The six-dimensional quantum dynamics calculations for the dissociative chemisorption of HCl on Au(111) are carried out using the time-dependent wave-packet approach, based on an accurate PES which was recently developed by neural network fitting to density functional theory energy points. The influence of vibrational excitation and rotational orientation of HCl on the reactivity is investigated by calculating the exact six-dimensional dissociation probabilities, as well as the four-dimensional fixed-site dissociation probabilities. The vibrational excitation of HCl enhances the reactivity and the helicopter orientation yields higher dissociation probability than the cartwheel orientation. A new interesting site-averaged effect is found for the title molecule-surface system that one can essentially reproduce the six-dimensional dissociation probability by averaging the four-dimensional dissociation probabilities over 25 fixed sites. © 2013 AIP Publishing LLC.

Despite significant progress made in the past decades, it remains extremely challenging to investigate the dissociative chemisorption dynamics of molecular species on surfaces at a full-dimensional quantum mechanical level, in particular for polyatomic-surface reactions. Here we report, to the best of our knowledge, the first full-dimensional quantum dynamics study for the dissociative chemisorption of H2O on rigid Cu(111) with all the nine molecular degrees of freedom fully coupled, based on an accurate full-dimensional potential energy surface. The full-dimensional quantum mechanical reactivity provides the dynamics features with the highest accuracy, revealing that the excitations in vibrational modes of H2O are more efficacious than increasing the translational energy in promoting the reaction. The enhancement of the excitation in asymmetric stretch is the largest, but that of symmetric stretch becomes comparable at very low energies. The full-dimensional characterization also allows the investigation of the validity of previous reduced-dimensional and approximate dynamical models.