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Title: Adaptive coupling of a deep neural network potential to a classical force field

Authors:
ORCiD logo [1]; ORCiD logo [2];  [3]
  1. Program in Applied and Computational Mathematics, Princeton University, Princeton, New Jersey 08544, USA
  2. Laboratory of Computational Physics, Institute of Applied Physics and Computational Mathematics, Huayuan Road 6, Beijing 100088, People’s Republic of China
  3. Department of Mathematics and Program in Applied and Computational Mathematics, Princeton University, Princeton, New Jersey 08544, USA, Center for Data Science and Beijing International Center for Mathematical Research, Peking University, Beijing, People’s Republic of China, and Beijing Institute of Big Data Research, Beijing 100871, People’s Republic of China
Publication Date:
Sponsoring Org.:
USDOE
OSTI Identifier:
1477902
Grant/Contract Number:  
SC0008626; SC0009248
Resource Type:
Journal Article: Publisher's Accepted Manuscript
Journal Name:
Journal of Chemical Physics
Additional Journal Information:
Journal Name: Journal of Chemical Physics Journal Volume: 149 Journal Issue: 15; Journal ID: ISSN 0021-9606
Publisher:
American Institute of Physics
Country of Publication:
United States
Language:
English

Citation Formats

Zhang, Linfeng, Wang, Han, and E, Weinan. Adaptive coupling of a deep neural network potential to a classical force field. United States: N. p., 2018. Web. doi:10.1063/1.5042714.
Zhang, Linfeng, Wang, Han, & E, Weinan. Adaptive coupling of a deep neural network potential to a classical force field. United States. doi:10.1063/1.5042714.
Zhang, Linfeng, Wang, Han, and E, Weinan. Sun . "Adaptive coupling of a deep neural network potential to a classical force field". United States. doi:10.1063/1.5042714.
@article{osti_1477902,
title = {Adaptive coupling of a deep neural network potential to a classical force field},
author = {Zhang, Linfeng and Wang, Han and E, Weinan},
abstractNote = {},
doi = {10.1063/1.5042714},
journal = {Journal of Chemical Physics},
issn = {0021-9606},
number = 15,
volume = 149,
place = {United States},
year = {2018},
month = {10}
}

Journal Article:
Free Publicly Available Full Text
This content will become publicly available on October 17, 2019
Publisher's Accepted Manuscript

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