen +as nref = 1, p = 3, dsub = dsup = 600 nm and dsep = 500 nm. + +Chapter 6 +Conclusions and perspectives +The work whose results have been presented in this thesis encompasses a fairly wide range of topics, +concerning mostly, but not exclusively, those related to PCs. Here we attempt to summarise these results, +putting them in perspective, highlighting those we find the most important, and offering some ideas on +future work. +In chapter 2, the most theoretical one in this thesis, we formulated an effective-medium model of +2D PCs. Using this model, we conducted an in-depth study of the validity of the effective-medium +description of PCs exhibiting the negative-refraction effect. We believe this to have been the first analysis +encompassing both the propagative and the evanescent region and not limited to at most a few discrete +incidence angles. We think we provided convincing arguments that the effective-medium approximation +of PCs with negative refraction is too simplistic and, therefore, such PCs cannot be used as a drop-in +replacement of homogeneous negative-index media. +The rest of the manuscript was more device-oriented. In chapter 3 we presented an algorithm for the +design of AR gratings for PCs and showed its applicability to certain specific PC components. At the +same time, we strived to be explicit about its limitations, which stem from its reliance on a number of +approximations. +It needs to be stressed that the possibilities offered by the numerical shape optimisation procedure, +which is the last step of the proposed algorithm, have not been exploited in full in the examples presented +in section 3.4. For instance, in the case of a flat lens, it is not sufficient that the device pass (almost) all +the incident energy; creation of a high-quality image requires also that the waves incident at different +angles arrive on the image plane with appropriate phases. Thus, it might be more judicious to formulate +the objective function (to be minimised) in terms of the amplitudes and phases of the transmitted waves +rather than the reflected ones. This would also allow to optimise the transmission of the evanescent +waves, and hence, possibly, to overcome the diffraction limit. +In chapter 4 we reported on our work on magneto-optical circulators. The crucial step was the +idea of studying closely the class of resonant cavities having the rotational symmetry. It led to the +formulation of a novel design principle for uniformly magnetised, and therefore manufacturable, cavities +that nonetheless exhibit a substantial mode frequency splitting. We then initially pursued the beaten +path of PC-based circulator designs. It was M. Vanwolleghem (Institut d’Electronique Fondamentale, +Orsay, France) who first suggested testing simpler systems based on uniform waveguides. Despite initial +problems with securing a sufficient degree of coupling between such waveguides and the central cavity (it +was not possible to use side-coupling owing to an extreme phase mismatch between the waveguide and +cavity modes), we finally succeeded by employing butt-coupling instead of side-coupling and optimising +the shape of the waveguide slot. +As we have remarked in section 4.5.4, the circulator designed on the basis of 2D calculations did +not fare well in experiment owing to excessive out-of-plane losses. In March 2010 it was therefore +deemed necessary to turn to 3D simulations. Good progress has already been made; in particular, at +143 +144 Chapter 6. Conclusions and perspectives +the end of section 4.6.2 we presented a 3D cavity with markedly reduced radiation losses. To arrive at +an experimental demonstration of a working circulator, however, further work is still necessary. The +optimisation should be repeated using the exact value of the refractive index of the potential coating +material, silicon nitride. More importantly, we do not understand yet the mechanism for the improvement +of the mode confinement provided by the optimised cavity. A Bloch-mode-based theory might be able +to explain this effect. We also hope that it will lead to successful designs—no longer based on the +effective-index approximation—of uncoated cavities, which should have smaller footprint than coated +ones, thanks to stronger in-plane mode localisation. +Even if a satisfactory 3D model of axisymmetric cavities is established in future, some numerical +optimisation of their geometry may still be necessary, or at least desirable. It is well known that gradient- +based optimisation techniques are in general more efficient than derivative-free methods, such as the +NEWUOA algorithm used thus far. It should be quite possible to calculate the derivative of the frequency +splitting ! of a given cavity over the radius of any particular ring, symbolically