A Performance and Cost Assessment of Machine Learning Interatomic Potentials

Zuo, Yunxing; Chen, Chi; Li, Xiangguo; Deng, Zhi; Chen, Yiming; Behler, Jörg; Csányi, Gábor; Shapeev, Alexander V; Thompson, Aidan P; Wood, Mitchell A; Ong, Shyue Ping

doi:10.1021/acs.jpca.9b08723

Title: A Performance and Cost Assessment of Machine Learning Interatomic Potentials

Journal Article · Thu Jan 09 00:00:00 EST 2020 · Journal of Physical Chemistry. A, Molecules, Spectroscopy, Kinetics, Environment, and General Theory

DOI:https://doi.org/10.1021/acs.jpca.9b08723· OSTI ID:1559244

Zuo, Yunxing ^[1]; Chen, Chi ^[1]; Li, Xiangguo ^[1]; Deng, Zhi ^[1]; Chen, Yiming ^[1]; Behler, Jörg ^[2]; Csányi, Gábor ^[3]; Shapeev, Alexander V ^[4]; Thompson, Aidan P ^[5]; Wood, Mitchell A ^[5]; Ong, Shyue Ping ^[1]

Univ. of California, San Diego, CA (United States). Dept. of NanoEngineering
Univ. of Goettingen (Germany). Inst. of Physical and Theoretical Chemistry
Univ. of Cambridge (United Kingdom). Dept. of Engineering
Skolkovo Institute of Science and Technology, Moscow (Russian Federation)
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

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Research Organization:: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States); Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

Sponsoring Organization:: USDOE Office of Science (SC); USDOE National Nuclear Security Administration (NNSA)

Grant/Contract Number:: AC02-05CH11231; AC04-94AL85000

OSTI ID:: 1559244

Alternate ID(s):: OSTI ID: 1596079

Report Number(s):: SAND2019-7998J; ark:/13030/qt0j64t2hz

Journal Information:: Journal of Physical Chemistry. A, Molecules, Spectroscopy, Kinetics, Environment, and General Theory, Vol. 124, Issue 4; ISSN 1089-5639

Publisher:: American Chemical SocietyCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 254 works

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