Stability of Prussian Blue Films for Sensing H<sub>2</sub>O<sub>2 </sub>in a PEM-fuel Cell Environment
Bibliographic record
Abstract
Developing a hydrogen peroxide (H 2 O 2 ) sensor able to measure small concentrations of H 2 O 2 in-situ is crucial to understanding the degradation mechanisms that take place in the Membrane-Electrode-Assembly of a PEM-fuel cell. Fiber optic sensing probes based on Prussian blue (PB) are promising for this application. The PB film is however required to sustain the harsh environment of PEM-fuel cells. In this work, Prussian blue films have been deposited at different synthesis temperatures, and using different precursors. The samples were immersed and left in a Phosphate-Buffer-Solution (PBS) at pH 2 at 80 °C for 21 hours and thereafter at 90 °C for 3 hours. These PB films were characterized using FTIR to analyze their stability following PBS processing at operating temperature and pH corresponding to an operating PEM-fuel cell. The PB film prepared using the single-source-precursor (SSP) at the temperature of 60 °C is found to be the most stable.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".