P‐Bridging Asymmetry Diatomic Catalysts Sites Drive Efficient Bifunctional Oxygen Electrocatalysis for Zinc‐Air Batteries
Bibliographic record
Abstract
Abstract Rechargeable zinc‐air batteries (ZABs) rely on the development of high‐performance bifunctional oxygen electrocatalysts to facilitate efficient oxygen reduction/evolution reactions (ORR/OER). Single‐atom catalysts (SACs), characterized by their precisely defined active sites, have great potential for applications in ZABs. However, the design and architecture of atomic site electrocatalysts with both high activity and durability present significant challenges, owing to their spatial confinement and electronic states. In this study, a strategy is proposed to fabricate structurally uniform dual single‐atom electrocatalyst (denoted as P‐FeCo/NC) consisting of P‐bridging Fe and Co bimetal atom (i.e., Fe‐P‐Co) decorated on N, P‐co‐doped carbon framework as an efficient and durable bifunctional electrocatalyst for ZABs. Experimental investigations and theoretical calculations reveal that the Fe‐P‐Co bridge‐coupling structure enables a facile adsorption/desorption of oxygen intermediates and low activation barrier. The resultant P‐FeCo/NC exhibits ultralow overpotential of 340 mV at 10 mA cm−2 for OER and high half‐wave potential of 0.95 V for ORR. In addition, the application of P‐FeCo/NC in rechargeable ZABs demonstrates enhanced performance with maximum power density of 115 mW cm−2 and long cyclic stability, which surpass Pt/C and RuO2 catalysts. This study provides valuable insights into the design and mechanism of atomically dispersed catalysts for energy conversion applications.
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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".