Abstract

State-to-state molecular scattering from surfaces represents a sensitive probe of the molecule–surface interaction potential. For NO scattering from Ag(111), a benchmark system for studying gas–surface energy transfer, abundant experimental data have provided us a great testing ground to validate the accuracy of first-principles description of molecule–surface interactions. Here, we use an accurate neural network fitting method to construct two high-dimensional potential energy surfaces (PESs) based on density functional theory (DFT) single points using PBE and revPBE functionals, respectively, for describing the rotationally inelastic scattering of NO from Ag(111). Quasi-classical trajectory calculations based on the two PESs have been compared with a diversity of experimental data and the influence of scattering angle, initial molecular orientation, and incidence energy on the rotational state distribution is discussed. It is found in general that revPBE-based results agree better than PBE-based ones with the measured scattering angle and final rotational state distributions, capturing reasonably the rotational rainbow feature at a small incidence energy and the steric effect. But neither PES reproduces all experimental data quantitatively. The different performance of the two PESs can be attributed to their difference in the attractiveness, anisotropy, and corrugation in the entrance channel. Our results suggest the need of further improvement of the accuracy of DFT with commonly used density functionals toward a chemically accurate description of molecule–surface interactions.

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