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MOFGalaxyNet – publication out!

The paper “MOFGalaxyNet: a social network analysis for predicting guest accessibility in metal–organic frameworks utilizing graph convolutional networks” by our Mehrdad Jalali, Dinga Wonanke and Christof Wöll was published open access in the Journal of Cheminformatics.

This study presents the newly designed tool MOFGalaxyNet, a galaxy-like social network. In combination with a Graphical Convolutional Network (GCN), MOFGalaxyNet predicts the guest accessibility of a given MOF, which is a key performance parameter for this material class. MOFGalaxyNet provides a robust approach for screening MOFs for host-guest interaction studies.