Hybrid Carbon Sphere Chain–MnO<sub>2</sub> Nanorods as Bifunctional Oxygen Electrocatalysts for Rechargeable Zinc–Air Batteries
Bibliographic record
Abstract
It is now recognized that the development of self-supported and efficient bifunctional air cathodes via the direct growth of earth-abundant catalysts onto the surface of the conductive collector would be a cutting-edge strategy to reduce interfacial resistance, enhance the mechanical tenure, and reduce the final weight and cost of manufacturing of rechargeable Zn–air batteries (ZABs). This work reports an innovative self-supported precious metal-free electrode, comprising carbon sphere chains (CSCs) directly grown onto a carbon paper (CP) substrate, wherein the CSCs have a functionalized surface bearing carbon nanobud defects, oxygen functional groups, and high-density MnO 2 hierarchical nanorods (NRs), uniformly coating the surface of CSCs. Not only is the metal-free functionalized CSC catalyst functional for both the oxygen reduction reaction (ORR) and the oxygen evolution reaction (OER) but its combination with MnO 2 NRs impressively enhances the ORR/OER activities. A homemade ZAB assembled with functionalized CSC/MnO 2 air cathode can successfully power a timer for a period of 17 days with no voltage loss, whereas two series-connected ZABs can light up 39 red light-emitting diode (LED) bulbs. The self-supported and earth-abundant-based CSC/MnO 2 materials open up an opportunity for lightweight and cost-effective ZABs and metal–air batteries in general.
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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".