New from OpenKIM: Machine Learning Based Tools to Develop, Test, Select and Deploy Advanced Interatomic Potentials

The OpenKIM project (https://openkim.org) archives, tests and deploys interatomic potentials for use in production molecular dynamics codes like LAMMPS. Over the last couple of years OpenKIM has introduced several new capabilities that will be described in this talk, including: (1) the “Crystal Genome” framework with properties for all known crystals; (2) support for bonded force fields; (3) support for arbitrary PyTorch machine learning (ML) potentials; (4) the “Deep Citation” framework for identifying potential past usage; and a comparison tool and ML-based recommender system for potential selection. An overview of these developments will be provided, with a more in-depth introduction in a separate breakout session.