TurboGAP is a software package designed for efficient molecular dynamics simulations using Gaussian approximation potential (GAP) machine-learning interatomic potentials (MLIP). In this work, we enhance the capabilities of TurboGAP for radiation damage simulations by implementing a two-temperature molecular dynamics model, based on electron density-dependent coupling of electronic and atomic subsystems. Additionally, we implement adaptive calculation of the timestep and grouping of atoms for cell-border cooling. Our implementation incorporates electronic stopping power either through a traditional friction-based model or a more realistic first-principles-derived model. By combining the computational efficiency of TurboGAP with the accuracy of GAP MLIP, we perform cascade simulations in silicon with primary knock-on atom (PKA) energies up to 10 keV. Our simulations scale to systems containing up to 1 million atoms. We study the generation and clustering of radiation-induced defects. We also calculate ion-beam mixing and compare our results with the experimental data, discussing how the GAP-MLIP along with the inclusion of a realistic electronic stopping model affects the prediction of experimental mixing values. • Implemented two-temperature molecular dynamics in the TurboGAP code. • Implemented adaptive timestep and selective grouping of atoms to the TurboGAP code. • Implemented two electronic stopping models to the TurboGAP code. • Simulated up to 10 keV PKA cascades in Si using systems up to 1 million atoms. • Improved ion-beam mixing predictions in Si are reported.
Saha et al. (Mon,) studied this question.