Investigating the Water Transport in Porous Media for PEMFCs by Liquid Water Visualization in ESEM
Bibliographic record
Abstract
Abstract A novel ex situ method of investigating the water transport in porous media for PEM fuel cells with an environmental scanning electron microscope (ESEM) is introduced. By applying two different experimental methods, a liquid water pressure gradient is created which is necessary for the liquid water transport in porous media. The first method relies on water condensation on the bottom surface of the GDL to introduce a liquid phase into the porous media. The second method applies an external pressure gradient. The relevance of the methods is shown by visualizing the water formation and transport in different GDL materials with the high spatial resolution of an ESEM. In all experiments, the fingering effect, proposed by other researchers could be confirmed. However, the water formation on the surface of the GDLs is not consistent with the common idea of water formation in GDLs. The methods were also used to investigate the advantageous effect of laser perforating GDLs on fuel cell performance. The water transport visualization near a hole of a laser perforated GDL supports the assumptions of lower liquid water saturation in the GDL (due to effective water transport in the channels), and larger in‐plane water transport towards the perforations.
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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 | 0.001 |
| 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".