Periodic calculations reveal interaction energy of carbon dioxide on graphene, highlighting insights into carbon capture.
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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Pia et al. (2025) studied this question.
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