Ex-situ Measurement of Properties of Gas Diffusion Layers of PEM Fuel Cells
Bibliographic record
Abstract
The gas diffusion layer (GDL) of the proton exchange membrane (PEM) fuel cell is a vital component in water management since humidification and water removal are both achieved through the GDL. Capillary action in the GDL porous structure enhances water removal from the cathode catalyst layer, and hence prevents flooding which blocks the pathways of the reactants to the activation sites. To improve the transport of water and reactants, GDL properties are varied by changing the geometry and the PTFE loading of the carbon fiber paper (CFP), both changing the internal wettability of the GDL. In essence, the wettability describes the interaction of water with the porous structures inside the GDL. The knowledge of the surface properties and pore structure is important to enhance water management in the cell. In this work, two ex-situ techniques are used to measure transport characteristics of GDLs, such as the internal wettability, pore size distribution and permeability. These measurements have been applied to different types of GDLs with different structures and PTFE loadings. The comparison between the results will determine the effect of material and treatment on the properties of GDLs which can provide basic insight into the two-phase flow in this porous layer.
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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 | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".