From 7e382d80b8b37fb7beaeaa53d13e0c4bf15f994c Mon Sep 17 00:00:00 2001
From: Jan Janssen <janssen@lanl.gov>
Date: Fri, 11 Aug 2023 15:08:21 -0600
Subject: [PATCH] Add notebook from live demonstration

---
 demo.ipynb | 2076 ++++++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 2076 insertions(+)
 create mode 100644 demo.ipynb

diff --git a/demo.ipynb b/demo.ipynb
new file mode 100644
index 0000000..3c614a0
--- /dev/null
+++ b/demo.ipynb
@@ -0,0 +1,2076 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "145b3354-3cf3-4588-937b-a623475e561f",
+   "metadata": {},
+   "source": [
+    "# Demo\n",
+    "Demonstrate pyiron for LAMMPS users. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "7ebda36b-38e3-4540-95c4-61ecc9941a99",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "487adf72653e441a81d5562b5d2a3208",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": []
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "from pyiron_atomistics import Project"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "d88e373f-05ff-4b35-857e-22883f6a17ff",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "pr = Project(\"demo\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "433b13d1-44e0-4b3f-ad11-f5d94a15fa2e",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'/home/janssen/pyiron/projects/2023-08-11-lammps-workshop/demo/'"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pr.path"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "57751a11-f1ad-41e7-8119-4b942a346965",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>id</th>\n",
+       "      <th>status</th>\n",
+       "      <th>chemicalformula</th>\n",
+       "      <th>job</th>\n",
+       "      <th>subjob</th>\n",
+       "      <th>projectpath</th>\n",
+       "      <th>project</th>\n",
+       "      <th>timestart</th>\n",
+       "      <th>timestop</th>\n",
+       "      <th>totalcputime</th>\n",
+       "      <th>computer</th>\n",
+       "      <th>hamilton</th>\n",
+       "      <th>hamversion</th>\n",
+       "      <th>parentid</th>\n",
+       "      <th>masterid</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>21751</td>\n",
+       "      <td>finished</td>\n",
+       "      <td>Al4</td>\n",
+       "      <td>lmp</td>\n",
+       "      <td>/lmp</td>\n",
+       "      <td>/home/janssen/pyiron/projects/</td>\n",
+       "      <td>2023-08-11-lammps-workshop/demo/</td>\n",
+       "      <td>2023-08-11 12:21:17.571885</td>\n",
+       "      <td>2023-08-11 12:21:18.193762</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>pyiron@ljubi#1</td>\n",
+       "      <td>Lammps</td>\n",
+       "      <td>0.1</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      id    status chemicalformula  job subjob  \\\n",
+       "0  21751  finished             Al4  lmp   /lmp   \n",
+       "\n",
+       "                      projectpath                           project  \\\n",
+       "0  /home/janssen/pyiron/projects/  2023-08-11-lammps-workshop/demo/   \n",
+       "\n",
+       "                   timestart                   timestop  totalcputime  \\\n",
+       "0 2023-08-11 12:21:17.571885 2023-08-11 12:21:18.193762           0.0   \n",
+       "\n",
+       "         computer hamilton hamversion parentid masterid  \n",
+       "0  pyiron@ljubi#1   Lammps        0.1     None     None  "
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pr.job_table()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "3f643ebc-390c-4591-abf8-fde88e642b73",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# pr.remove_jobs()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "bdac98d2-b3ac-44c2-b268-550e1faeaf72",
+   "metadata": {},
+   "source": [
+    "# Atomistic structures"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "9fa5aa25-9b43-4467-bef3-bd0674d26aa9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "structure = pr.create.structure.ase.bulk(\"Al\", cubic=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "1938a06d-630b-4e91-a1e3-d91077059d27",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Al: [0. 0. 0.]\n",
+       "Al: [0.    2.025 2.025]\n",
+       "Al: [2.025 0.    2.025]\n",
+       "Al: [2.025 2.025 0.   ]\n",
+       "tags: \n",
+       "    indices: [0 0 0 0]\n",
+       "pbc: [ True  True  True]\n",
+       "cell: \n",
+       "Cell([4.05, 4.05, 4.05])"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "structure"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "cd4903a5-4a39-4a37-83a6-7b2cda80038b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "6c0ccc00a696493189e3861132cefb4b",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "NGLWidget()"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "structure.plot3d()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "id": "825f43cc-d6d4-46c5-80e8-859054332483",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "structure_big = structure.repeat([4,4,4])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "id": "775c3738-c0ee-4971-a577-a6e87e262368",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "del structure_big[10]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "id": "3202586b-7f30-4c63-afad-aacf2d5780e0",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "ddb1b2aec10c49559984ca1bb34fca73",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "NGLWidget()"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "structure_big.plot3d()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "252feff8-6460-49aa-ba59-a5f874818666",
+   "metadata": {},
+   "source": [
+    "# LAMMPS calculation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "c4b97fb4-3f96-4072-aad3-998872d7dfdc",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "job = pr.create.job.Lammps(job_name=\"lmp\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "e188d5d2-4ec2-438d-ae26-b821f5c1a6c0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "job.structure = structure"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "962e3852-641c-4926-8ff0-731ff081a981",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Config</th>\n",
+       "      <th>Filename</th>\n",
+       "      <th>Model</th>\n",
+       "      <th>Name</th>\n",
+       "      <th>Species</th>\n",
+       "      <th>Citations</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>39</th>\n",
+       "      <td>[pair_style eam/alloy\\n, pair_coeff * * NiAlH_jea.eam.alloy Ni Al H\\n]</td>\n",
+       "      <td>[potential_LAMMPS/1995--Angelo-J-E--Ni-Al-H--LAMMPS--ipr1/NiAlH_jea.eam.alloy]</td>\n",
+       "      <td>NISTiprpy</td>\n",
+       "      <td>1995--Angelo-J-E--Ni-Al-H--LAMMPS--ipr1</td>\n",
+       "      <td>[Ni, Al, H]</td>\n",
+       "      <td>[{'Angelo_1995': {'title': 'Trapping of hydrogen to lattice defects in nickel', 'journal': 'Modelling and Simulation in Materials Science and Engineering', 'volume': '3', 'pages': '289--307', 'num...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>40</th>\n",
+       "      <td>[pair_style eam/alloy\\n, pair_coeff * * Farkas_Nb-Ti-Al_1996.eam.alloy Nb Ti Al\\n]</td>\n",
+       "      <td>[potential_LAMMPS/1996--Farkas-D--Nb-Ti-Al--LAMMPS--ipr1/Farkas_Nb-Ti-Al_1996.eam.alloy]</td>\n",
+       "      <td>NISTiprpy</td>\n",
+       "      <td>1996--Farkas-D--Nb-Ti-Al--LAMMPS--ipr1</td>\n",
+       "      <td>[Nb, Ti, Al]</td>\n",
+       "      <td>[{'Farkas_1996': {'title': 'Interatomic potentials for ternary Nb - Ti - Al alloys', 'journal': 'Modelling and Simulation in Materials Science and Engineering', 'volume': '4', 'pages': '23--32', '...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>43</th>\n",
+       "      <td>[pair_style eam/alloy\\n, pair_coeff * * mg-al-set.eam.alloy Al Mg\\n]</td>\n",
+       "      <td>[potential_LAMMPS/1997--Liu-X-Y--Al-Mg--LAMMPS--ipr1/mg-al-set.eam.alloy]</td>\n",
+       "      <td>NISTiprpy</td>\n",
+       "      <td>1997--Liu-X-Y--Al-Mg--LAMMPS--ipr1</td>\n",
+       "      <td>[Al, Mg]</td>\n",
+       "      <td>[{'Liu_1997': {'title': 'Anisotropic surface segregation in Al-Mg alloys', 'journal': 'Surface Science', 'volume': '373', 'pages': '357--370', 'number': '2-3', 'doi': '10.1016/s0039-6028(96)01154-...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>46</th>\n",
+       "      <td>[pair_style eam/alloy\\n, pair_coeff * * almg.liu.eam.alloy Al Mg\\n]</td>\n",
+       "      <td>[potential_LAMMPS/1998--Liu-X-Y--Al-Mg--LAMMPS--ipr1/almg.liu.eam.alloy]</td>\n",
+       "      <td>NISTiprpy</td>\n",
+       "      <td>1998--Liu-X-Y--Al-Mg--LAMMPS--ipr1</td>\n",
+       "      <td>[Al, Mg]</td>\n",
+       "      <td>[{'Liu_1998': {'title': 'Grain-boundary segregation in Al-10%Mg alloys at hot working temperatures', 'journal': 'Acta Materialia', 'volume': '46', 'pages': '3467--3476', 'number': '10', 'doi': '10...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>48</th>\n",
+       "      <td>[pair_style eam/alloy\\n, pair_coeff * * al-cu-set.eam.alloy Al Cu\\n]</td>\n",
+       "      <td>[potential_LAMMPS/1999--Liu-X-Y--Al-Cu--LAMMPS--ipr1/al-cu-set.eam.alloy]</td>\n",
+       "      <td>NISTiprpy</td>\n",
+       "      <td>1999--Liu-X-Y--Al-Cu--LAMMPS--ipr1</td>\n",
+       "      <td>[Al, Cu]</td>\n",
+       "      <td>[{'Liu_1999': {'title': \"A new investigation of copper's role in enhancing Al-Cu interconnect electromigration resistance from an atomistic view\", 'journal': 'Acta Materialia', 'volume': '47', 'pa...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>948</th>\n",
+       "      <td>[pair_style kim Sim_LAMMPS_MEAM_JelinekGrohHorstemeyer_2012_AlSiMgCuFe__SM_656517352485_000\\n, pair_coeff * * Al Si Mg Cu Fe\\n]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>OPENKIM</td>\n",
+       "      <td>Sim_LAMMPS_MEAM_JelinekGrohHorstemeyer_2012_AlSiMgCuFe__SM_656517352485_000</td>\n",
+       "      <td>[Al, Si, Mg, Cu, Fe]</td>\n",
+       "      <td>[{'B._2012': {'title': 'Modified embedded atom method potential for Al, Si, Mg, Cu, and Fe alloys', 'volume': '85', 'year': '2012', 'journal': 'Physical Review B', 'doi': '10.1103/PhysRevB.85.2451...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>958</th>\n",
+       "      <td>[pair_style kim Sim_LAMMPS_MEAM_PascuetFernandez_2015_AlU__SM_721930391003_000\\n, pair_coeff * * Al U\\n]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>OPENKIM</td>\n",
+       "      <td>Sim_LAMMPS_MEAM_PascuetFernandez_2015_AlU__SM_721930391003_000</td>\n",
+       "      <td>[Al, U]</td>\n",
+       "      <td>[{'M.I._2015': {'title': '{A}tomic interaction of the {MEAM} type for the study of intermetallics in the {A}l–{U} alloy', 'volume': '467', 'year': '2015', 'journal': 'Journal of Nuclear Materials'...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>959</th>\n",
+       "      <td>[pair_style kim Sim_LAMMPS_MEAM_PascuetFernandez_2015_Al__SM_811588957187_000\\n, pair_coeff * * Al\\n]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>OPENKIM</td>\n",
+       "      <td>Sim_LAMMPS_MEAM_PascuetFernandez_2015_Al__SM_811588957187_000</td>\n",
+       "      <td>[Al]</td>\n",
+       "      <td>[{'M.I._2015': {'title': '{A}tomic interaction of the {MEAM} type for the study of intermetallics in the {A}l–{U} alloy', 'volume': '467', 'year': '2015', 'journal': 'Journal of Nuclear Materials'...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>979</th>\n",
