Main-group element-boosted oxygen electrocatalysis of Cu-N-C sites for zinc-air battery with cycling over 5000 h
Bibliographic record
Abstract
Developing highly active and durable air cathode catalysts is crucial yet challenging for rechargeable zinc-air batteries. Herein, a size-adjustable, flexible, and self-standing carbon membrane catalyst encapsulating adjacent Cu/Na dual-atom sites is prepared using a solution blow spinning technique combined with a pyrolysis strategy. The intrinsic activity of the Cu-N4 site is boosted by the neighboring Na-containing functional group, which enhances O2 adsorption and optimizes the rate-determining step of O2 activation (*O2 → *OOH) during the oxygen reduction reaction process. Meanwhile, the Cu-N4 sites are encapsulated within carbon nanofibers and anchored by the carbon matrix to form a C2-Cu-N4 configuration, thereby reinforcing the stability of the Cu centers. Moreover, the introduction of Na-containing functional groups on the carbon atoms significantly reduces the positive charge on their outer shell C atoms, rendering the carbon skeletons less susceptible to corrosion by oxygen species and further preventing the dissolution of Cu centers. Under these multi-type regulations, the zinc-air battery with Cu/Na-carbon membrane catalyst as the air cathode demonstrates long-term discharge/charge cycle stability of over 5000 h. This considerable stability improvement represents a critical step towards developing Cu-N4 active sites modified with the neighboring main-group metal-containing functional groups to overcome the durability barriers of zinc-air batteries for future practical applications. Balancing the activity and stability of oxygen electrocatalysts is challenging but crucial for rechargeable zinc-air batteries. Here, the authors report a highly active Cu-N-C catalyst boosted by the main-group element for zinc-air battery with a long cycle stability over 5000 h.
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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".