Active Water Management for PEM Fuel Cells
Bibliographic record
Abstract
Proton exchange membrane (PEM) fuel cells require humidified gases to maintain proper membrane humidification, but this often results in a problematic accumulation of liquid water. Typically, excessive air flow rates and serpentine channel designs are used to mitigate flooding at the cost of system efficiency. In this paper, we present an active water management system that decouples water removal from oxidant delivery. The system uses a porous carbon flow field plate as an integrated wick that can passively redistribute water within the fuel cell. The system also employs an external electro-osmotic (EO) pump that actively removes excess water from the channels and gas diffusion layer. For a fuel cell with 23 parallel air channels, we demonstrate a 60% increase in maximum power density over a standard graphite plate with a low air stoichiometry of 1.3. EO pumping represents a negligible parasitic load, consuming typically less than 0.5% of the fuel cell power. Experimental and modeling results show that simple passive water transport through the porous carbon alone can prevent flooding at certain operating conditions and flow field dimensions. However, active water management with EO pumping facilitates robust operation with a high volumetric power density across all operating conditions.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".