This limited improvement aligns with the findings of recent work by Li et al., which demonstrated that adding quantum mechanical features only aids the prediction of activation energies using the D-MPNN model when the training dataset is extremely small (less than 2,000 samples), a threshold smaller than the dataset used in our study.