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Record W2324171142 · doi:10.1149/1.3502361

Fabrication of Hydrophobic Coating on GDL with Silicone Based Materials

2010· article· en· W2324171142 on OpenAlexafffund
Yongxin Wang, Saher Al Shakhshir, Xianguo Li

Bibliographic record

VenueECS Transactions · 2010
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsUniversity of Waterloo
FundersAUTO21 Network of Centres of ExcellenceNatural Sciences and Engineering Research Council of Canada
KeywordsPolydimethylsiloxaneMaterials scienceContact angleCoatingComposite materialPolymerElectrolyteFabricationSurface energySiliconeProton exchange membrane fuel cellSuperhydrophobic coatingLayer (electronics)Chemical engineeringFuel cellsChemistryElectrode

Abstract

fetched live from OpenAlex

In this study, a hydrophobic coating is fabricated on gas distribution layer (GDL) with silica particle/polydimethylsiloxane (PDMS). For the coated GDL surface, the measured water contact angle is about 162° and sliding angle about 5°. The pore size of the coated GDL is about 7.1 μm, and shows low energy resistance to the gas transport. Performance tests of the polymer electrolyte membrane fuel cells (PEMFCs) indicate that PEMFCs made of such GDLs offer the better performance than conventional PEMFCs.

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 score0.081
Threshold uncertainty score0.961

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)0.0010.000

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 head0.005
GPT teacher head0.180
Teacher spread0.175 · 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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