A neural network potential energy surface for the F + CH4 reaction including multiple channels based on coupled cluster theory

Jun Chen; Xin Xu; Shu Liu; Dong H Zhang

doi:10.1039/C7CP08365C

A neural network potential energy surface for the F + CH₄ reaction including multiple channels based on coupled cluster theory

Phys Chem Chem Phys. 2018 Apr 4;20(14):9090-9100. doi: 10.1039/C7CP08365C.

Authors

Jun Chen¹, Xin Xu², Shu Liu², Dong H Zhang²

Affiliations

¹ State Key Laboratory of Molecular Reaction Dynamics and Center for Theoretical Computational Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China. zhangdh@dicp.ac.cn and Collaborative Innovation Center of Chemistry for Energy Materials (iChEM), College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China. chen@xmu.edu.cn.
² State Key Laboratory of Molecular Reaction Dynamics and Center for Theoretical Computational Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China. zhangdh@dicp.ac.cn.

PMID: 29564426
DOI: 10.1039/C7CP08365C

Abstract

We report here a new global and full dimensional potential energy surface (PES) for the F + CH4 reaction. This PES was constructed by using neural networks (NN) fitting to about 99 000 ab initio energies computed at the UCCSD(T)-F12a/aug-cc-pVTZ level of theory, and the correction terms considering the influence of a larger basis set as well as spin-orbit couplings were further implemented with a hierarchial scheme. This PES, covering both the abstraction and substitution channels, has an overall fitting error of 8.24 meV in total, and 4.87 meV for energies within 2.5 eV using a segmented NN fitting method, and is more accurate than the previous PESs.