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Machine Learning Potential Repository
Published 27 Jul 2020 in physics.comp-ph, cond-mat.mtrl-sci, physics.chem-ph, and physics.data-an | (2007.14206v1)
Abstract: This paper introduces a machine learning potential repository that includes Pareto optimal machine learning potentials. It also shows the systematic development of accurate and fast machine learning potentials for a wide range of elemental systems. As a result, many Pareto optimal machine learning potentials are available in the repository from a website. Therefore, the repository will help many scientists to perform accurate and fast atomistic simulations.
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