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Record W2326836150 · doi:10.1149/1.3210673

Identification of Dominant Transport Mechanisms in PEMFC Cathode Catalyst Layers Operated under Low RH

2009· article· en· W2326836150 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueECS Transactions · 2009
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsLimiting currentProton exchange membrane fuel cellCurrent densityCatalysisCathodeDiffusionOxygen transportDissolutionCurrent (fluid)Analytical Chemistry (journal)OxygenMass transportChemistryMaterials scienceChemical engineeringElectrodeElectrical engineeringThermodynamicsChromatographyElectrochemistryPhysical chemistryEngineering physicsOrganic chemistry

Abstract

fetched live from OpenAlex

Mass transport phenomena under reduced RH were studied in H2/O2, air and heliox. IR corrected limiting current density and EIS were employed to identify the predominant transport mechanism at various RHs and current densities. It was found that the limiting current density decreased with increasing RH in H2/O2 fuel cell; EIS reveals that the low frequency arcs expand with increasing current density, but contract with increasing RH. The hydration-related low frequency arcs were hidden by gas phase diffusion arcs when operated under air or heliox. It was speculated that low frequency arcs are related to the dissolution and diffusion of reactant in the ionomer thin film. Under low RH operation, oxygen transport in the ionomer thin film within catalyst layer may become an important factor in cell voltage loss.

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.

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 score0.376
Threshold uncertainty score0.479

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 head0.006
GPT teacher head0.205
Teacher spread0.199 · 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