Skip to content

Commit

Permalink
Merge pull request #6147 from openjournals/joss.07205
Browse files Browse the repository at this point in the history
Merging automatically
  • Loading branch information
editorialbot authored Nov 15, 2024
2 parents e10636a + 0b3355c commit ae1649e
Show file tree
Hide file tree
Showing 4 changed files with 972 additions and 0 deletions.
325 changes: 325 additions & 0 deletions joss.07205/10.21105.joss.07205.crossref.xml
Original file line number Diff line number Diff line change
@@ -0,0 +1,325 @@
<?xml version="1.0" encoding="UTF-8"?>
<doi_batch xmlns="http://www.crossref.org/schema/5.3.1"
xmlns:ai="http://www.crossref.org/AccessIndicators.xsd"
xmlns:rel="http://www.crossref.org/relations.xsd"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
version="5.3.1"
xsi:schemaLocation="http://www.crossref.org/schema/5.3.1 http://www.crossref.org/schemas/crossref5.3.1.xsd">
<head>
<doi_batch_id>20241115201036-e0bbc5c513db4f3cb44254dc894fec170e258398</doi_batch_id>
<timestamp>20241115201036</timestamp>
<depositor>
<depositor_name>JOSS Admin</depositor_name>
<email_address>[email protected]</email_address>
</depositor>
<registrant>The Open Journal</registrant>
</head>
<body>
<journal>
<journal_metadata>
<full_title>Journal of Open Source Software</full_title>
<abbrev_title>JOSS</abbrev_title>
<issn media_type="electronic">2475-9066</issn>
<doi_data>
<doi>10.21105/joss</doi>
<resource>https://joss.theoj.org</resource>
</doi_data>
</journal_metadata>
<journal_issue>
<publication_date media_type="online">
<month>11</month>
<year>2024</year>
</publication_date>
<journal_volume>
<volume>9</volume>
</journal_volume>
<issue>103</issue>
</journal_issue>
<journal_article publication_type="full_text">
<titles>
<title>cifkit: A Python package for coordination geometry and
atomic site analysis</title>
</titles>
<contributors>
<person_name sequence="first" contributor_role="author">
<given_name>Sangjoon</given_name>
<surname>Lee</surname>
<affiliations>
<institution><institution_name>Department of Applied Physics and Applied Mathematics, Columbia University, New York, NY 10027, United States</institution_name></institution>
</affiliations>
<ORCID>https://orcid.org/0000-0002-2367-3932</ORCID>
</person_name>
<person_name sequence="additional"
contributor_role="author">
<given_name>Anton O.</given_name>
<surname>Oliynyk</surname>
<affiliations>
<institution><institution_name>Department of Chemistry, Hunter College, City University of New York, New York, NY 10065, United States</institution_name></institution>
<institution><institution_name>Ph.D. Program in Chemistry, The Graduate Center of the City University of New York, New York, NY 10016, United States</institution_name></institution>
</affiliations>
<ORCID>https://orcid.org/0000-0003-0732-7340</ORCID>
</person_name>
</contributors>
<publication_date>
<month>11</month>
<day>15</day>
<year>2024</year>
</publication_date>
<pages>
<first_page>7205</first_page>
</pages>
<publisher_item>
<identifier id_type="doi">10.21105/joss.07205</identifier>
</publisher_item>
<ai:program name="AccessIndicators">
<ai:license_ref applies_to="vor">http://creativecommons.org/licenses/by/4.0/</ai:license_ref>
<ai:license_ref applies_to="am">http://creativecommons.org/licenses/by/4.0/</ai:license_ref>
<ai:license_ref applies_to="tdm">http://creativecommons.org/licenses/by/4.0/</ai:license_ref>
</ai:program>
<rel:program>
<rel:related_item>
<rel:description>Software archive</rel:description>
<rel:inter_work_relation relationship-type="references" identifier-type="doi">10.5281/zenodo.14086943</rel:inter_work_relation>
</rel:related_item>
