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Record W2329813891 · doi:10.1149/1.3484645

The Effect of MPL Permeability on Water Fluxes in PEM Fuel Cells: A Lumped Approach

2010· article· en· W2329813891 on OpenAlexafffund
Morteza Baghalha, Michael Eikerling, Jürgen Stumper

Bibliographic record

VenueECS Transactions · 2010
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsAutomotive Fuel Cell Cooperation (Canada)Simon Fraser University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCathodeAnodeElectrolyteMicroporous materialWater vaporProton exchange membrane fuel cellPolymerChemical engineeringChemistryGaseous diffusionDiffusionPermeability (electromagnetism)Current densityMaterials scienceMembraneAnalytical Chemistry (journal)ThermodynamicsComposite materialChromatographyFuel cellsElectrodeOrganic chemistry

Abstract

fetched live from OpenAlex

The distribution of water fluxes in an operating polymer electrolyte fuel cell (PEFC) is strongly influenced by the properties of the cathode catalyst layer (CCL) adjacent media, viz. polymer electrolyte membrane (PEM) and microporous layer (MPL). We propose a water analysis model which treats each layer as an effective homogeneous medium. The model is applied under steady state conditions, with varying humidification of the cathode feed gas (from dry to fully saturated). We distinguish contributions to water removal due to liquid and vapor transport via anode and cathode. The model warrants definition of a critical current density up to which water removal out of the CCL to the cathode side proceeds completely via vapor diffusion. Above the critical current density, excessive water generation leads to the build-up of an excess liquid pressure in the CCL, which acts as a driving force for hydraulic fluxes to PEM and MPL sides.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.063
Threshold uncertainty score0.264

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.003
GPT teacher head0.180
Teacher spread0.177 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations5
Published2010
Admission routes2
Has abstractyes

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