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

Draney, Jack S. [Princeton University] (ORCID:0000000202892554); Panagiotopoulos, Athanassios [Princeton University] (ORCID:0000000281526615); Graves, David [Princeton University] (ORCID:0000000222886768)

doi:10.34770/wq4t-wa25

DOE OSTI · 2589045

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

Draney, Jack S. [Princeton University] (ORCID:0000000202892554)·Panagiotopoulos, Athanassios [Princeton University] (ORCID:0000000281526615)·Graves, David [Princeton University] (ORCID:0000000222886768)

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Abstract

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.

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active learning deep potential interatomic potentials molecular dynamics plasma-surface interactions

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Draney, Jack S. [Princeton University] (ORCID:0000000202892554), Panagiotopoulos, Athanassios [Princeton University] (ORCID:0000000281526615), Graves, David [Princeton University] (ORCID:0000000222886768). 2025-09-10. Dataset, Code, and Models for Training Deep Learning Potentials for Low Temperature Plasma-Surface Interactions. https://doi.org/10.34770/wq4t-wa25

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