Molecular Dynamics Simulation of Shock Compression Behavior Based on First-Principles Calculation and Machine-Learning

Abstract

Artificial neural network (ANN) potential, which is an interatomic potential constructed by machine-leaning, attracts attention as a promising method to achieve extra-large-scale molecular dynamics (MD) simulation with first-principles accuracy. Application of this ANN-MD to far-from-equilibrium phenomena is very important in not only materials science but also high-pressure research field. In this article, a research example of ANN-MD simulation for elastic- and plastic-shock compression behavior in crystalline silica was described.