A Mixed Wettability Pore Size Distribution Based Mathematical Model for Analyzing Two-Phase Flow in Porous Electrodes
Bibliographic record
Abstract
The non-isothermal, two-phase membrane electrodes assembly numerical model previously developed in Part I [ J. Electrochem. Soc. , 164 , 6, F530 (2017)] is validated by comparing to experimentally measured electrochemical performance data under various operating conditions. Water accumulation in catalyst layer (CL) and gas diffusion layer (GDL) are also compared to the neutron and X-ray imaging data and shown to be in agreement. Water fluxes at cathode and anode boundaries and phase change induced flow are analyzed and compared to experimental data. Simulation results indicate that when liquid water is present, reactant transport in the catalyst layer is the key factor limiting fuel cell performance. The model shows that at high relative humidity, 80°C is the optimal operating temperature in order to delay water accumulation without degrading performance due to oxygen dilution by water vapor. The impact of CL and GDL hydrophilic volume fraction, hydrophobic contact angle and pore size distribution on performance are also studied. Results suggest that when liquid water is present, GDL parameters have minimal effect on performance and a CL should have a large hydrophobic contact angle, a low hydrophilic volume fraction, and large pore radius.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".