Machine learning potentials represent a transformative bridge between empirical force fields and fully fledged quantum-mechanical simulations, offering near ab initio accuracy at a fraction of the ...

illustrating the comprehensive zero-shot benchmark of 19 universal machine learning interatomic potentials and the dominant impact of training data composition for surface energy prediction. A ...

Machine learning potential (MLP) training for surface reconstruction analyses. (a) Workflow for MLP training and large-scale configuration space searching. (b-c) Molecular dynamics (MD) simulations at ...