Interstellar surface physics and chemistry using machine learning techniques

Despite the cold conditions found in dense molecular clouds, where temperatures are as low as 10-20 K, rich chemistry allows for the build-up of organics that eventually will be inherited in subsequent star and planet formation events. At the core of this chemistry, there is a genuinely complex interplay between gas-phase and surface processes occurring atop interstellar ices. A conjoint effort from many fronts, e.g. experiments, observations and computer simulations, needs to be undertaken to disentangle the physics and chemistry occurring in molecular clouds. This talk will present the particularities of computationally studying surface processes of relevance to astrochemistry. After introducing this, I will present our recent efforts to merge machine learning techniques to study interstellar surface physics and chemistry. Firstly, I will focus on illustrating the dynamics of the nitrogen atom on water ice to exemplify the study of surface physics. Secondly, I will briefly introduce the study of surface chemistry by discussing our recent results on the hydrogenation of the phosphorous atom on top of ices.