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Record W1567063734 · doi:10.1149/1.1952627

Transport Phenomena in Polymer Electrolyte Membranes

2005· article· en· W1567063734 on OpenAlexafffund
J. Fimrite, Henning Struchtrup, Ned Djilali

Bibliographic record

VenueJournal of The Electrochemical Society · 2005
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of CanadaMitacs
KeywordsMembraneElectrolyteThermodynamicsTransport phenomenaConductivitySorptionMaterials sciencePolymerChemistryPhysicsElectrodePhysical chemistryAdsorptionComposite material

Abstract

fetched live from OpenAlex

This paper presents a critical examination and analysis of classical and recently proposed models for transport phenomena in polymer electrolyte membranes. Key experimental observations related to membrane conductivity, membrane hydration, and sorption isotherms are first reviewed. Proton transport mechanisms in bulk water, and the influence of the membrane phase on these mechanisms, are examined. Finally, various formulations and underlying assumptions to account for macroscopic transport are reviewed, and an analysis of the binary friction model (BFM) and dusty fluid model (DFM) is performed to resolve an outstanding formulation issue. It is shown that the BFM provides a physically consistent modeling framework and implicitly accounts for viscous transport (i.e., Schloegl equation), whereas the dusty fluid model erroneously accounts twice for viscous transport. In Part II we apply the BFM framework to develop a general transport model for perfluorosulfonic acid membranes.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.003
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.177
Teacher spread0.174 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations102
Published2005
Admission routes2
Has abstractyes

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