FFLAME: a fragment-to-framework learning approach for MOF potentials
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Metal-organic frameworks (MOFs) exhibit immense structural diversity and hold promise for applications ranging from gas storage and separation to energy storage and conversion. However, structural flexibility makes accurate and scalable property prediction dif... ...