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CO(2) on Graphene: Benchmarking Computational Approaches to Noncovalent Interactions

[Image: see text] Designing and optimizing graphene-based gas sensors in silico entail constructing appropriate atomistic representations for the physisorption complex of an analyte on an infinite graphene sheet, then selecting accurate yet affordable methods for geometry optimizations and energy co...

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Autores principales: Ehlert, Christopher, Piras, Anna, Gryn’ova, Ganna
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2023
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10551916/
https://www.ncbi.nlm.nih.gov/pubmed/37810719
http://dx.doi.org/10.1021/acsomega.3c03251
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author Ehlert, Christopher
Piras, Anna
Gryn’ova, Ganna
author_facet Ehlert, Christopher
Piras, Anna
Gryn’ova, Ganna
author_sort Ehlert, Christopher
collection PubMed
description [Image: see text] Designing and optimizing graphene-based gas sensors in silico entail constructing appropriate atomistic representations for the physisorption complex of an analyte on an infinite graphene sheet, then selecting accurate yet affordable methods for geometry optimizations and energy computations. In this work, diverse density functionals (DFs), coupled cluster theory, and symmetry-adapted perturbation theory (SAPT) in conjunction with a range of finite and periodic surface models of bare and supported graphene were tested for their ability to reproduce the experimental adsorption energies of CO(2) on graphene in a low-coverage regime. Periodic results are accurately reproduced by the interaction energies extrapolated from finite clusters to infinity. This simple yet powerful scheme effectively removes size dependence from the data obtained using finite models, and the latter can be treated at more sophisticated levels of theory relative to periodic systems. While for small models inexpensive DFs such as PBE-D3 afford surprisingly good agreement with the gold standard of quantum chemistry, CCSD(T), interaction energies closest to experiment are obtained by extrapolating the SAPT results and with nonlocal van der Waals functionals in the periodic setting. Finally, none of the methods and models reproduce the experimentally observed CO(2) tilted adsorption geometry on the Pt(111) support, calling for either even more elaborate theoretical approaches or a revision of the experiment.
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spelling pubmed-105519162023-10-06 CO(2) on Graphene: Benchmarking Computational Approaches to Noncovalent Interactions Ehlert, Christopher Piras, Anna Gryn’ova, Ganna ACS Omega [Image: see text] Designing and optimizing graphene-based gas sensors in silico entail constructing appropriate atomistic representations for the physisorption complex of an analyte on an infinite graphene sheet, then selecting accurate yet affordable methods for geometry optimizations and energy computations. In this work, diverse density functionals (DFs), coupled cluster theory, and symmetry-adapted perturbation theory (SAPT) in conjunction with a range of finite and periodic surface models of bare and supported graphene were tested for their ability to reproduce the experimental adsorption energies of CO(2) on graphene in a low-coverage regime. Periodic results are accurately reproduced by the interaction energies extrapolated from finite clusters to infinity. This simple yet powerful scheme effectively removes size dependence from the data obtained using finite models, and the latter can be treated at more sophisticated levels of theory relative to periodic systems. While for small models inexpensive DFs such as PBE-D3 afford surprisingly good agreement with the gold standard of quantum chemistry, CCSD(T), interaction energies closest to experiment are obtained by extrapolating the SAPT results and with nonlocal van der Waals functionals in the periodic setting. Finally, none of the methods and models reproduce the experimentally observed CO(2) tilted adsorption geometry on the Pt(111) support, calling for either even more elaborate theoretical approaches or a revision of the experiment. American Chemical Society 2023-09-20 /pmc/articles/PMC10551916/ /pubmed/37810719 http://dx.doi.org/10.1021/acsomega.3c03251 Text en © 2023 The Authors. Published by American Chemical Society https://creativecommons.org/licenses/by-nc-nd/4.0/Permits non-commercial access and re-use, provided that author attribution and integrity are maintained; but does not permit creation of adaptations or other derivative works (https://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Ehlert, Christopher
Piras, Anna
Gryn’ova, Ganna
CO(2) on Graphene: Benchmarking Computational Approaches to Noncovalent Interactions
title CO(2) on Graphene: Benchmarking Computational Approaches to Noncovalent Interactions
title_full CO(2) on Graphene: Benchmarking Computational Approaches to Noncovalent Interactions
title_fullStr CO(2) on Graphene: Benchmarking Computational Approaches to Noncovalent Interactions
title_full_unstemmed CO(2) on Graphene: Benchmarking Computational Approaches to Noncovalent Interactions
title_short CO(2) on Graphene: Benchmarking Computational Approaches to Noncovalent Interactions
title_sort co(2) on graphene: benchmarking computational approaches to noncovalent interactions
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10551916/
https://www.ncbi.nlm.nih.gov/pubmed/37810719
http://dx.doi.org/10.1021/acsomega.3c03251
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