Crack-Engineered Microporous Layer for Mitigating Cathode Flooding in Polymer Electrolyte Fuel Cells
Bibliographic record
Abstract
Crack engineering within the microporous layer (MPL) of the gas diffusion layer (GDL) has emerged as a promising strategy to alleviate severe cathode flooding in polymer electrolyte fuel cells (PEFCs), especially under high current operation. Here, we report a connected-crack MPL architecture that forms continuous liquid water highways, extending from the catalyst layer (CL) to the GDL backing layer, effectively separating the liquid/gas transport. Three-dimensional reconstruction using X-ray computed tomography reveals that the microengineered cracks significantly reduce flooding at the CL-MPL interface by providing efficient drainage. Compared to the noncrack GDL, the connected-crack GDL (C-GDL) exhibits 20% higher peak power density of 1.23 W cm –2 . Pore-scale simulations further validate the antiflooding capabilities of C-GDL, showing a 25-fold enhancement in water removal. This crack-engineered GDL thus offers an efficient and scalable route to water management challenges, enabling robust and high-performance PEFCs suitable for heavy-duty vehicle electrification.
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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 | 0.000 |
| 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) | 0.001 | 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".