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Record W2105868312 · doi:10.1149/1.2982019

Surfactant Assisted Catalyst Layer Deposition for PEM Fuel Cells

2008· article· en· W2105868312 on OpenAlexafffund
Alexander Bauer, David P. Wilkinson, Előd Gyenge, Dan Bizzotto, Siyu Ye

Bibliographic record

VenueECS Transactions · 2008
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaBallard Power Systems
KeywordsRotating disk electrodeMaterials sciencePlatinumChemical engineeringCatalysisCurrent densityPulmonary surfactantDeposition (geology)Layer (electronics)Mesoporous materialElectrodeWaferNanometreParticle sizeAnalytical Chemistry (journal)ElectrochemistryNanotechnologyChemistryCyclic voltammetryComposite materialChromatographyPhysical chemistry

Abstract

fetched live from OpenAlex

The potentiostatic electrodeposition of platinum onto gold coated Si wafers and a gold rotating disk electrode (RDE) was carried out with non-ionic surfactants that functioned as templating agents to obtain mesoporous deposits with size features in the nanometer range. The particle size and morphology were studied by surface analysis (SEM and AFM). The electrochemically active surface area of Pt electrodeposited onto the RDE by using a mixture of Brij 56 and n-heptane was increased by a factor of ~2 compared to Pt deposited without structure directing additives. Corresponding oxygen reduction tests at 2500 rpm revealed an improvement of about 14 % (from 5.9 to 7.2 x 10-4 A cm-2) for the cathodic current density at 0.9 V vs. RHE while the mass transfer limited current density was increased by ~25 % from 4.4 to 5.5 x 10-3 A cm-2.

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 score0.347
Threshold uncertainty score0.895

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 studies0.0010.000
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 head0.021
GPT teacher head0.226
Teacher spread0.205 · 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

Citations0
Published2008
Admission routes2
Has abstractyes

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