Interaction strength of carbon dioxide on graphene from periodic quantum diffusion Monte Carlo

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.

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Publication Details

Journal
The Journal of Chemical Physics
Published
2025-08-19
DOI
https://doi.org/10.1063/5.0283254
Citations
1
Primary Topic
Graphene research and applications
Type
article
Field-Weighted Citation Impact
0.52

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article

Interaction strength of carbon dioxide on graphene from periodic quantum diffusion Monte Carlo

Dario Alfè, Andrea Zen, Angelos Michaelides, Flaviano Della Pia et al.
1 citations
The Journal of Chemical Physics
Graphene research and applications
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article

Interaction strength of carbon dioxide on graphene from periodic quantum diffusion Monte Carlo

Dario Alfè, Andrea Zen, Angelos Michaelides, Flaviano Della Pia, Fabian Berger, Giaan Kler-Young
article en
1 citations

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.

The Journal of Chemical PhysicsVol. 163(7)
University of Cambridge (GB), London Centre for Nanotechnology (GB), Thomas Young Centre (GB), Istituto Nazionale di Fisica Nucleare, Sezione di Napoli (IT), University College London (GB), University of Naples Federico II (IT)
Alexander von Humboldt-Stiftung, Dell EMC, European Commission, Isaac Newton Trust, Engineering and Physical Sciences Research Council, Science and Technology Facilities Council, European Research Council
Openalex Percentile: Top 34%
Graphene research and applications
0.52
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