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Title: Atomate: A high-level interface to generate, execute, and analyze computational materials science workflows

Abstract

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.

Authors:
 [1];  [2];  [2];  [2];  [2];  [3];  [3];  [4];  [5];  [2];  [2];  [6];  [5];  [4];  [3];  [1];  [2]
+ Show Author Affiliations
  1. Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States); University of California, Berkeley, CA (United States)
  2. Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
  3. University of California, San Diego, CA (United States)
  4. University of California, Berkeley, CA (United States); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States); Kavli Energy NanoScience Institute, Berkeley, CA (United States)
  5. Pennsylvania State University, University Park, PA (United States)
  6. University of California, Berkeley, CA (United States)
Publication Date:
Research Org.:
Energy Frontier Research Centers (EFRC) (United States). Center for Next Generation of Materials by Design: Incorporating Metastability (CNGMD); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Basic Energy Sciences (BES). Materials Sciences & Engineering Division; National Science Foundation (NSF); USDOE Office of Science (SC), Basic Energy Sciences (BES)
OSTI Identifier:
1525252
Alternate Identifier(s):
OSTI ID: 1495847
Grant/Contract Number:  
AC02-05CH11231; 1640899; EDCBEE; DGE-1449785; AC36-08GO28308; 1550423; ACI-1053575; AC02 05CH11231; AC0205CH11231
Resource Type:
Accepted Manuscript
Journal Name:
Computational Materials Science
Additional Journal Information:
Journal Volume: 139; Journal Issue: C; Journal ID: ISSN 0927-0256
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
36 MATERIALS SCIENCE

Citation Formats

Mathew, Kiran, Montoya, Joseph H., Faghaninia, Alireza, Dwarakanath, Shyam, Aykol, Muratahan, Tang, Hanmei, Chu, Iek-heng, Smidt, Tess, Bocklund, Brandon, Horton, Matthew, Dagdelen, John, Wood, Brandon, Liu, Zi-Kui, Neaton, Jeffrey, Ong, Shyue Ping, Persson, Kristin, and Jain, Anubhav. Atomate: A high-level interface to generate, execute, and analyze computational materials science workflows. United States: N. p., 2017. Web. doi:10.1016/j.commatsci.2017.07.030.
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Mathew, Kiran, Montoya, Joseph H., Faghaninia, Alireza, Dwarakanath, Shyam, Aykol, Muratahan, Tang, Hanmei, Chu, Iek-heng, Smidt, Tess, Bocklund, Brandon, Horton, Matthew, Dagdelen, John, Wood, Brandon, Liu, Zi-Kui, Neaton, Jeffrey, Ong, Shyue Ping, Persson, Kristin, & Jain, Anubhav. Atomate: A high-level interface to generate, execute, and analyze computational materials science workflows. United States. https://doi.org/10.1016/j.commatsci.2017.07.030
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Mathew, Kiran, Montoya, Joseph H., Faghaninia, Alireza, Dwarakanath, Shyam, Aykol, Muratahan, Tang, Hanmei, Chu, Iek-heng, Smidt, Tess, Bocklund, Brandon, Horton, Matthew, Dagdelen, John, Wood, Brandon, Liu, Zi-Kui, Neaton, Jeffrey, Ong, Shyue Ping, Persson, Kristin, and Jain, Anubhav. Fri . "Atomate: A high-level interface to generate, execute, and analyze computational materials science workflows". United States. https://doi.org/10.1016/j.commatsci.2017.07.030. https://www.osti.gov/servlets/purl/1525252.
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@article{osti_1525252,
title = {Atomate: A high-level interface to generate, execute, and analyze computational materials science workflows},
author = {Mathew, Kiran and Montoya, Joseph H. and Faghaninia, Alireza and Dwarakanath, Shyam and Aykol, Muratahan and Tang, Hanmei and Chu, Iek-heng and Smidt, Tess and Bocklund, Brandon and Horton, Matthew and Dagdelen, John and Wood, Brandon and Liu, Zi-Kui and Neaton, Jeffrey and Ong, Shyue Ping and Persson, Kristin and Jain, Anubhav},
abstractNote = {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.},
doi = {10.1016/j.commatsci.2017.07.030},
journal = {Computational Materials Science},
number = C,
volume = 139,
place = {United States},
year = {2017},
month = {8}
}
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Journal Article:
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Publisher's Version of Record
https://doi.org/10.1016/j.commatsci.2017.07.030
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