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Title: Python Materials Genomics (pymatgen): A robust, open-source python library for materials analysis

Abstract

We present the Python Materials Genomics (pymatgen) library, a robust, open-source Python library for materials analysis. A key enabler in high-throughput computational materials science efforts is a robust set of software tools to perform initial setup for the calculations (e.g., generation of structures and necessary input files) and post-calculation analysis to derive useful material properties from raw calculated data. The pymatgen library aims to meet these needs by (1) defining core Python objects for materials data representation, (2) providing a well-tested set of structure and thermodynamic analyses relevant to many applications, and (3) establishing an open platform for researchers to collaboratively develop sophisticated analyses of materials data obtained both from first principles calculations and experiments. The pymatgen library also provides convenient tools to obtain useful materials data via the Materials Project's REpresentational State Transfer (REST) Application Programming Interface (API). As an example, using pymatgen's interface to the Materials Project's RESTful API and phasediagram package, we demonstrate how the phase and electrochemical stability of a recently synthesized material, Li4SnS4, can be analyzed using a minimum of computing resources. Here, we find that Li4SnS4 is a stable phase in the Li-Sn-S phase diagram (consistent with the fact that it can be synthesized),more » but the narrow range of lithium chemical potentials for which it is predicted to be stable would suggest that it is not intrinsically stable against typical electrodes used in lithium-ion batteries.« less

Authors:
 [1];  [1];  [2];  [3];  [2];  [2];  [2];  [4];  [2];  [1]
  1. Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)
  2. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
  3. Univ. catholique de Louvain, Louvain-La-Neuve (Belgium)
  4. 3M, St. Paul, MN (United States)
Publication Date:
Research Org.:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Basic Energy Sciences (BES)
OSTI Identifier:
1511345
Grant/Contract Number:  
AC02-05CH11231
Resource Type:
Accepted Manuscript
Journal Name:
Computational Materials Science
Additional Journal Information:
Journal Volume: 68; Journal Issue: C; Journal ID: ISSN 0927-0256
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
36 MATERIALS SCIENCE; Materials; Project; Design; Thermodynamics; High-throughput

Citation Formats

Ong, Shyue Ping, Richards, William Davidson, Jain, Anubhav, Hautier, Geoffroy, Kocher, Michael, Cholia, Shreyas, Gunter, Dan, Chevrier, Vincent L., Persson, Kristin A., and Ceder, Gerbrand. Python Materials Genomics (pymatgen): A robust, open-source python library for materials analysis. United States: N. p., 2012. Web. doi:10.1016/j.commatsci.2012.10.028.
Ong, Shyue Ping, Richards, William Davidson, Jain, Anubhav, Hautier, Geoffroy, Kocher, Michael, Cholia, Shreyas, Gunter, Dan, Chevrier, Vincent L., Persson, Kristin A., & Ceder, Gerbrand. Python Materials Genomics (pymatgen): A robust, open-source python library for materials analysis. United States. doi:10.1016/j.commatsci.2012.10.028.
Ong, Shyue Ping, Richards, William Davidson, Jain, Anubhav, Hautier, Geoffroy, Kocher, Michael, Cholia, Shreyas, Gunter, Dan, Chevrier, Vincent L., Persson, Kristin A., and Ceder, Gerbrand. Sat . "Python Materials Genomics (pymatgen): A robust, open-source python library for materials analysis". United States. doi:10.1016/j.commatsci.2012.10.028. https://www.osti.gov/servlets/purl/1511345.
@article{osti_1511345,
title = {Python Materials Genomics (pymatgen): A robust, open-source python library for materials analysis},
author = {Ong, Shyue Ping and Richards, William Davidson and Jain, Anubhav and Hautier, Geoffroy and Kocher, Michael and Cholia, Shreyas and Gunter, Dan and Chevrier, Vincent L. and Persson, Kristin A. and Ceder, Gerbrand},
abstractNote = {We present the Python Materials Genomics (pymatgen) library, a robust, open-source Python library for materials analysis. A key enabler in high-throughput computational materials science efforts is a robust set of software tools to perform initial setup for the calculations (e.g., generation of structures and necessary input files) and post-calculation analysis to derive useful material properties from raw calculated data. The pymatgen library aims to meet these needs by (1) defining core Python objects for materials data representation, (2) providing a well-tested set of structure and thermodynamic analyses relevant to many applications, and (3) establishing an open platform for researchers to collaboratively develop sophisticated analyses of materials data obtained both from first principles calculations and experiments. The pymatgen library also provides convenient tools to obtain useful materials data via the Materials Project's REpresentational State Transfer (REST) Application Programming Interface (API). As an example, using pymatgen's interface to the Materials Project's RESTful API and phasediagram package, we demonstrate how the phase and electrochemical stability of a recently synthesized material, Li4SnS4, can be analyzed using a minimum of computing resources. Here, we find that Li4SnS4 is a stable phase in the Li-Sn-S phase diagram (consistent with the fact that it can be synthesized), but the narrow range of lithium chemical potentials for which it is predicted to be stable would suggest that it is not intrinsically stable against typical electrodes used in lithium-ion batteries.},
doi = {10.1016/j.commatsci.2012.10.028},
journal = {Computational Materials Science},
number = C,
volume = 68,
place = {United States},
year = {2012},
month = {12}
}

