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题名: A global potential energy surface for the H-2 + OH <-> H2O + H reaction using neural networks
作者: 陈俊1, 2;  Xu, Xin1, 2;  Xu, Xin3;  Zhang, Dong H.1, 2
刊名: JOURNAL OF CHEMICAL PHYSICS
发表日期: 2013-04-21
DOI: 10.1063/1.4801658
卷: 138, 期:15
收录类别: SCI
文章类型: Article
WOS标题词: Science & Technology ;  Physical Sciences
类目[WOS]: Physics, Atomic, Molecular & Chemical
研究领域[WOS]: Physics
英文摘要: A global potential energy surface for the H-2 + OH <-> H2O + H reaction has been constructed using the neural networks method based on similar to 17 000 ab initio energies calculated at UCCSD(T)-F12a/AVTZ level of theory. Time-dependent wave packet calculations showed that the new potential energy surface is very well converged with respect to the number of ab initio data points, as well as to the fitting process. Various tests revealed that the new surface is considerably more smooth and accurate than the existing YZCL2 and XXZ surfaces, representing the best available potential energy surface for the benchmark four-atom system. Equally importantly, the number of ab initio energies required to obtain the well converged potential energy surface is rather limited, indicating the neural network fitting is a powerful method to construct accurate potential energy surfaces for polyatomic reactions. (C) 2013 AIP Publishing LLC. [http://dx.doi.org/10.1063/1.4801658]
关键词[WOS]: VIBRATIONAL-STATE CONTROL ;  NEURAL-NETWORKS ;  BIMOLECULAR REACTION ;  RATE COEFFICIENTS ;  4-ATOM REACTION ;  H-ATOMS ;  DYNAMICS ;  CHEMISTRY ;  H2O ;  RELAXATION
语种: 英语
WOS记录号: WOS:000317814900015
Citation statistics: 
内容类型: 期刊论文
URI标识: http://cas-ir.dicp.ac.cn/handle/321008/137571
Appears in Collections:中国科学院大连化学物理研究所_期刊论文

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作者单位: 1.Chinese Acad Sci, Dalian Inst Chem Phys, State Key Lab Mol React Dynam, Dalian 116023, Peoples R China
2.Chinese Acad Sci, Dalian Inst Chem Phys, Ctr Theoret Computat Chem, Dalian 116023, Peoples R China
3.Fudan Univ, Dept Chem, Shanghai 200433, Peoples R China

Recommended Citation:
Chen, Jun,Xu, Xin,Xu, Xin,et al. A global potential energy surface for the H-2 + OH <-> H2O + H reaction using neural networks[J]. JOURNAL OF CHEMICAL PHYSICS,2013,138(15).
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