The binding energies (BE) of molecules on the interstellar grains are crucial in the chemical evolution of the interstellar medium (ISM). Both temperature-programmed desorption (TPD) laboratory experiments and quantum chemistry computations have often provided, so far, only single values of the BE for each molecule. This is a severe limitation, as the ices enveloping the grain mantles are structurally amorphous, giving rise to a manifold of possible adsorption sites, each with different BEs. However, the amorphous ice nature prevents the knowledge of structural details, hindering the development of a common accepted atomistic icy model. In this work, we propose a computational framework that closely mimics the formation of the interstellar grain mantle through a water by water accretion. On that grain, an unbiased random (but well reproducible) positioning of the studied molecule is then carried out. Here we present the test case of NH₃, a ubiquitous species in the molecular ISM. We provide the BE distribution computed by a hierarchy approach, using the semiempirical xTB-GFN2 as a low-level method to describe the whole icy cluster in combination with the B97D3 DFT functional as a high-level method on the local zone of the NH₃ interaction. The final ZPE-corrected BE is computed at the ONIOM(DLPNO-CCSD(T)//B97D3:xTB-GFN2) level, ensuring the best cost/accuracy ratio. The main peak of the predicted NH₃ BE distribution is in agreement with experimental TPD and computed data in the literature. A second broad peak at very low BE values is also present, which has never been detected before. It may provide the solution to a longstanding puzzle about the presence of gaseous NH₃ also observed in cold ISM objects.

Water is one of the most important and abundant molecules in star-forming regions. In protoplanetary disks, where planets and comets form, H₂O is in a gas or solid form, depending on the dust temperature, i.e., the distance from the center and its binding energy (BE). Not surprisingly, several experimental and theoretical studies of the H₂O BE have been published. We report new ab initio calculations carried out on a large model of interstellar ice, where we identified 144 different adsorption sites. The BE associated with those sites ranges between 14.2 kJ mol⁻¹ (1705 K) and 61.6 kJ mol⁻¹ (7390 K). The distribution of the computed BEs as a function of BE follows a Gaussian peaked at 35.4 kJ mol⁻¹ (4230 K) with a standard deviation of 9.7 kJ mol⁻¹ (1160 K). The computed pre-exponential factor (ν) ranges between 9 × 10¹² and 6 × 10¹⁴ s⁻¹. We evaluated the impact of the newly calculated BE and ν distributions on the snowline of a generic protoplanetary disk. We found that the region where water is frozen onto the ice is much smaller (a factor of 10 smaller radius) than that computed with the single BE (5600 K) and ν (2 × 10¹² s⁻¹) values commonly adopted by astrochemical models. Besides, ∼10% of water remains frozen in relatively warm (∼150 K) regions, where the single BE and ν model would predict a full release of the ice in the gas phase. This last aspect may have an impact on the quantity trapped in the planetesimals eventually forming rocky planets.

Interstellar grains are composed by a rocky core (usually amorphous silicates) covered by an icy mantle, the most abundant molecule being H₂O followed by CO, CO₂, NH₃, and also radicals in minor quantities. In dense molecular clouds, gas-phase chemical species freeze onto the grain surface, making it an important reservoir of molecular diversity/complexity whose evolution leads to interstellar complex organic molecules (iCOMs). Many different models of water clusters have appeared in the literature, but without a systematic study on the properties of the grain (such as the H-bonds features, the oxygen radial distribution function, the dangling species present on the mantle surface, the surface electrostatic potential, etc.). In this work, we present a computer procedure (ACO-FROST) grounded on the newly developed semiempirical GFN2 tight-binding quantum mechanical method and the GFN-FF force field method to build-up structures of amorphous ice of large size. These methods show a very favorable accuracy/cost ratio as they are ideally designed to take noncovalent interactions into account. ACO-FROST program can be tuned to build grains of different composition mimicking dirty icy grains. These icy grain models allow studying the adsorption features (structure, binding energy, vibrational frequencies, etc.) of relevant species on a large variety of adsorption sites so to obtain a statistically meaningful distribution of the physicochemical properties of interest to be transferred in numerical models. As a test case, we computed the binding energy of ammonia adsorbed at the different sites of the icy grain surface, showing a broad distribution not easily accounted for by other more size limited icy grain models. Our method is also the base for further refinements, adopting the present grain in a more rigorous QM:MM treatment, capable of giving binding energies within the chemical accuracy.

The universe is molecularly rich, comprising from the simplest molecule (H₂) to complex organic molecules (e.g., CH₃CHO and NH₂CHO), some of which of biological relevance (e.g., amino acids). This chemical richness is intimately linked to the different physical phases forming Solar-like planetary systems, in which at each phase, molecules of increasing complexity form. Interestingly, synthesis of some of these compounds only takes place in the presence of interstellar (IS) grains, i.e., solid-state sub-micron sized particles consisting of naked dust of silicates or carbonaceous materials that can be covered by water-dominated ice mantles. Surfaces of IS grains exhibit particular characteristics that allow the occurrence of pivotal chemical reactions, such as the presence of binding/catalytic sites and the capability to dissipate energy excesses through the grain phonons. The present know-how on the physicochemical features of IS grains has been obtained by the fruitful synergy of astronomical observational with astrochemical modelling and laboratory experiments. However, current limitations of these disciplines prevent us from having a full understanding of the IS grain surface chemistry as they cannot provide fundamental atomic-scale of grain surface elementary steps (i.e., adsorption, diffusion, reaction and desorption). This essential information can be obtained by means of simulations based on computational chemistry methods. One capability of these simulations deals with the construction of atom-based structural models mimicking the surfaces of IS grains, the very first step to investigate on the grain surface chemistry. This perspective aims to present the current state-of-the-art methods, techniques and strategies available in computational chemistry to model (i.e., construct and simulate) surfaces present in IS grains. Although we focus on water ice mantles and olivinic silicates as IS test case materials to exemplify the modelling procedures, a final discussion on the applicability of these approaches to simulate surfaces of other cosmic grain materials (e.g., cometary and meteoritic) is given.

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.