Artificial neural network potential for gold clusters

作     者：Ling-Zhi Cao Peng-Ju Wang Lin-Wei Sai Jie Fu Xiang-Mei Duan 曹凌志;王鹏举;赛琳伟;付洁;段香梅

作者机构：School of Physical Science and TechnologyNingbo UniversityNingbo 315211China Laboratory of Clean Energy Storage and ConversionNingbo UniversityNingbo 315211China Key Laboratory of Materials Modification by LaserIon and Electron BeamsMinistry of EducationDalian University of TechnologyDalian 116024China College of ScienceHohai UniversityChangzhou 213022China 

出 版 物：《Chinese Physics B》 (中国物理B（英文版）)

年 卷 期：2020年第29卷第11期

页      面：86-91页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081704[工学-应用化学] 07[理学] 081104[工学-模式识别与智能系统] 08[工学] 0817[工学-化学工程与技术] 0835[工学-软件工程] 0703[理学-化学] 070301[理学-无机化学] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：Project supported by the National Natural Science Foundation of China(Grant Nos.11804175,11874033,11804076,and 91961204) the K.C.Wong Magna Foundation in Ningbo University 

主　　题：empirical potential artificial neural network gold cluster first-principles 

摘      要：In cluster science, it is challenging to identify the ground state structures(GSS) of gold(Au) clusters. Among different search approaches, first-principles method based on density functional theory(DFT) is the most reliable one with high precision. However, as the cluster size increases, it requires more expensive computational cost and becomes *** this paper, we have developed an artificial neural network(ANN) potential for Au clusters, which is trained to the DFT binding energies and forces of 9000 Au N clusters(11 ≤ N ≤ 100). The root mean square errors of energy and force are 13.4 meV/atom and 0.4 eV/A, respectively. We demonstrate that the ANN potential has the capacity to differentiate the energy level of Au clusters and their isomers and highlight the need to further improve the accuracy. Given its excellent transferability, we emphasis that ANN potential is a promising tool to breakthrough computational bottleneck of DFT method and effectively accelerate the pre-screening of Au clusters’ GSS.