Fundamental invariant-neural network as a correction to the intramolecular force field illustrated for the full-dimensional potential energy surface of propane

energy by the FI-NN method is able to improve the accuracy of the force field. We demonstrate this enhanced methodology through the development of an intramolecular force field for propane, where CCSD(T)-F12a/AVTZ energies are initially approximated by the force field and subsequently refined using the FI-NN approach. Compared to the PES fitted by FI-NN, this combined method reduces the root mean square error (RMSE) by 50%.