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There are different environments in the interstellar medium (ISM), depending on the density, temperature and chemical composition. Among them, molecular clouds, often referred to as the cradle of stars, are paradigmatic environments relative to the chemical diversity and complexity in space. Indeed, there, radio to far-infrared observations revealed the presence of several molecules in the gas phase, while near-infrared spectroscopy detected the existence of submicron sized dust grains covered by H2O -dominated ice mantles. The interaction between gas-phase species and the surfaces of water ices is measured by the binding energy (BE), a crucial parameter in astrochemical modelling. In this work, the BEs of a set of sulphur-containing species on water ice mantles have been computed by adopting a periodic ab initio approach using a crystalline surface model. The Density Functional Theory (DFT)-based B3LYP-D3(BJ) functional was used for the prediction of the structures and energetics. DFT BEs were refined by adopting an ONIOM-like procedure to estimate them at CCSD(T) level toward complete basis set extrapolation, in which a very good correlation between values has been found. Moreover, we show that geometry optimization with the computationally cheaper HF-3c method followed by single point energy calculations at DFT to compute the BEs is a suitable cost-effective recipe to arrive at BE values of the same quality as those computed at full DFT level. Finally, computed data were compared with the available literature data., Proceedings of the 21st International Conference on Computational Science and Its Applications, ICCSA 2021

Interstellar Grains (IGs) spread in the Interstellar Medium (ISM) host a multitude of chemical reactions that could lead to the production of interstellar Complex Organic Molecules (iCOMs), relevant in the context of prebiotic chemistry. These IGs are composed of a silicate-based core covered by several layers of amorphous water ice, known as a grain mantle. Molecules from the ISM gas-phase can be adsorbed at the grain surfaces, diffuse and react to give iCOMs and ultimately desorbed back to the gas phase. Thus, the study of the Binding Energy (BE) of these molecules at the water ice grain surface is important to understand the molecular composition of the ISM and its evolution in time. In this paper, we propose to use a recently developed semiempirical quantum approach, named GFN-xTB, and more precisely the GFN2 method, to compute the BE of several molecular species at the crystalline water ice slab model. This method is very cheap in term of computing power and time and was already showed in a previous work to be very accurate with small water clusters. To support our proposition, we decided to use, as a benchmark, the recent work published by some of us in which a crystalline model of proton-ordered water ice (P-ice) was adopted to predict the BEs of 21 molecules relevant in the ISM. The relatively good results obtained confirm GFN2 as the method of choice to model adsorption processes occurring at the icy grains in the ISM. The only notable exception was for the CO molecule, in which both structure and BE are badly predicted by GFN2, a real pity due to the relevance of CO in astrochemistry.