Sequential electrocatalytic reactions along a membrane electrode assembly drive efficient nitrate-to-ammonia conversion
Bibliographic record
Abstract
Electrochemical ammonia (NH 3 ) synthesis from nitrate (NO 3 − ) offers a promising greener alternative to the fossil-fuel-based Haber-Bosch process to support the increasing demand for nitrogen fertilizers while removing environmental waste. Previous studies have mainly focused on designing catalysts to promote the direct conversion (NO 3 − → NH 3 ) while suppressing the two-step pathway (NO 3 − → NO 2 − → NH 3 ). We hypothesize that efficient nitrate reduction is possible on simple catalysts by instead promoting the two-step reaction and using chemical reactor principles in a membrane electrode assembly, despite NO 2 − intermediates. Here, we use an unmodified copper catalyst and control reactivity through current density, flow rate, and electrolyte recycling. Balancing the electrolyte flow rate with current density results in ideal residence times for NO 2 − , allowing for 91% FE NH3 in a 5 cm 2 electrolyzer with a NO 3 − to NH 3 partial current of 1.8 A. This work shows that traditional engineering principles can substantially boost the NO 3 reduction reaction, even for simple catalysts.
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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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".