MétaCan
Menu
Back to cohort
Record W2903727223 · doi:10.1002/elan.201800553

The Effect of Cracks on the In‐plane Electrical Conductivity of PEFC Catalyst Layers

2018· article· en· W2903727223 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

VenueElectroanalysis · 2018
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsAutomotive Fuel Cell Cooperation (Canada)Alpha Technologies (Canada)University of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceConductivityCrackingCatalysisElectrodeComposite materialMembrane electrode assemblyPlane (geometry)PlatinumLayer (electronics)Electrical resistivity and conductivityCarbon fibersIonomerThermal conductivityFuel cellsChemical engineeringChemistryPolymerElectrolyteElectrical engineering

Abstract

fetched live from OpenAlex

Abstract Fuel cell catalyst layers are a mixture of carbon, ionomer and platinum that are usually applied to the membrane during electrode assembly and can vary in structure for a number of reasons including the method of application, thickness of the layer, milling and heat treatments. Under some conditions significant cracking can occur which may or may not be beneficial to overall fuel cell performance but certainly has an effect on the catalyst's effective transport properties. The influence of cracking on the in‐plane electrical conductivity is studied experimentally and numerically through an image‐based approach. The conductivity is found to depend strongly on the crack structure which can be predicted with image based modelling. This fact is useful for determining the bulk conductivity from cracked samples for diagnostic purposes.

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)0.001
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 score0.012
Threshold uncertainty score0.258

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.004
GPT teacher head0.201
Teacher spread0.197 · 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