Wood Carbon Based Single-Atom Catalyst for Rechargeable Zn–Air Batteries
Bibliographic record
Abstract
Low-cost and efficient oxygen reduction reaction (ORR)/oxygen evolution reaction (OER) bifunctional electrocatalysts are vital for the applications of rechargeable Zn–air batteries (ZABs). Given the high catalytic activity of single-atom catalysts (SACs), preparing SACs on a large scale for ZABs is desirable but remains challenging. Herein, in situ formation of single-atom Fe–N–C catalysts on plate wood-based porous carbon is achieved via a facile Lewis acid pretreatment and carbonization process. Lewis acid FeCl 3 pretreatment on the cell wall of wood not only produces abundant microchannels but also successfully introduces atomically dispersed Fe–N active species into the hierarchical structure. Such uniformly dispersive SACs on the hierarchical structure enhance the ORR/OER performance and durability. A ZAB using the catalyst in the cathode shows a high power density (70.2 mW cm –2, at quasi solid state) and long-term stability. This work provides a new path for the large-scale preparation of high-performance SACs.
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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 | 0.001 |
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".