Six-dimensional potential energy surface of the dissociative chemisorption of HCl on Au(111) using neural networks

Abstract

We constructed a six-dimensional potential energy surface (PES) for the dissociative chemisorption of HCl on Au(111) using the neural networks method based on roughly 70000 energies obtained from extensive density functional theory (DFT) calculations. The resulting PES is accurate and smooth, based on the small fitting errors and good agreement between the fitted PES and the direct DFT calculations. Time-dependent wave packet calculations show that the potential energy surface is very well converged with respect to the number of DFT data points, as well as to the fitting process. The dissociation probabilities of HCl initially in the ground rovibrational state from six-dimensional quantum dynamical calculations are quite different from the four-dimensional fixed-site calculations, indicating it is essential to perform full-dimensional quantum dynamical studies for the title molecule-surface interaction system.