Surface astrochemistry: a computational chemistry perspective

TL;DR

This paper discusses how computational chemistry can improve understanding of surface reactions in astrochemistry, addressing uncertainties in molecular binding energies and reaction mechanisms on dust grains.

Contribution

It presents three examples demonstrating the application of computational chemistry to fundamental questions in grain surface astrochemistry.

Findings

Computational methods can estimate binding energies for molecules lacking experimental data.

Simulations help elucidate reaction pathways on dust grain surfaces.

Improved data enhances the accuracy of astrochemical models.

Abstract

Molecules in space are synthesized via a large variety of gas-phase reactions, and reactions on dust-grain surfaces, where the surface acts as a catalyst. Especially, saturated, hydrogen-rich molecules are formed through surface chemistry. Astrochemical models have developed over the decades to understand the molecular processes in the interstellar medium, taking into account grain surface chemistry. However, essential input information for gas-grain models, such as binding energies of molecules to the surface, have been derived experimentally only for a handful of species, leaving hundreds of species with highly uncertain estimates. Moreover, some fundamental processes are not well enough constrained to implement these into the models. The proceedings gives three examples how computational chemistry techniques can help answer fundamental questions regarding grain surface chemistry.