CO2 reduction catalysis of CO doped Cu nanoparticles anchored to graphene: A DFT study

Abstract

This study investigates the structural and electronic properties of graphene-supported Cu₁₉ and Cu₁₈Co nanocluster catalysts using density functional theory (DFT). The stable configurations of the catalysts were optimized, and their corresponding structural features and charge distribution characteristics were analyzed. Furthermore, we systematically explored the possible reaction mechanisms for CO₂ reduction to C1 products on both Cu₁₈Co/G and Cu₁₉/G catalysts. Through comparative analysis of reaction pathway activation energies, the optimal routes for CO₂ catalytic reduction to four distinct C1 products were identified. The study reveals that for CO production, the rate-determining step activation energies are 1.48 eV on Cu₁₈Co/G and 0.68 eV on Cu₁₉/G, respectively. For HCOOH formation, the corresponding activation barriers are 1.31 eV and 1.09 eV for Cu₁₈Co/G and Cu₁₉/G catalysts. Meanwhile, the activation energies of the rate-determining steps for the optimal pathways of CO₂ reduction to CH₃OH were determined to be 1.88 eV and 1.24 eV for Cu₁₈Co/G and Cu₁₉/G, respectively. These results indicate that the pure copper nanocluster catalyst Cu₁₉/G exhibits superior activity for the catalytic reduction of CO₂ to three major products: CO, HCOOH and CH₃OH. In contrast, for CH₄ formation, the activation barriers of the rate-determining steps were calculated to be 1.48 eV and 1.60 eV on Cu₁₈Co/G and Cu₁₉/G catalysts. Our findings reveal that the Co-doped Cu₁₈Co/G catalyst promotes selective CH₄ production in CO₂ reduction. Our systematic evaluation reveals distinct product selectivity trends for CO₂ reduction to C1 products between the two catalysts. The Cu₁₉/G system exhibits the following activity hierarchy: CO > HCOOH > CH₃OH > CH₄, indicating unfavorable CH₄ formation kinetics. The Cu₁₈Co/G catalyst exhibits a distinct product selectivity trend for CO₂ reduction to C1 products: HCOOH > CH₄ = CO > CH₃OH. The CH₃OH yield was found to be the lowest among all products. Our findings aim to provide theoretical guidance for the design and optimization of CO₂ catalysts.