Neural-network potential energy surface with small database and high precision: A benchmark of the H + H2 system-Reference-Cited by-同舟云学术

Neural-network potential energy surface with small database and high precision: A benchmark of the H + H2 system

Published:2019-09-21 Issue:11 Volume:151 Page:114302
ISSN:0021-9606
Container-title:The Journal of Chemical Physics
language:en
Short-container-title:J. Chem. Phys.

Author:

Song Qingfei¹²^ORCID,Zhang Qiuyu¹²,Meng Qingyong¹²^ORCID

Affiliation:

1. Department of Applied Chemistry, Northwestern Polytechnical University, West Youyi Road 127, 710072 Xi’an, China

2. Ministry-of-Education Key Laboratory of Materials Physics and Chemistry under Extraordinary Conditions, Northwestern Polytechnical University, West Youyi Road 127, 710072 Xi’an, China

Publisher

AIP Publishing

Subject

Physical and Theoretical Chemistry,General Physics and Astronomy

Link

http://aip.scitation.org/doi/pdf/10.1063/1.5118692

Reference59 articles.

1. Interpolation of diabatic potential-energy surfaces: Quantum dynamics on ab initio surfaces

2. Representing molecule-surface interactions with symmetry-adapted neural networks

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

4. Neural network potential-energy surfaces in chemistry: a tool for large-scale simulations

5. Constructing high-dimensional neural network potentials: A tutorial review

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