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Predictive power of polynomial machine learning potentials for liquid states in 22 elemental systems
The polynomial machine learning potentials (MLPs) described by polynomial rotational invariants have been systematically developed for various systems and used in diverse applications in crystalline states. In this study, we systematically investigat
Externí odkaz:
http://arxiv.org/abs/2401.14877
