Full-scale ab initio simulations of laser-driven atomistic dynamics

TL;DR

This paper presents a novel ab initio simulation framework that models laser-driven atomistic dynamics, incorporating excited states and nonthermal effects, to better interpret experimental results under extreme conditions.

Contribution

It introduces a combined electron-temperature-dependent neural network potential and hybrid approach for simulating laser-driven microscopic dynamics from solid to liquid phases.

Findings

Nonthermal effects from hot electrons significantly influence lattice dynamics.

The framework enables realistic simulations that bridge experimental and theoretical studies.

Large-scale simulations reveal detailed thermodynamic pathways during laser-induced transformations.

Abstract

The coupling of excited states and ionic dynamics is the basic and challenging point for the materials response at extreme conditions. In laboratory, the intense laser produces transient nature and complexity with highly nonequilibrium states, making it extremely difficult and interesting for both experimental measurements and theoretical methods. With the inclusion of laser-excited states, we extended ab initio method into the direct simulations of whole laser-driven microscopic dynamics from solid to liquid. We constructed the framework of combining the electron-temperaturedependent deep neural network potential energy surface with hybrid atomistic-continuum approach, controlling non-adiabatic energy exchange and atomistic dynamics, which enables consistent interpretation of experimental data. By large scale ab inito simulations, we demonstrate that the nonthermal effects introduced by hot electrons play a dominant role in modulating the lattice dynamics, thermodynamic pathway, and structural transformation. We highlight that the present work provides a path to realistic computational studies of laser-driven processes, thus bridging the gap between experiments and simulations.