Oxygen Reduction at PtNi Alloys in Direct Methanol Fuel Cells—Electrode Development and Characterization
Bibliographic record
Abstract
Catalyst layers made from novel catalysts must be fabricated in a way that the catalyst can function to its full potential. To characterize a PtNi alloy catalyst for use in the cathode of Direct Methanol Fuel Cells (DMFCs), the effects of the manufacturing technique, ink composition, layer composition, and catalyst loading were here studied in order to reach the maximum performance potential of the catalyst. For a more detailed understanding, beyond the DMFCs performance measurements, we look at the electrochemically active surface area of the catalyst and charge-transfer resistance, as well as the layer quality and ink properties, and relate them to the aspects stated above. As a result, we make catalyst layers with optimized parameters by ultrasonic spray coating that shows the high performance of the catalyst even when containing less Pt than commercial products. Using this approach, we can adjust the catalyst layers to the requirements of DMFCs, hydrogen fuel cells, or polymer electrolyte membrane electrolysis cells.
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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 | 0.000 | 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 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".