Development of a general-purpose machine-learning interatomic potential for aluminum by the physically-informed neural network method

Abstract Interatomic potentials constitute the key component of large-scale atomistic simulations of materials. The recently proposed physically-informed neural network (PINN) method combines a high-dimensional regression implemented by an artificial neural network with a physics-based bond-order in...

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