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

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

doi:10.1016/j.commatsci.2017.07.030

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

Journal Article · Wed Nov 01 00:00:00 EDT 2017 · Computational Materials Science

DOI:https://doi.org/10.1016/j.commatsci.2017.07.030· OSTI ID:1462697

Mathew, Kiran ^[1]; Montoya, Joseph H. ^[2]; Faghaninia, Alireza ^[2]; Dwarakanath, Shyam ^[2]; Aykol, Muratahan ^[2]; Tang, Hanmei ^[3]; Chu, Iek-heng ^[3]; Smidt, Tess ^[4]; Bocklund, Brandon ^[5]; Horton, Matthew ^[2]; Dagdelen, John ^[2]; Wood, Brandon ^[6]; Liu, Zi-Kui ^[5]; Neaton, Jeffrey ^[4]; Ong, Shyue Ping ^[3]; Persson, Kristin ^[1]; Jain, Anubhav ^[2]

Lawrence Berkeley National Laboratory. (LBNL), Berkeley, CA (United States). Energy Storage and Distributed Resources Division; University of California Berkeley, Berkeley, CA (United States). Department of Materials Science
Lawrence Berkeley National Laboratory. (LBNL), Berkeley, CA (United States). Energy Storage and Distributed Resources Division
University of California San Diego, La Jolla, CA (United States). Department of Nanoengineering
University of California, Berkeley, CA (United States). Department of Physics; Lawrence Berkeley National Laboratory. (LBNL), Berkeley, CA (United States). Molecular Foundry; Kavli Energy NanoSciences Institute at Berkeley, Berkeley, CA (United States).
The Pennsylvania State University, University Park, PA (United States). Department of Materials Science and Engineering
University of California Berkeley, Berkeley, CA (United States). Department of Materials Science

We introduce atomate, an open-source Python framework for computational materials science simula-tion, analysis, and design with an emphasis on automation and extensibility. Built on top of open sourcePython 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 elec-tronic bandstructure, elastic properties, and piezoelectric, dielectric, and ferroelectric properties. Atomatealso enables the computational characterization of materials by providing workflows that calculate X-rayabsorption (XAS), Electron energy loss (EELS) and Raman spectra. One of the major features of atomate isthat it provides both fully functional workflows as well as reusable components that enable one to com-pose 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 abuilder framework that creates summary reports for each computed material based on multiplesimulations.

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Research Organization:: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC); Energy Frontier Research Centers (EFRC) (United States). Center for Next Generation of Materials by Design: Incorporating Metastability (CNGMD)

Sponsoring Organization:: USDOE Office of Science (SC), Basic Energy Sciences (BES); USDOE Office of Science (SC), Basic Energy Sciences (BES) (SC-22). Materials Sciences & Engineering Division; USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR)

DOE Contract Number:: AC02-05CH11231; AC36-08GO28308

OSTI ID:: 1462697

Journal Information:: Computational Materials Science, Vol. 139, Issue C; ISSN 0927-0256

Publisher:: Elsevier

Country of Publication:: United States

Language:: English

References (45)

