In Fig. , we perform the same type of feature importance analysis using SHAP values, for the DNN model trained on MFFs. Here, we highlight the most important chemical substructures in the prediction of gas permeability. As shown in Fig. (a), the most important substructure overall is 2854, the methyl group. We believe that this feature facilitates permeability because it is hydrophobic and its shape contributes to steric frustration between polymer chains. Similarly, the quaternary carbon connected to an aliphatic ring (substructure 2168) contributes to increasing permeability, which supports our findings above. The DNN model also learns that the number of connection bonds, substructure 1781, is correlated with gas permeability, because many highpermeability PIMs are ladder polymers with four connection points per repeating unit, as opposed to two for a typical polymer. The correlation matrix between chemical substructures (Fig. of Supporting Information) suggests that most of the important substructure features are independent of one another. However, substructures 1781, 1432, and 822 are highly correlated and all have a positive relation to gas permeability (Fig. ). Upon closer examination, we find that substructure 1781 is contained within substructure 1432, which is contained in substructure 822.