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Record W2075768537 · doi:10.1115/fuelcell2012-91454

The Impact of an MPL on Water Management of an Operating PEMFC Using Synchrotron X-Ray Radiography

2012· article· en· W2075768537 on OpenAlexaff
Jongmin Lee, James Hinebaugh, Aimy Bazylak

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsProton exchange membrane fuel cellSynchrotronMaterials scienceElectrolyteStoichiometryPorosityCurrent densityDiffusionFuel cellsPolymerX-rayAnalytical Chemistry (journal)Chemical engineeringNuclear engineeringComposite materialChemistryOpticsChromatographyPhysicsEngineeringElectrode

Abstract

fetched live from OpenAlex

High quality through-plane images of an operating polymer electrolyte membrane fuel cell (PEMFC) were visualized by employing synchrotron X-ray radiography to quantify liquid water in gas diffusion layers (GDL). Two types of GDLs, Toray carbon paper with and without micro-porous layers (MPLs), were employed and imaged during the operation. Performance data and x-ray images of these GDLs are compared to determine the impact of an MPL on water management. At low current density (<0.4A/cm2) under high stoichiometric ratio, the MPL has little overall effect, but may behave as a diffusion barrier for reactants. At higher current density (0.6A/cm2) and under low stoichiometric ratios, the MPL is observed to significantly affect the water management of the PEMFC and is credited for increased cell performance.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.010
GPT teacher head0.247
Teacher spread0.237 · 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 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

Citations2
Published2012
Admission routes1
Has abstractyes

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