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Development and Validation of Neural Network Potentials for Multicomponent Oxide Glasses

By Ryuki Kayano and others at
LogoChiba University
A neural network potential (MLP) for molecular dynamics simulation (MD) of multicomponent oxide glasses was developed with special consideration of structural reproducibility. The MLP was constructed through pre-training using the dataset of density functional theory (DFT) data provided by the Open Catalysis project and fine-tuning for the dataset of nine-component... Show more
July 10, 2024
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Development and Validation of Neural Network Potentials for Multicomponent Oxide Glasses
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