A Comparative Study of the Oxygen Reduction Reaction on Pt and Ag in Alkaline Media
Bibliographic record
Abstract
Abstract Investigating the ORR under practical conditions is vital for optimizing metal–air batteries and alkaline fuel cells. Herein, we characterized Pt and Ag gas diffusion electrodes (GDE) in a GDE half‐cell in high alkaline concentrations at elevated temperatures by polarization curves and electrochemical impedance spectroscopy (EIS) combined with the distribution of relaxation times (DRT) analysis. The Pt catalyst's polarization curve displays substantial losses below 0.82 V vs. RHE. The DRT analysis reveals significantly increased charge transfer resistance and a decelerated ORR at that potential. RRDE measurements attributed the polarization loss observed for Pt catalysts to increased peroxide formation in this potential region triggered by the desorption of oxygenated species. Therefore, the ORR activity of Ag exceeds some of the here‐used Pt catalysts at high current densities. This work combines the benefits of the RRDE and the GDE half‐cell to study catalysts and identify the reaction mechanisms under conditions relevant to practical fuel cells and batteries. Moreover, the DRT analysis is introduced as an analytical tool to determine the charge transfer resistance contribution and the corresponding frequency of the ORR.
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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".