Highly Accessible Electrocatalyst with <i>I</i><i>n Situ</i> Formed Copper-Cluster Active Sites for Enhanced Nitrate-to-Ammonia Conversion
Bibliographic record
Abstract
Ammonia synthesis via nitrate electroreduction is more attractive and sustainable than the energy-extensive Haber–Bosch process and intrinsically sluggish nitrogen electroreduction. Herein, we have designed a single-site Cu catalyst on hierarchical nitrogen-doped carbon nanocage support (Cu 1 /hNCNC) for nitrate electroreduction, which achieves an ultrahigh ammonia yield rate (YR NH3 ) of 99.4 mol h –1 g Cu –1 (2.30 mol h –1 g cat. –1 ) with ammonia Faradaic efficiency (FE NH3 ) of 99.3%, far beyond the most reported single-site catalysts on carbon-based supports. The combined operando characterization and theoretical studies indicate that the in situ formed Cu-cluster active sites are responsible for the high YR NH3 and FE NH3 due to the enhanced NO 3 – adsorption and subsequent protonation on the unique Cu 3 –N 4 moieties, and meanwhile, the hierarchical hNCNC support facilitates the mass/charge transfer kinetics, thus promoting the high expression of intrinsic activity. The demonstration of plasma N 2 oxidization and nitrate electroreduction cascade reaction manifests the great potential of the Cu 1 /hNCNC electrocatalyst in sustainable NH 3 synthesis. These findings offer valuable insights into the design of effective catalysts for electrosynthetic reactions.
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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 | 0.001 | 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".