Additional features do not significantly increase performance over the models simply trained on molecular structure. Performance of all tree-based models except HGB degrades by ca. 0.01-0.02 between models trained on molecular structure and material properties compared to models trained on molecular structure and the fabrication subset of features. This can be attributed to the fact that the material properties features do not contain missing data and are closely tied to molecular structure. That is not the case for the other features in the fabrication and device architecture subsets. Furthermore, adding the device architecture subset of features significantly decreases model performance for all but HGB across both ECFP and Mordred molecular descriptors. This may be related to the imbalanced selection of HTLs and ETLs in OPV device fabrication.