Preferentially Engineering FeN<sub>4</sub> Edge Sites onto Graphitic Nanosheets for Highly Active and Durable Oxygen Electrocatalysis in Rechargeable Zn–Air Batteries
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Single‐atom FeN 4 sites at the edges of carbon substrates are considered more active for oxygen electrocatalysis than those in plane; however, the conventional high‐temperature pyrolysis process does not allow for precisely engineering the location of the active site down to atomic level. Enlightened by theoretical prediction, herein, a self‐sacrificed templating approach is developed to obtain edge‐enriched FeN 4 sites integrated in the highly graphitic nanosheet architecture. The in situ formed Fe clusters are intentionally introduced to catalyze the growth of graphitic carbon, induce porous structure formation, and most importantly, facilitate the preferential anchoring of FeN 4 to its close approximation. Due to these attributes, the as‐resulted catalyst (denoted as Fe/N‐G‐SAC) demonstrates unprecedented catalytic activity and stability for the oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) by showing an impressive half‐wave potential of 0.89 V for the ORR and a small overpotential of 370 mV at 10 mA cm −2 for the OER. Moreover, the Fe/N‐G‐SAC cathode displays encouraging performance in a rechargeable Zn–air battery prototype with a low charge–discharge voltage gap of 0.78 V and long‐term cyclability for over 240 cycles, outperforming the noble metal benchmarks.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it