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Global Potential Energy Surface for the H+CH4→H2+CH3 Reaction usingNeural Networks (cited: 12)
Xin Xu,Jun Chen,Dong H. Zhang*
Author NameAffiliationE-mail
Xin Xu State Key Laboratory of Molecular Reaction Dynamics and Center for Theoretical Computational Chem-istry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China  
Jun Chen State Key Laboratory of Molecular Reaction Dynamics and Center for Theoretical Computational Chem-istry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China  
Dong H. Zhang* State Key Laboratory of Molecular Reaction Dynamics and Center for Theoretical Computational Chem-istry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China zhangdh@dicp.ac.cn 
Abstract:
A global potential energy surface (PES) for the H+CH4→H2+CH3 reaction has been con-structed using the neural networks method based on 47783 high level ab initio geometry points. Extensive quasi-classical trajectories and quantum scattering calculations were car-ried out to check the convergence of the PES. This PES, fully converged with respect to the tting 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.
Key words:  Potential energy surface, Neural networks, Ab inito, CH5
FundProject:
用神经网络方法拟合的反应体系H+CH4→H2+CH3的一个全域势能 (cited:12)
徐昕,陈俊,张东辉*
摘要:
利用神经网络方法,基于47783个高精度从头算能量点构建了反应体系H+CH4→H2+CH3的一个全域势能面.通过大量的准经典轨线以及量子散射计算测试了势能面的收敛性质.这个势能面对于拟合过程以及从头算点的数目都已经完全收敛,拟合误差很小且比Shepard插值的势能面计算速度更快,代表了此标志性多原子反应体系最好的势能面.
关键词:  势能面,神经网络,从头算,CH5
DOI:10.1063/1674-0068/27/04/373-379
分类号: