Neural-network assisted study of nitrogen atom dynamics on amorphous solid water – I. adsorption and desorption

Abstract

ABSTRACT Dynamics of adsorption and desorption of (4S)-N on amorphous solid water are analysed using molecular dynamic simulations. The underlying potential energy surface was provided by machine-learned interatomic potentials. Binding energies confirm the latest available theoretical and experimental results. The nitrogen sticking coefficient is close to unity at dust temperatures of 10 K but decreases at higher temperatures. We estimate a desorption time-scale of 1 μs at 28 K. The estimated time-scale allows chemical processes mediated by diffusion to happen before desorption, even at higher temperatures. We found that the energy dissipation process after a sticking event happens on the picosecond time-scale at dust temperatures of 10 K, even for high energies of the incoming adsorbate. Our approach allows the simulation of large systems for reasonable time-scales at an affordable computational cost and ab initio accuracy. Moreover, it is generally applicable for the study of adsorption dynamics of interstellar radicals on dust surfaces.