Modeling interstellar amorphous solid water grains by tight-binding based methods: comparison between GFN-XTB and CCSD(T) results for water clusters
| Autor: | Aurèle Germain, Piero Ugliengo |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Chemical Physics (physics.chem-ph)
Materials science 010304 chemical physics Binding energy Complexes Organic Molecules FOS: Physical sciences AWS water models 01 natural sciences Article Amorphous solid Interstellar medium Tight binding Chemical physics Physics - Chemical Physics 0103 physical sciences Water cluster 010303 astronomy & astrophysics Parametrization Quantum Order of magnitude |
| Zdroj: | Computational Science and Its Applications – ICCSA 2020 ISBN: 9783030588137 ICCSA (5) Lecture Notes in Computer Science Lecture Notes in Computer Science-Computational Science and Its Applications – ICCSA 2020 Computational Science and Its Applications – ICCSA 2020-20th International Conference, Cagliari, Italy, July 1–4, 2020, Proceedings, Part V Computational Science and Its Applications – ICCSA 2020 |
| ISSN: | 0302-9743 1611-3349 |
| Popis: | One believed path to Interstellar Complexes Organic Molecules (iCOMs) formation inside the Interstellar Medium (ISM) is through chemical recombination at the surface of amorphous solid water (ASW) mantle covering the silicate-based core of the interstellar grains. The study of these iCOMs formation and their binding energy to the ASW, using computational chemistry, depends strongly on the ASW models used, as different models may exhibit sites with different adsorbing features. ASW extended models are rare in the literature because large sizes require very large computational resources when quantum mechanical methods based on DFT are used. To circumvent this problem, we propose to use the newly developed GFN-xTB Semi-empirical Quantum Mechanical (SQM) methods from the Grimme's group. These methods are, at least, two orders of magnitude faster than conventional DFT, only require modest central memory, and in this paper we aim to benchmark their accuracy against rigorous and resource hungry quantum mechanical methods. We focused on 38 water structures studied by MP2 and CCSD(T) approaches comparing energetic and structures with three levels of GFN-xTB parametrization (GFN0, GFN1, GFN2) methods. The extremely good results obtained at the very cheap GFN-xTB level for both water cluster structures and energetic paved the way towards the modeling of very large AWS models of astrochemical interest. 9 pages, 4 figures, Submitted to LNCS (Springer) ICCSA2020 |
| Databáze: | OpenAIRE |
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