Strong Vibrational Relaxation of NO Scattered from Au(111): Importance of an Accurate Adiabatic Potential Energy Surface

TL;DR

This study develops a highly accurate neural network-based adiabatic potential energy surface for NO scattering from Au(111), significantly improving the modeling of vibrational relaxation and inelasticity in molecule-surface interactions.

Contribution

The paper introduces a globally accurate high-dimensional PES constructed with neural networks, enhancing the quantitative agreement of vibrational energy loss predictions with experimental data.

Findings

Vibrational energy loss is much larger with the new PES.

Translational inelasticity is more accurately modeled.

Energy dependence of vibrational inelasticity is improved.

Abstract

Experimental observations of multi-quantum relaxation of highly vibrationally excited NO scattering from Au(111) are a benchmark for the breakdown of Born-Oppenheimer approximation in molecule-surface systems. This remarkable vibrational inelasticity was long thought to be almost exclusively mediated by electron transfer; but, no theories have quantitatively reproduced various experimental data. This was suggested to be due to errors in the adiabatic potential energy surface (PES) used in those studies. Here, we investigate electronically adiabatic molecular dynamics of this system with a globally accurate high dimensional PES, newly developed with neural networks from first principles. The NO vibrational energy loss is much larger than that on earlier adiabatic PES. Additionally, the translational inelasticity and translational energy dependence of vibrational inelasticity are also more accurately reproduced. There is reason to be optimistic that electronically nonadiabatic theories using this adiabatic PES as a starting point might accurately reproduce experimental results on this important system.