Atomically Dispersed Ni–Cu Dual Sites: Efficient Electrocatalytic Conversion of 4-Nitrophenol to <i>p</i>-Aminophenol in a Hybrid Acid/Alkali Flow Electrolyzer
Bibliographic record
Abstract
4-Nitrophenol (4-NP), a toxic and recalcitrant pollutant, necessitates effective remediation strategies. Here, a noble metal-free NiCu-NC electrocatalyst is developed, where dual atomic Ni–Cu sites are elegantly anchored on a rhombic dodecahedral nitrogen-doped carbon matrix, enabling selective electrochemical reduction of 4-NP into value-added p -aminophenol (4-AP). This catalyst achieves a low overpotential and a high Faradaic efficiency of 95.7% for 4-AP production. Density functional theory (DFT) calculations reveal that the NiCu dual-atom configuration minimizes the energy barrier for the rate-determining step, thereby enhancing catalytic performance. Furthermore, a hybrid acid/alkali flow electrolysis cell is designed to couple the cathodic 4-NP reduction with the anodic oxygen evolution. This system maintains stable operation for over 400 h while maintaining a high Faradaic efficiency (>91%) and near-complete conversion (99%) for valorization of 4-NP. This work demonstrates a practical electrocatalytic approach for pollutant transformation and chemical production with potential implications for wastewater treatment and resource utilization.
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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) | 0.001 | 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".