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Self-learning analytical interatomic potential describing laser-excited silicon

We develop an electronic-temperature dependent interatomic potential $Φ(T_\text{e})$ for unexcited and laser-excited silicon. The potential is designed to reproduce ab initio molecular dynamics simulations by requiring force- and energy matching for each time step. $Φ(T_\text{e})$ has a simple and flexible analytical form, can describe all relevant interactions and is applicable for any kind of boundary conditions (bulk, thin films, clusters). Its overall shape is automatically adjusted by a self-learning procedure, which finally finds the global minimum in the parameter space. We show that $Φ(T_\text{e})$ can reproduce all thermal and nonthermal features provided by ab initio simulations. We apply the potential to simulate laser-excited Si nanoparticles and find critical damping of their breathing modes due to nonthermal melting.