A Mixed Wettability Pore Size Distribution Based Mathematical Model for Analyzing Two-Phase Flow in Porous Electrodes
Bibliographic record
Abstract
A multi-dimensional, non-isothermal, two-phase membrane electrode assembly (MEA) numerical model is developed where the micro-structure of the porous layers is characterized by a mixed wettability pore size distribution (PSD). The PSD model is used to predict local water saturation based on gas and liquid pressures, and can be used to study the effect of varying pore size and wettability. The MEA model accounts for gas transport via molecular and Knudsen diffusion, liquid water transport, sorbed water transport by back-diffusion, electro- and thermo-osmosis, and heat generation and transport. Multi-step kinetic models are used to predict anode and cathode electrochemical reactions. Local transport losses are accounted for using a local transport resistance. The PSD model is used to predict capillary pressure vs. saturation and saturation vs. relative liquid permeability curves based on PSDs from several GDLs obtained using mercury intrusion porosimetry. The PSD-based MEA model electrochemical performance predictions are also compared to experimental data from the literature. Results show that the numerical model is able to capture the performance changes associated with varying temperate and the introduction of a micro-porous layer.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".