Hydroxyl-mediated interfacial oxophilicity engineering for efficient CO2-to-C2+ oxygenates conversion at industrial current densities
Bibliographic record
Abstract
Electrocatalytic CO 2 reduction (eCO 2 RR) to multi-carbon (C 2+ ) products is a promising pathway for renewable energy storage and carbon neutrality. However, selectively steering the reaction toward high-value C 2+ oxygenates, rather than ethylene, remains a major challenge due to the intertwined reaction pathways following the initial C–C coupling step. Herein, we propose a hydroxyl-mediated interfacial oxophilic engineering strategy to selectively stabilize oxygenated intermediates and promote their directional transformation into C 2+ oxygenates. In situ spectroscopic analyses and DFT calculations reveal that hydroxyl species preferentially anchor at low-coordinated Cu sites at the Cu/Cu 2 O interface, creating a locally oxophilic and chemically asymmetric microenvironment. This interfacial hydroxyl layer not only stabilizes Cu δ+ species under high current densities but also promotes the retention of *OCCHO and *CHO-like intermediates, while disfavoring their deoxygenation to ethylene. As a result, the catalyst achieves a C 2+ oxygenates Faradaic efficiency of 68% at an industrially relevant current density of 200 mA cm -2 in a 5 cm 2 membrane electrode assembly. This work highlights the critical role of interfacial oxophilicity in governing product selectivity and offers a generalizable design principle for constructing high-performance eCO 2 RR catalysts that break the traditional trade-off between C–C coupling efficiency and product selectivity.
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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".