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A recently proposed class of machine-learning interatomic potentials — Moment tensor potentials (MTPs) — is investigated in this work. MTPs are able to actively select configurations and parametrize the potential on-the-fly. It is shown that MTPs accurately reproduce energies, forces and stresses calculated ab initio. As a more comprehensive test, MTPs are employed to calculate vacancy diffusion rates in Al, Mo and Si. We demonstrate that the results are in a good agreement with ab initio data for the materials considered.

生成讲解博客的中文版本

生成AI智能校验的中文版本