<rel:related_item>
<rel:description>GitHub review issue</rel:description>
<rel:inter_work_relation relationship-type="hasReview" identifier-type="uri">https://github.com/openjournals/joss-reviews/issues/7205</rel:inter_work_relation>
</rel:related_item>
</rel:program>
<doi_data>
<doi>10.21105/joss.07205</doi>
<resource>https://joss.theoj.org/papers/10.21105/joss.07205</resource>
<collection property="text-mining">
<item>
<resource mime_type="application/pdf">https://joss.theoj.org/papers/10.21105/joss.07205.pdf</resource>
</item>
</collection>
</doi_data>
<citation_list>
<citation key="tyvanchuk_crystal_2024">
<article_title>The crystal and electronic structure of
RE23Co6.7In20.3 (RE = Gd–Tm, Lu): A new structure type based on
intergrowth of AlB2- and CsCl-type related slabs</article_title>
<author>Tyvanchuk</author>
<journal_title>Journal of Alloys and
Compounds</journal_title>
<volume>976</volume>
<doi>10.1016/j.jallcom.2023.173241</doi>
<issn>0925-8388</issn>
<cYear>2024</cYear>
<unstructured_citation>Tyvanchuk, Y., Babizhetskyy, V.,
Baran, S., Szytuła, A., Smetana, V., Lee, S., Oliynyk, A. O., &amp;
Mudring, A.-V. (2024). The crystal and electronic structure of
RE23Co6.7In20.3 (RE = Gd–Tm, Lu): A new structure type based on
intergrowth of AlB2- and CsCl-type related slabs. Journal of Alloys and
Compounds, 976, 173241.
https://doi.org/10.1016/j.jallcom.2023.173241</unstructured_citation>
</citation>
<citation key="lee_machine_2024">
<article_title>Machine learning descriptors in materials
chemistry used in multiple experimentally validated studies: Oliynyk
elemental property dataset</article_title>
<author>Lee</author>
<journal_title>Data in Brief</journal_title>
<volume>53</volume>
<doi>10.1016/j.dib.2024.110178</doi>
<issn>2352-3409</issn>
<cYear>2024</cYear>
<unstructured_citation>Lee, S., Chen, C., Garcia, G., &amp;
Oliynyk, A. (2024). Machine learning descriptors in materials chemistry
used in multiple experimentally validated studies: Oliynyk elemental
property dataset. Data in Brief, 53.
https://doi.org/10.1016/j.dib.2024.110178</unstructured_citation>
</citation>
<citation key="barua_interpretable_2024">
<article_title>Interpretable machine learning model on
thermal conductivity using publicly available datasets and our internal
lab dataset</article_title>
<author>Barua</author>
<journal_title>Chemistry of Materials</journal_title>
<issue>14</issue>
<volume>36</volume>
<doi>10.1021/acs.chemmater.4c01696</doi>
<issn>0897-4756</issn>
<cYear>2024</cYear>
<unstructured_citation>Barua, N. K., Hall, E., Cheng, Y.,
Oliynyk, A. O., &amp; Kleinke, H. (2024). Interpretable machine learning
model on thermal conductivity using publicly available datasets and our
internal lab dataset. Chemistry of Materials, 36(14), 7089–7100.
https://doi.org/10.1021/acs.chemmater.4c01696</unstructured_citation>
</citation>
<citation key="larsen_atomic_2017">
<article_title>The atomic simulation environment—a python
library for working with atoms</article_title>
<author>Larsen</author>
<journal_title>Journal of Physics: Condensed
Matter</journal_title>
<issue>27</issue>
<volume>29</volume>
<doi>10.1088/1361-648X/aa680e</doi>
<issn>0953-8984</issn>
<cYear>2017</cYear>
<unstructured_citation>Larsen, A. H., Mortensen, J. J.,
Blomqvist, J., Castelli, I. E., Christensen, R., Dułak, M., Friis, J.,
Groves, M. N., Hammer, B., Hargus, C., Hermes, E. D., Jennings, P. C.,
Jensen, P. B., Kermode, J., Kitchin, J. R., Kolsbjerg, E. L., Kubal, J.,
Kaasbjerg, K., Lysgaard, S., … Jacobsen, K. W. (2017). The atomic
simulation environment—a python library for working with atoms. Journal
of Physics: Condensed Matter, 29(27), 273002.
