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Record W1969174668 · doi:10.1149/1.3635573

Nano to Micro Scale Characterization of Water Uptake in The Catalyst Coated Membrane Measured by Soft X-ray Scanning Transmission X-ray Microscopy

2011· article· en· W1969174668 on OpenAlexafffund
Viatcheslav Berejnov, Darija Susac, Jürgen Stumper, Adam P. Hitchcock

Bibliographic record

VenueECS Transactions · 2011
Typearticle
Languageen
FieldMaterials Science
TopicElectron and X-Ray Spectroscopy Techniques
Canadian institutionsAutomotive Fuel Cell Cooperation (Canada)McMaster University
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsMembraneMaterials scienceProton exchange membrane fuel cellMicroscopyAnalytical Chemistry (journal)Relative humidityAbsorption (acoustics)CathodeWater vaporAbsorption of waterCharacterization (materials science)X-rayResolution (logic)Chemical engineeringElectrodeChemistryNanotechnologyOpticsComposite materialChromatography

Abstract

fetched live from OpenAlex

We describe a method of quantitative mapping the water content in the catalyst coated membranes (CCM) of proton exchange membrane (PEM) fuel cells with high spatial resolution (~30 nm) using soft X-ray Scanning Transmission X-ray Microscopy. Detailed component chemical maps of CCMs at different environmental conditions (relative humidity (RH)) were generated from O 1s optical density measurements by fitting to the soft X-ray absorption reference spectra for liquid and gaseous water and those of the electrode and membrane materials. Under high RH conditions, different distributions of water (vapor and liquid) were found for the cathode layer and the membrane. These results are related to differences in hydrophilicity / hydrophobicity of different regions.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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)0.0020.000

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 head0.014
GPT teacher head0.244
Teacher spread0.230 · 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 source (direct Gemma or distilled Codex), 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

Citations15
Published2011
Admission routes2
Has abstractyes

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