Atomic Layer Deposition of ORR Catalysts for Rechargeable Zinc-Air Batteries
Bibliographic record
Abstract
The move towards cleaner and renewal energy production, such as solar and wind power, necessitates the development of efficient, safe and cost effective energy storage methods. Zinc-air batteries (ZABs) are prime candidates to meet these requirements and store large amounts of electricity. They use oxygen in the atmosphere as the cathode reactant in the discharge process. Oxygen diffuses into the cell and is reduced to hydroxyl ions in the presence of a catalyst at the air electrode (oxygen reduction reaction or ORR). At the same time, the zinc electrode is oxidized and dissolves in the electrolyte, producing zincate ions. During recharging, zinc metal is reduced from zincate ions and plated at the zinc electrode. Oxygen evolution (OER) occurs at the air electrode. There are challenges in implementing zinc-air batteries for large scale energy storage. The ORR and OER processes at the air electrode are sluggish and electrode stability can be poor because of catalyst delamination and/or substrate corrosion during battery cycling. Effective electrodes for ZABs require a catalyst that is efficient, stable and electrochemically active. Atomic layer deposition (ALD) is a gas phase deposition technique capable of fabricating thin films from a wide variety of materials. ALD utilizes alternating pulses of reactants that each undergo self-limiting reactions on the sample surface, producing uniform and conformal films, with good composition control and sub-nanometer thickness control. These features of ALD are particularly attractive for fabricating ORR catalysts in zinc-air battery electrodes, as they can lead to increased surface areas and three-phase boundary areas, both of which should lead to better performance and cyclability. In this study, ALD is used to produce air electrodes with Mn oxide as the ORR catalyst. The process is optimized and deposits are characterized using microstructural characterization (e.g., electron microscopy, X-ray diffraction, surface science techniques and Raman spectroscopy) and electrochemical characterization (e.g., linear sweep voltammetry, electrochemical impedance spectroscopy and galvanostatic cycling) methods. Successful materials are tested in two different battery configurations, i.e., a two electrode set-up and a three-electrode set-up where the ORR and OER reactions are decoupled. The three-electrode configuration limits the potential window to which each electrode is subjected, greatly improving stability and cyclability.
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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".