Electrochemical Characterization of IrO 2 -Pt and RuO 2 -Pt Mixtures as Bifunctional Electrodes for Unitized Regenerative Fuel Cells
Bibliographic record
Abstract
Unitized Regenerative fuel Cell (URFC) is an attractive and efficient method for producing hydrogen and clean energy. Nevertheless, to combine a polymer electrolyte water electrolyzer (PEMWE) and a polymer electrolyte fuel cell (PEMFC) is still a big challenge. Here, it is necessary to overcome several practical and structural features. For instance, the oxygen reduction (ORR) and the water oxidation (OER) are the limiting reaction steps at the oxygen electrode for PEMFC or PEMWE, respectively. Therefore, its high-efficiency depends on the type of electrocatalysts and the capability of the oxygen electrode to operate under the PEMFC or PEMWE conditions. As a consequence, a broad research is focused on developing a new design for the oxygen electrode in URFCs. In this work, several bifunctional electrodes for OER and ORR were designed by mixing electrocatalysts of Pt and IrO2 or Pt and RuO2 supported on Ebonex®. Elec- trochemical characterization by CV, LV and EIS in aqueous 0.5 M H2SO4 reveals that IrO2-Pt and RuO2-Pt supported on Ebonex®, exhibit high electrocatalytic properties for ORR and OER showing up a possible use in URFCs. In addition, IrO2 based electrodes display a higher stability than those based on RuO2.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".