Global optimization of gold nanocrystals based on an iterative QM/MM method

被引：1
|
作者：
Zhai, Dong [1 ]
Wang, Hong-Lei [1 ]
Yang, Li [1 ]
Sun, Lei [1 ]
Deng, Weiqiao [1 ,2 ]
机构：
[1] Shandong Univ, Inst Mol Sci & Engn, Inst Frontier & Interdisciplinary Sci, Qingdao 266237, Peoples R China
[2] Chinese Acad Sci, Dalian Inst Chem Phys, State Key Lab Mol React Dynam, Dalian Natl Lab Clean Energy, Dalian 116023, Peoples R China
来源：
CHEMICAL PHYSICS LETTERS | 2023年 / 812卷
关键词：
Global optimization; Gold nanocrystals; Iterative; QM; MM method; CRYSTAL-STRUCTURE PREDICTION; EMBEDDED-ATOM-METHOD; CATALYTIC-ACTIVITIES; CLUSTERS; ALGORITHM; QUANTUM; SIMULATIONS; SURFACES; CALYPSO;
D O I：
10.1016/j.cplett.2022.140264
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：
The morphology of nanocrystals plays a crucial role in determining their physical and chemical properties. It is important to develop a time-saving scheme used for the nanocrystals optimization, despite supercomputers having exhibited good performance for the optimization using quantum mechanics (QM) methods. Here, we report an iterative global optimization method, which combines the iterative QM and molecular mechanics (MM) methods. The QM/MM energy is described by using an effective and simple subtractive approach, and a genetic algorithm technique is developed. The benchmark simulations of gold nanocrystals reveal that the scheme is efficient in locating the global minimum of nanocrystals.
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页数：7
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