Accurate Ex-situ Measurements of PEM Fuel Cells Catalyst Layer Dry Diffusivity
Bibliographic record
Abstract
Polymer electrolyte membrane fuel cells (PEMFC) efficiently convert the reaction energy of hydrogen and oxygen to electricity, water and heat. The oxygen reduction reaction occurs in composite nanostructured catalyst layers (CL) formed from Pt nanoparticles supported on a network of carbon particle agglomerates. Oxygen reaches the reaction site through diffusion. Understanding the diffusion properties of CL is vital to proper design and operation of CL and PEMFC. Measuring the diffusivity of thin porous layers is challenging, as is selecting a suitable substrate and appropriate CL coating procedures. In this work, CL is coated on 70 μm thick hydrophobic porous polymer substrates with a Mayer bar coater. Several samples are prepared and their thickness are measured accurately. The diffusivity of the CL and the substrate are measured using a dry diffusivity test bed and the resulting CL-diffusivity values are determined for different Pt loadings.
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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) | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".