OUTCAR dataset for machine learning potential about a h-BN growth on Pt(111) surface

The growth of monolayer h-BN from boron and nitrogen atoms on Pt(111) is investigated using molecular dynamics combined with machine-learning potentials trained based on first-principles data. The MD simulation can be performed to investigate the h-BN growth on the Pt(111) surface. The training dataset and machine learning potential have been made by the active learning method [1].

[1] L. Zhang, D.-Y. Lin, H. Wang, R. Car, E. Weinan, Active learning of uniformly accurate interatomic potentials for materials simulation, Physical Review Materials 3 (2019) 023804.