https://doi.org/10.1088/1361-648X/aa680e</unstructured_citation>
</citation>
<citation key="hall_crystallographic_1991">
<article_title>The crystallographic information file (CIF):
A new standard archive file for crystallography</article_title>
<author>Hall</author>
<journal_title>Acta Crystallographica Section
A</journal_title>
<issue>6</issue>
<volume>47</volume>
<doi>10.1107/S010876739101067X</doi>
<issn>1600-5724</issn>
<cYear>1991</cYear>
<unstructured_citation>Hall, S. R., Allen, F. H., &amp;
Brown, I. D. (1991). The crystallographic information file (CIF): A new
standard archive file for crystallography. Acta Crystallographica
Section A, 47(6), 655–685.
https://doi.org/10.1107/S010876739101067X</unstructured_citation>
</citation>
<citation key="ong_python_2013">
<article_title>Python materials genomics (pymatgen): A
robust, open-source python library for materials
analysis</article_title>
<author>Ong</author>
<journal_title>Computational Materials
Science</journal_title>
<volume>68</volume>
<doi>10.1016/j.commatsci.2012.10.028</doi>
<issn>0927-0256</issn>
<cYear>2013</cYear>
<unstructured_citation>Ong, S. P., Richards, W. D., Jain,
A., Hautier, G., Kocher, M., Cholia, S., Gunter, D., Chevrier, V. L.,
Persson, K. A., &amp; Ceder, G. (2013). Python materials genomics
(pymatgen): A robust, open-source python library for materials analysis.
Computational Materials Science, 68, 314–319.
https://doi.org/10.1016/j.commatsci.2012.10.028</unstructured_citation>
</citation>
<citation key="waroquiers_chemenv_2020">
<article_title>ChemEnv: A fast and robust coordination
environment identification tool</article_title>
<author>Waroquiers</author>
<journal_title>Acta Crystallographica Section B: Structural
Science, Crystal Engineering and Materials</journal_title>
<issue>4</issue>
<volume>76</volume>
<doi>10.1107/S2052520620007994</doi>
<issn>2052-5206</issn>
<cYear>2020</cYear>
<unstructured_citation>Waroquiers, D., George, J., Horton,
M., Schenk, S., Persson, K. A., Rignanese, G.-M., Gonze, X., &amp;
Hautier, G. (2020). ChemEnv: A fast and robust coordination environment
identification tool. Acta Crystallographica Section B: Structural
Science, Crystal Engineering and Materials, 76(4), 683–695.
https://doi.org/10.1107/S2052520620007994</unstructured_citation>
</citation>
<citation key="sullivan_pyvista_2019">
<article_title>PyVista: 3D plotting and mesh analysis
through a streamlined interface for the visualization toolkit
(VTK)</article_title>
<author>Sullivan</author>
<journal_title>Journal of Open Source
Software</journal_title>
<issue>37</issue>
<volume>4</volume>
<doi>10.21105/joss.01450</doi>
<issn>2475-9066</issn>
<cYear>2019</cYear>
<unstructured_citation>Sullivan, C. B., &amp; Kaszynski, A.
