Energy Dissipation during Diffusion at Metal Surfaces: Disentangling the Role of Phonons versus Electron-Hole Pairs

Helium spin echo experiments combined with $\textit{ab initio}$ based Langevin molecular dynamics simulations are used to quantify the adsorbate-substrate coupling during the thermal diffusion of Na atoms on Cu(111). An analysis of trajectories within the local density friction approximation allows the contribution from electron-hole pair excitations to be separated from the total energy dissipation. Despite the minimal electronic friction coefficient of Na and the relatively small mass mismatch to Cu promoting efficient phononic dissipation, about (20±5)% of the total energy loss is attributable to electronic friction. The results suggest a significant role of electronic nonadiabaticity in the rapid thermalization generally relied upon in adiabatic diffusion theories.S. P. R. acknowledges the support of the Technische Universität München—Institute for Advanced Study, funded by the German Excellence Initiative and the European Union Seventh Framework Programme under Grant Agreement No. 291763

Energy Dissipation during Diffusion at Metal Surfaces: Disentangling the Role of Phonons versus Electron-Hole Pairs

Helium spin echo experiments combined with $\textit{ab initio}$ based Langevin molecular dynamics simulations are used to quantify the adsorbate-substrate coupling during the thermal diffusion of Na atoms on Cu(111). An analysis of trajectories within the local density friction approximation allows the contribution from electron-hole pair excitations to be separated from the total energy dissipation. Despite the minimal electronic friction coefficient of Na and the relatively small mass mismatch to Cu promoting efficient phononic dissipation, about (20±5)% of the total energy loss is attributable to electronic friction. The results suggest a significant role of electronic nonadiabaticity in the rapid thermalization generally relied upon in adiabatic diffusion theories.S. P. R. acknowledges the support of the Technische Universität München—Institute for Advanced Study, funded by the German Excellence Initiative and the European Union Seventh Framework Programme under Grant Agreement No. 291763

A Decade of Computational Surface Catalysis

We briefly survey recent developments in surface catalysis modeling. The differentiated view on required level of accuracy established in the wake of multi-scale modeling approaches led to the emergence of high-throughput computational screening approaches. The large amounts of data created this way are now increasingly mined with machine learning techniques. We discuss status and challenges in this exciting mix of methodologies that describe catalytic systems from the electrons to the reactor. Next to the traditional focus on understanding and predicting catalytic activity, we argue that approaches to dynamical catalyst restructuring, to concomitant heat management, and to catalyst lifetime are important themes for the decade to come