Unveiling the interplay of electronic and phononic excitations in laser-induced oxygen activation on Ru(0001)

Abstract

Understanding laser-induced dynamics on metal surfaces poses significant challenges due to the intricate interplay between electronic and phononic degrees of freedom, which evolve on distinct timescales. In this study, we introduce a machine learning-accelerated approach to molecular dynamics simulations that incorporates anisotropic electronic friction, providing deeper insights into these complex processes. Our framework extends the accessible time and length scales for nonadiabatic dynamics simulations, enabling a detailed investigation of the laser-induced activation of oxygen on the Ru(0001) surface. Statistical analysis reveals that strong electronic excitation dominates the first 800 fs after laser exposure. Beyond this timescale, energy deposited by electronic excitation continues to drive oxygen activation, while phonons, although always present as a dissipation channel, play a weaker role by buffering energy loss and redistributing kinetic energy among vibrational modes. The observed non-linear yield–fluence relationship, described by Y ∼ Fn, underscores the pivotal role of electronic excitation. In addition, we identify the z-direction as the key activation mode for oxygen diffusion, with the exponent of the power law representing the quantized energy required for this process. This approach significantly accelerates dynamic simulations while offering valuable insights into the interplay between electronic and phononic excitations during laser-induced oxygen activation on Ru(0001).