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Unified Learning of Interatomic Potentials and Electronic Hamiltonians, with Applications in 2D Materials
We introduce UnIPH, an equivariant graph neural network designed to jointly predict both interatomic potentials and tight-binding (TB) Hamiltonians for an atomic structure. UnIPH is trained using density functional theory (DFT) calculations followed by Wannier projection to predict energies and forc
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