Effect of Compression on the Effective Thermal Conductivity and Thermal Contact Resistance in PEM Fuel Cell Gas Diffusion Layers
Bibliographic record
Abstract
Heat transfer through the gas diffusion layer (GDL) of a PEM fuel cell is a key process in the design and operation a PEM fuel cell. The analysis of this process requires determination of the effective thermal conductivity as well as the thermal contact resistance between the GDL and adjacent surfaces/layers. In the present study, a guarded-hot-plate apparatus has been designed and built to measure the effective thermal conductivity and thermal contact resistance in GDLs under vacuum and atmospheric pressure. Toray carbon papers with the porosity of 78% and different thicknesses are used in the experiments under a wide range of compressive loads. Moreover, novel analytical models are developed for the effective thermal conductivity and thermal contact resistance and compared against the present experimental data. Results show good agreements between the experimental data and the analytical models. It is observed that the thermal contact resistance is the dominant component of the total thermal resistance and neglecting this phenomenon may result in enormous errors.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".