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Review

Multi-Scale Simulation of Mechanical and Thermal Transport Properties of Materials Based on Machine Learning Potential

Jing WU1,2, An HUANG1, Hanpeng XIE1, Donghai WEI1, Aonan LI1, Bo PENG1, Huimin WANG3, Zhenzhen QIN4, Te-huan LIU2( ), Guangzhao QIN1( )
State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, College of Mechanical and Vehicle Engineering, Hunan University, Changsha 410082, China
School of Energy and Power Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
Hunan Key Laboratory for Micro-Nano Energy Materials & Device and School of Physics and Optoelectronics, Xiangtan University, Xiangtan 411105, Hunan, China
School of Physics and Microelectronics, Zhengzhou University, Zhengzhou 450001, China
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Abstract

With the development of artificial intelligence technology, machine learning atomic interaction potential has become popular to solve a problem regarding the low accuracy of empirical potential. Machine learning atomic interaction potential avoids a low efficiency of conventional fitting method for empirical potential and becomes an emerging tool for material exploration and research. This review represented the characteristics of existing machine learning potential and the applications in phase change, intrinsic properties and interface researches. In addition, the challenge and development trends of machine learning atomic interaction potential were also prospected.

Keywords

machine learningatomic interaction potentialmultiscalemechanical and thermal properties
CLC number: TK11；TB3 Document code: A Article ID: 0454-5648(2023)02-0531-13

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Journal of the Chinese Ceramic Society
Volume 51 Issue 2,
February 2023
Pages 531-543
DOI: 10.14062/j.issn.0454-5648.20220826

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WU J, HUANG A, XIE H, et al. Multi-Scale Simulation of Mechanical and Thermal Transport Properties of Materials Based on Machine Learning Potential. Journal of the Chinese Ceramic Society, 2023, 51(2): 531-543. https://doi.org/10.14062/j.issn.0454-5648.20220826

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Received: 01 October 2022
Revised: 04 November 2022
Published: 28 December 2022
© 2023 Journal of the Chinese Ceramic Society