Identification of cathode materials for lithium batteries guided by first-principles calculations Ceder, G.; Chiang, Y. -M.; Sadoway, D. R. Nature, Vol. 392, Issue 6677 https://doi.org/10.1038/33647	journal	April 1998
Electrodes with High Power and High Capacity for Rechargeable Lithium Batteries Kang, Kisuk; Shirley Meng, Ying; Breger, Julien Science, Vol. 311, Issue 5763, p. 977-980 https://doi.org/10.1126/science.1122152	journal	February 2006
Automated Search for New Thermoelectric Materials: The Case of LiZnSb Madsen, Georg K. H. Journal of the American Chemical Society, Vol. 128, Issue 37 https://doi.org/10.1021/ja062526a	journal	September 2006
Computational and experimental investigation of TmAgTe ₂ and XYZ ₂ compounds, a new group of thermoelectric materials identified by first-principles high-throughput screening Zhu, Hong; Hautier, Geoffroy; Aydemir, Umut Journal of Materials Chemistry C, Vol. 3, Issue 40 https://doi.org/10.1039/C5TC01440A	journal	January 2015
Identification of Active Edge Sites for Electrochemical H₂ Evolution from MoS₂ Nanocatalysts Jaramillo, T. F.; Jorgensen, K. P.; Bonde, J. Science, Vol. 317, Issue 5834, p. 100-102 https://doi.org/10.1126/science.1141483	journal	July 2007
Discovery of a Ni-Ga catalyst for carbon dioxide reduction to methanol Studt, Felix; Sharafutdinov, Irek; Abild-Pedersen, Frank Nature Chemistry, Vol. 6, Issue 4 https://doi.org/10.1038/nchem.1873	journal	March 2014
Computational predictions of energy materials using density functional theory Jain, Anubhav; Shin, Yongwoo; Persson, Kristin A. Nature Reviews Materials, Vol. 1, Issue 1 https://doi.org/10.1038/natrevmats.2015.4	journal	January 2016
AiiDA: automated interactive infrastructure and database for computational science Pizzi, Giovanni; Cepellotti, Andrea; Sabatini, Riccardo Computational Materials Science, Vol. 111 https://doi.org/10.1016/j.commatsci.2015.09.013	journal	January 2016
The MAterials Simulation Toolkit (MAST) for atomistic modeling of defects and diffusion Mayeshiba, Tam; Wu, Henry; Angsten, Thomas Computational Materials Science, Vol. 126 https://doi.org/10.1016/j.commatsci.2016.09.018	journal	January 2017
Materials Design and Discovery with High-Throughput Density Functional Theory: The Open Quantum Materials Database (OQMD) Saal, James E.; Kirklin, Scott; Aykol, Muratahan JOM, Vol. 65, Issue 11 https://doi.org/10.1007/s11837-013-0755-4	journal	September 2013
An object-oriented scripting interface to a legacy electronic structure code Bahn, S. R.; Jacobsen, K. W. Computing in Science & Engineering, Vol. 4, Issue 3 https://doi.org/10.1109/5992.998641	journal	January 2002
AFLOW: An automatic framework for high-throughput materials discovery Curtarolo, Stefano; Setyawan, Wahyu; Hart, Gus L. W. Computational Materials Science, Vol. 58 https://doi.org/10.1016/j.commatsci.2012.02.005	journal	June 2012
The Harvard Clean Energy Project: Large-Scale Computational Screening and Design of Organic Photovoltaics on the World Community Grid Hachmann, Johannes; Olivares-Amaya, Roberto; Atahan-Evrenk, Sule The Journal of Physical Chemistry Letters, Vol. 2, Issue 17 https://doi.org/10.1021/jz200866s	journal	August 2011
Managing the Computational Chemistry Big Data Problem: The ioChem-BD Platform Álvarez-Moreno, M.; de Graaf, C.; López, N. Journal of Chemical Information and Modeling, Vol. 55, Issue 1 https://doi.org/10.1021/ci500593j	journal	December 2014
A high-throughput infrastructure for density functional theory calculations Jain, Anubhav; Hautier, Geoffroy; Moore, Charles J. Computational Materials Science, Vol. 50, Issue 8 https://doi.org/10.1016/j.commatsci.2011.02.023	journal	June 2011
Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set Kresse, G.; Furthmüller, J. Physical Review B, Vol. 54, Issue 16, p. 11169-11186 https://doi.org/10.1103/PhysRevB.54.11169	journal	October 1996
Parameter-free calculations of X-ray spectra with FEFF9 Rehr, John J.; Kas, Joshua J.; Vila, Fernando D. Physical Chemistry Chemical Physics, Vol. 12, Issue 21 https://doi.org/10.1039/b926434e	journal	January 2010
Fast Parallel Algorithms for Short-Range Molecular Dynamics Plimpton, Steve Journal of Computational Physics, Vol. 117, Issue 1 https://doi.org/10.1006/jcph.1995.1039	journal	March 1995
Advances in molecular quantum chemistry contained in the Q-Chem 4 program package Shao, Yihan; Gan, Zhengting; Epifanovsky, Evgeny Molecular Physics, Vol. 113, Issue 2 https://doi.org/10.1080/00268976.2014.952696	journal	September 2014
Commentary: The Materials Project: A materials genome approach to accelerating materials innovation Jain, Anubhav; Ong, Shyue Ping; Hautier, Geoffroy APL Materials, Vol. 1, Issue 1 https://doi.org/10.1063/1.4812323	journal	July 2013
Python Materials Genomics (pymatgen): A robust, open-source python library for materials analysis Ong, Shyue Ping; Richards, William Davidson; Jain, Anubhav Computational Materials Science, Vol. 68 https://doi.org/10.1016/j.commatsci.2012.10.028	journal	February 2013
FireWorks: a dynamic workflow system designed for high-throughput applications: FireWorks: A Dynamic Workflow System Designed for High-Throughput Applications Jain, Anubhav; Ong, Shyue Ping; Chen, Wei Concurrency and Computation: Practice and Experience, Vol. 27, Issue 17 https://doi.org/10.1002/cpe.3505	journal	May 2015
First principles phonon calculations in materials science Togo, Atsushi; Tanaka, Isao Scripta Materialia, Vol. 108 https://doi.org/10.1016/j.scriptamat.2015.07.021	journal	November 2015
The Computational Materials Repository Landis, David D.; Hummelshoj, Jens S.; Nestorov, Svetlozar Computing in Science & Engineering, Vol. 14, Issue 6 https://doi.org/10.1109/MCSE.2012.16	journal	November 2012
The Materials Application Programming Interface (API): A simple, flexible and efficient API for materials data based on REpresentational State Transfer (REST) principles Ong, Shyue Ping; Cholia, Shreyas; Jain, Anubhav Computational Materials Science, Vol. 97 https://doi.org/10.1016/j.commatsci.2014.10.037	journal	February 2015
Charting the complete elastic properties of inorganic crystalline compounds de Jong, Maarten; Chen, Wei; Angsten, Thomas Scientific Data, Vol. 2, Issue 1 https://doi.org/10.1038/sdata.2015.9	journal	March 2015
A database to enable discovery and design of piezoelectric materials de Jong, Maarten; Chen, Wei; Geerlings, Henry Scientific Data, Vol. 2, Issue 1 https://doi.org/10.1038/sdata.2015.53	journal	September 2015
A high-throughput framework for determining adsorption energies on solid surfaces Montoya, Joseph H.; Persson, Kristin A. npj Computational Materials, Vol. 3, Issue 1 https://doi.org/10.1038/s41524-017-0017-z	journal	March 2017
Generalized Gradient Approximation Made Simple Perdew, John P.; Burke, Kieron; Ernzerhof, Matthias Physical Review Letters, Vol. 77, Issue 18, p. 3865-3868 https://doi.org/10.1103/PhysRevLett.77.3865	journal	October 1996
Hybrid functionals based on a screened Coulomb potential Heyd, Jochen; Scuseria, Gustavo E.; Ernzerhof, Matthias The Journal of Chemical Physics, Vol. 118, Issue 18 https://doi.org/10.1063/1.1564060	journal	May 2003
