Photodesorption of diatomic molecules from surfaces: A theoretical approach based on first principles

Abstract

Photodesorption of small molecules from surfaces is one of the most fundamental processes in surface photochemistry. Despite its apparent simplicity, a microscopic understanding beyond a qualitative picture still poses a true challenge for theory. While the dynamics of nuclear motion can be treated on various levels of sophistication, all approaches suffer from the lack of sufficiently accurate potential energy surfaces, in particular for electronically excited states involved in the desorption scenario. In the last decade, a systematic and accurate methodology has been developed which allows a reliable calculation of accurate ground and excited state potential energy surfaces (PES) for different adsorbate–substrate systems. These potential energy surfaces serve as a prerequisite for subsequent quantum dynamical wave packet calculations, which allow for a direct simulation of experimentally observable quantities such as quantum state resolved velocity distributions. In the first part of this review, we will focus on scalar properties of desorbing diatomic molecules from insulating surfaces, where we also present a recently developed strategy of obtaining accurate potential energy surfaces using quantum chemical approaches. In general, diatomic molecules on large band gap materials such as oxide surfaces are studied which allows the use of sufficiently large cluster models and accurate ab initio methods beyond density functional theory (DFT). In the second part, we will focus on the vectorial aspects of the dynamics of nuclear motion and present simulations of experimentally accessible observables such as velocity distributions, Doppler profiles and alignment parameters. For each system, the microscopic mechanism of photodesorption is elucidated. We will demonstrate that the driving force of surface photochemistry is strongly dependent on details of the electronic structure of the adsorbate–substrate systems. This implies that great caution is advisable if experimental results are interpreted using empirical or semi-empirical models.