Electrodeposited Transition Metal Oxides As Separate Electrodes for Rechargeable Zinc-Air Batteries
Bibliographic record
Abstract
The rapid growth of renewable energy production requires an economical and efficient way to store and deliver the electricity. Electrically rechargeable Zinc-air batteries have gained revived interest among the various technologies available with their high theoretical energy density and low cost1. However, the large-scale industrial deployment of zinc-air batteries has been hampered by several problems, i.e., low round-trip energy efficiency and reduced cycling stability, both of which can be primarily attributed to the degradation of the air electrodes. Unlike conventional batteries like Li-ion, the charging and discharging processes for zinc-air batteries have different requirements for the electrodes. The discharge process is driven by the oxygen reduction reaction (ORR) and requires an air electrode that is not flooded by the electrolyte. The charging process (oxygen evolution reaction, OER), on the other hand, is more favored when the electrode is submerged in the electrolyte. In addition, the ORR active sites at the electrode can be damaged by the oxidation potential of the OER process2. Therefore, a design with physically decoupled electrodes for discharge and charge can avoid these adverse effects. This approach also allows for more flexibility to optimize ORR and OER electrocatalysts individually. In this study, ORR and OER active catalysts based on transition metal oxides are electrodeposited on different current collectors. The ORR catalyst is based on manganese oxides, while the OER catalyst is a cobalt-iron solid solution oxide. Scanning electron microscopy (SEM) reveals that both catalysts are nanostructured with high surface areas for electrochemical reactions. Electrochemical tests show that the both catalysts have comparable or even better activity than their commercial Pt-Ru catalyst counterparts. The durability of the manganese oxide catalyst is significantly enhanced by using it exclusively for ORR instead of as an ORR-OER bifunctional catalyst. The catalysts were assembled into a zinc-air battery as decoupled electrodes for discharge and charge tests. Preliminary cell testing shows that the discharge-charge efficiency was around 59% at 10 mA/cm2 current density. Both electrodes demonstrate excellent stability after 50 hours of battery testing. References 1. E. Davari and D.G. Ivey, Sustainable Energy & Fuels, in press, 29 proof pages, DOI: 10.1039/c7se00413c (2017). 2. Y. Li and J. Lu, ACS Energy Letters, 2 (6), 1370-1377 (2017).
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".