Sulfur Mediated Interfacial Proton‐Directed Transfer Boosts Electrocatalytic Nitric Oxide Reduction to Ammonia over Dual‐Site Catalysts
Bibliographic record
Abstract
Abstract Electrocatalytic nitric oxide reduction reaction (NORR) for ammonia (NH 3 ) synthesis represents a sustainable strategy that simultaneously realizes the nitrogen cycle and resource integration. The key issue hindering the NORR efficiency is accelerating proton (*H) transfer to facilitate NO hydrogenation while inhibiting the hydrogen evolution reaction (HER). Herein, we demonstrate an interface‐engineered sulfur‐mediated Cu@Co electrocatalyst (S‐Cu@Co/C) that boosts NORR performance through dual modulation of electronic structure and proton transfer on active sites. A comprehensive program of experimental and theoretical calculations was employed to discover that sulfur incorporation induces electron redistribution in the Cu–Co interface, creating electron‐rich sulfur and electron‐deficient metals. This electronic configuration synergistically enhances NO adsorption on Cu sites and promotes water dissociation on Co sites. More critically, sulfur could direct the rapid transfer of *H from Co to Cu sites, thereby accelerating the NO hydrogenation and suppressing HER. Consequently, S‐Cu@Co/C achieves an NH 3 yield rate of 655.3 µmol h −1 cm −2 in a flow cell and a Faradaic efficiency of 92.4% in an H‐cell. Remarkably, the catalyst could maintain continuous electrolysis tests and steady NH 3 yield up to 100 h. This work provides innovative insights into the fabrication of efficient electrocatalysts via heteroatom‐mediated interfacial engineering strategies.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".