denoted r here. The +derivative of the eigenvalue k20 of the problem eq. (5.75) over r is simple to calculate, at least assuming +that there are no repeated eigenvalues: +2 @k @AO @BO 0 = yEŽ  k20  xE; (6.1)@r @r @r +where xE and yE are the right and left eigenvectors corresponding to k2 and normalised so that yEŽ0 BO xE = 1. +(See refs. 203 and 204 for a review on the computation of eigenvalue derivatives.) The derivatives of AO +and BO over r can be evaluated from the explicit formulas (5.76) for their entries. +An optimised cavity will eventually need to be integrated with the input and output waveguides. +Which numerical method will be most suitable for the simulation of the complete 3D system is not clear +yet; some views on this matter have been offered in the conclusions to chapter 4. +Finally, as noted in section 4.1.3, Yu et al. [155] have recently proposed theoretically an isolator based +on time-dependent refractive-index modulation. In the structure presented in their article, introduction of +a boundary separating the modulated and unmodulated parts of the waveguides is needed; this requires +a precise alignment of the electric field enforcing the modification of the refractive index. 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Ces réseaux permettent d’améliorer significativement la transmission à travers une +lentille plate d’indice négatif. +Nous proposons une nouvelle génération de circulateurs magnétooptiques compacts, fonctionnant +dans un champ magnétique extérieur uniforme et constitués d’une cavité résonnante en anneaux circu- +laires couplée directement à des guides d’ondes standards. +Nous généralisons la méthode multipolaire 2D aux matériaux gyrotropiques et la formulons sans +« lattice sums » pour les structures périodiques. Enfin, nous décrivons en détail la méthode des éléments +finis pour le calcul des modes propres des cavités 3D en anneaux circulaires et matériaux gyrotropiques. +Mots clés cristaux photoniques, composants magnétooptiques, théories du milieu effectif, réseaux +antiréfléchissants, méthodes numériques, optique intégrée. +Design and numerical modelling of integrated optical components +Abstract This thesis is devoted to the design and theoretical and numerical analysis of a number of +photonic crystal (PC) components. In its first part we study the influence of the surface structure of +two-dimensional (2D) PCs on their optical properties. We formulate an effective-medium model of +such PCs, able to reproduce the commonly observed strong dependence of their effective parameters +on the position of their truncation plane. We then develop an algorithm for the design of compact +wide-angle antireflection gratings for 2D PCs and show them to improve significantly the transmission +through a PC flat lens. +In the second part of the manuscript we introduce a new approach to the design of resonant cavities +to be used in compact magneto-optical circulators. In contrast to structures proposed previously, they +are devoid of oppositely-polarised magnetic domains, which significantly facilitates their fabrication. We +show that these cavities need not be embedded in PCs, but can be coupled directly with standard rib +waveguides. +Some numerical techniques developed in the course of this thesis are presented in the last part +of the manuscript. We extend the multiple-scattering method to the case of gyrotropic materials and +introduce a straightforward and extremely accurate method for the calculation of band structures of +2D PCs composed of circular cylinders, based on Fourier-Bessel expansions. Finally, we describe the +implementation of the finite-element method for the calculation of eigenmodes of open, axisymmetric, +three-dimensional cavities containing gyrotropic materials. +Keywords photonic crystals, magneto-optical devices, effective-medium theory, antireflection gratings, +numerical methods, integrated optics. +Laboratoire d’accueil Équipe CLARTE, Institut Fresnel, Campus de Saint Jérôme, +avenue Escadrille Normandie-Niemen, 13397 Marseille Cedex 20 +Formation doctorale physique théorique et mathématique diff --git a/examples/theses/these_archivage_2903871_-_ziyadeh_-_optimise.pdf b/examples/theses/these_archivage_2903871_-_ziyadeh_-_optimise.pdf new file mode 100644 index 00000000..a5cf3014 Binary files /dev/null and b/examples/theses/these_archivage_2903871_-_ziyadeh_-_optimise.pdf differ diff --git a/examples/theses/these_archivage_3274485.pdf b/examples/theses/these_archivage_3274485.pdf new file mode 100644 index 00000000..c929fcf9 Binary files /dev/null and b/examples/theses/these_archivage_3274485.pdf differ diff --git a/pom.xml b/pom.xml index 39be6284..3e59f66e 100644 --- a/pom.xml +++ b/pom.xml @@ -214,25 +214,11 @@ gson 2.3.1 - org.xml-cml svg2xml 0.1-SNAPSHOT -