Neuroevolution machine learning potentials: Combining high accuracy and low cost in atomistic simulations and application to heat transport

Abstract

Zheyong Fan, 2, ∗ Zezhu Zeng, Cunzhi Zhang, Yanzhou Wang, 2 Haikuan Dong, 2 Yue Chen, and Tapio Ala-Nissila 6 College of Physical Science and Technology, Bohai University, Jinzhou, P. R. China MSP group, QTF Centre of Excellence, Department of Applied Physics, Aalto University, FI-00076 Aalto, Espoo, Finland Department of Mechanical Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong SAR, China Pritzker School of Molecular Engineering, The University of Chicago, Chicago, Illinois 60637, United States Beijing Advanced Innovation Center for Materials Genome Engineering, Department of Physics, University of Science and Technology Beijing, Beijing 100083, China Interdisciplinary Centre for Mathematical Modelling, Department of Mathematical Sciences, Loughborough University, Loughborough, Leicestershire LE11 3TU, UK (Dated: July 20, 2021)