High Performance Oxygen Reduction/Evolution Electrodes for Zinc–Air Batteries Prepared by Atomic Layer Deposition of MnO<sub><i>x</i></sub>
Bibliographic record
Abstract
Oxygen reduction electrodes for zinc–air batteries (ZAB) have been prepared by depositing conformal films of MnO x directly onto high surface area gas diffusion layers (GDL) via atomic layer deposition (ALD). MnO x films were prepared by means of two deposition conditions: one using a forming gas (95% N 2, 5% H 2 ) plasma (FG-MnO x ) and one using an O 2 plasma (O 2 -MnO x ). A composite electrode of FG-MnO x + CoO x was also examined. The conformal nature of ALD films allowed for MnO x to be deposited within the porosity of the GDL, as confirmed by X-ray microanalysis. Full cell ZAB tests showed excellent performance for MnO x -coated electrodes, outperforming Pt/Ru–C at current densities larger than 100 mA cm –2 . Annealed FG-MnO x and O 2 -MnO x electrodes had maximum power densities of 170 and 184 mW cm –2, respectively. With the catalyst distributed within the structure of the GDL, performance limitations associated with electrolyte flooding and air diffusion are reduced, improving discharge potential and cycling behavior. FG-MnO x + CoO x electrodes showed good cycling stability, both in a trielectrode configuration and bifunctionally. When cycled at 20 mA cm –2 for 100 h (200 cycles), FG-MnO x + CoO x had initial and final discharge potentials of 1.18 and 1.15 V, respectively.
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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 | 0.001 | 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".