Stochastic Generation of Sintered Titanium Powder-Based Porous Transport Layers in Polymer Electrolyte Membrane Electrolyzers and Investigation of Structural Properties
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Bibliographic record
Abstract
The stochastic modeling of sintered titanium powder-based porous transport layers in polymer electrolyte membrane (PEM) electrolyzers using information gathered from microscale computed tomography (μ-CT) is proposed. The stochastic reconstructions were compared to the μ-CT reconstruction in terms of surface morphology and structural properties. Seeding parameter and filling radius were found to be the key parameters in this stochastic model. Parametric studies on the stochastic parameters were conducted, comparing pore and throat size distributions, mean pore and throat sizes, and numbers of pores and throats, with the μ-CT reconstruction. Increasing the seeding parameter led to increases in the number of pores and throats while decreasing mean pore and throat sizes. Increasing the filling radius led to decreases in number of pores and throats but increases in the mean pore and throat sizes. With appropriate seeding and filling parameters, the structural properties of the stochastic reconstruction closely matched the μ-CT reconstruction.
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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) | 0.000 | 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) | 0.000 | 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 it