Correlative analysis of metal organic framework structures through manifold learning of Hirshfeld surfaces

We demonstrate the use of non-linear manifold learning methods to map the connectivity and extent of similarity between diverse metal–organic framework (MOF) structures in terms of their surface areas by taking into account both crystallographic and electronic structure information.