+       "      <td>[pair_style kim Sim_LAMMPS_SMTBQ_SallesPolitanoAmzallag_2016_AlO__SM_853967355976_000\\n, pair_coeff * * Al O\\n]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>OPENKIM</td>\n",
+       "      <td>Sim_LAMMPS_SMTBQ_SallesPolitanoAmzallag_2016_AlO__SM_853967355976_000</td>\n",
+       "      <td>[Al, O]</td>\n",
+       "      <td>[{'N._2016': {'title': 'Molecular dynamics study of high-pressure alumina polymorphs with a tight-binding variable-charge model', 'volume': '111', 'year': '2016', 'journal': 'Computational Materia...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>980</th>\n",
+       "      <td>[pair_style kim Sim_LAMMPS_SMTBQ_SallesPolitanoAmzallag_2016_Al__SM_404097633924_000\\n, pair_coeff * * Al\\n]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>OPENKIM</td>\n",
+       "      <td>Sim_LAMMPS_SMTBQ_SallesPolitanoAmzallag_2016_Al__SM_404097633924_000</td>\n",
+       "      <td>[Al]</td>\n",
+       "      <td>[{'N._2016': {'title': 'Molecular dynamics study of high-pressure alumina polymorphs with a tight-binding variable-charge model', 'volume': '111', 'year': '2016', 'journal': 'Computational Materia...</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>136 rows × 6 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                                                                                                              Config  \\\n",
+       "39                                                            [pair_style eam/alloy\\n, pair_coeff * * NiAlH_jea.eam.alloy Ni Al H\\n]   \n",
+       "40                                                [pair_style eam/alloy\\n, pair_coeff * * Farkas_Nb-Ti-Al_1996.eam.alloy Nb Ti Al\\n]   \n",
+       "43                                                              [pair_style eam/alloy\\n, pair_coeff * * mg-al-set.eam.alloy Al Mg\\n]   \n",
+       "46                                                               [pair_style eam/alloy\\n, pair_coeff * * almg.liu.eam.alloy Al Mg\\n]   \n",
+       "48                                                              [pair_style eam/alloy\\n, pair_coeff * * al-cu-set.eam.alloy Al Cu\\n]   \n",
+       "..                                                                                                                               ...   \n",
+       "948  [pair_style kim Sim_LAMMPS_MEAM_JelinekGrohHorstemeyer_2012_AlSiMgCuFe__SM_656517352485_000\\n, pair_coeff * * Al Si Mg Cu Fe\\n]   \n",
+       "958                         [pair_style kim Sim_LAMMPS_MEAM_PascuetFernandez_2015_AlU__SM_721930391003_000\\n, pair_coeff * * Al U\\n]   \n",
+       "959                            [pair_style kim Sim_LAMMPS_MEAM_PascuetFernandez_2015_Al__SM_811588957187_000\\n, pair_coeff * * Al\\n]   \n",
+       "979                  [pair_style kim Sim_LAMMPS_SMTBQ_SallesPolitanoAmzallag_2016_AlO__SM_853967355976_000\\n, pair_coeff * * Al O\\n]   \n",
+       "980                     [pair_style kim Sim_LAMMPS_SMTBQ_SallesPolitanoAmzallag_2016_Al__SM_404097633924_000\\n, pair_coeff * * Al\\n]   \n",
+       "\n",
+       "                                                                                     Filename  \\\n",
+       "39             [potential_LAMMPS/1995--Angelo-J-E--Ni-Al-H--LAMMPS--ipr1/NiAlH_jea.eam.alloy]   \n",
+       "40   [potential_LAMMPS/1996--Farkas-D--Nb-Ti-Al--LAMMPS--ipr1/Farkas_Nb-Ti-Al_1996.eam.alloy]   \n",
+       "43                  [potential_LAMMPS/1997--Liu-X-Y--Al-Mg--LAMMPS--ipr1/mg-al-set.eam.alloy]   \n",
+       "46                   [potential_LAMMPS/1998--Liu-X-Y--Al-Mg--LAMMPS--ipr1/almg.liu.eam.alloy]   \n",
+       "48                  [potential_LAMMPS/1999--Liu-X-Y--Al-Cu--LAMMPS--ipr1/al-cu-set.eam.alloy]   \n",
+       "..                                                                                        ...   \n",
+       "948                                                                                        []   \n",
+       "958                                                                                        []   \n",
+       "959                                                                                        []   \n",
+       "979                                                                                        []   \n",
+       "980                                                                                        []   \n",
+       "\n",
+       "         Model  \\\n",
+       "39   NISTiprpy   \n",
+       "40   NISTiprpy   \n",
+       "43   NISTiprpy   \n",
+       "46   NISTiprpy   \n",
+       "48   NISTiprpy   \n",
+       "..         ...   \n",
+       "948    OPENKIM   \n",
+       "958    OPENKIM   \n",
+       "959    OPENKIM   \n",
+       "979    OPENKIM   \n",
+       "980    OPENKIM   \n",
+       "\n",
+       "                                                                            Name  \\\n",
+       "39                                       1995--Angelo-J-E--Ni-Al-H--LAMMPS--ipr1   \n",
+       "40                                        1996--Farkas-D--Nb-Ti-Al--LAMMPS--ipr1   \n",
+       "43                                            1997--Liu-X-Y--Al-Mg--LAMMPS--ipr1   \n",
+       "46                                            1998--Liu-X-Y--Al-Mg--LAMMPS--ipr1   \n",
+       "48                                            1999--Liu-X-Y--Al-Cu--LAMMPS--ipr1   \n",
+       "..                                                                           ...   \n",
+       "948  Sim_LAMMPS_MEAM_JelinekGrohHorstemeyer_2012_AlSiMgCuFe__SM_656517352485_000   \n",
+       "958               Sim_LAMMPS_MEAM_PascuetFernandez_2015_AlU__SM_721930391003_000   \n",
+       "959                Sim_LAMMPS_MEAM_PascuetFernandez_2015_Al__SM_811588957187_000   \n",
+       "979        Sim_LAMMPS_SMTBQ_SallesPolitanoAmzallag_2016_AlO__SM_853967355976_000   \n",
+       "980         Sim_LAMMPS_SMTBQ_SallesPolitanoAmzallag_2016_Al__SM_404097633924_000   \n",
+       "\n",
+       "                  Species  \\\n",
+       "39            [Ni, Al, H]   \n",
+       "40           [Nb, Ti, Al]   \n",
+       "43               [Al, Mg]   \n",
+       "46               [Al, Mg]   \n",
+       "48               [Al, Cu]   \n",
+       "..                    ...   \n",
+       "948  [Al, Si, Mg, Cu, Fe]   \n",
+       "958               [Al, U]   \n",
+       "959                  [Al]   \n",
+       "979               [Al, O]   \n",
+       "980                  [Al]   \n",
+       "\n",
+       "                                                                                                                                                                                                   Citations  \n",
+       "39   [{'Angelo_1995': {'title': 'Trapping of hydrogen to lattice defects in nickel', 'journal': 'Modelling and Simulation in Materials Science and Engineering', 'volume': '3', 'pages': '289--307', 'num...  \n",
+       "40   [{'Farkas_1996': {'title': 'Interatomic potentials for ternary Nb - Ti - Al alloys', 'journal': 'Modelling and Simulation in Materials Science and Engineering', 'volume': '4', 'pages': '23--32', '...  \n",
+       "43   [{'Liu_1997': {'title': 'Anisotropic surface segregation in Al-Mg alloys', 'journal': 'Surface Science', 'volume': '373', 'pages': '357--370', 'number': '2-3', 'doi': '10.1016/s0039-6028(96)01154-...  \n",
+       "46   [{'Liu_1998': {'title': 'Grain-boundary segregation in Al-10%Mg alloys at hot working temperatures', 'journal': 'Acta Materialia', 'volume': '46', 'pages': '3467--3476', 'number': '10', 'doi': '10...  \n",
+       "48   [{'Liu_1999': {'title': \"A new investigation of copper's role in enhancing Al-Cu interconnect electromigration resistance from an atomistic view\", 'journal': 'Acta Materialia', 'volume': '47', 'pa...  \n",
+       "..                                                                                                                                                                                                       ...  \n",
+       "948  [{'B._2012': {'title': 'Modified embedded atom method potential for Al, Si, Mg, Cu, and Fe alloys', 'volume': '85', 'year': '2012', 'journal': 'Physical Review B', 'doi': '10.1103/PhysRevB.85.2451...  \n",
+       "958  [{'M.I._2015': {'title': '{A}tomic interaction of the {MEAM} type for the study of intermetallics in the {A}l–{U} alloy', 'volume': '467', 'year': '2015', 'journal': 'Journal of Nuclear Materials'...  \n",
+       "959  [{'M.I._2015': {'title': '{A}tomic interaction of the {MEAM} type for the study of intermetallics in the {A}l–{U} alloy', 'volume': '467', 'year': '2015', 'journal': 'Journal of Nuclear Materials'...  \n",
+       "979  [{'N._2016': {'title': 'Molecular dynamics study of high-pressure alumina polymorphs with a tight-binding variable-charge model', 'volume': '111', 'year': '2016', 'journal': 'Computational Materia...  \n",
+       "980  [{'N._2016': {'title': 'Molecular dynamics study of high-pressure alumina polymorphs with a tight-binding variable-charge model', 'volume': '111', 'year': '2016', 'journal': 'Computational Materia...  \n",
+       "\n",
+       "[136 rows x 6 columns]"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "job.view_potentials()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "27930c52-aa78-4813-8790-50c60220bdfa",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['1995--Angelo-J-E--Ni-Al-H--LAMMPS--ipr1',\n",
+       " '1996--Farkas-D--Nb-Ti-Al--LAMMPS--ipr1',\n",
+       " '1997--Liu-X-Y--Al-Mg--LAMMPS--ipr1',\n",
+       " '1998--Liu-X-Y--Al-Mg--LAMMPS--ipr1',\n",
+       " '1999--Liu-X-Y--Al-Cu--LAMMPS--ipr1',\n",
+       " '1999--Mishin-Y--Al--LAMMPS--ipr1',\n",
+       " '2000--Landa-A--Al-Pb--LAMMPS--ipr1',\n",
+       " '2000--Sturgeon-J-B--Al--LAMMPS--ipr1',\n",
+       " '2002--Mishin-Y--Ni-Al--LAMMPS--ipr1',\n",
+       " '2003--Lee-B-J--Al--LAMMPS--ipr1',\n",
+       " '2003--Zope-R-R--Al--LAMMPS--ipr1',\n",
+       " '2003--Zope-R-R--Ti-Al--LAMMPS--ipr1',\n",
+       " '2004--Liu-X-Y--Al--LAMMPS--ipr1',\n",
+       " '2004--Mishin-Y--Ni-Al--LAMMPS--ipr1',\n",
+       " '2004--Mishin-Y--Ni-Al--LAMMPS--ipr2',\n",
+       " '2004--Zhou-X-W--Al--LAMMPS--ipr2',\n",
+       " '2005--Mendelev-M-I--Al-Fe--LAMMPS--ipr1',\n",
+       " '2007--Silva-A-C--Al-Ni--LAMMPS--ipr1',\n",
+       " '2008--Mendelev-M-I--Al--LAMMPS--ipr1',\n",
+       " '2009--Kim-Y-M--Mg-Al--LAMMPS--ipr1',\n",
+       " '2009--Mendelev-M-I--Al-Mg--LAMMPS--ipr1',\n",
+       " '2009--Purja-Pun-G-P--Ni-Al--LAMMPS--ipr1',\n",
+       " '2009--Zhakhovskii-V-V--Al--LAMMPS--ipr2',\n",
+       " '2010--Lee-E--Fe-Al--LAMMPS--ipr1',\n",
+       " '2010--Mendelev-M-I--fictional-Al-1--LAMMPS--ipr1',\n",
+       " '2010--Mendelev-M-I--fictional-Al-2--LAMMPS--ipr1',\n",
+       " '2010--Mendelev-M-I--fictional-Al-3--LAMMPS--ipr1',\n",
+       " '2010--Winey-J-M--Al--LAMMPS--ipr1',\n",
+       " '2011--Apostol-F--Al-Cu--LAMMPS--ipr1',\n",
+       " '2011--Ko-W-S--Al-H--LAMMPS--ipr1',\n",
+       " '2012--Dong-W-P--Co-Al--LAMMPS--ipr1',\n",
+       " '2012--Jelinek-B--Al-Si-Mg-Cu-Fe--LAMMPS--ipr2',\n",
+       " '2012--Schopf-D--Al-Mn-Pd--LAMMPS--ipr1',\n",
+       " '2013--Shim-J-H--V-Al--LAMMPS--ipr1',\n",
+       " '2013--Shim-J-H--V-Al-H--LAMMPS--ipr1',\n",
+       " '2015--Choudhary-K--Al--LAMMPS--ipr1',\n",
+       " '2015--Choudhary-K--Al-O--LAMMPS--ipr1',\n",
+       " '2015--Kim-Y-K--Ni-Al-Co--LAMMPS--ipr1',\n",
+       " '2015--Kumar-A--Al-Ni--LAMMPS--ipr1',\n",
+       " '2015--Kumar-A--Al-Ni-O--LAMMPS--ipr1',\n",
