中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Construction of diabatic energy surfaces for LiFH with artificial neural networks

文献类型:期刊论文

作者Guan, Yafu; Fu, Bina1; Zhang, Dong H.
刊名JOURNAL OF CHEMICAL PHYSICS
出版日期2017-12-14
卷号147期号:22
ISSN号0021-9606
DOI10.1063/1.5007031
文献子类Article
英文摘要A new set of diabatic potential energy surfaces (PESs) for LiFH is constructed with artificial neural networks (NNs). The adiabatic PESs of the ground state and the first excited state are directly fitted with NNs. Meanwhile, the adiabatic-to-diabatic transformation (ADT) angles (mixing angles) are obtained by simultaneously fitting energy difference and interstate coupling gradients. No prior assumptions of the functional form of ADT angles are used before fitting, and the ab initio data including energy difference and interstate coupling gradients are well reproduced. Converged dynamical results show remarkable differences between adiabatic and diabatic PESs, which suggests the significance of non-adiabatic processes. Published by AIP Publishing.
WOS关键词NONADIABATIC COUPLING TERMS ; QUANTUM DYNAMICS ; EXCITED-STATES ; CONFIGURATIONAL UNIFORMITY ; DISSOCIATIVE CHEMISORPTION ; MARQUARDT ALGORITHM ; MOLECULAR-SYSTEMS ; NUCLEAR-DYNAMICS ; CHEMISTRY ; CU(111)
WOS研究方向Chemistry ; Physics
语种英语
WOS记录号WOS:000418350100021
出版者AMER INST PHYSICS
源URL[http://cas-ir.dicp.ac.cn/handle/321008/168408]  
专题大连化学物理研究所_中国科学院大连化学物理研究所
通讯作者Fu, Bina
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
推荐引用方式
GB/T 7714
Guan, Yafu,Fu, Bina,Zhang, Dong H.. Construction of diabatic energy surfaces for LiFH with artificial neural networks[J]. JOURNAL OF CHEMICAL PHYSICS,2017,147(22).
APA Guan, Yafu,Fu, Bina,&Zhang, Dong H..(2017).Construction of diabatic energy surfaces for LiFH with artificial neural networks.JOURNAL OF CHEMICAL PHYSICS,147(22).
MLA Guan, Yafu,et al."Construction of diabatic energy surfaces for LiFH with artificial neural networks".JOURNAL OF CHEMICAL PHYSICS 147.22(2017).

入库方式: OAI收割

来源:大连化学物理研究所

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