Self-Learning Method for Construction of Analytical Interatomic Potentials to Describe Laser-Excited Materials

Abstract

Large-scale simulations using interatomic potentials provide deep insight into the processes occurring in solids subject to external perturbations. The atomistic description of laser-induced ultrafast nonthermal phenomena, however, constitutes a particularly difficult case and has so far not been possible on experimentally accessible length scales and timescales because of two main reasons: (i) ab initio simulations are restricted to a very small number of atoms and ultrashort times and (ii) simulations relying on electronic temperature- (Te) dependent interatomic potentials do not reach the necessary ab initio accuracy. Here we develop a self-learning method for constructing Te-dependent interatomic potentials which permit ultralarge-scale atomistic simulations of systems suddenly brought to extreme nonthermal states with density-functional theory (DFT) accuracy. The method always finds the global minimum in the parameter space. We derive a highly accurate analytical Te-dependent interatomic potential Φ(Te) for silicon that yields a remarkably good description of laser-excited and -unexcited Si bulk and Si films. Using Φ(Te) we simulate the laser excitation of Si nanoparticles and find strong damping of their breathing modes due to nonthermal melting.

Bernd Bauerhenne et al., Self-Learning Method for Construction of Analytical Interatomic Potentials to Describe Laser-Excited Materials, Phys. Rev. Lett.