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Cited by: 662 works
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Figures / Tables:

Fig. 1 Fig. 1: Overview of the pymatgen library. Text in italics represent names of Python packages, modules or classes.

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Materials discovery by chemical analogy: role of oxidation states in structure prediction
journal, January 2018

  • Davies, Daniel W.; Butler, Keith T.; Isayev, Olexandr
  • Faraday Discussions, Vol. 211
  • DOI: 10.1039/c8fd00032h

Atomic layer deposition and first principles modeling of glassy Li 3 BO 3 –Li 2 CO 3 electrolytes for solid-state Li metal batteries
journal, January 2018

  • Kazyak, Eric; Chen, Kuan-Hung; Davis, Andrew L.
  • Journal of Materials Chemistry A, Vol. 6, Issue 40
  • DOI: 10.1039/c8ta08761j

Origins of ultralow thermal conductivity in 1-2-1-4 quaternary selenides
journal, January 2019

  • Kuo, Jimmy Jiahong; Aydemir, Umut; Pöhls, Jan-Hendrik
  • Journal of Materials Chemistry A, Vol. 7, Issue 6
  • DOI: 10.1039/c8ta09660k

Rational synthesis and electrochemical performance of LiVOPO 4 polymorphs
journal, January 2019

  • Hidalgo, Marc Francis V.; Lin, Yuh-Chieh; Grenier, Antonin
  • Journal of Materials Chemistry A, Vol. 7, Issue 14
  • DOI: 10.1039/c8ta12531g

Unveiling new stable manganese based photoanode materials via theoretical high-throughput screening and experiments
journal, January 2019

  • Noh, Juhwan; Kim, Sungwon; Gu, Geun ho
  • Chemical Communications, Vol. 55, Issue 89
  • DOI: 10.1039/c9cc06736a

LiAl 5 O 8 as a potential coating material in lithium-ion batteries: a first principles study
journal, January 2019

  • Mo, Sijia; Zhang, Bingkai; Zhang, Kecheng
  • Physical Chemistry Chemical Physics, Vol. 21, Issue 25
  • DOI: 10.1039/c9cp02650a

Bulk and surface DFT investigations of inorganic halide perovskites screened using machine learning and materials property databases
journal, January 2019

  • Jain, Deepak; Chaube, Suryanaman; Khullar, Prerna
  • Physical Chemistry Chemical Physics, Vol. 21, Issue 35
  • DOI: 10.1039/c9cp03240a

Efficient Pourbaix diagrams of many-element compounds
journal, January 2019

  • Patel, Anjli M.; Nørskov, Jens K.; Persson, Kristin A.
  • Physical Chemistry Chemical Physics, Vol. 21, Issue 45
  • DOI: 10.1039/c9cp04799a

Out-of-plane ion transport makes nitrogenated holey graphite a promising high-rate anode for both Li and Na ion batteries
journal, January 2019

