Electrochemical Nitrate Reduction to Ammonia on AuCu Single‐Atom Alloy Aerogels under Wide Potential Window
Bibliographic record
Abstract
Abstract Electrocatalytic nitrate reduction to ammonia (NO 3 RR) is very attractive for nitrate removal and ammonia production in industrial processes. However, the nitrate reduction reaction is characterized by intense hydrogen competition at strong reduction potentials, which greatly limits the Faraday efficiency at strong reduction potentials. Herein, we reported an Au x Cu single‐atom alloy aerogels (Au x Cu SAAs) with three‐dimensional network structure with significant nitrate reduction performance of Faraday efficiency (FE) higher than 90 % over a wide potential range (0 ~ −1 V RHE ). The FE of the catalyst was close to 100 % at a high reduction potential of −0.8 V RHE , accompanying with NH 3 yield reaching 6.21 mmol h 1 cm 2 . More importantly, the catalyst maintained a long‐term operation over 400 h at 400 mA cm 2 for the NO 3 RR using a continuous flow system in a H‐cell. Experimental and theoretical analysis demonstrate that the catalyst can lower the energy barrier for the hydrogenation reaction of *NO 2 , leading to a rapid consumption of the generated *H, facilitate the hydrogenation process of NO 3 RR, and inhibit the competitive HER at high overpotentials, which efficiently promotes the nitrate reduction reaction, especially in industrial applications.
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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) | 0.000 | 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 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".