+       " '2015--Mendelev-M-I--Al-Sm--LAMMPS--ipr1',\n",
+       " '2015--Pascuet-M-I--Al--LAMMPS--ipr1',\n",
+       " '2015--Pascuet-M-I--Al-U--LAMMPS--ipr2',\n",
+       " '2015--Purja-Pun-G-P--Al-Co--LAMMPS--ipr2',\n",
+       " '2015--Purja-Pun-G-P--Ni-Al-Co--LAMMPS--ipr2',\n",
+       " '2016--Kim-Y-K--Al-Ti--LAMMPS--ipr1',\n",
+       " '2016--Zhou-X-W--Al-Cu--LAMMPS--ipr2',\n",
+       " '2017--Botu-V--Al--LAMMPS--ipr1',\n",
+       " '2017--Kim-J-S--Pt-Al--LAMMPS--ipr1',\n",
+       " '2017--Kim-Y-K--Ni-Al-Ti--LAMMPS--ipr1',\n",
+       " '2018--Dickel-D-E--Mg-Al-Zn--LAMMPS--ipr1',\n",
+       " '2018--Jeong-G-U--Pd-Al--LAMMPS--ipr1',\n",
+       " '2018--Zhou-X-W--Al-Cu-H--LAMMPS--ipr1',\n",
+       " '2019--Plummer-G--Ti-Al-C--LAMMPS--ipr1',\n",
+       " '2020--Farkas-D--Fe-Ni-Cr-Co-Al--LAMMPS--ipr1',\n",
+       " '2020--Purja-Pun-G-P--Al--LAMMPS--ipr1',\n",
+       " '2020--Starikov-S--Si-Au-Al--LAMMPS--ipr1',\n",
+       " '2020--Starikov-S--Si-Au-Al--LAMMPS--ipr2',\n",
+       " '2021--Plummer-G--Ti-Al-C--LAMMPS--ipr1',\n",
+       " '2021--Song-H--Al-Sm--LAMMPS--ipr1',\n",
+       " '2022--Fereidonnejad-R--Al-Hf--LAMMPS--ipr1',\n",
+       " '2022--Fereidonnejad-R--Al-Nb--LAMMPS--ipr1',\n",
+       " '2022--Fereidonnejad-R--Al-Ta--LAMMPS--ipr1',\n",
+       " '2022--Fereidonnejad-R--Al-Ti--LAMMPS--ipr1',\n",
+       " '2022--Fereidonnejad-R--Al-Zr--LAMMPS--ipr1',\n",
+       " '2022--Mahata-A--Al-Cu--LAMMPS--ipr1',\n",
+       " '2022--Mahata-A--Al-Fe--LAMMPS--ipr1',\n",
+       " '2022--Mahata-A--Al-Ni--LAMMPS--ipr1',\n",
+       " '2022--Mendelev-M-I--Ni-Al--LAMMPS--ipr1',\n",
+       " 'EAM_CubicNaturalSpline_ErcolessiAdams_1994_Al__MO_800509458712_002',\n",
+       " 'EAM_Dynamo_AngeloMoodyBaskes_1995_NiAlH__MO_418978237058_005',\n",
+       " 'EAM_Dynamo_CaiYe_1996_AlCu__MO_942551040047_005',\n",
+       " 'EAM_Dynamo_ErcolessiAdams_1994_Al__MO_123629422045_005',\n",
+       " 'EAM_Dynamo_FarkasJones_1996_NbTiAl__MO_042691367780_000',\n",
+       " 'EAM_Dynamo_JacobsenNorskovPuska_1987_Al__MO_411692133366_000',\n",
+       " 'EAM_Dynamo_LandaWynblattSiegel_2000_AlPb__MO_699137396381_005',\n",
+       " 'EAM_Dynamo_LiuAdams_1998_AlMg__MO_019873715786_000',\n",
+       " 'EAM_Dynamo_LiuErcolessiAdams_2004_Al__MO_051157671505_000',\n",
+       " 'EAM_Dynamo_LiuLiuBorucki_1999_AlCu__MO_020851069572_000',\n",
+       " 'EAM_Dynamo_LiuOhotnickyAdams_1997_AlMg__MO_559870613549_000',\n",
+       " 'EAM_Dynamo_MendelevAstaRahman_2009_AlMg__MO_658278549784_005',\n",
+       " 'EAM_Dynamo_MendelevFangYe_2015_AlSm__MO_338600200739_000',\n",
+       " 'EAM_Dynamo_MendelevKramerBecker_2008_Al__MO_106969701023_005',\n",
+       " 'EAM_Dynamo_MendelevSrolovitzAckland_2005_AlFe__MO_577453891941_005',\n",
+       " 'EAM_Dynamo_MishinFarkasMehl_1999_Al__MO_651801486679_005',\n",
+       " 'EAM_Dynamo_MishinMehlPapaconstantopoulos_2002_NiAl__MO_109933561507_005',\n",
+       " 'EAM_Dynamo_Mishin_2004_NiAl__MO_101214310689_005',\n",
+       " 'EAM_Dynamo_PunMishin_2009_NiAl__MO_751354403791_005',\n",
+       " 'EAM_Dynamo_PunYamakovMishin_2013_AlCo__MO_678952612413_000',\n",
+       " 'EAM_Dynamo_PunYamakovMishin_2013_NiAlCo__MO_826591359508_000',\n",
+       " 'EAM_Dynamo_SchopfBrommerFrigan_2012_AlMnPd__MO_137572817842_000',\n",
+       " 'EAM_Dynamo_SturgeonLaird_2000_Al__MO_120808805541_005',\n",
+       " 'EAM_Dynamo_VailheFarkas_1997_CoAl__MO_284963179498_005',\n",
+       " 'EAM_Dynamo_WineyKubotaGupta_2010_Al__MO_149316865608_005',\n",
+       " 'EAM_Dynamo_Zhakhovsky_2009_Al__MO_519613893196_000',\n",
+       " 'EAM_Dynamo_ZhouJohnsonWadley_2004NISTretabulation_Al__MO_060567868558_000',\n",
+       " 'EAM_Dynamo_ZhouJohnsonWadley_2004_Al__MO_131650261510_005',\n",
+       " 'EAM_Dynamo_ZhouWadleyJohnson_2001_Al__MO_049243498555_000',\n",
+       " 'EAM_Dynamo_ZopeMishin_2003_Al__MO_664470114311_005',\n",
+       " 'EAM_Dynamo_ZopeMishin_2003_TiAl__MO_117656786760_005',\n",
+       " 'EAM_ErcolessiAdams_1994_Al__MO_324507536345_003',\n",
+       " 'EAM_IMD_BrommerGaehler_2006A_AlNiCo__MO_122703700223_003',\n",
+       " 'EAM_IMD_BrommerGaehler_2006B_AlNiCo__MO_128037485276_003',\n",
+       " 'EAM_IMD_SchopfBrommerFrigan_2012_AlMnPd__MO_878712978062_003',\n",
+       " 'EAM_QuinticClampedSpline_ErcolessiAdams_1994_Al__MO_450093727396_002',\n",
+       " 'EAM_QuinticHermiteSpline_ErcolessiAdams_1994_Al__MO_781138671863_002',\n",
+       " 'EMT_Asap_Standard_JacobsenStoltzeNorskov_1996_AlAgAuCuNiPdPt__MO_115316750986_001',\n",
+       " 'EMT_Asap_Standard_JacobsenStoltzeNorskov_1996_Al__MO_623376124862_001',\n",
+       " 'MEAM_LAMMPS_AlmyrasSangiovanniSarakinos_2019_NAlTi__MO_958395190627_000',\n",
+       " 'MEAM_LAMMPS_CostaAgrenClavaguera_2007_AlNi__MO_131642768288_000',\n",
+       " 'MEAM_LAMMPS_DongKimKo_2012_CoAl__MO_099716416216_000',\n",
+       " 'MEAM_LAMMPS_JelinekGrohHorstemeyer_2012_AlSiMgCuFe__MO_262519520678_000',\n",
+       " 'MEAM_LAMMPS_JeongParkDo_2018_PdAl__MO_616482358807_000',\n",
+       " 'MEAM_LAMMPS_KimJungLee_2015_NiAlCo__MO_876687166519_000',\n",
+       " 'MEAM_LAMMPS_KimKimJung_2016_AlTi__MO_618133763375_000',\n",
+       " 'MEAM_LAMMPS_KimKimJung_2017_NiAlTi__MO_478967255435_000',\n",
+       " 'MEAM_LAMMPS_KimKimLee_2009_AlMg__MO_058537087384_000',\n",
+       " 'MEAM_LAMMPS_KimSeolJi_2017_PtAl__MO_793141037706_000',\n",
+       " 'MEAM_LAMMPS_KoShimLee_2011_AlH__MO_127847080751_000',\n",
+       " 'MEAM_LAMMPS_LeeLee_2010_FeAl__MO_332211522050_000',\n",
+       " 'MEAM_LAMMPS_PascuetFernandez_2015_AlU__MO_596300673917_000',\n",
+       " 'MEAM_LAMMPS_PascuetFernandez_2015_Al__MO_315820974149_000',\n",
+       " 'MEAM_LAMMPS_ShimKoKim_2013_AlVH__MO_344724145339_000',\n",
+       " 'Morse_Shifted_GirifalcoWeizer_1959HighCutoff_Al__MO_140175748626_004',\n",
+       " 'Morse_Shifted_GirifalcoWeizer_1959LowCutoff_Al__MO_411898953661_004',\n",
+       " 'Morse_Shifted_GirifalcoWeizer_1959MedCutoff_Al__MO_279544746097_004',\n",
+       " 'Sim_LAMMPS_ADP_ApostolMishin_2011_AlCu__SM_667696763561_000',\n",
+       " 'Sim_LAMMPS_ADP_StarikovGordeevLysogorskiy_2020_SiAuAl__SM_113843830602_000',\n",
+       " 'Sim_LAMMPS_AGNI_BotuBatraChapman_2017_Al__SM_666183636896_000',\n",
+       " 'Sim_LAMMPS_BOP_ZhouWardFoster_2016_AlCu__SM_566399258279_000',\n",
+       " 'Sim_LAMMPS_MEAM_AlmyrasSangiovanniSarakinos_2019_NAlTi__SM_871795249052_000',\n",
+       " 'Sim_LAMMPS_MEAM_JelinekGrohHorstemeyer_2012_AlSiMgCuFe__SM_656517352485_000',\n",
+       " 'Sim_LAMMPS_MEAM_PascuetFernandez_2015_AlU__SM_721930391003_000',\n",
+       " 'Sim_LAMMPS_MEAM_PascuetFernandez_2015_Al__SM_811588957187_000',\n",
+       " 'Sim_LAMMPS_SMTBQ_SallesPolitanoAmzallag_2016_AlO__SM_853967355976_000',\n",
+       " 'Sim_LAMMPS_SMTBQ_SallesPolitanoAmzallag_2016_Al__SM_404097633924_000']"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "job.list_potentials()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "b17c90ba-d950-46a1-9b3e-8bbf94b8d568",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "job.potential = '1999--Mishin-Y--Al--LAMMPS--ipr1'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "cac7ea76-82f0-4ab3-a117-fb89b977adb6",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Parameter</th>\n",
+       "      <th>Value</th>\n",
+       "      <th>Comment</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>units</td>\n",
+       "      <td>metal</td>\n",
+       "      <td></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>dimension</td>\n",
+       "      <td>3</td>\n",
+       "      <td></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>boundary</td>\n",
+       "      <td>p p p</td>\n",
+       "      <td></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>atom_style</td>\n",
+       "      <td>atomic</td>\n",
+       "      <td></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>read_data</td>\n",
+       "      <td>structure.inp</td>\n",
+       "      <td></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>include</td>\n",
+       "      <td>potential.inp</td>\n",
+       "      <td></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>fix___ensemble</td>\n",
+       "      <td>all nvt temp 500.0 500.0 0.1</td>\n",
+       "      <td></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>variable___dumptime</td>\n",
+       "      <td>equal 100</td>\n",
+       "      <td></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>variable___thermotime</td>\n",
+       "      <td>equal 100</td>\n",
+       "      <td></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>timestep</td>\n",
+       "      <td>0.001</td>\n",
+       "      <td></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>velocity</td>\n",
+       "      <td>all create 1000.0 61040 dist gaussian</td>\n",
+       "      <td></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>dump___1</td>\n",
+       "      <td>all custom ${dumptime} dump.out id type xsu ysu zsu fx fy fz vx vy vz</td>\n",
+       "      <td></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>dump_modify___1</td>\n",
+       "      <td>sort id format line \"%d %d %20.15g %20.15g %20.15g %20.15g %20.15g %20.15g %20.15g %20.15g %20.15g\"</td>\n",
+       "      <td></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>thermo_style</td>\n",
+       "      <td>custom step temp pe etotal pxx pxy pxz pyy pyz pzz vol</td>\n",
+       "      <td></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>thermo_modify</td>\n",
+       "      <td>format float %20.15g</td>\n",
+       "      <td></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>thermo</td>\n",
+       "      <td>${thermotime}</td>\n",
+       "      <td></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>run</td>\n",
+       "      <td>10000</td>\n",
+       "      <td></td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                Parameter  \\\n",
+       "0                   units   \n",
+       "1               dimension   \n",
+       "2                boundary   \n",
+       "3              atom_style   \n",
+       "4               read_data   \n",
+       "5                 include   \n",
+       "6          fix___ensemble   \n",
+       "7     variable___dumptime   \n",
+       "8   variable___thermotime   \n",
+       "9                timestep   \n",
+       "10               velocity   \n",
+       "11               dump___1   \n",
+       "12        dump_modify___1   \n",
+       "13           thermo_style   \n",
+       "14          thermo_modify   \n",
+       "15                 thermo   \n",
+       "16                    run   \n",
+       "\n",
+       "                                                                                                  Value  \\\n",
+       "0                                                                                                 metal   \n",
+       "1                                                                                                     3   \n",
+       "2                                                                                                 p p p   \n",
+       "3                                                                                                atomic   \n",
+       "4                                                                                         structure.inp   \n",
+       "5                                                                                         potential.inp   \n",
