Coupling complementary strategy to flexible graph neural network for quick discovery of coformer in diverse co-crystal materials

Abstract

Experimental determination of new cocrystals remains challenging due to the need of a systematic screening with a large range of coformers. Here the authors develop a flexible deep learning framework based on graph neural network demonstrated to quickly predict the formation of co-crystals.