Enhanced Carbon‐Carbon Coupling at Interfaces with Abrupt Coordination Number Changes
Bibliographic record
Abstract
Abstract Cu‐catalyzed electrochemical CO2 reduction reaction (CO2RR) produces multi‐carbon (C2+) chemicals with considerable selectivities and activities, yet required high overpotentials impede its practical application. Here, we design interfaces with abrupt coordination number (CN) changes that greatly reduce the applied potential for achieving high C2+ Faradaic efficiency (FE). Encouraged by the mechanistic finding that the coupling between *CO and *CO(H) is the most probable C−C bond formation path, we use Cu2O‐ and Cu‐phthalocyanine‐derived Cu (OD−Cu and PD−Cu) to build the interface. Using operando X‐ray absorption spectroscopy (XAS), we find that the Cu CN of OD−Cu is ~11, favoring CO* adsorption, while the PD−Cu has a COH*‐favorable CN of ~4. Operando Raman spectroscopy revealed that the interfaces with abrupt CN changes promote *OCCOH formation. As a result, the designed catalyst achieves a C2+ FE of 85±2 % at 220 mA cm−2 in a zero‐gap CO2 electrolyzer. An improvement of C2+ FE by 3 times is confirmed at the low potential regime where the current density is 60–140 mA cm−2, compared to bare OD−Cu. We report a 45‐h stable CO2RR operation at 220 mA cm−2, producing a C2+ product FE of ~80 %.
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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) | 0.001 | 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".