Quantum-accurate machine learning potentials for metal-organic frameworks using temperature driven active learning
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Understanding structural flexibility of metal-organic frameworks (MOFs) via molecular dynamics simulations is crucial to design better MOFs. Density functional theory (DFT) and quantum-chemistry methods provide highly accurate molecular dynamics, but the compu... ...
