Two‐dimensional Cu Plates with Steady Fluid Fields for High‐rate Nitrate Electroreduction to Ammonia and Efficient Zn‐Nitrate Batteries
Bibliographic record
Abstract
Abstract Nitrate electroreduction reaction (eNO3−RR) to ammonia (NH3) provides a promising strategy for nitrogen utilization, while achieving high selectivity and durability at an industrial scale has remained challenging. Herein, we demonstrated that the performance of eNO3−RR could be significantly boosted by introducing two‐dimensional Cu plates as electrocatalysts and eliminating the general carrier gas to construct a steady fluid field. The developed eNO3−RR setup provided superior NH3 Faradaic efficiency (FE) of 99 %, exceptional long‐term electrolysis for 120 h at 200 mA cm−2, and a record‐high yield rate of 3.14 mmol cm−2 h−1. Furthermore, the proposed strategy was successfully extended to the Zn‐nitrate battery system, providing a power density of 12.09 mW cm−2 and NH3 FE of 85.4 %, outperforming the state‐of‐the‐art eNO3−RR catalysts. Coupled with the COMSOL multiphysics simulations and in situ infrared spectroscopy, the main contributor for the high‐efficiency NH3 production could be the steady fluid field to timely rejuvenate the electrocatalyst surface during the electrocatalysis.
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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".