Extending the Representation of Multistate Coupled Potential Energy Surfaces To Include Properties Operators Using Neural Networks: Application to the 1,21A States of Ammonia-Reference-Cited by-同舟云学术

Extending the Representation of Multistate Coupled Potential Energy Surfaces To Include Properties Operators Using Neural Networks: Application to the 1,21A States of Ammonia

Published:2019-11-19 Issue:1 Volume:16 Page:302-313
ISSN:1549-9618
Container-title:Journal of Chemical Theory and Computation
language:en
Short-container-title:J. Chem. Theory Comput.

Author:

Guan Yafu¹,Guo Hua²^ORCID,Yarkony David R.¹^ORCID

Affiliation:

1. Department of Chemistry, Johns Hopkins University, Baltimore, Maryland 21218, United States

2. Department of Chemistry and Chemical Biology, University of New Mexico, Albuquerque, New Mexico 87131, United States

Funder

Division of Chemistry

U.S. Department of Energy

Publisher

American Chemical Society (ACS)

Subject

Physical and Theoretical Chemistry,Computer Science Applications

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jctc.9b00898

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5. Nonadiabatic dynamics: The SHARC approach

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