Nonadiabatic Derivative Couplings Calculated Using Information of Potential Energy Surfaces without Wavefunctions: Ab Initio and Machine Learning Implementations

Nonadiabatic Derivative Couplings Calculated Using Information of Potential Energy Surfaces without Wavefunctions: Ab Initio and Machine Learning Implementations

In this work, we implemented an approximate algorithm for calculating nonadiabatic coupling matrix elements (NACMEs) of a polyatomic system with ab initio methods and machine learning (ML) models. Utilizing this algorithm, one can calculate NACMEs using only the information of potential energy surfa...

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Bibliographic Details
Main Authors: Wen-Kai Chen, Sheng-Rui Wang, Xiang-Yang Liu, Wei-Hai Fang, Ganglong Cui
Format: Article
Language:English
Published: MDPI AG 2023-05-01
Series:Molecules
Subjects:
nonadiabatic couplings
machine learning
excited states
Online Access:https://www.mdpi.com/1420-3049/28/10/4222

Internet

https://www.mdpi.com/1420-3049/28/10/4222

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