Optimizing Porous Transport Layer Design Parameters via Stochastic Pore Network Modelling: Reactant Transport and Interfacial Contact Considerations
Bibliographic record
Abstract
In this work, we designed sintered titanium powder-based porous transport layers (PTLs) for polymer electrolyte membrane (PEM) electrolyzers by tailoring the powder diameter and porosity via a new approach. We examined how the PTL powder diameter and porosity influence reactant transport and PTL-catalyst layer (CL) interfacial contact by using a stochastic generation model combined with a pore network model. We enhanced reactant transport by increasing powder diameter and porosity, as shown through increases in single- and two-phase permeabilities of liquid water. Compared to the impact of increasing the powder diameter, increasing the PTL porosity dominated the impact on permeability of liquid water. However, we observed a trade-off to the benefits of increasing the powder diameter such that larger powders led to a higher surface roughness at the PTL-CL interface. From this work, we recommend that the PTL powder diameter and porosity must be strategically selected for the desired target operating conditions of the PEM electrolyzer. We recommend a PTL with d P = 25 μ m and ε = 26.5% for an electrolyzer cell operating at non-starvation conditions, and a PTL with d P = 25 μ m and ε = 40.5% for an electrolyzer cell operating at starvation conditions.
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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) | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".