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A global potential energy surface for the H2 + OH ⇆ H2O + H reaction using neural networks
被引:155
作者:
Chen, Jun
[1
,2
]
Xu, Xin
[1
,2
,3
]
Xu, Xin
[1
,2
,3
]
Zhang, Dong H.
[1
,2
]
机构:
[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
基金:
中国国家自然科学基金;
关键词:
VIBRATIONAL-STATE CONTROL;
NEURAL-NETWORKS;
BIMOLECULAR REACTION;
RATE COEFFICIENTS;
4-ATOM REACTION;
H-ATOMS;
DYNAMICS;
CHEMISTRY;
H2O;
RELAXATION;
D O I:
10.1063/1.4801658
中图分类号:
O64 [物理化学(理论化学)、化学物理学];
学科分类号:
070304 ;
081704 ;
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]
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