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Bond order predictions using deep neural networks

Published:2021-02-14 Issue:6 Volume:129 Page:064701
ISSN:0021-8979
Container-title:Journal of Applied Physics
language:en
Short-container-title:Journal of Applied Physics

Author:

Magedov Sergey¹^ORCID,Koh Christopher²^ORCID,Malone Walter²^ORCID,Lubbers Nicholas³^ORCID,Nebgen Benjamin²^ORCID

Affiliation:

1. Department of Physics, New Mexico Institute of Mining and Technology, Socorro, New Mexico 87801, USA

2. Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87544, USA

3. Computer, Computational and Statistical Sciences Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87544, USA

Funder

Los Alamos National Laboratory

Publisher

AIP Publishing

Subject

General Physics and Astronomy

Link

https://aip.scitation.org/doi/pdf/10.1063/5.0016011

Reference61 articles.

1. Generalized Neural-Network Representation of High-Dimensional Potential-Energy Surfaces

2. Hierarchical modeling of molecular energies using a deep neural network

3. ANI-1: an extensible neural network potential with DFT accuracy at force field computational cost

4. Accurate and transferable multitask prediction of chemical properties with an atoms-in-molecules neural network

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