Development of a High Resolution Thermal Model of the Microporous Layer found in PEM Fuel Cells
Bibliographic record
Abstract
In this study, the nanoscale features of the polymer electrolyte membrane (PEM) fuel cell microporous layer (MPL) are considered in the determination of the effective thermal conductivity. A combination of scanning electron microscopy and atomic force microscopy was used to visualize SGL-10BB and SGL-10BC MPLs, and we found that the MPL typically consists of randomly positioned spherical particles with diameters ranging from 10-100 nm. We developed a unit-cell model packed with spherical particles of various diameters to represent the MPL based on our high resolution visualizations. A thermal analysis based on the Gauss-Seidel iterative method for conductive heat transfer was utilized to obtain the effective thermal conductivity of various unit-cell configurations. It was found that the nature of contact between MPL particles dominates the effective thermal conductivity, which provides valuable insight for future MPL designs. To the authors’ best knowledge, this is the first investigation of how the nanoscale features (namely particle to particle contacts) affect the bulk effective thermal conductivity of the material. This nanostructed model can also be used for future investigations, such as oxygen diffusion and electrical conductivity studies.
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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".