  • Huang, He; Wu, Hong-Hui; Chi, Cheng
  • Nanoscale, Vol. 11, Issue 40
  • DOI: 10.1039/c9nr06011a

Electronic properties of heterogenized Ru( ii ) polypyridyl photoredox complexes on covalent triazine frameworks
journal, January 2019

  • De Vos, Arthur; Lejaeghere, Kurt; Muniz Miranda, Francesco
  • Journal of Materials Chemistry A, Vol. 7, Issue 14
  • DOI: 10.1039/c9ta00573k

A Li 2 CuPS 4 superionic conductor: a new sulfide-based solid-state electrolyte
journal, January 2019

  • Xu, Zhenming; Chen, Ronghan; Zhu, Hong
  • Journal of Materials Chemistry A, Vol. 7, Issue 20
  • DOI: 10.1039/c9ta01317b

Depth-dependent oxygen redox activity in lithium-rich layered oxide cathodes
journal, January 2019

  • Naylor, Andrew J.; Makkos, Eszter; Maibach, Julia
  • Journal of Materials Chemistry A, Vol. 7, Issue 44
  • DOI: 10.1039/c9ta09019c

Revealing cooperative Li-ion migration in Li 1+x Al x Ti 2−x (PO 4 ) 3 solid state electrolytes with high Al doping
journal, January 2020

  • Zhang, Bingkai; Lin, Zhan; Dong, Huafeng
  • Journal of Materials Chemistry A, Vol. 8, Issue 1
  • DOI: 10.1039/c9ta09770h

Constructing first-principles phase diagrams of amorphous Li x Si using machine-learning-assisted sampling with an evolutionary algorithm
journal, June 2018

  • Artrith, Nongnuch; Urban, Alexander; Ceder, Gerbrand
  • The Journal of Chemical Physics, Vol. 148, Issue 24
  • DOI: 10.1063/1.5017661

Predicting the stability of ternary intermetallics with density functional theory and machine learning
journal, June 2018

  • Schmidt, Jonathan; Chen, Liming; Botti, Silvana
  • The Journal of Chemical Physics, Vol. 148, Issue 24
  • DOI: 10.1063/1.5020223

Nonlinear elastic behavior and anisotropic electronic properties of two-dimensional borophene
journal, April 2019

  • Faghihnasiri, Mahdi; Jafari, Homayoun; Ramazani, Ali
  • Journal of Applied Physics, Vol. 125, Issue 14
  • DOI: 10.1063/1.5079932

Machine learning reveals orbital interaction in materials
journal, January 2017

  • Lam Pham, Tien; Kino, Hiori; Terakura, Kiyoyuki
  • Science and Technology of Advanced Materials, Vol. 18, Issue 1
  • DOI: 10.1080/14686996.2017.1378060

Computational methods for 2D materials: discovery, property characterization, and application design
journal, November 2017

  • Paul, J. T.; Singh, A. K.; Dong, Z.
  • Journal of Physics: Condensed Matter, Vol. 29, Issue 47
  • DOI: 10.1088/1361-648x/aa9305

Carbon diffusion in molten uranium: an ab initio molecular dynamics study
journal, March 2018

  • Garrett, Kerry E.; Abrecht, David G.; Kessler, Sean H.
  • Modelling and Simulation in Materials Science and Engineering, Vol. 26, Issue 3
  • DOI: 10.1088/1361-651x/aaad72

Transferability of interatomic potentials for molybdenum and silicon
journal, January 2019

  • Lysogorskiy, Y.; Hammerschmidt, T.; Janssen, J.
  • Modelling and Simulation in Materials Science and Engineering, Vol. 27, Issue 2
  • DOI: 10.1088/1361-651x/aafd13

Rare-earth magnetic nitride perovskites
journal, March 2019

  • Flores-Livas, José A.; Sarmiento-Pérez, R.; Botti, Silvana
  • Journal of Physics: Materials, Vol. 2, Issue 2
  • DOI: 10.1088/2515-7639/ab083e

From DFT to machine learning: recent approaches to materials science–a review
journal, May 2019

