Global Potential Energy Surface for the H+CH4⇆H2+CH3 Reaction using Neural Networks

被引：51
|
作者：
Xu, Xin
Chen, Jun
Zhang, Dong H. [1 ]
机构：
[1] Chinese Acad Sci, Dalian Inst Chem Phys, State Key Lab Mol React Dynam, Dalian 116023, Peoples R China
来源：
CHINESE JOURNAL OF CHEMICAL PHYSICS | 2014年 / 27卷 / 04期
基金：
中国国家自然科学基金;
关键词：
Potential energy surface; Neural networks; Ab inito; CH5; ABSTRACTION REACTION DYNAMICS; TRANSITION-STATE THEORY; QUANTUM DYNAMICS; FEEDFORWARD NETWORKS; POLYATOMIC SYSTEMS; SIMPLEST REACTION; H-ATOMS; CHEMISTRY; KINETICS; H+CH4;
D O I：
10.1063/1674-0068/27/04/373-379
中图分类号：
O64 [物理化学（理论化学）、化学物理学]; O56 [分子物理学、原子物理学];
学科分类号：
070203 ; 070304 ; 081704 ; 1406 ;
摘要：
A global potential energy surface (PES) for the H+CH4 <-> H-2+CH3 reaction has been constructed using the neural networks method based on 47783 high level ab initio geometry points. Extensive quasi-classical trajectories and quantum scattering calculations were carried out to check the convergence of the PES. This PES, fully converged with respect to the fitting procedure and the number of ab initio points, has a very small fitting error, and is much faster on evaluation than the modified Shepard interpolating PES, representing the best available PES for this benchmark polyatomic system.
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页码：373 / 379
页数：7
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