Investigation of Select Pure Earth Metals as Redox Catalytic Electrodes in Single Compartment Hydrogen Peroxide Fuel Cells
Bibliographic record
Abstract
Hydrogen peroxide is a promising alternative to hydrogen gas for fuel cells, as it can act as the oxidizing and reducing agent and be stored in a stable liquid form, it simplifies the structure of the fuel cell. This study aims to investigate the use of antimony, bismuth, indium, tantalum, silver, dysprosium, erbium, gadolinium, holmium, and terbium as electrodes for the first time in a single-compartment hydrogen peroxide fuel cell. In this study, the procedure for custom electrodes for these metals is documented. The performance of the electrodes was evaluated by measuring the open circuit potential, comparing the cyclic voltammograms and observing the physical reactions of the cell combinations. The results of the study show the catalytic reaction is likely due to the formation of molecular oxide layers on the electrode surface. It was evident that an acidic peroxide electrolyte favors the best catalytic reaction. Tantalum and antimony were found to be the best-performing electrodes in this electrolyte, providing the best stability and performance.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".