+       "6                                                                          all nvt temp 500.0 500.0 0.1   \n",
+       "7                                                                                            equal 100    \n",
+       "8                                                                                            equal 100    \n",
+       "9                                                                                                 0.001   \n",
+       "10                                                                all create 1000.0 61040 dist gaussian   \n",
+       "11                                all custom ${dumptime} dump.out id type xsu ysu zsu fx fy fz vx vy vz   \n",
+       "12  sort id format line \"%d %d %20.15g %20.15g %20.15g %20.15g %20.15g %20.15g %20.15g %20.15g %20.15g\"   \n",
+       "13                                               custom step temp pe etotal pxx pxy pxz pyy pyz pzz vol   \n",
+       "14                                                                                 format float %20.15g   \n",
+       "15                                                                                        ${thermotime}   \n",
+       "16                                                                                                10000   \n",
+       "\n",
+       "   Comment  \n",
+       "0           \n",
+       "1           \n",
+       "2           \n",
+       "3           \n",
+       "4           \n",
+       "5           \n",
+       "6           \n",
+       "7           \n",
+       "8           \n",
+       "9           \n",
+       "10          \n",
+       "11          \n",
+       "12          \n",
+       "13          \n",
+       "14          \n",
+       "15          \n",
+       "16          "
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "job.input.control"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "1cdc0e8c-7244-4f3e-9e5b-9d11fb0f2a7a",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/janssen/mambaforge/lib/python3.10/site-packages/pyiron_base/storage/parameters.py:280: UserWarning: The input in GenericParameters changed, while the state of the job was already finished.\n",
+      "  warnings.warn(\n"
+     ]
+    }
+   ],
+   "source": [
+    "job.input.control[\"run\"] = 10"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "b83d0a0f-e4a6-419e-a80d-f859326a2e62",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "job.calc_md(temperature=500.0, n_ionic_steps=10000)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "39996077-a72c-4c4b-979d-75b1018cef7c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Parameter</th>\n",
+       "      <th>Value</th>\n",
+       "      <th>Comment</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>units</td>\n",
+       "      <td>metal</td>\n",
+       "      <td></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>dimension</td>\n",
+       "      <td>3</td>\n",
+       "      <td></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>boundary</td>\n",
+       "      <td>p p p</td>\n",
+       "      <td></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>atom_style</td>\n",
+       "      <td>atomic</td>\n",
+       "      <td></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>read_data</td>\n",
+       "      <td>structure.inp</td>\n",
+       "      <td></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>include</td>\n",
+       "      <td>potential.inp</td>\n",
+       "      <td></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>fix___ensemble</td>\n",
+       "      <td>all nvt temp 500.0 500.0 0.1</td>\n",
+       "      <td></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>variable___dumptime</td>\n",
+       "      <td>equal 100</td>\n",
+       "      <td></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>variable___thermotime</td>\n",
+       "      <td>equal 100</td>\n",
+       "      <td></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>timestep</td>\n",
+       "      <td>0.001</td>\n",
+       "      <td></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>velocity</td>\n",
+       "      <td>all create 1000.0 61040 dist gaussian</td>\n",
+       "      <td></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>dump___1</td>\n",
+       "      <td>all custom ${dumptime} dump.out id type xsu ysu zsu fx fy fz vx vy vz</td>\n",
+       "      <td></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>dump_modify___1</td>\n",
+       "      <td>sort id format line \"%d %d %20.15g %20.15g %20.15g %20.15g %20.15g %20.15g %20.15g %20.15g %20.15g\"</td>\n",
+       "      <td></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>thermo_style</td>\n",
+       "      <td>custom step temp pe etotal pxx pxy pxz pyy pyz pzz vol</td>\n",
+       "      <td></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>thermo_modify</td>\n",
+       "      <td>format float %20.15g</td>\n",
+       "      <td></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>thermo</td>\n",
+       "      <td>${thermotime}</td>\n",
+       "      <td></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>run</td>\n",
+       "      <td>10000</td>\n",
+       "      <td></td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                Parameter  \\\n",
+       "0                   units   \n",
+       "1               dimension   \n",
+       "2                boundary   \n",
+       "3              atom_style   \n",
+       "4               read_data   \n",
+       "5                 include   \n",
+       "6          fix___ensemble   \n",
+       "7     variable___dumptime   \n",
+       "8   variable___thermotime   \n",
+       "9                timestep   \n",
+       "10               velocity   \n",
+       "11               dump___1   \n",
+       "12        dump_modify___1   \n",
+       "13           thermo_style   \n",
+       "14          thermo_modify   \n",
+       "15                 thermo   \n",
+       "16                    run   \n",
+       "\n",
+       "                                                                                                  Value  \\\n",
+       "0                                                                                                 metal   \n",
+       "1                                                                                                     3   \n",
+       "2                                                                                                 p p p   \n",
+       "3                                                                                                atomic   \n",
+       "4                                                                                         structure.inp   \n",
+       "5                                                                                         potential.inp   \n",
+       "6                                                                          all nvt temp 500.0 500.0 0.1   \n",
+       "7                                                                                            equal 100    \n",
+       "8                                                                                            equal 100    \n",
+       "9                                                                                                 0.001   \n",
+       "10                                                                all create 1000.0 61040 dist gaussian   \n",
+       "11                                all custom ${dumptime} dump.out id type xsu ysu zsu fx fy fz vx vy vz   \n",
+       "12  sort id format line \"%d %d %20.15g %20.15g %20.15g %20.15g %20.15g %20.15g %20.15g %20.15g %20.15g\"   \n",
+       "13                                               custom step temp pe etotal pxx pxy pxz pyy pyz pzz vol   \n",
+       "14                                                                                 format float %20.15g   \n",
+       "15                                                                                        ${thermotime}   \n",
+       "16                                                                                                10000   \n",
+       "\n",
+       "   Comment  \n",
+       "0           \n",
+       "1           \n",
+       "2           \n",
+       "3           \n",
+       "4           \n",
+       "5           \n",
+       "6           \n",
+       "7           \n",
+       "8           \n",
+       "9           \n",
+       "10          \n",
+       "11          \n",
+       "12          \n",
+       "13          \n",
+       "14          \n",
+       "15          \n",
+       "16          "
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "job.input.control"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "cb755cbc-3643-48f6-9257-f5f122a158da",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "\u001b[0;31mSignature:\u001b[0m \u001b[0mjob\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0minput\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcontrol\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mload_string\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0minput_str\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+       "\u001b[0;31mDocstring:\u001b[0m\n",
+       "Load a multi line string to overwrite the current parameter settings\n",
+       "\n",
+       "Args:\n",
+       "    input_str (str): multi line string\n",
+       "\u001b[0;31mFile:\u001b[0m      ~/mambaforge/lib/python3.10/site-packages/pyiron_base/storage/parameters.py\n",
+       "\u001b[0;31mType:\u001b[0m      method"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "job.input.control.load_string?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "ca14438b-3cb7-49f3-a7ad-c0ba76005998",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['flux']"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "job.server.list_queues()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "1ba41de8-22cd-4d60-a8a0-a1e404937eeb",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>cores_max</th>\n",
+       "      <th>cores_min</th>\n",
+       "      <th>memory_max</th>\n",
+       "      <th>run_time_max</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>flux</th>\n",
+       "      <td>12</td>\n",
+       "      <td>1</td>\n",
+       "      <td>None</td>\n",
+       "      <td>172800</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     cores_max cores_min memory_max run_time_max\n",
+       "flux        12         1       None       172800"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "job.server.view_queues()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "11cf5e21-d93d-4b36-8a48-99322445f99d",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2023-08-11 12:52:57,488 - pyiron_log - WARNING - The job lmp is being loaded instead of running. To re-run use the argument 'delete_existing_job=True in create_job'\n"
+     ]
+    }
+   ],
+   "source": [
+    "job.run()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "4d458c95-2027-485e-a1a6-ad045bb14871",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>id</th>\n",
+       "      <th>status</th>\n",
+       "      <th>chemicalformula</th>\n",
+       "      <th>job</th>\n",
+       "      <th>subjob</th>\n",
+       "      <th>projectpath</th>\n",
+       "      <th>project</th>\n",
+       "      <th>timestart</th>\n",
