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Title: Density functional theory based neural network force fields from energy decompositions

Abstract

Not provided.

Authors:
; ; ;
Publication Date:
Research Org.:
Oak Ridge National Laboratory, Oak Ridge Leadership Computing Facility (OLCF); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1544118
Resource Type:
Journal Article
Journal Name:
Physical Review B
Additional Journal Information:
Journal Volume: 99; Journal Issue: 6; Journal ID: ISSN 2469-9950
Publisher:
American Physical Society (APS)
Country of Publication:
United States
Language:
English

Citation Formats

Huang, Yufeng, Kang, Jun, Goddard, William A., and Wang, Lin-Wang. Density functional theory based neural network force fields from energy decompositions. United States: N. p., 2019. Web. doi:10.1103/PhysRevB.99.064103.
Huang, Yufeng, Kang, Jun, Goddard, William A., & Wang, Lin-Wang. Density functional theory based neural network force fields from energy decompositions. United States. doi:10.1103/PhysRevB.99.064103.
Huang, Yufeng, Kang, Jun, Goddard, William A., and Wang, Lin-Wang. Fri . "Density functional theory based neural network force fields from energy decompositions". United States. doi:10.1103/PhysRevB.99.064103.
@article{osti_1544118,
title = {Density functional theory based neural network force fields from energy decompositions},
author = {Huang, Yufeng and Kang, Jun and Goddard, William A. and Wang, Lin-Wang},
abstractNote = {Not provided.},
doi = {10.1103/PhysRevB.99.064103},
journal = {Physical Review B},
issn = {2469-9950},
number = 6,
volume = 99,
place = {United States},
year = {2019},
month = {2}
}

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