Hollow Schottky Heterostructures for Highly Efficient Bifunctional Oxygen Electrocatalysis in Zinc-Air Batteries
Bibliographic record
Abstract
With advantages such as high theoretical energy density and eco-friendly operation, rechargeable zinc-air batteries (RZABs) have gained considerable interest as viable systems for future sustainable energy storage. Nevertheless, achieving high efficiency and long-term stability in bifunctional electrocatalysts that can simultaneously drive the oxygen reduction and evolution reactions remains a significant obstacle. In this work, we report the rationally designed hollow FeCo/CoFe 2 O 4 heterostructure (H–FeCo/FeCoO) as a high-performance bifunctional electrocatalyst for RZABs, in which the interconnected hollow architectures and well-defined Schottky interfaces are built via a polystyrene sphere-assisted strategy. The obtained H–FeCo/FeCoO bifunctional catalysts exhibit high activities for both ORR and OER, with a narrow voltage gap (Δ E ) of 660 mV, outperforming that of the Pt/C + RuO 2 benchmark. The as-assembled RZAB delivers a remarkable power density of 310 mW cm –2, and demonstrates excellent operational stability exceeding 500 h. Based on the DFT calculations, the rate-determining steps in ORR/OER processes and valence electron distributions in H–FeCo/FeCoO have been demonstrated, unveiling the origins of boosted catalytic activity and accelerated oxygen delivery. Current work presents a compelling design strategy for exploring advanced bifunctional catalysts with improved mass transport and electrochemical activity/durability for next-generation energy storage devices.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".