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Refining Machine Learning Potentials through Thermodynamic Theory of Phase Transitions
Foundational Machine Learning Potentials can resolve the accuracy and transferability limitations of classical force fields. They enable microscopic insights into material behavior through Molecular Dynamics simulations, which can crucially expedite material design and discovery. However, insufficie
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