Balancing Reactant Transport and PTL-CL Contact in PEM Electrolyzers by Optimizing PTL Design Parameters via Stochastic Pore Network Modeling
Bibliographic record
Abstract
The impacts of sintered titanium powder diameter and porous transport layer (PTL) porosity on reactant transport and PTL-catalyst layer (CL) contact in the polymer electrolyte membrane (PEM) electrolyzer were studied using stochastic generation and a pore network model. Enhanced reactant transport was established with increased powder diameter and porosity, observed through increases in single- and two-phase permeabilities. Compared to increasing the powder diameter, increasing the PTL porosity dominated increases in permeabilities, especially at higher porosities ( e > 40%). However, we observed a trade-off whereby increasing the powder diameter led to increased surface roughness at the PTL-CL interface. High roughnesses were observed at porosities > 40%. In conclusion, the powder diameter and porosity must be strategically selected for the desired target operating conditions of the PEM electrolyzer.
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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 | 0.001 | 0.001 |
| 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) | 0.000 | 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 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".