This is the authors' abstract. We don't add key points for this paper.
Electrochemical CO 2 reduction reaction (eCO 2 RR) in acidic media faces critical challenges, primarily insufficient product selectivity due to the competitive hydrogen evolution reaction (HER). Understanding the electrical double layer (EDL) and the local reaction environment (LRE) is crucial for efficient CO 2 conversion. Existing continuum EDL models often provide inaccurate species distributions within the EDL and misjudge competitive reactions at high overpotentials. To overcome these, this study develops a continuum EDL model based on the “local hard-sphere Poisson–Nernst–Planck (LHSPNP) equation”. By incorporating excess chemical potential from hard-sphere repulsion and more comprehensive size-effect terms, the LHSPNP model offers a more accurate description of ion exclusion and species interactions. It precisely captures CO 2 and H 3 O + distributions and accurately reproduces experimental partial current densities for CO and H 2 at high overpotentials, notably predicting the transition in the proton source for HER. The model reveals that modulating the concentration and type of alkali metal cations is essential for optimizing eCO 2 RR. Weakly hydrated cations accumulate at the outer Helmholtz plane (OHP), suppressing H 3 O + mass transfer and enhancing the electric field strength in the compact layer, thereby promoting CO 2 electroreduction. Additionally, cationic polymers with a sufficiently high charge density can replicate these cation effects, enabling efficient CO 2 electroreduction in acidic electrolytes without alkali metal cations. By elucidating species distribution and mass transfer within the EDL, this work provides critical design guidelines for optimizing eCO 2 RR systems, facilitating industrial CO 2 electroreduction.
Answers are grounded in this paper and cite their sources.
No takes yet. Share an insight, caveat, or question.
Wang et al. (2025) studied this question.
Synapse has enriched 10 related papers. Consider them for comparative context: