Molten FeCl2 and FeCl3 form extended polymer chains with six or more Fe centers linked by Cl atoms, showing an octahedral-to-tetrahedral coordination shift upon melting, as revealed by HEXRD, EPSR, and MACE MLIP simulations.
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NEPMaker uses D-optimality active learning to identify and locally embed extrapolative atomic environments from large simulations into periodic structures for training neuroevolution potentials, aiming to cut extrapolation errors in complex materials.
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Structure of Molten FeCl2 and FeCl3
Molten FeCl2 and FeCl3 form extended polymer chains with six or more Fe centers linked by Cl atoms, showing an octahedral-to-tetrahedral coordination shift upon melting, as revealed by HEXRD, EPSR, and MACE MLIP simulations.
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NEPMaker: Active learning of neuroevolution machine learning potential for large cells
NEPMaker uses D-optimality active learning to identify and locally embed extrapolative atomic environments from large simulations into periodic structures for training neuroevolution potentials, aiming to cut extrapolation errors in complex materials.