In‐Situ Silica Xerogel Assisted Facile Synthesis of Fe‐N‐C Catalysts with Dense Fe‐N<i><sub>x</sub></i> Active Sites for Efficient Oxygen Reduction
Bibliographic record
Abstract
Abstract In the past decade, atomically dispersed Fe active sites (coordinated with nitrogen) on carbon materials (FeNC) have emerged rapidly as promising single‐atom catalysts (SACs) for the oxygen reduction reaction (ORR) to substitute precious group metal (PGM) catalysts, owing to their earth abundance and low cost. Nonetheless, the production of highly active FeNC SACs is largely restricted by material cost, low product yield and difficulty of microstructure design. Herein, the authors demonstrate a facile in‐situ xerogel (ISG) assisted synthetic strategy, using cheap materials, to construct FeNC SACs (ISG FeNC). The porous silica xerogel, formed in‐situ with the FeNC precursors, encourages the emergence of enormous micropores/mesopores and homogeneous confinement/protection to the precursors during pyrolysis, benefiting to the formation of abundant accessible active sites (27.6 × 10 19 sites g –1 ). Correspondingly, the ISG FeNC exhibits excellent ORR activity with a half‐wave potential ( E 1/2 = 0.91 V) in alkaline medium. The Zn–air battery assembled using the ISG FeNC SACs as the bifunctional catalyst of air cathode, demonstrates commendable performance with high peak power density of 249.1 mW cm –2 and superior long‐term stability (660 cycles with 220 h). This work offers an economic and efficient way to fabricate PGM‐free SACs for diverse applications.
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How this classification was reachedexpand
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".