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Record W1975066296 · doi:10.1149/05801.0797ecst

Characterization and Performance of Catalyst Layers Prepared by Inkjet Printing Technology

2013· article· en· W1975066296 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueECS Transactions · 2013
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsMcMaster UniversityAutomotive Fuel Cell Cooperation (Canada)
FundersBasic Energy SciencesNatural Sciences and Engineering Research Council of CanadaLawrence Berkeley National LaboratoryCanadian Light SourceU.S. Department of Energy
KeywordsIonomerMaterials scienceNafionCoatingChemical engineeringCharacterization (materials science)CatalysisMembraneCathodeBar (unit)Composite materialFuel cellsInkjet printingNanotechnologyInkwellElectrodePolymerChemistryOrganic chemistryElectrochemistryEngineering

Abstract

fetched live from OpenAlex

The relationship between the structure of cathode catalyst layers (CCLs) prepared by different coating techniques and fuel cell performance was investigated. Inkjet printing technique was employed for producing CCLs directly on Nafion membranes, while Mayar bar was used to prepare conventional CCL coating that was decaled-transferred on to the membrane. Scanning transmission X-ray microscopy was used to determine the ionomer and carbon support distributions within the interior of both CCL structures. Distinctly different ionomer distributions were observed impacting Pt- utilization.

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 score0.031
Threshold uncertainty score0.230

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 head0.003
GPT teacher head0.159
Teacher spread0.156 · 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