TY - JOUR
T1 - Atomate
T2 - A high-level interface to generate, execute, and analyze computational materials science workflows
AU - Mathew, Kiran
AU - Montoya, Joseph H.
AU - Faghaninia, Alireza
AU - Dwarakanath, Shyam
AU - Aykol, Muratahan
AU - Tang, Hanmei
AU - Chu, Iek heng
AU - Smidt, Tess
AU - Bocklund, Brandon
AU - Horton, Matthew
AU - Dagdelen, John
AU - Wood, Brandon
AU - Liu, Zi Kui
AU - Neaton, Jeffrey
AU - Ong, Shyue Ping
AU - Persson, Kristin
AU - Jain, Anubhav
N1 - Publisher Copyright:
© 2017 Elsevier B.V.
PY - 2017/11
Y1 - 2017/11
N2 - We introduce atomate, an open-source Python framework for computational materials science simulation, analysis, and design with an emphasis on automation and extensibility. Built on top of open source Python packages already in use by the materials community such as pymatgen, FireWorks, and custodian, atomate provides well-tested workflow templates to compute various materials properties such as electronic bandstructure, elastic properties, and piezoelectric, dielectric, and ferroelectric properties. Atomate also enables the computational characterization of materials by providing workflows that calculate X-ray absorption (XAS), Electron energy loss (EELS) and Raman spectra. One of the major features of atomate is that it provides both fully functional workflows as well as reusable components that enable one to compose complex materials science workflows that use a diverse set of computational tools. Additionally, atomate creates output databases that organize the results from individual calculations and contains a builder framework that creates summary reports for each computed material based on multiple simulations.
AB - We introduce atomate, an open-source Python framework for computational materials science simulation, analysis, and design with an emphasis on automation and extensibility. Built on top of open source Python packages already in use by the materials community such as pymatgen, FireWorks, and custodian, atomate provides well-tested workflow templates to compute various materials properties such as electronic bandstructure, elastic properties, and piezoelectric, dielectric, and ferroelectric properties. Atomate also enables the computational characterization of materials by providing workflows that calculate X-ray absorption (XAS), Electron energy loss (EELS) and Raman spectra. One of the major features of atomate is that it provides both fully functional workflows as well as reusable components that enable one to compose complex materials science workflows that use a diverse set of computational tools. Additionally, atomate creates output databases that organize the results from individual calculations and contains a builder framework that creates summary reports for each computed material based on multiple simulations.
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U2 - 10.1016/j.commatsci.2017.07.030
DO - 10.1016/j.commatsci.2017.07.030
M3 - Article
AN - SCOPUS:85026733777
SN - 0927-0256
VL - 139
SP - 140
EP - 152
JO - Computational Materials Science
JF - Computational Materials Science
ER -