A. (2019). PyVista: 3D plotting and mesh analysis through a streamlined
interface for the visualization toolkit (VTK). Journal of Open Source
Software, 4(37), 1450.
https://doi.org/10.21105/joss.01450</unstructured_citation>
</citation>
<citation key="wojdyr_gemmi_2022">
<article_title>GEMMI: A library for structural
biology</article_title>
<author>Wojdyr</author>
<journal_title>Journal of Open Source
Software</journal_title>
<issue>73</issue>
<volume>7</volume>
<doi>10.21105/joss.04200</doi>
<issn>2475-9066</issn>
<cYear>2022</cYear>
<unstructured_citation>Wojdyr, M. (2022). GEMMI: A library
for structural biology. Journal of Open Source Software, 7(73), 4200.
https://doi.org/10.21105/joss.04200</unstructured_citation>
</citation>
<citation key="harris_array_2020">
<article_title>Array programming with NumPy</article_title>
<author>Harris</author>
<journal_title>Nature</journal_title>
<issue>7825</issue>
<volume>585</volume>
<doi>10.1038/s41586-020-2649-2</doi>
<issn>1476-4687</issn>
<cYear>2020</cYear>
<unstructured_citation>Harris, C. R., Millman, K. J., Walt,
S. J. van der, Gommers, R., Virtanen, P., Cournapeau, D., Wieser, E.,
Taylor, J., Berg, S., Smith, N. J., Kern, R., Picus, M., Hoyer, S.,
Kerkwijk, M. H. van, Brett, M., Haldane, A., Río, J. F. del, Wiebe, M.,
Peterson, P., … Oliphant, T. E. (2020). Array programming with NumPy.
Nature, 585(7825), 357–362.
https://doi.org/10.1038/s41586-020-2649-2</unstructured_citation>
</citation>
<citation key="virtanen_scipy_2020">
<article_title>SciPy 1.0: Fundamental algorithms for
scientific computing in python</article_title>
<author>Virtanen</author>
<journal_title>Nature Methods</journal_title>
<issue>3</issue>
<volume>17</volume>
<doi>10.1038/s41592-019-0686-2</doi>
<issn>1548-7105</issn>
<cYear>2020</cYear>
<unstructured_citation>Virtanen, P., Gommers, R., Oliphant,
T. E., Haberland, M., Reddy, T., Cournapeau, D., Burovski, E., Peterson,
P., Weckesser, W., Bright, J., Walt, S. J. van der, Brett, M., Wilson,
J., Millman, K. J., Mayorov, N., Nelson, A. R. J., Jones, E., Kern, R.,
Larson, E., … Mulbregt, P. van. (2020). SciPy 1.0: Fundamental
algorithms for scientific computing in python. Nature Methods, 17(3),
261–272.
https://doi.org/10.1038/s41592-019-0686-2</unstructured_citation>
</citation>
<citation key="hunter_matplotlib_2007">
<article_title>Matplotlib: A 2D graphics
environment</article_title>
<author>Hunter</author>
<journal_title>Computing in Science &amp;
Engineering</journal_title>
<issue>3</issue>
<volume>9</volume>
<doi>10.1109/MCSE.2007.55</doi>
<issn>1558-366X</issn>
<cYear>2007</cYear>
<unstructured_citation>Hunter, J. D. (2007). Matplotlib: A
2D graphics environment. Computing in Science &amp; Engineering, 9(3),
90–95. https://doi.org/10.1109/MCSE.2007.55</unstructured_citation>
</citation>
<citation key="jaffal_composition_2024">
<article_title>Composition and structure analyzer/featurizer
for explainable machine-learning models to predict solid state
structures</article_title>
<author>Jaffal</author>
<doi>10.26434/chemrxiv-2024-rrbhc</doi>
<cYear>2024</cYear>
<unstructured_citation>Jaffal, E., Lee, S., Shiryaev, D.,
Vtorov, A., Barua, N., Kleinke, H., &amp; Oliynyk, A. (2024).
Composition and structure analyzer/featurizer for explainable
machine-learning models to predict solid state structures. ChemRxiv.
https://doi.org/10.26434/chemrxiv-2024-rrbhc</unstructured_citation>
</citation>
</citation_list>
</journal_article>
</journal>
</body>
</doi_batch>
Binary file added joss.07205/10.21105.joss.07205.pdf
Binary file not shown.
Loading

0 comments on commit ae1649e

Please sign in to comment.