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This content will become publicly available on January 16, 2019

Title: An atomistic fingerprint algorithm for learning ab initio molecular force fields

Authors:
ORCiD logo [1] ;  [1] ;  [1]
  1. Division of Applied Mathematics, Brown University, Providence, Rhode Island 02912, USA
Publication Date:
Grant/Contract Number:
Collaboratory on Mathematics for Mesoscopic Modeling of Materials
Type:
Publisher's Accepted Manuscript
Journal Name:
Journal of Chemical Physics
Additional Journal Information:
Journal Volume: 148; Journal Issue: 3; Related Information: CHORUS Timestamp: 2018-02-14 18:32:18; Journal ID: ISSN 0021-9606
Publisher:
American Institute of Physics
Sponsoring Org:
USDOE
Country of Publication:
United States
Language:
English
OSTI Identifier:
1417101

Tang, Yu-Hang, Zhang, Dongkun, and Karniadakis, George Em. An atomistic fingerprint algorithm for learning ab initio molecular force fields. United States: N. p., Web. doi:10.1063/1.5008630.
Tang, Yu-Hang, Zhang, Dongkun, & Karniadakis, George Em. An atomistic fingerprint algorithm for learning ab initio molecular force fields. United States. doi:10.1063/1.5008630.
Tang, Yu-Hang, Zhang, Dongkun, and Karniadakis, George Em. 2018. "An atomistic fingerprint algorithm for learning ab initio molecular force fields". United States. doi:10.1063/1.5008630.
@article{osti_1417101,
title = {An atomistic fingerprint algorithm for learning ab initio molecular force fields},
author = {Tang, Yu-Hang and Zhang, Dongkun and Karniadakis, George Em},
abstractNote = {},
doi = {10.1063/1.5008630},
journal = {Journal of Chemical Physics},
number = 3,
volume = 148,
place = {United States},
year = {2018},
month = {1}
}