  • Schleder, Gabriel R.; Padilha, Antonio C. M.; Acosta, Carlos Mera
  • Journal of Physics: Materials, Vol. 2, Issue 3
  • DOI: 10.1088/2515-7639/ab084b

Machine learning for the modeling of interfaces in energy storage and conversion materials
journal, July 2019


Modeling the structural distortion and magnetic ground state of the polar lacunar spinel GaV 4 Se 8
journal, July 2019


Ab initio insight into the formation of small polarons: A study across four metal peroxides
journal, November 2019


Computational screening of Fe-Ta hard magnetic phases
journal, January 2020


Mapping skyrmion stability in uniaxial lacunar spinel magnets from first principles
journal, February 2020


Dynamic instabilities in strongly correlated VSe 2 monolayers and bilayers
journal, December 2017


Electronic-Structure Origin of Cation Disorder in Transition-Metal Oxides
journal, October 2017


Accurate force field for molybdenum by machine learning large materials data
journal, September 2017


Crystal structure prediction accelerated by Bayesian optimization
journal, January 2018


Effects of composition, crystal structure, and surface orientation on band alignment of divalent metal oxides: A first-principles study
journal, December 2018


High-density electron doping of SmNiO 3 from first principles
journal, November 2019


COD::CIF::Parser : an error-correcting CIF parser for the Perl language
journal, February 2016

  • Merkys, Andrius; Vaitkus, Antanas; Butkus, Justas
  • Journal of Applied Crystallography, Vol. 49, Issue 1
  • DOI: 10.1107/s1600576715022396

The thermodynamic scale of inorganic crystalline metastability
journal, November 2016

  • Sun, Wenhao; Dacek, Stephen T.; Ong, Shyue Ping
  • Science Advances, Vol. 2, Issue 11
  • DOI: 10.1126/sciadv.1600225

Atomistic Structure and Ab Initio Electrochemical Properties of Li 4 Ti 5 O 12 Defect Spinel for Li Ion Batteries
journal, December 2013

  • Tsai, Ping-chun; Hsu, Wen-Dung; Lin, Shih-kang
  • Journal of The Electrochemical Society, Vol. 161, Issue 3
  • DOI: 10.1149/2.095403jes

A Combinatorial Investigation of Fe-Si-Zn Thin Film Negative Electrodes for Li-Ion Batteries
journal, November 2014

  • MacEachern, L.; Dunlap, R. A.; Obrovac, M. N.
  • Journal of The Electrochemical Society, Vol. 162, Issue 1
  • DOI: 10.1149/2.1051501jes

A data ecosystem to support machine learning in materials science
journal, October 2019

  • Blaiszik, Ben; Ward, Logan; Schwarting, Marcus
  • MRS Communications, Vol. 9, Issue 4
  • DOI: 10.1557/mrc.2019.118

Robocrystallographer: automated crystal structure text descriptions and analysis
journal, July 2019


SMACT: Semiconducting Materials by Analogy and Chemical Theory
journal, June 2019

  • Davies, Daniel; Butler, Keith; Jackson, Adam
  • Journal of Open Source Software, Vol. 4, Issue 38
  • DOI: 10.21105/joss.01361

WulffPack: A Python package for Wulff constructions
journal, January 2020

  • Rahm, J.; Erhart, Paul
  • Journal of Open Source Software, Vol. 5, Issue 45
  • DOI: 10.21105/joss.01944

Assessing Local Structure Motifs Using Order Parameters for Motif Recognition, Interstitial Identification, and Diffusion Path Characterization
journal, November 2017

  • Zimmermann, Nils E. R.; Horton, Matthew K.; Jain, Anubhav
  • Frontiers in Materials, Vol. 4
  • DOI: 10.3389/fmats.2017.00034

Computational Screening of New Perovskite Materials Using Transfer Learning and Deep Learning
journal, December 2019

  • Li, Xiang; Dan, Yabo; Dong, Rongzhi
  • Applied Sciences, Vol. 9, Issue 24
  • DOI: 10.3390/app9245510

    Figures/Tables have been extracted from DOE-funded journal article accepted manuscripts.