+       "      <th>timestop</th>\n",
+       "      <th>totalcputime</th>\n",
+       "      <th>computer</th>\n",
+       "      <th>hamilton</th>\n",
+       "      <th>hamversion</th>\n",
+       "      <th>parentid</th>\n",
+       "      <th>masterid</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>21751</td>\n",
+       "      <td>finished</td>\n",
+       "      <td>Al4</td>\n",
+       "      <td>lmp</td>\n",
+       "      <td>/lmp</td>\n",
+       "      <td>/home/janssen/pyiron/projects/</td>\n",
+       "      <td>2023-08-11-lammps-workshop/demo/</td>\n",
+       "      <td>2023-08-11 12:21:17.571885</td>\n",
+       "      <td>2023-08-11 12:21:18.193762</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>pyiron@ljubi#1</td>\n",
+       "      <td>Lammps</td>\n",
+       "      <td>0.1</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      id    status chemicalformula  job subjob  \\\n",
+       "0  21751  finished             Al4  lmp   /lmp   \n",
+       "\n",
+       "                      projectpath                           project  \\\n",
+       "0  /home/janssen/pyiron/projects/  2023-08-11-lammps-workshop/demo/   \n",
+       "\n",
+       "                   timestart                   timestop  totalcputime  \\\n",
+       "0 2023-08-11 12:21:17.571885 2023-08-11 12:21:18.193762           0.0   \n",
+       "\n",
+       "         computer hamilton hamversion parentid masterid  \n",
+       "0  pyiron@ljubi#1   Lammps        0.1     None     None  "
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pr.job_table()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "46f944a8-7b82-4e94-a9df-0b421042234a",
+   "metadata": {},
+   "source": [
+    "# Analysis"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "3253116f-1a25-4929-ba53-8428b85e3cdc",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([1000.        ,  752.0015943 ,  581.97828295,  565.88498131,\n",
+       "        498.64163307,  619.46212912,  839.79469054,  735.46121047,\n",
+       "        490.9818782 ,  425.72892636,  511.25870675,  728.11331086,\n",
+       "        979.29177938,  779.08050078,  318.19269923,  319.76544017,\n",
+       "        615.98147637,  764.33185652,  537.13919302,  566.83533086,\n",
+       "        324.06236624,  239.681096  ,  357.65958767,  529.71207802,\n",
+       "        678.65954585, 1017.29045232,  965.27929927,  538.05571921,\n",
+       "        415.48645095,  441.8216159 ,  609.74969834,  696.54891985,\n",
+       "        589.34487532,  512.24203853,  411.42514663,  243.03455806,\n",
+       "        223.14397594,  373.19610873,  458.5817006 ,  564.98024262,\n",
+       "        788.10126229,  546.27031088,  342.6747628 ,  328.98287765,\n",
+       "        399.97450592,  607.28820557,  734.54679262,  727.88113948,\n",
+       "        744.91136117,  503.00152276,  275.34234858,  319.44515758,\n",
+       "        638.80953199,  603.46319087,  658.63014981,  408.61543622,\n",
+       "        214.18100485,  172.29883429,  136.02885008,  178.75290088,\n",
+       "        275.3730367 ,  512.79746057,  718.8203184 ,  537.29244852,\n",
+       "        242.26061934,  233.39828518,  316.69127405,  171.43394863,\n",
+       "        166.37733062,  533.3350456 ,  469.09494053,  358.06977249,\n",
+       "        482.30113254,  429.48687577,  367.35969121,  677.47890948,\n",
+       "        751.07498074,  516.81094117,  443.34143158,  379.24775963,\n",
+       "        498.15543097,  869.38443683, 1093.11902342,  850.26532134,\n",
+       "        573.17328841,  563.33684203,  704.39942526, 1092.24591094,\n",
+       "       1259.10019361,  866.66215626,  529.51239522,  519.50456174,\n",
+       "        529.78547674,  411.20641589,  567.71018046,  759.89599555,\n",
+       "        384.52677489,  334.85213855,  371.31468598,  503.71616875,\n",
+       "        874.70226638])"
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "job.output.temperature"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "id": "9ef394fb-b0bc-42a0-84c2-8ecfa0addcc6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import matplotlib.pyplot as plt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "c8f7240b-fc6a-45df-ba75-4a54bd58031f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0, 0.5, 'Temperature K')"
+      ]
+     },
+     "execution_count": 25,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.plot(job.output.steps, job.output.temperature)\n",
+    "plt.xlabel(\"Timestep\")\n",
+    "plt.ylabel(\"Temperature K\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b7a36bd6-48f2-4161-af90-c7f40a7e37d0",
+   "metadata": {},
+   "source": [
+    "# Access output "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "id": "6b0ac0ca-1110-4a14-9148-bf3fa57abc51",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([1000.        ,  752.0015943 ,  581.97828295,  565.88498131,\n",
+       "        498.64163307,  619.46212912,  839.79469054,  735.46121047,\n",
+       "        490.9818782 ,  425.72892636,  511.25870675,  728.11331086,\n",
+       "        979.29177938,  779.08050078,  318.19269923,  319.76544017,\n",
+       "        615.98147637,  764.33185652,  537.13919302,  566.83533086,\n",
+       "        324.06236624,  239.681096  ,  357.65958767,  529.71207802,\n",
+       "        678.65954585, 1017.29045232,  965.27929927,  538.05571921,\n",
+       "        415.48645095,  441.8216159 ,  609.74969834,  696.54891985,\n",
+       "        589.34487532,  512.24203853,  411.42514663,  243.03455806,\n",
+       "        223.14397594,  373.19610873,  458.5817006 ,  564.98024262,\n",
+       "        788.10126229,  546.27031088,  342.6747628 ,  328.98287765,\n",
+       "        399.97450592,  607.28820557,  734.54679262,  727.88113948,\n",
+       "        744.91136117,  503.00152276,  275.34234858,  319.44515758,\n",
+       "        638.80953199,  603.46319087,  658.63014981,  408.61543622,\n",
+       "        214.18100485,  172.29883429,  136.02885008,  178.75290088,\n",
+       "        275.3730367 ,  512.79746057,  718.8203184 ,  537.29244852,\n",
+       "        242.26061934,  233.39828518,  316.69127405,  171.43394863,\n",
+       "        166.37733062,  533.3350456 ,  469.09494053,  358.06977249,\n",
+       "        482.30113254,  429.48687577,  367.35969121,  677.47890948,\n",
+       "        751.07498074,  516.81094117,  443.34143158,  379.24775963,\n",
+       "        498.15543097,  869.38443683, 1093.11902342,  850.26532134,\n",
+       "        573.17328841,  563.33684203,  704.39942526, 1092.24591094,\n",
+       "       1259.10019361,  866.66215626,  529.51239522,  519.50456174,\n",
+       "        529.78547674,  411.20641589,  567.71018046,  759.89599555,\n",
+       "        384.52677489,  334.85213855,  371.31468598,  503.71616875,\n",
+       "        874.70226638])"
+      ]
+     },
+     "execution_count": 26,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "job[\"output/generic/temperature\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "id": "7cd37f8c-aba7-4474-9ee8-642fe2a14e50",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "job.decompress()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "id": "117afb67-56b6-43c7-a5d6-418644ee4f93",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['LAMMPS (28 Mar 2023 - Update 1)\\n',\n",
+       " 'units metal\\n',\n",
+       " 'dimension 3\\n',\n",
+       " 'boundary p p p\\n',\n",
+       " 'atom_style atomic\\n',\n",
+       " 'read_data structure.inp\\n',\n",
+       " 'Reading data file ...\\n',\n",
+       " '  orthogonal box = (0 0 0) to (4.05 4.05 4.05)\\n',\n",
+       " '  1 by 1 by 1 MPI processor grid\\n',\n",
+       " '  reading atoms ...\\n',\n",
+       " '  4 atoms\\n',\n",
+       " '  read_data CPU = 0.000 seconds\\n',\n",
+       " 'include potential.inp\\n',\n",
+       " 'pair_style eam/alloy\\n',\n",
+       " 'pair_coeff * * Al99.eam.alloy Al\\n',\n",
+       " 'fix ensemble all nvt temp 500.0 500.0 0.1\\n',\n",
+       " 'variable dumptime  equal 100\\n',\n",
+       " 'variable thermotime  equal 100\\n',\n",
+       " 'timestep 0.001\\n',\n",
+       " 'velocity all create 1000.0 61040 dist gaussian\\n',\n",
+       " 'dump 1 all custom ${dumptime} dump.out id type xsu ysu zsu fx fy fz vx vy vz\\n',\n",
+       " 'dump 1 all custom 100 dump.out id type xsu ysu zsu fx fy fz vx vy vz\\n',\n",
+       " 'dump_modify 1 sort id format line \"%d %d %20.15g %20.15g %20.15g %20.15g %20.15g %20.15g %20.15g %20.15g %20.15g\"\\n',\n",
+       " 'thermo_style custom step temp pe etotal pxx pxy pxz pyy pyz pzz vol\\n',\n",
+       " 'thermo_modify format float %20.15g\\n',\n",
+       " 'thermo ${thermotime}\\n',\n",
+       " 'thermo 100\\n',\n",
+       " 'run 10000\\n',\n",
+       " 'Neighbor list info ...\\n',\n",
+       " '  update: every = 1 steps, delay = 0 steps, check = yes\\n',\n",
+       " '  max neighbors/atom: 2000, page size: 100000\\n',\n",
+       " '  master list distance cutoff = 8.28721\\n',\n",
+       " '  ghost atom cutoff = 8.28721\\n',\n",
+       " '  binsize = 4.143605, bins = 1 1 1\\n',\n",
+       " '  1 neighbor lists, perpetual/occasional/extra = 1 0 0\\n',\n",
+       " '  (1) pair eam/alloy, perpetual\\n',\n",
+       " '      attributes: half, newton on\\n',\n",
+       " '      pair build: half/bin/atomonly/newton\\n',\n",
+       " '      stencil: half/bin/3d\\n',\n",
+       " '      bin: standard\\n',\n",
+       " 'Per MPI rank memory allocation (min/avg/max) = 4.492 | 4.492 | 4.492 Mbytes\\n',\n",
+       " '   Step          Temp          PotEng         TotEng          Pxx            Pxy            Pxz            Pyy            Pyz            Pzz           Volume    \\n',\n",
+       " '         0                  1000    -13.4399999525399    -13.0522195175399     6625.59782087403    -7443.22978534659    -866.826476810976     11104.5819648942      2194.1609925506     983.150164376666            66.430125\\n',\n",
+       " '       100      752.001594301928    -13.3510663255047    -13.0594548201456     14823.0879874269    -87.7928884692233     1137.71342997224     16898.6400048557    -556.480327719691     5238.13408507839            66.430125\\n',\n",
+       " '       200      581.978282952345    -13.3078875458599    -13.0822077541361     17180.8414119011     3765.91742831798    -4994.82425608563     14413.9418378016     316.496079390417     12359.7074556628            66.430125\\n',\n",
+       " '       300      565.884981307815    -13.3539313457144    -13.1344922215029     11697.6983345439    -3587.74213027796     3538.34815961484     8607.88003313948     456.848520957984     8323.49797764467            66.430125\\n',\n",
+       " '       400      498.641633066463     -13.352845302581    -13.1594818332014     13524.9897448273    -4092.22622336295    -22.8578637074882     10785.2272865822     52.1007735309335     2402.44560863964            66.430125\\n',\n",
+       " '       500      619.462129116665    -13.3350171997656    -13.0948019058707     17958.8214681728     5631.92615189808    -4683.45184381048     9426.59186549594     853.542008954574     5547.71875220764            66.430125\\n',\n",
+       " '       600       839.79469054124    -13.2273588065167    -12.9017028561079      29646.057759672    -4376.58570315802     12883.3461258884     13007.4546584373    -4075.96903381633     20325.1020137433            66.430125\\n',\n",
