A soft damping function for dispersion corrections with less overfitting

The use of damping functions in empirical dispersion correction schemes is common and widespread. These damping functions contain scaling and damping parameters, and they are usually optimized for the best performance in practical systems. In this study, it is shown that the overfitting problem can be present in current damping functions, which can sometimes yield erroneous results for real applications beyond the nature of training sets. To this end, we present a damping function called linear soft damping (lsd) that suffers less from this overfitting. This linear damping function damps the asymptotic curve more softly than existing damping functions, attempting to minimize the usual overcorrection. The performance of the proposed damping function was tested with benchmark sets for thermochemistry, reaction energies, and intramolecular interactions, as well as intermolecular interaction…