Machine-learning interatomic potentials from a users perspective: a comparison of accuracy, speed and data efficiency
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DOI: 10.1088/1361-651x/adf56d
Abstract: Machine learning interatomic potentials (MLIPs) have massively changed the field of atomistic modeling. They enable the accuracy of density functional theory in large-scale simulations while being nearly as fast as classical interatomic potentials (IPs). Over… read more here.
Keywords: learning interatomic; interatomic potentials; potentials users; machine learning ... See more keywords