First‐Row Transition Metals for Catalyzing Oxygen Redox
Bibliographic record
Abstract
Rechargeable zinc-air batteries are widely recognized as a highly promising technology for energy conversion and storage, offering a cost-effective and viable alternative to commercial lithium-ion batteries due to their unique advantages. However, the practical application and commercialization of zinc-air batteries are hindered by the sluggish kinetics of the oxygen reduction reaction (ORR) and oxygen evolution reaction (OER). Recently, extensive research has focused on the potential of first-row transition metals (Mn, Fe, Co, Ni, and Cu) as promising alternatives to noble metals in bifunctional ORR/OER electrocatalysts, leveraging their high-efficiency electrocatalytic activity and excellent durability. This review provides a comprehensive summary of the recent advancements in the mechanisms of ORR/OER, the performance of bifunctional electrocatalysts, and the preparation strategies employed for electrocatalysts based on first-row transition metals in alkaline media for zinc-air batteries. The paper concludes by proposing several challenges and highlighting emerging research trends for the future development of bifunctional electrocatalysts based on first-row transition metals.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".