Benchmarking 11 universal machine learning interatomic potentials on a new 40,000-structure, 0D-3D dataset shows energy and geometry errors grow as dimensionality falls, with eSEN the most transferable.
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Universal Machine Learning Potential for Systems with Reduced Dimensionality
Benchmarking 11 universal machine learning interatomic potentials on a new 40,000-structure, 0D-3D dataset shows energy and geometry errors grow as dimensionality falls, with eSEN the most transferable.