Stabilizing Cu <sup>0</sup> /Cu <sup>+</sup> Interfaces via High‐Entropy Electrochemical Potential Regulation Strategy for Enhanced CO <sub>2</sub> ‐to‐Ethylene Conversion in Acidic Medium
Bibliographic record
Abstract
Abstract The electrochemical CO 2 reduction reaction (CO 2 RR) in acidic media represents an efficient carbon‐negative strategy, mitigating greenhouse effects while selectively producing value‐added multi‐carbon compounds. The Cu 0 /Cu + interfaces could promote C─C coupling processes, but preserving the interface integrity under highly reductive potentials and acidic conditions presents substantial challenges. Here, a high‐entropy electrochemical potential regulation strategy is reported that leverages high‐entropy doping synergy to atomically tailor the surface electronic structure of Cu‐based catalysts. This strategy creates an electron shield effect around the host element (Cu), protecting it from excessive reduction and facilitating the formation and stabilization of Cu 0 /Cu + interfaces during acidic CO 2 RR. Comprehensive operando characterizations combined with density functional theory calculations reveal that the electron shield effect strategically modulates the electron‐accepting capability of Cu. The optimized surface electronic structure facilitates C─C coupling, significantly enhancing the CO 2 ‐to‐C 2+ conversion efficiency. The designed catalyst achieves a remarkable Faradaic efficiency of 66.7% for ethylene production at −1.69 V vs the reversible hydrogen electrode in acidic electrolyte (pH 2), while maintaining excellent stability with an average ethylene Faradaic efficiency of 63.1% over 52‐h continuous operation. This work establishes a new strategy for designing and stabilizing active interfaces of copper‐based electrocatalysts for efficient and durable acidic CO 2 electroreduction.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".