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

► Python Materials Genomics (pymatgen) is a robust, open-source library for materials analysis. ► Well-tested set of structure and thermodynamic analyses relevant to many applications. ► Open platform for researchers to collaboratively develop sophisticated analyses of materials. ► Convenient tools...

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Vydané v:Computational materials science Ročník 68; s. 314 - 319
Hlavní autori: Ong, Shyue Ping, Richards, William Davidson, Jain, Anubhav, Hautier, Geoffroy, Kocher, Michael, Cholia, Shreyas, Gunter, Dan, Chevrier, Vincent L., Persson, Kristin A., Ceder, Gerbrand
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Amsterdam Elsevier B.V 01.02.2013
Elsevier
Predmet:
Cross-disciplinary physics: materials science; rheology
Design
Exact sciences and technology
High-throughput
Materials
Materials science
Phase diagrams and microstructures developed by solidification and solid-solid phase transformations
Physics
Project
Thermodynamics
Design
High-throughput
Project
Thermodynamics
Materials
Phase diagrams
Computerized simulation
Calculation methods
Materials properties
Density functional method
Chemical potential
Thermodynamic analysis
Phase stability
ISSN:0927-0256, 1879-0801
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Popis
Shrnutí:► Python Materials Genomics (pymatgen) is a robust, open-source library for materials analysis. ► Well-tested set of structure and thermodynamic analyses relevant to many applications. ► Open platform for researchers to collaboratively develop sophisticated analyses of materials. ► Convenient tools to obtain useful materials data via the Materials Project’s RESTful API. ► Evaluated phase and electrochemical stability of recently synthesized material Li4SnS4. 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. 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.
ISSN:0927-0256
1879-0801
DOI:10.1016/j.commatsci.2012.10.028