From ultrasoft pseudopotentials to the projector augmented-wave method Kresse, G.; Joubert, D. Physical Review B, Vol. 59, Issue 3, p. 1758-1775 https://doi.org/10.1103/PhysRevB.59.1758	journal	January 1999
Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis set Kresse, G.; Furthmüller, J. Computational Materials Science, Vol. 6, Issue 1, p. 15-50 https://doi.org/10.1016/0927-0256(96)00008-0	journal	July 1996
BoltzTraP. A code for calculating band-structure dependent quantities Madsen, Georg K. H.; Singh, David J. Computer Physics Communications, Vol. 175, Issue 1 https://doi.org/10.1016/j.cpc.2006.03.007	journal	July 2006
Matplotlib: A 2D Graphics Environment Hunter, John D. Computing in Science & Engineering, Vol. 9, Issue 3 https://doi.org/10.1109/MCSE.2007.55	journal	January 2007
High-throughput computational screening of thermal conductivity, Debye temperature, and Grüneisen parameter using a quasiharmonic Debye model Toher, Cormac; Plata, Jose J.; Levy, Ohad Physical Review B, Vol. 90, Issue 17 https://doi.org/10.1103/PhysRevB.90.174107	journal	November 2014
First-principles thermodynamics from phonon and Debye model: Application to Ni and Ni3Al Shang, Shun-Li; Wang, Yi; Kim, DongEung Computational Materials Science, Vol. 47, Issue 4 https://doi.org/10.1016/j.commatsci.2009.12.006	journal	February 2010
GIBBS: isothermal-isobaric thermodynamics of solids from energy curves using a quasi-harmonic Debye model Blanco, M. A.; Francisco, E.; Luaña, V. Computer Physics Communications, Vol. 158, Issue 1 https://doi.org/10.1016/j.comphy.2003.12.001	journal	March 2004
First-principles phonon calculations of thermal expansion in ${Ti}_{3} {SiC}_{2}$ , ${Ti}_{3} {AlC}_{2}$ , and ${Ti}_{3} {GeC}_{2}$ Togo, Atsushi; Chaput, Laurent; Tanaka, Isao Physical Review B, Vol. 81, Issue 17 https://doi.org/10.1103/PhysRevB.81.174301	journal	May 2010
A beginner's guide to the modern theory of polarization Spaldin, Nicola A. Journal of Solid State Chemistry, Vol. 195 https://doi.org/10.1016/j.jssc.2012.05.010	journal	November 2012
Improved tangent estimate in the nudged elastic band method for finding minimum energy paths and saddle points Henkelman, Graeme; Jónsson, Hannes The Journal of Chemical Physics, Vol. 113, Issue 22 https://doi.org/10.1063/1.1323224	journal	December 2000
Improved initial guess for minimum energy path calculations Smidstrup, Søren; Pedersen, Andreas; Stokbro, Kurt The Journal of Chemical Physics, Vol. 140, Issue 21 https://doi.org/10.1063/1.4878664	journal	June 2014
First-Principles Molecular Dynamics Simulations of Silicate Melts: Structural and Dynamical Properties Karki, B. B. Reviews in Mineralogy and Geochemistry, Vol. 71, Issue 1 https://doi.org/10.2138/rmg.2010.71.17	journal	January 2010
Fast Crystallization of the Phase Change Compound GeTe by Large-Scale Molecular Dynamics Simulations Sosso, Gabriele C.; Miceli, Giacomo; Caravati, Sebastiano The Journal of Physical Chemistry Letters, Vol. 4, Issue 24 https://doi.org/10.1021/jz402268v	journal	December 2013
Raman vibrational spectra of bulk to monolayer $Re S_{2}$ with lower symmetry Feng, Yanqing; Zhou, Wei; Wang, Yaojia Physical Review B, Vol. 92, Issue 5 https://doi.org/10.1103/PhysRevB.92.054110	journal	August 2015
High-pressure synthesis of rhombohedral α-AgGaO2 via direct solid state reaction Akhtar, Meysam; Menon, Madhu; Sunkara, Mahendra Journal of Alloys and Compounds, Vol. 641 https://doi.org/10.1016/j.jallcom.2015.04.051	journal	August 2015

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