To finalize the FF model for formula screening, we still need to determine the optimal value for the charge scaling factor. Using conductivity errors as our gauge, the scaling factor is set to 0.7 at 273 K and 298 K. However, at low temperature (253 K), 0.6 gives a better result, while 0.8 is optimal at higher temperature (333 K). We plotted the heat map of the correlation between scaling factors and temperatures in Figure . This is physically understandable, as the charge shielding effect weakens at higher temperatures, so the scaling factor should be larger when the temperature increases. The final results for the training set are plotted in Figure and b, computed using the temperature-dependent charge scaling factors and in comparison with the original and the corresponding charge-scaled GAFF. It is clear that multimodal optimization based on small amount of experimental data largely enhances the accuracy of MD. We further examine the optimized model in the extrapolation test dataset, which is composed by the worst and the best performers at each temperature.