Fig. 4

Impact of MD descriptors in QSPR models for viscosity predictions. A Simulation snapshot of methyl acetate at T = 298 K, which was used to compute eight MD descriptors. B Test set root-mean-square error (RMSE) for descriptor-based LGBM model and GNN-based EdgePool model when including two-dimensional descriptors (2D), molecular dynamics (MD) descriptors, or combinations of 2D and MD (2D and MD) into the QSPR models. The average RMSE is reported across five random, out-of-sample train-test splits and the RMSE uncertainty is estimated by computing the standard deviation across the splits. C Log-scale learning curve showing test set RMSE versus train set size when using 20% of the dataset as test set and re-training the models with increasing training set sizes. These curves are plotted for LGBM and EdgePool models with and without MD descriptors. Twenty train-test splits were implemented to obtain accurate measurements of test RMSE, where the mean test set RMSE is reported and the uncertainty is estimated by the standard deviation of the test set RMSEs