Geometric and Electronic Engineering of Atomically Dispersed Copper‐Cobalt Diatomic Sites for Synergistic Promotion of Bifunctional Oxygen Electrocatalysis in Zinc–Air Batteries
Bibliographic record
Abstract
Abstract The development of rechargeable zinc–air batteries is heavily dependent on bifunctional oxygen electrocatalysts to offer exceptional oxygen reduction/evolution reaction (ORR/OER) activities. However, the design of such electrocatalysts with high activity and durability is challenging. Herein, a strategy is proposed to create an electrocatalyst comprised of copper‐cobalt diatomic sites on a highly porous nitrogen‐doped carbon matrix (Cu‐Co/NC) with abundantly accessible metal sites and optimal geometric and electronic structures. Experimental findings and theoretical calculations demonstrate that the synergistic effect of Cu‐Co dual‐metal sites with metal‐N 4 coordination induce asymmetric charge distributions with moderate adsorption/desorption behavior with oxygen intermediates. This electrocatalyst exhibits extraordinary bifunctional oxygen electrocatalytic activities in alkaline media, with a half‐wave potential of 0.92 V for ORR and a low overpotential of 335 mV at 10 mA cm −2 for OER. In addition, it demonstrates exceptional ORR activity in acidic (0.85 V) and neutral (0.74 V) media. When applied to a zinc–air battery, it achieves extraordinary operational performance and outstanding durability (510 h), ranking it as one of the most efficient bifunctional electrocatalysts reported to date. This work demonstrates the importance of geometric and electronic engineering of isolated dual‐metal sites for boosting bifunctional electrocatalytic activity in electrochemical energy devices.
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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".