Increasing the Electrolyte Capacity of Alkaline Zn–Air Fuel Cells by Scavenging Zincate with Ca(OH)<sub>2</sub>
Bibliographic record
Abstract
Abstract The use of calcium hydroxide for scavenging zincate species is demonstrated to be a highly effective approach for increasing the electrolyte capacity and improving the performance of the zinc–air fuel cell system. A fundamental approach is established in this study to quantify the formation of calcium zincate as the product of scavenging and the amount of water compensation necessary for optimal performance. The good agreement between predicted and experimental results proves the validity of the proposed theoretical approach. By applying the results of theoretical predictions, both the electrolyte capacity and the cell longevity have been increased by more than 40 %. It is also found that, using Ca(OH)2 to scavenge zincate species in concentrated KOH solutions, affects mostly the removal of zincate, rather than ZnO, from the electrolyte, whereas the presence of excess, free, mobile H2O plays a key role in dissolving ZnO and forming zincate. The results obtained in this study demonstrate that the proposed approach can widely and effectively be applied to all zinc–air cell systems during their discharge cycle.
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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".