Comparison of molecular and crystal graphs in the property prediction of molecular crystals

Abstract

Molecular crystals are composed of organic molecules, and molecular and crystal structures can be used in materials informatics (MI). There is a scarce report on the effectiveness comparison of molecular and crystal representations on the prediction task, and a fundamental question arises in MI of molecular crystals: which descriptor is useful and how effective it is in prediction task. This work aims to answer this question We used bandgap as the target property. Using this dataset, we compared regression results of molecular and crystal graphs through some graph neural network. As the result, molecular graph afforded higher prediction accuracy for bandgap, and we discussed the possible reason.