Quantifying Cathode Water Transport via Anode Relative Humidity Measurements in a Polymer Electrolyte Membrane Fuel Cell
Bibliographic record
Abstract
A relative humidity (RH) measurement based on pressure drop analysis is presented as a diagnostic tool to experimentally quantify the amount of excess water on the cathode side of a polymer electrolyte membrane fuel cell (PEMFC). Ex-situ pressure drop calibration curves collected at fixed RH values, used with a set of well-defined equations for the anode pressure drop, allows for an estimate of in-situ relative humidity values. During the in-situ test, a dry anode inlet stream at increasing flow rates is used to create an evaporative gradient to drive water from the cathode to the anode. This combination of techniques thus quantitatively determines the changing net cell water flux. Knowing the cathodic water production rate, the net water flux to the anode can explain the influence of liquid and vapor transport as a function of GDL selection. Experimentally obtained quantified values for the water removal rate for a variety of cathode gas diffusion layer (GDL) setups are presented, which were chosen to experimentally vary a range of water management abilities, from high to low performance. The results show that more water is transported to the anode when a GDL with poor water management capabilities is used, due to the higher levels of initial saturation occurring on the cathode. At sufficiently high concentration gradients, the anode removes more water than is produced by the reaction, allowing for the quantification of excess water saturating the cathode. The protocol is broadly accessible and applicable as a quantitative diagnostic tool of water management in PEMFCs.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| 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".