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NewtonNet: a Newtonian message passing network for deep learning of interatomic potentials and forces.
Haghighatlari, Mojtaba; Li, Jie; Guan, Xingyi; Zhang, Oufan; Das, Akshaya; Stein, Christopher J; Heidar-Zadeh, Farnaz; Liu, Meili; Head-Gordon, Martin; Bertels, Luke; Hao, Hongxia; Leven, Itai; Head-Gordon, Teresa.
Afiliação
  • Haghighatlari M; Kenneth S. Pitzer Theory Center and Department of Chemistry, University of California Berkeley CA USA thg@berkeley.edu.
  • Li J; Kenneth S. Pitzer Theory Center and Department of Chemistry, University of California Berkeley CA USA thg@berkeley.edu.
  • Guan X; Kenneth S. Pitzer Theory Center and Department of Chemistry, University of California Berkeley CA USA thg@berkeley.edu.
  • Zhang O; Chemical Sciences Division, Lawrence Berkeley National Laboratory Berkeley CA USA.
  • Das A; Kenneth S. Pitzer Theory Center and Department of Chemistry, University of California Berkeley CA USA thg@berkeley.edu.
  • Stein CJ; Kenneth S. Pitzer Theory Center and Department of Chemistry, University of California Berkeley CA USA thg@berkeley.edu.
  • Heidar-Zadeh F; Kenneth S. Pitzer Theory Center and Department of Chemistry, University of California Berkeley CA USA thg@berkeley.edu.
  • Liu M; Chemical Sciences Division, Lawrence Berkeley National Laboratory Berkeley CA USA.
  • Head-Gordon M; Theoretical Physics and Center for Nanointegration Duisburg-Essen (CENIDE), University of Duisburg-Essen 47048 Duisburg Germany.
  • Bertels L; Kenneth S. Pitzer Theory Center and Department of Chemistry, University of California Berkeley CA USA thg@berkeley.edu.
  • Hao H; Center for Molecular Modeling (CMM), Ghent University B-9052 Ghent Belgium.
  • Leven I; Department of Chemistry, Queen's University Kingston Ontario K7L 3N6 Canada.
  • Head-Gordon T; Kenneth S. Pitzer Theory Center and Department of Chemistry, University of California Berkeley CA USA thg@berkeley.edu.
Digit Discov ; 1(3): 333-343, 2022 Jun 13.
Article em En | MEDLINE | ID: mdl-35769203
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Digit Discov Ano de publicação: 2022 Tipo de documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Digit Discov Ano de publicação: 2022 Tipo de documento: Article