Activation of CO<sub>2</sub> at the electrode–electrolyte interface by a co-adsorbed cation and an electric field
Bibliographic record
Abstract
Carboxylate *CO2- has recently been identified as the first intermediate of the CO2 electroreduction independent of the reaction pathway. However, on the fundamental level, the structural and electronic properties of *CO2- remain poorly understood especially under the electrocatalytic conditions, which limits our capacity to rationally control the transformation of this reaction intermediate to CO or formate. To close this gap, we model using density functional theory (DFT) the interactions of *CO2- with the copper Cu(111) surface and a co-adsorbed sodium cation in the electric double layer (EDL), as well as the effects of electrode potential on these interactions. We demonstrate that *CO2- is activated by a co-adsorbed alkali cation most strongly when it forms with the cation a noncovalent bond (ion pair), where the cation is coordinated in the on-top position. The most stable structure of this ion pair with a sodium cation is hydration-shared. An external negative electric field not only enhances activation of *CO2- but also tilts it in the *CO2- plane, elongating the metal-C bond and contracting the metal-O bond. This tilting facilitates hydrogenation of the C atom and dissociation of the surface-coordinated C-O bond. Based on a detailed analysis of the projected density of states (pDOS), we interpret these findings in terms of electrostatic and chemical effects. The provided insights can help understand the relationship between properties of the catalytic system and its catalytic activity in the CO2 conversion to CO and formate, and hence help develop new CO2 electroreduction catalysts.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".