Python Materials Genomics (pymatgen): A robust, open-source python library for materials analysis
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 stru...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | en_US |
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Elsevier
2016
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| Online Access: | http://hdl.handle.net/1721.1/101936 https://orcid.org/0000-0002-8126-5048 |
| _version_ | 1826204563308281856 |
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| author | Ong, Shyue Ping Richards, William Davidson Jain, Anubhav Hautier, Geoffroy Kocher, Michael Cholia, Shreyas Gunter, Dan Chevrier, Vincent L. Persson, Kristin A. Ceder, Gerbrand |
| author2 | Massachusetts Institute of Technology. Department of Materials Science and Engineering |
| author_facet | Massachusetts Institute of Technology. Department of Materials Science and Engineering Ong, Shyue Ping Richards, William Davidson Jain, Anubhav Hautier, Geoffroy Kocher, Michael Cholia, Shreyas Gunter, Dan Chevrier, Vincent L. Persson, Kristin A. Ceder, Gerbrand |
| author_sort | Ong, Shyue Ping |
| collection | MIT |
| description | 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, Li[subscript 4]SnS[subscript 4], can be analyzed using a minimum of computing resources. We find that Li[subscript 4]SnS[subscript 4] 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. |
| first_indexed | 2024-09-23T12:57:27Z |
| format | Article |
| id | mit-1721.1/101936 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T12:57:27Z |
| publishDate | 2016 |
| publisher | Elsevier |
| record_format | dspace |
| spelling | mit-1721.1/1019362022-09-28T11:09:12Z Python Materials Genomics (pymatgen): A robust, open-source python library for materials analysis Ong, Shyue Ping Richards, William Davidson Jain, Anubhav Hautier, Geoffroy Kocher, Michael Cholia, Shreyas Gunter, Dan Chevrier, Vincent L. Persson, Kristin A. Ceder, Gerbrand Massachusetts Institute of Technology. Department of Materials Science and Engineering Ceder, Gerbrand Ong, Shyue Ping Richards, William Davidson Ceder, Gerbrand 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, Li[subscript 4]SnS[subscript 4], can be analyzed using a minimum of computing resources. We find that Li[subscript 4]SnS[subscript 4] 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. United States. Dept. of Energy. Office of Basic Energy Sciences (Grant DE-FG02-96ER45571) 2016-03-30T16:55:07Z 2016-03-30T16:55:07Z 2012-12 2012-07 Article http://purl.org/eprint/type/JournalArticle 09270256 http://hdl.handle.net/1721.1/101936 Ong, Shyue Ping, William Davidson Richards, Anubhav Jain, Geoffroy Hautier, Michael Kocher, Shreyas Cholia, Dan Gunter, Vincent L. Chevrier, Kristin A. Persson, and Gerbrand Ceder. “Python Materials Genomics (pymatgen): A Robust, Open-Source Python Library for Materials Analysis.” Computational Materials Science 68 (February 2013): 314–319. https://orcid.org/0000-0002-8126-5048 en_US http://dx.doi.org/10.1016/j.commatsci.2012.10.028 Computational Materials Science Creative Commons Attribution-NonCommercial-NoDerivs License http://creativecommons.org/licenses/by-nc-nd/4.0/ application/pdf Elsevier Prof. Ceder |
| spellingShingle | 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 |
| title | Python Materials Genomics (pymatgen): A robust, open-source python library for materials analysis |
| title_full | Python Materials Genomics (pymatgen): A robust, open-source python library for materials analysis |
| title_fullStr | Python Materials Genomics (pymatgen): A robust, open-source python library for materials analysis |
| title_full_unstemmed | Python Materials Genomics (pymatgen): A robust, open-source python library for materials analysis |
| title_short | Python Materials Genomics (pymatgen): A robust, open-source python library for materials analysis |
| title_sort | python materials genomics pymatgen a robust open source python library for materials analysis |
| url | http://hdl.handle.net/1721.1/101936 https://orcid.org/0000-0002-8126-5048 |
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