A machine-learning interatomic potential for La-Si-P is developed via iterative training, reproducing DFT energetics and liquid structure, with melting temperatures 5 to 20 percent below experiment.
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Developing a Neural Network Machine Learning Interatomic Potential for Molecular Dynamics Simulations of La-Si-P Systems
A machine-learning interatomic potential for La-Si-P is developed via iterative training, reproducing DFT energetics and liquid structure, with melting temperatures 5 to 20 percent below experiment.