Flaviano Della Pia, Giaan Kler-Young, Andrea Zen, Fabian Berger, Dario Alfè, Angelos Michaelides
{"title":"Interaction strength of carbon dioxide on graphene from periodic quantum diffusion Monte Carlo.","authors":"Flaviano Della Pia, Giaan Kler-Young, Andrea Zen, Fabian Berger, Dario Alfè, Angelos Michaelides","doi":"10.1063/5.0283254","DOIUrl":null,"url":null,"abstract":"<p><p>Despite the importance of graphene based carbon capture devices, an accurate estimate of the interaction strength of a carbon dioxide molecule with graphene from periodic calculations is lacking. In this work, we compute a fixed node quantum diffusion Monte Carlo reference value for the interaction energy of a carbon dioxide molecule with a periodic free-standing graphene sheet, obtaining a value of -152 ± 15 meV. In addition, we evaluate the performance of several widely used density functional theory approximations and foundation machine learning interatomic potentials, for both carbon dioxide and water adsorption on graphene, competitive processes that play an important role in carbon capture technologies. Among the approaches tested, the B86bPBE-XDM, PBE-D3, revPBE-D3, rev-vdW-DF2, SCAN+rVV10, and PBE0-D3-ATM functionals achieve the closest agreement with DMC for the carbon dioxide-graphene interaction. The vdW-DF2, rev-vdW-DF2, and PBE0-D4-ATM functionals perform better for the competitive adsorption of water and carbon dioxide.</p>","PeriodicalId":15313,"journal":{"name":"Journal of Chemical Physics","volume":"163 7","pages":""},"PeriodicalIF":3.1000,"publicationDate":"2025-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Chemical Physics","FirstCategoryId":"92","ListUrlMain":"https://doi.org/10.1063/5.0283254","RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"CHEMISTRY, PHYSICAL","Score":null,"Total":0}
引用次数: 0
Abstract
Despite the importance of graphene based carbon capture devices, an accurate estimate of the interaction strength of a carbon dioxide molecule with graphene from periodic calculations is lacking. In this work, we compute a fixed node quantum diffusion Monte Carlo reference value for the interaction energy of a carbon dioxide molecule with a periodic free-standing graphene sheet, obtaining a value of -152 ± 15 meV. In addition, we evaluate the performance of several widely used density functional theory approximations and foundation machine learning interatomic potentials, for both carbon dioxide and water adsorption on graphene, competitive processes that play an important role in carbon capture technologies. Among the approaches tested, the B86bPBE-XDM, PBE-D3, revPBE-D3, rev-vdW-DF2, SCAN+rVV10, and PBE0-D3-ATM functionals achieve the closest agreement with DMC for the carbon dioxide-graphene interaction. The vdW-DF2, rev-vdW-DF2, and PBE0-D4-ATM functionals perform better for the competitive adsorption of water and carbon dioxide.
期刊介绍:
The Journal of Chemical Physics publishes quantitative and rigorous science of long-lasting value in methods and applications of chemical physics. The Journal also publishes brief Communications of significant new findings, Perspectives on the latest advances in the field, and Special Topic issues. The Journal focuses on innovative research in experimental and theoretical areas of chemical physics, including spectroscopy, dynamics, kinetics, statistical mechanics, and quantum mechanics. In addition, topical areas such as polymers, soft matter, materials, surfaces/interfaces, and systems of biological relevance are of increasing importance.
Topical coverage includes:
Theoretical Methods and Algorithms
Advanced Experimental Techniques
Atoms, Molecules, and Clusters
Liquids, Glasses, and Crystals
Surfaces, Interfaces, and Materials
Polymers and Soft Matter
Biological Molecules and Networks.