Liquid Water Scavenging of PEMFC Contaminants
Bibliographic record
Abstract
Models were derived for the scavenging effect of product liquid water on airborne proton exchange membrane fuel cell (PEMFC) contaminants. A time scale analysis of contaminant mass transfer processes, product water accumulation in the gas diffusion electrode, and dissociation reactions indicated that the contaminant saturates the product liquid water simplifying model derivation. The baseline model only accounts for contaminant solubility. A multi-scale extension to this model was derived for the presence of contaminant dissociation reactions within the product liquid water using SO 2 as a model contaminant. The extended model demonstrates the large impact of dissociation reactions at low SO 2 concentrations. For both models, explicit expressions for the average gas phase contaminant concentration within the fuel cell were also derived and can be used as a surrogate for the effective contaminant concentration to correlate the fuel cell performance loss and facilitate the definition of tolerance limits and filtering equipment. The model was validated using a non-operating PEMFC. The water was transferred from the anode to the cathode by thermo-osmosis. Model contaminants, methanol and SO 2 , were injected with an inert carrier gas to avoid reactions. The model proved to be acceptable with parameters approximately equal to published values.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".