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Record W2042777302 · doi:10.1149/05002.0361ecst

3D Chemical Mapping of PEM Fuel Cell Cathodes by Scanning Transmission Soft X-ray SpectroTomography

2013· article· en· W2042777302 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
FieldPhysics and Astronomy
TopicAdvanced X-ray Imaging Techniques
Canadian institutionsAutomotive Fuel Cell Cooperation (Canada)McMaster University
FundersBasic Energy SciencesU.S. Department of Energy
KeywordsCathodeMaterials scienceX-raySample (material)Absorption (acoustics)IonomerOrientation (vector space)Transmission (telecommunications)Scanning electron microscopeCarbon fibersTransmission electron microscopyNanoscopic scaleOpticsAnalytical Chemistry (journal)ChemistryComposite materialNanotechnologyComputer sciencePhysicsGeometryChromatography

Abstract

fetched live from OpenAlex

Soft X-ray spectrotomography was applied for 3D chemical analysis of fuel cell cathodes at the nano scale. The goal was to obtain 3D maps of the components constituting the catalyst layer, and, in particular, to differentiate 3D networks of carbon support and ionomer. Using scanning transmission soft X-ray microscopy (STXM) with a rotating sample holder we produced a series of images at selected photon energies and different rotational angles of the sample. The rotational image stacks were tomographically reconstructed, while the X-ray absorption fingerprints at the C1s and F1s edges were used to generate 3D maps of the networks of carbon-support/catalyst and the fluorine-rich ionomer.

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: Methods · Consensus signal: none
Teacher disagreement score0.805
Threshold uncertainty score0.881

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 head0.226
Teacher spread0.219 · 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