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Record W2056041210 · doi:10.1002/fuce.201400118

Humidity and Temperature Cycling Effects on Cracks and Delaminations in PEMFCs

2015· article· en· W2056041210 on OpenAlexafffund
Roshanak Banan, Jean W. Zu, Aimy Bazylak

Bibliographic record

VenueFuel Cells · 2015
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsUniversity of Toronto
FundersOntario Ministry of Research and InnovationNatural Sciences and Engineering Research Council of CanadaUniversitat de Girona
KeywordsMaterials scienceAnodeComposite materialCathodeRelative humidityDelamination (geology)Proton exchange membrane fuel cellHumidityMembraneElectrodeElectrical engineeringChemistryMeteorology

Abstract

fetched live from OpenAlex

Abstract Temperature and relative humidity (hygrothermal) cycles during PEM fuel cell operation can lead to the introduction and exacerbation of micro‐scale mechanical defects. We developed a two‐dimensional finite element model based on cohesive zone theory to describe the delamination propagation at the cathodic membrane/catalyst layer interface due to temperature and hygrothermal duty cycles. Particularly, the effects of hygrothermal cycle amplitudes, relative humidity (RH) distribution profiles, and gas flow channel position were studied. It was found that doubling the hygrothermal cycle amplitude resulted in a 6‐fold increase in fatigue stresses, and a defect length growth to 0,1 mm before reaching the end of the fuel cell life (40,000 cycles). A counter intuitive result was also observed, whereby a crack located within the membrane was found to grow faster than a delamination located at the catalyst layer/membrane interface. When introducing an anode/cathode channel offset, a 2‐fold increase in the rate of delamination propagation was found compared to the case with the aligned anode and cathode channels.

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)0.000
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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.007
GPT teacher head0.195
Teacher spread0.188 · 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

Citations53
Published2015
Admission routes2
Has abstractyes

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