+       " '       700      735.461210468307    -13.1619021427079    -12.8767046745869     34541.0373388057    -3913.10999446247    -5898.16926402937      27960.756637454     9102.90986057353     16945.4696690426            66.430125\\n',\n",
+       " '       800      490.981878204272    -13.3287811514583    -13.1383879851511     15207.6265869357     2604.44150480075    -2277.63773097276     9632.04642818511     -3267.0477650551     6649.69103185672            66.430125\\n',\n",
+       " '       900      425.728926364381    -13.3636857835995    -13.1985964353418     11072.1651178264    -2388.62903563817     3841.62182909539     4472.81387189081    -1008.06117943329     6700.87950261038            66.430125\\n',\n",
+       " '      1000      511.258706752416    -13.3413555242286    -13.1430994005267     11483.9756384329    -580.193183533776     419.224438274943     9997.74120624911     5312.66672569025     8697.86369127453            66.430125\\n',\n",
+       " '      1100      728.113310861693    -13.2966923760874    -13.0143442796721     16671.5205830041      1778.6551306524    -3902.92933285756     16387.9791747922    -6561.58641306022     16665.0192773678            66.430125\\n',\n",
+       " '      1200      979.291779381618    -13.3090297968583    -12.9292796046577     18218.5848290967    -1420.94293790538     5063.97815569781     8334.38851820968    -1565.23432174142     23078.1946158316            66.430125\\n',\n",
+       " '      1300      779.080500782665    -13.3551498132323    -13.0530376377388     9964.80509648424     5581.70283586649     2266.25133132941     6885.46657604573     6938.98464634491     15768.7089705936            66.430125\\n',\n",
+       " '      1400      318.192699225883    -13.3704538376724    -13.2470649343528     7051.58795899356    -4256.37544736247     -1591.1285874893      6919.5091290425    -1417.67795388745     8254.19514594419            66.430125\\n',\n",
+       " '      1500      319.765440168471    -13.3568132807521    -13.2328144992656     9112.29108435426      3387.8729701242    -137.113664775729     6538.20425198815    -1047.65233045884     8660.43291870639            66.430125\\n',\n",
+       " '      1600      615.981476372798    -13.3547568424816    -13.1158912776218     10457.8401099676     2627.09951606258     2660.10209009612     6104.30716788548     3094.54711505783     10076.5705265436            66.430125\\n',\n",
+       " '      1700      764.331856522524    -13.2947172369479    -12.9983242971412      17612.076934005    -9248.05558862264     2133.34638366385     16132.1428743873    -243.316057110884     11990.0889085912            66.430125\\n',\n",
+       " '      1800      537.139193016898    -13.2074937216187    -12.9992016516951     24538.4343114321     11521.2372419228    -5740.54081606686      21944.658609078    -1591.86167715659     17570.6190148991            66.430125\\n',\n",
+       " '      1900       566.83533086309    -13.2923344851192    -13.0725268339437      15749.694475194     2202.69883385506     4249.25849421552     9635.80884750921     2878.99799253046     14323.9560881393            66.430125\\n',\n",
+       " '      2000      324.062366242423    -13.3721440664564    -13.2464790211078     8096.41348533948    -3991.87463520647     173.732527810127     7046.64139720135    -1231.81279624193     3158.40741569049            66.430125\\n',\n",
+       " '      2100      239.681096002017    -13.3866959758106    -13.2937523361416     6719.96261188474      2138.2036631951    -945.712305237015     6843.66646615247    -278.143942913025     1856.62724268544            66.430125\\n',\n",
+       " '      2200       357.65958766798    -13.3819662568538     -13.243272866366     7770.66493934794     2452.44689746702     2031.83096401075     6370.10837862363     1714.57049307372      4787.5754100445            66.430125\\n',\n",
+       " '      2300      529.712078016213    -13.3589535432661    -13.1535415632283     13435.5407287333    -3700.48318222738    -1525.69052968491     6635.66162250436    -3785.33368406697     8962.19281450725            66.430125\\n',\n",
+       " '      2400      678.659545853821    -13.3370987958827    -13.0739279019746     20818.5104780164    -1722.41276406009     753.797375102893     11027.0935208412     1733.61144167237     7213.40108494733            66.430125\\n',\n",
+       " '      2500      1017.29045232027    -13.3970413344091     -13.002556000287      15205.056136639     8835.34624476738    -677.236708831649     8515.84813862488    -455.581617864962     4143.91336415893            66.430125\\n',\n",
+       " '      2600      965.279299268909    -13.3597277859385    -12.9854113593715     17625.5071296434    -2855.93388818345     2641.23564523235     11066.5377474625     -3688.8050038548     8229.44443131572            66.430125\\n',\n",
+       " '      2700      538.055719209154     -13.323330818495    -13.1146833376458     19837.6839600348    -3331.94296851464    -3482.93101589635     10853.1281633261     598.888224458104     10139.2443307828            66.430125\\n',\n",
+       " '      2800      415.486450946544    -13.3837808392278    -13.2226633225431     10246.1690417032     3854.67851978798     308.079989439478     4228.61083698263     212.288210157886     5578.02664997059            66.430125\\n',\n",
+       " '      2900      441.821615897597    -13.3865264244753    -13.2151966460701     8833.32349803841     563.241532859981     2594.74248411042     5574.75609998888    -842.974402687681     3236.41184184962            66.430125\\n',\n",
+       " '      3000      609.749698344084    -13.2817785622613    -13.0453295589963     21288.8858881321    -9431.42154896148    -7278.54662071598     16320.5623975099    -1454.46613708368     8754.14272763016            66.430125\\n',\n",
+       " '      3100      696.548919854249    -13.2164679474397    -12.9463599042998     25469.1353652897     9481.98467143145     5770.67154263987     15739.0125372385     4910.51585263183      21445.869669254            66.430125\\n',\n",
+       " '      3200      589.344875323352    -13.2371786637373    -13.0086422516194     21311.4769303811      1228.2971227164     676.213599502287     17537.8281071456    -4758.95300957477     14414.0907586438            66.430125\\n',\n",
+       " '      3300      512.242038531633    -13.3054685268887    -13.1068310863616     15688.7076919394    -4738.83170050818    -6095.98118671537     14764.7938526357    -219.454631570647     6261.52705507109            66.430125\\n',\n",
+       " '      3400      411.425146633112    -13.3524371077359    -13.1928944854046     9109.72863538115     3724.63762901728     5037.82482822487     6556.44291118351     2455.02291000244     8914.16565887104            66.430125\\n',\n",
+       " '      3500      243.034558062904    -13.3926617457904    -13.2984176991448     4411.86432267834    -545.284053638995     318.045027389042     2619.41652682602    -274.899463540236     6789.20509380357            66.430125\\n',\n",
+       " '      3600      223.143975938846    -13.4053295113547    -13.3187986432975     3765.71787170353    -1361.57265125758    -1985.82985925778     3181.50906881288    -1055.37833121373      4642.2835477156            66.430125\\n',\n",
+       " '      3700       373.19610873208    -13.3748220904341    -13.2301039410497     8522.89109213249     5712.83116730573     1742.95971926498     7445.63837106997     2101.20835199428     5771.53869230508            66.430125\\n',\n",
+       " '      3800      458.581700595601     -13.313447420925     -13.135618409585      13986.674300789     -4439.2105637272     6509.03257594852     9186.22321227263     2566.54817543673     14239.0488995424            66.430125\\n',\n",
+       " '      3900      564.980242624691     -13.268005847791    -13.0489175635396     17055.5667270501     2039.96975709053    -12941.9254172493     11797.6801935846    -9490.71694590599     21442.2364886868            66.430125\\n',\n",
+       " '      4000      788.101262294748    -13.2578419116047     -12.952231661288     20350.0518506765     984.787349881281     5642.79879112806     19067.2215547131     6721.24101271685     10281.6990306072            66.430125\\n',\n",
+       " '      4100      546.270310884967    -13.1882331707149    -12.9764002319324      27745.357268099     1856.03065087389     8056.77555325637     23361.7109929698     5480.55234188888     15418.2956158992            66.430125\\n',\n",
+       " '      4200      342.674762798481    -13.2997263985915      -13.16684383001     13574.1002794064     2083.67653023237     -8147.2471516568     10432.9141862608    -6273.51952444712     11965.0552784698            66.430125\\n',\n",
+       " '      4300      328.982877647342     -13.357268419089    -13.2296952956873     8888.44213786885    -1957.46640893499     4230.59951640472     7567.34759095066     3278.20280505295     3786.24383909323            66.430125\\n',\n",
+       " '      4400      399.974505919135    -13.3301610591127    -13.1750587712185     15155.3015620291     773.878762136857     383.151697698634     11209.4813060968    -453.562710031655     1382.63961757583            66.430125\\n',\n",
+       " '      4500      607.288205570841    -13.2830406579364    -13.0475461734097     23153.7907286489     5133.93766216813    -9511.80670289714     12635.4971368606    -4267.16195373036     11583.6472208028            66.430125\\n',\n",
+       " '      4600      734.546792621317    -13.3054903896753    -13.0206475149048     20011.2648201048     -5328.0907075166      10945.426860841     12030.0199194215     4477.64423388396     15280.6896161177            66.430125\\n',\n",
+       " '      4700      727.881139482533    -13.3296515300005    -13.0473934651036     19203.5830523612     -1447.6367385771    -3441.59181290915     15555.8018025069    -2995.29456094738     6353.63403679939            66.430125\\n',\n",
+       " '      4800      744.911361168068    -13.3891092782361    -13.1002472265659     12645.6712315307     6949.86020660159    -1770.67428487542     7529.64957979208     741.441145572394     4483.78238602476            66.430125\\n',\n",
+       " '      4900      503.001522764098    -13.3734704276236    -13.1784162783204     11248.4399863908    -1756.86281241934     4970.79044760912     5917.96892340095    -114.982312351629     7560.45453736963            66.430125\\n',\n",
+       " '      5000      275.342348584065    -13.3468610318343    -13.2400886561264      10800.651854302    -4184.03474985082    -1954.72211406221     9318.55282972239     532.913169526477     6736.31796783464            66.430125\\n',\n",
+       " '      5100      319.445157582775      -13.35579281665    -13.2319182344839     7078.46855864508     6087.68502490788    -787.477080739088     9639.27070471255    -521.973612033357     5906.93817823271            66.430125\\n',\n",
+       " '      5200      638.809531986736    -13.2974095129755    -13.0496916747796     10690.1819950034     1044.60209824009      3124.2750534991      15649.648784208     1398.19884900274     10268.1948097211            66.430125\\n',\n",
+       " '      5300      603.463190871926    -13.1848520736102    -12.9508408549474     28703.6668858092     -15808.285599615     874.520094616148     27851.7553104292     1493.25318897105     13428.2919129649            66.430125\\n',\n",
+       " '      5400      658.630149808988    -13.2628940867555    -13.0074902007584     19817.2061189338     10234.4264154496    -5526.60203506673     15778.3771830709    -3665.75473328894     15063.4677224546            66.430125\\n',\n",
