Zinc Anode Self-Corrosion in Aqueous Sulphate Electrolytes: A Respirometric Study
Bibliographic record
Abstract
Rechargeable Zn-ion batteries are targeted for non-portable applications, such as grid-scale energy storage, and provide several advantages over the Li-ion batteries currently used for these applications, including safety due to the aqueous electrolytes employed, while relying on Zn that is inexpensive, non-toxic and mined/produced within Canada. Parasitic corrosion reactions (self-corrosion) of the negative Zn electrode (anode during discharge) are problematic since they limit cycle life and produce hydrogen gas (pre-mature pressure-induced failure). The objective of this study was to determine the extent to which parasitic self-corrosion reactions of the negative Zn electrode occur during cycling under both aerated and deaerated conditions This was achieved using a custom-built, in-situ respiratory technique to measure relative changes in hydrogen and oxygen gas composition during corrosion of Zn during bulk immersion in Na2SO4 (aq) and ZnSO4 (aq) under open-circuit and charge/discharge cycling conditions. X-ray photoelectron spectroscopy (XPS) was used to characterize the structure and composition of the surface films formed. The results are discussed within the context of how cathode reactions are affected by surface film formation.
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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".