Atomic Layer Deposition‐Modified Bifunctional Electrocatalysts for Rechargeable Zinc‐Air Batteries: Boosting Activity and Cycle Life
Bibliographic record
Abstract
Abstract The integration of transition metal‐carbon composites has shown remarkable potential in achieving superior bifunctional electrocatalytic activity and robust stability in rechargeable zinc‐air batteries (ZABs), primarily through electronic structure modulation and strategic structural design. While significant research is dedicated to the initial structure and performance of bifunctional electrocatalysts for rechargeable ZABs, their dynamic evolution during charge–discharge cycling remains underexplored. In this study, CoFe nanoparticles are encapsulated within carbon nanotubes co‐doped with nitrogen and phosphorus (NPC) to mitigate dissolution and erosion risks. Further, the catalyst surface (CoFe‐NPC) is precisely modified with a thin layer of nickel oxide (NiO) via atomic layer deposition (ALD), forming a protective layer with catalytic activity. The resulting ALD‐modified catalyst, CoFe‐NPC@NiO, exhibits outstanding bifunctional performance (Δ E = 0.592 V) for the oxygen reduction reaction (ORR) and oxygen evolution reaction (OER). Notably, the liquid flow ZAB using the CoFe‐NPC@NiO cathode demonstrates exceptional rechargeable stability (2700 h, ≈4 months). Theoretical calculations and in situ X‐ray absorption spectroscopy (XAS) analyses reveal that NiO modification significantly enhances both the catalytic activity and stability of the electrocatalyst. This work will provide valuable insights into the design of advanced electrocatalysts, facilitating advancements in activity enhancement, stability improvement, and selectivity optimization.
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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 | 0.000 | 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) | 0.000 | 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 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".