+       " '      5500      408.615436219916    -13.3074935296405    -13.1490404580354     11537.0177269845     2517.72486036752     1674.49038592385     12599.2247053026     3062.29481522397     9165.36948980144            66.430125\\n',\n",
+       " '      5600      214.181004846646    -13.3352824813837    -13.2522272781555     10042.0347487875    -6791.92860405605     554.498964676772     10311.0907260387     36.4669900935877      5157.2182910593            66.430125\\n',\n",
+       " '      5700      172.298834291888    -13.3707289928959    -13.3039148759842     6400.18178072042     5082.23616603447    -743.879626382557     4212.38766379057    -1378.76061157984     4559.27926112731            66.430125\\n',\n",
+       " '      5800      136.028850081669    -13.3887752770879    -13.3360259504306     3926.79081461726    -276.695073654235    -910.828111422089      1036.7390223984     635.565770976792     4773.60247883934            66.430125\\n',\n",
+       " '      5900       178.75290088311    -13.3488726347945    -13.2795557571326     7802.85665673096    -5280.15024991408     1993.56239714999      6170.8967141139     2586.04828746319     8112.00007388103            66.430125\\n',\n",
+       " '      6000      275.373036698717    -13.2694475863946    -13.1626633104363     14672.8636484693      11995.964290812     -1801.1148631604     17933.0358480735    -8081.06565663138     12337.6147963397            66.430125\\n',\n",
+       " '      6100      512.797460568173    -13.2454496515042    -13.0465968291782     18469.4529340031    -5968.29370303197    -7844.90086831589     16483.5511409443     7476.40659710538     17510.6914899744            66.430125\\n',\n",
+       " '      6200      718.820318398019    -13.2294407269771    -12.9506962712219     22970.6367741134    -3963.68944123737     16889.8748124017     14261.2884007715     4128.60311750063     21732.7477926628            66.430125\\n',\n",
+       " '      6300       537.29244851735    -13.1997390194405    -12.9913875200322       21046.44399146     8108.13333296496    -3799.35341153282      27468.132463863    -11298.3874186838     16096.9026193795            66.430125\\n',\n",
+       " '      6400      242.260619340518    -13.2728185630642    -13.1788746347129     16059.4973806241    -3820.97489919767    -7435.07561094868      14533.670369733     5990.15197266297     11400.0064573487            66.430125\\n',\n",
+       " '      6500      233.398285180173    -13.3275784920319    -13.2370712034764     11254.2609684994     1151.27569880809     8710.27252364146     6596.75931464323    -1576.61412084322     7561.63691264234            66.430125\\n',\n",
+       " '      6600      316.691274048549    -13.3068262126309    -13.1840195326197     9931.98717398665    -428.170910495119     -3216.6621270373     9760.70644483179    -1656.72803613997     6150.39624007583            66.430125\\n',\n",
+       " '      6700      171.433948628845    -13.1680774032779    -13.1015986721048     22152.1709952688    -5929.09887634124    -13400.8662631463      21123.484977994     6527.17128857872     16979.3158755078            66.430125\\n',\n",
+       " '      6800      166.377330618575    -13.1326507357981    -13.0681328621567     26224.8126389432     8112.52187053912     18638.4133019284      23250.531120324    -6287.45339708243      22420.285186898            66.430125\\n',\n",
+       " '      6900      533.335045599337    -13.2486760898958    -13.0418591939126     11912.8349541348    -5629.27790123737    -3264.41830974208     17090.9599841291      4604.3738520954     12214.1031482074            66.430125\\n',\n",
+       " '      7000      469.094940533178    -13.2155509717412     -13.033645131645     19230.4622708079    -6423.64287033721    -15330.3949593156     19819.1886633363    -338.005721617695     15420.4516803404            66.430125\\n',\n",
+       " '      7100      358.069772487474    -13.2104830987355    -13.0716306465999     21774.8981932935     11517.7195110654     13947.7917483598     23140.9852138709     -2207.5715215206     16454.4902510214            66.430125\\n',\n",
+       " '      7200      482.301132542525    -13.3311541653604    -13.1441272223821     6071.08707595867    -6333.69858356555    -2692.42043145266     15307.8791600596     5370.20016828775     9327.79991743147            66.430125\\n',\n",
+       " '      7300      429.486875766292    -13.3478004696329    -13.1812538621215     6892.97715707806    -3697.91926998771    -3435.11385980753     13034.5964312161    -3430.79609096981      7068.9489265742            66.430125\\n',\n",
+       " '      7400      367.359691206823    -13.2675659741853    -13.1251110733277     19984.7695551153     13002.4061684046     5987.61045855143     17961.6108261008     638.716054343819     9804.79554332469            66.430125\\n',\n",
+       " '      7500      677.478909479777    -13.1777750680053    -12.9150620017839     24720.9856816389    -13430.9207214661    -4790.46386875401     21847.9154731102     8831.32658069122      24595.062383959            66.430125\\n',\n",
+       " '      7600      751.074980740868    -13.1765367908108    -12.8852846080614     21637.6961269886     -12047.390056172     372.264954324314     27828.8615954799    -8371.58421885642     23000.9742141646            66.430125\\n',\n",
+       " '      7700      516.810941166969    -13.2544615011863    -13.0540523296078     20784.2805582267     16029.4698763303    -1464.54819207407     18752.0853885752    -294.422281638691     10449.6963153528            66.430125\\n',\n",
+       " '      7800      443.341431583668    -13.2907014556401     -13.118782322447     15180.2896059221    -6919.72873377909     2104.43155237321     7008.17631779092     4773.15653781723     13808.6099740448            66.430125\\n',\n",
+       " '      7900      379.247759631364     -13.251541922798    -13.1044770615954     18988.4994793144    -6283.25967216026    -218.156988130714     10989.8775232903    -5932.30021847363     16334.9890922027            66.430125\\n',\n",
+       " '      8000      498.155430971824    -13.2492753058632    -13.0561003761433     22763.9100047029     16185.1059870204    -3610.92191369781     17255.0699407336     1226.05191440965     13087.7534705521            66.430125\\n',\n",
+       " '      8100      869.384436832226    -13.2917247860436    -12.9545945109465     20522.7526891678    -12285.3805820924     5288.93041125218     10062.5242889147     2183.33372722819     15948.8562586509            66.430125\\n',\n",
+       " '      8200      1093.11902341676    -13.2267926009059    -12.8029024304986     32886.1249824911    -3387.38461840213     384.931044419718     15754.0343659085    -5870.34420041017     20520.8105065561            66.430125\\n',\n",
+       " '      8300         850.265321341    -13.2821231627655    -12.9524069065905     25662.8859757372     10896.0031726171     -6313.1836222938     19459.7030524433    -858.617706966621     9948.70732275628            66.430125\\n',\n",
+       " '      8400      573.173288406115    -13.3734761765111    -13.1512107894026     10577.3039896081    -4588.00897185719     3919.25110554926     6341.82228703794     430.456404681648     8098.13939925982            66.430125\\n',\n",
+       " '      8500      563.336842026792    -13.3888429956427      -13.17039198999     9264.26127591903     1461.95200572219     1616.69196463304     4396.36071912336     79.8760725744146     7605.95840580559            66.430125\\n',\n",
+       " '      8600      704.399425255622    -13.3602845596818    -13.0871322441424     15456.4353909877     5251.83782484571    -3611.82091952748     11445.2357166518    -1277.93644202075     7045.26391464036            66.430125\\n',\n",
+       " '      8700      1092.24591093621    -13.2782190842901    -12.8546674898203     25501.0405829234    -4181.63704343133     1350.61469079385     20135.5797752432     4513.33888820315      19821.697788226            66.430125\\n',\n",
+       " '      8800      1259.10019361054    -13.3385539748237    -12.8502995540368     12535.7287048136     3163.49199179866     4929.39487783262     12820.6605708832     -3440.2420135181     23389.0415739445            66.430125\\n',\n",
+       " '      8900      866.662156259006    -13.3450142275705    -13.0089395996183     14613.1253915239    -5548.29739807979    -4320.88481506945     10508.2800454874      -184.4649920624     12660.6469268201            66.430125\\n',\n",
+       " '      9000      529.512395217305    -13.2605971749326    -13.0552626279774     23286.5303746273     9089.16756708102     2093.25524067014      15274.228688302     6068.56350435318     15814.1778482348            66.430125\\n',\n",
+       " '      9100       519.50456174447    -13.2977244976144    -13.0962707926766     12512.4993952396    -3361.73696695038     1290.75642649497     12407.2521558807    -6869.14422265064     15255.9348753319            66.430125\\n',\n",
+       " '      9200      529.785476741152    -13.3305984446017    -13.1251580019743     9225.04169980917    -6765.30261518417    -1487.05524833991      8312.3874978437     3747.44474087485     11502.3835391865            66.430125\\n',\n",
+       " '      9300      411.206415889871    -13.2673260652777    -13.1078682624491     19925.7201302961     12095.6828998679    -15.4268099120751     13215.3009734592     5123.30722018268     12031.7863420483            66.430125\\n',\n",
+       " '      9400      567.710180457456    -13.1913853690112    -12.9712384682795     24917.4897718619    -5674.15941995512    -1111.02285300759     19978.3684698905    -13001.5635299206     20639.7619477284            66.430125\\n',\n",
+       " '      9500      759.895995551107    -13.1279222364159    -12.8332494367063     27857.8826021108    -23980.5350948139     1043.97373212993     30578.4314629184       14461.83161579     22863.6367032474            66.430125\\n',\n",
+       " '      9600      384.526774894323    -13.1825073020238    -13.0333953419861     26205.4046643232     22199.1850799717     922.245666517741     22124.9420734002     234.919280919446     13540.5373319406            66.430125\\n',\n",
+       " '      9700      334.852138550811    -13.3137560104901    -13.1839069025422      11901.343861533    -1383.62161849762    -3842.76218576955      6511.5361718493    -4938.22862245399     10430.7570440005            66.430125\\n',\n",
+       " '      9800      371.314685980746    -13.3092590413902    -13.1652704709387     13312.7910609963    -9978.48348387502     2289.28085548708     11806.9147820196     5809.87069553342      10835.711210013            66.430125\\n',\n",
+       " '      9900      503.716168754364    -13.2703875852666    -13.0750563102305      16744.347058307     13101.2217937565    -776.706563185312     22358.6592431022    -4441.43951201798     9625.89526257975            66.430125\\n',\n",
+       " '     10000      874.702266383889    -13.2839348148909     -12.944742389537      14458.239769642     1515.35798000008    -4962.65496379813     19711.8675472838    -899.171840771311     11134.9032957219            66.430125\\n',\n",
+       " 'Loop time of 0.124536 on 1 procs for 10000 steps with 4 atoms\\n',\n",
+       " '\\n',\n",
+       " 'Performance: 6937.740 ns/day, 0.003 hours/ns, 80297.917 timesteps/s, 321.192 katom-step/s\\n',\n",
+       " '104.1% CPU use with 1 MPI tasks x no OpenMP threads\\n',\n",
