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Record W2081586698 · doi:10.1149/05801.0315ecst

Investigation of Water Transport in Perforated Gas Diffusion Layer by Neutron Radiography

2013· article· en· W2081586698 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.

Bibliographic record

VenueECS Transactions · 2013
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsFord Motor Company (Canada)
FundersNational Institute of Standards and TechnologyU.S. Department of Energy
KeywordsNeutron imagingWater transportMaterials scienceGaseous diffusionProton exchange membrane fuel cellPerforationDiffusionMembrane electrode assemblyLiquid waterPorosityLayer (electronics)ElectrodeFuel cellsBubbleMembraneComposite materialChemical engineeringNeutronChemistryWater flowEnvironmental scienceEnvironmental engineeringMechanicsGeologyNuclear physics

Abstract

fetched live from OpenAlex

The influence of gas diffusion layer (GDL) modifications by laser perforation technique on fuel cell water management is investigated in this study. The liquid water distribution in membrane-electrode-assembly (MEA) and water breakthrough in GDL are visualized using high resolution neutron radiography. The perforated GDL reduces water transport resistance, enhances water breakthrough in GDL, and promotes uniform water distribution in MEA. The observed effects account for the improved fuel cell performance caused by the perforated GDL.

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 score0.025
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 head0.006
GPT teacher head0.163
Teacher spread0.157 · 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