Predicting Oxygen Transport Properties of Polymer Electrolyte Membrane Fuel Cell Gas Diffusion Layers with Local Saturation Considerations: A Pore Network Modelling Approach
Bibliographic record
Abstract
Polymer electrolyte membrane (PEM) fuel cells are a promising means of reducing anthropogenic greenhouse gas emissions. However, mass transport losses hinder the performance of PEM fuel cells, impeding their commercialization. This thesis comprises of two studies that determine the impact of liquid water within the substrate on the oxygen transport behaviour of the fuel cell. First, the impact of channel and land region saturation on the oxygen transport properties of the substrate were determined. The oxygen transport properties of the substrate were severely affected by channel region saturation, while land region saturation had a relatively minor impact. Next, the contribution of the substrate to the oxygen transport resistance of a PEM fuel cell was determined. It was determined that significant oxygen transport resistance arises from the catalyst layer (CL) or CL-microporous layer interface. This thesis offers insight into designing next-generation components for improved PEM fuel cell performance.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".