Dataset, Code, and Models for Training Deep Learning Potentials for Low Temperature Plasma-Surface Interactions

This repository contains datasets, training scripts, and finished models,
and test simulations used in the development of DeepREBO— a
machine-learned interatomic potential trained to emulate the REBO2
empirical potential. The data was generated to study deep potential
development for simulations of plasma-surface interactions. It uses an
active learning framework, starting from a minimal dataset and iteratively
expanding it. Included are those generated datasets, the trained models,
and simulations used to evaluate the performance of the training process.
This resource supports reproducibility and provides a reference framework
for training deep potentials in plasma-surface interaction studies.