+       " '\\n',\n",
+       " 'MPI task timing breakdown:\\n',\n",
+       " 'Section |  min time  |  avg time  |  max time  |%varavg| %total\\n',\n",
+       " '---------------------------------------------------------------\\n',\n",
+       " 'Pair    | 0.062597   | 0.062597   | 0.062597   |   0.0 | 50.26\\n',\n",
+       " 'Neigh   | 0          | 0          | 0          |   0.0 |  0.00\\n',\n",
+       " 'Comm    | 0.028713   | 0.028713   | 0.028713   |   0.0 | 23.06\\n',\n",
+       " 'Output  | 0.0025701  | 0.0025701  | 0.0025701  |   0.0 |  2.06\\n',\n",
+       " 'Modify  | 0.012855   | 0.012855   | 0.012855   |   0.0 | 10.32\\n',\n",
+       " 'Other   |            | 0.0178     |            |       | 14.29\\n',\n",
+       " '\\n',\n",
+       " 'Nlocal:              4 ave           4 max           4 min\\n',\n",
+       " 'Histogram: 1 0 0 0 0 0 0 0 0 0\\n',\n",
+       " 'Nghost:            662 ave         662 max         662 min\\n',\n",
+       " 'Histogram: 1 0 0 0 0 0 0 0 0 0\\n',\n",
+       " 'Neighs:            280 ave         280 max         280 min\\n',\n",
+       " 'Histogram: 1 0 0 0 0 0 0 0 0 0\\n',\n",
+       " '\\n',\n",
+       " 'Total # of neighbors = 280\\n',\n",
+       " 'Ave neighs/atom = 70\\n',\n",
+       " 'Neighbor list builds = 0\\n',\n",
+       " 'Dangerous builds = 0\\n',\n",
+       " 'Total wall time: 0:00:00\\n']"
+      ]
+     },
+     "execution_count": 28,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "job[\"log.lammps\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "id": "3b562c59-9324-43fd-b5cc-c37c390fdc3c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "b80a900d71d447cb9aa17fa4aa430cad",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "NGLWidget(max_frame=100)"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "job.animate_structures()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "id": "76dba382-58c6-4048-b6f8-6212b738905d",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'/home/janssen/mambaforge/share/pyiron/lammps/bin/run_lammps_2020.03.03.sh'"
+      ]
+     },
+     "execution_count": 30,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "job.executable"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "id": "875ad8ba-1e7b-46bb-a4ef-8365ca4d5075",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "job.executable.version = '2022.11.03_flux_mpi'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "id": "a3bb95c2-c125-49cc-a5fa-8ed4e0f4d8ea",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "#!/bin/bash\n",
+      "\n",
+      "############### This is important for other programs ##########################\n",
+      "# The FLUX_PMI_LIBRARY_PATH variable is always created under a flux instance (flux start).\n",
+      "PMIPATH=$(dirname $FLUX_PMI_LIBRARY_PATH)\n",
+      "# This is to stack LD_LIBRARY_PATH exports to look at the conda environment and flux pmi paths\n",
+      "# Suggested by Danny /https://flux-framework.readthedocs.io/en/latest/tutorials/lab/coral2.html \n",
+      "# BOTH exports are needed for pretty much any MPI process under flux\n",
+      "CONDA_LD=\"${CONDA_PREFIX}/lib/\"\n",
+      "export TMP_LD_LIBRARY_PATH=$CONDA_LD:$PMIPATH:$LD_LIBRARY_PATH\n",
+      "################################################################################\n",
+      "\n",
+      "flux run -n$1 --env=LD_LIBRARY_PATH=${TMP_LD_LIBRARY_PATH} lmp_mpi -in control.inp;\n"
+     ]
+    }
+   ],
+   "source": [
+    "!cat $job.executable"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "id": "35a7789d-582b-45cc-be64-ddb0e67dadc8",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['2020.03.03', '2020.03.03_mpi', '2022.11.03_flux', '2022.11.03_flux_mpi']"
+      ]
+     },
+     "execution_count": 33,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "job.executable.list_executables()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "id": "2a0bd26f-b4af-4747-aeaa-9705e1d8d54b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "job.server.cores = 2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "id": "3e92d7d5-eb69-442d-9f74-d4b41098dfef",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "1"
+      ]
+     },
+     "execution_count": 35,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "job.server.threads"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "id": "4f47f7db-6426-4ce3-937c-43b4db5f170d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "job.server.gpus"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "id": "9fd7c203-78f2-4e2f-97ce-a7718a3e0d2b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0, 0.5, 'Y coordinates')"
+      ]
+     },
+     "execution_count": 37,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.hist2d(job.output.positions[:, :, 0].flatten(), job.output.positions[:, :, 1].flatten(), bins=50)\n",
+    "plt.xlabel(\"X coordinates\")\n",
+    "plt.ylabel(\"Y coordinates\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "id": "d748408a-197d-4955-a7eb-161b42abe3c8",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>author</th>\n",
+       "      <th>title</th>\n",
+       "      <th>journal</th>\n",
+       "      <th>volume</th>\n",
+       "      <th>pages</th>\n",
+       "      <th>issn</th>\n",
+       "      <th>doi</th>\n",
+       "      <th>url</th>\n",
+       "      <th>year</th>\n",
+       "      <th>number</th>\n",
+       "      <th>publisher</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>[Jan Janssen, Sudarsan Surendralal, Yury Lysogorskiy, Mira Todorova, Tilmann Hickel, Ralf Drautz, Jörg Neugebauer]</td>\n",
+       "      <td>pyiron: An integrated development environment for computational materials science</td>\n",
+       "      <td>Computational Materials Science</td>\n",
+       "      <td>161</td>\n",
+       "      <td>24 - 36</td>\n",
+       "      <td>0927-0256</td>\n",
+       "      <td>https://doi.org/10.1016/j.commatsci.2018.07.043</td>\n",
+       "      <td>http://www.sciencedirect.com/science/article/pii/S0927025618304786</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>[Ask Hjorth Larsen, Jens Jørgen Mortensen, Jakob Blomqvist, Ivano E Castelli, Rune Christensen, Marcin Dułak, Jesper Friis, Michael N Groves, Bjørk Hammer, Cory Hargus, Eric D Hermes, Paul C Jenni...</td>\n",
+       "      <td>The atomic simulation environment—a Python library for working with atoms</td>\n",
+       "      <td>Journal of Physics: Condensed Matter</td>\n",
+       "      <td>29</td>\n",
+       "      <td>273002</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>http://stacks.iop.org/0953-8984/29/i=27/a=273002</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>27</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>[Steve Plimpton]</td>\n",
+       "      <td>Fast Parallel Algorithms for Short-Range Molecular Dynamics</td>\n",
+       "      <td>Journal of Computational Physics</td>\n",
+       "      <td>117</td>\n",
+       "      <td>1-19</td>\n",
+       "      <td>0021-9991</td>\n",
+       "      <td>10.1006/jcph.1995.1039</td>\n",
+       "      <td>http://www.sciencedirect.com/science/article/pii/S002199918571039X</td>\n",
+       "      <td>1995</td>\n",
+       "      <td>1</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>[Y. Mishin, D. Farkas, M. J. Mehl, D. A. Papaconstantopoulos]</td>\n",
+       "      <td>Interatomic potentials for monoatomic metals from experimental data and ab initio calculations</td>\n",
+       "      <td>Physical Review B</td>\n",
+       "      <td>59</td>\n",
+       "      <td>3393--3407</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10.1103/physrevb.59.3393</td>\n",
+       "      <td>https://doi.org/10.1103%2Fphysrevb.59.3393</td>\n",
+       "      <td>1999</td>\n",
+       "      <td>5</td>\n",
+       "      <td>American Physical Society (APS)</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                                                                                                                                                                                    author  \\\n",
+       "0                                                                                       [Jan Janssen, Sudarsan Surendralal, Yury Lysogorskiy, Mira Todorova, Tilmann Hickel, Ralf Drautz, Jörg Neugebauer]   \n",
+       "1  [Ask Hjorth Larsen, Jens Jørgen Mortensen, Jakob Blomqvist, Ivano E Castelli, Rune Christensen, Marcin Dułak, Jesper Friis, Michael N Groves, Bjørk Hammer, Cory Hargus, Eric D Hermes, Paul C Jenni...   \n",
+       "2                                                                                                                                                                                         [Steve Plimpton]   \n",
+       "3                                                                                                                                            [Y. Mishin, D. Farkas, M. J. Mehl, D. A. Papaconstantopoulos]   \n",
+       "\n",
+       "                                                                                            title  \\\n",
+       "0               pyiron: An integrated development environment for computational materials science   \n",
+       "1                       The atomic simulation environment—a Python library for working with atoms   \n",
+       "2                                     Fast Parallel Algorithms for Short-Range Molecular Dynamics   \n",
+       "3  Interatomic potentials for monoatomic metals from experimental data and ab initio calculations   \n",
+       "\n",
+       "                                journal volume       pages       issn  \\\n",
+       "0       Computational Materials Science    161     24 - 36  0927-0256   \n",
+       "1  Journal of Physics: Condensed Matter     29      273002        NaN   \n",
+       "2      Journal of Computational Physics    117        1-19  0021-9991   \n",
+       "3                     Physical Review B     59  3393--3407        NaN   \n",
+       "\n",
+       "                                               doi  \\\n",
+       "0  https://doi.org/10.1016/j.commatsci.2018.07.043   \n",
+       "1                                              NaN   \n",
+       "2                           10.1006/jcph.1995.1039   \n",
+       "3                         10.1103/physrevb.59.3393   \n",
+       "\n",
+       "                                                                  url  year  \\\n",
+       "0  http://www.sciencedirect.com/science/article/pii/S0927025618304786  2019   \n",
+       "1                    http://stacks.iop.org/0953-8984/29/i=27/a=273002  2017   \n",
+       "2  http://www.sciencedirect.com/science/article/pii/S002199918571039X  1995   \n",
+       "3                          https://doi.org/10.1103%2Fphysrevb.59.3393  1999   \n",
+       "\n",
+       "  number                        publisher  \n",
+       "0    NaN                              NaN  \n",
+       "1     27                              NaN  \n",
+       "2      1                              NaN  \n",
+       "3      5  American Physical Society (APS)  "
+      ]
+     },
+     "execution_count": 38,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pr.list_publications()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1e2d91d0-5955-471a-833a-a2091053f28d",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.12"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}