Stochastic Modelling For Controlling the Structure of Sintered Titanium Powder-Based Porous Transport Layers for Polymer Electrolyte Membrane Electrolyzers
Bibliographic record
Abstract
A stochastic modelling technique for simulating sintered titanium powder-based porous transport layers (PTLs) of the polymer electrolyte membrane (PEM) electrolyzer was developed and used to generate PTLs with varying structures and transport properties. Two stochastic parameters (seeding parameter and the filling radius) were introduced in the model to control the powder-based PTL structure. The seeding parameter was used to control the titanium particle packing density, whereby increasing the packing density led to smaller the mean pore and throat diameters. The filling radius was used to create and control the sinter neck and grain morphology. Larger filling radii resulted in larger mean pore and throat sizes. PTLs with larger pores and throats exhibited higher single-phase permeabilities. A representative PTL was numerically generated with a single-phase permeability that deviated from the commercial benchmark by only 2%. Specifically, this work can be used to inform state-of-the-art manufacturing procedures so that the spatial distribution of the particles and their sinter necks can be tailored to achieve prescribed transport properties for enhanced PEM electrolyzer performance.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".