ZIFs‐Derived Hollow Nanostructures via a Strong/Weak Coetching Strategy for Long‐Life Rechargeable Zn–Air Batteries
Bibliographic record
Abstract
Abstract Recently, zeolitic imidazolate frameworks (ZIFs) composites have emerged as promising precursors for synthesizing hollow‐structured N‐doped carbon‐based noble‐metal materials with diverse structures and compositions. Here, a strong/weak competitive coordination strategy is presented for synthesizing high‐performance electrocatalysts with hollow features. During the competitive coordination process, the cubic zeolitic‐imidazole framework‐8 (Cube‐8)@ZIF‐67 with core–shell structures are transformed into Cube‐8@ZIF‐67@PF/POM with yolk–shell nanostructures employing phosphomolybdic acid (POM) and potassium ferricyanide (PF) as the strong chelator and the weak chelator, respectively. After calcination, the hollow Mo/Fe/Co@NC catalyst exhibits superior performance in both oxygen evolution reaction (OER) and oxygen reduction reaction (ORR). Interestingly, the Mo/Fe/Co@NC catalyst exhibits efficient electrocatalytic performance for Zn–air batteries (ZABs), with a high power density (≈150 mW cm −2 ) and superior cycling life (≈500 h) compared to commercial platinum/carbon (Pt/C) and ruthenium dioxide (RuO 2 ) mixture benchmarks catalysts. In addition, the density functional theory further proves that after the introduction of Mo and Fe atoms, the adsorption energy with the adsorption intermediates is weakened by adjusting the d ‐band center, thus weakening the reaction barrier and promoting the reaction kinetics of OER. Undoubtedly, this study presents novel insights into the fabrication of ZIFs‐derived hollow structure bifunctional oxygen electrocatalysts for clean‐energy diverse 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".