Machine learning aids in simulating dynamics of interacting atoms

A revolutionary machine-learning (ML) approach to simulate the motions of atoms in materials such as aluminum is described in this week's Nature Communications journal. This automated approach to "interatomic potential development" could transform the field of computational materials discovery.

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