MnO2 Nanotubes Synthesized with One-step Hydrothermal Method as Efficient Bi-functional Cathode Catalyst for a Rechargeable Zinc-air Battery
Bibliographic record
Abstract
This paper reports the preparation and electro-catalytic activity of MnO 2 nanotube catalysts for both oxygen reduction reaction (ORR) and oxygen evolution reduction (OER) in alkaline media.The catalysts were synthesized by a simple hydrothermal method under controlling the different temperatures.Results of electrochemical characterization with emphasis on the activity of the catalyst are presented, which was demonstrated by cyclic voltammetry (CV) and linear sweep voltammetry (LSV) employing a rotating disk electrode (RDE) technique.The experiments show that the as-prepared MnO 2 catalyst with nanotube structure exhibited high electro-catalytic activity and stability during battery discharge, charge and cycling processes in 6 M KOH electrolyte.The primary Zn-air battery showed a discharge peak power density ~293 mW cm -2 , which corresponds to the energy density ~725 mA hg -1 .The rechargeable Zn-air battery exhibited a small charge-discharge voltage polarization of ~0.7 V at 10 mA cm -2 , high reversibility and stability over short charge and discharge cycles, and ~1.1 V for a long charge and discharge cycles test.
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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) | 0.000 | 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 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".