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Record W2143004776 · doi:10.1002/cphc.200500504

The Use of <sup>1</sup>H NMR Microscopy to Study Proton‐Exchange Membrane Fuel Cells

2005· article· en· W2143004776 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

VenueChemPhysChem · 2005
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsProton exchange membrane fuel cellFuel cellsMicroscopyProtonHydrogenChemistryMembraneAnalytical Chemistry (journal)Materials scienceNanotechnologyChemical engineeringNuclear magnetic resonancePhysicsNuclear physicsChromatographyOrganic chemistryEngineeringOptics

Abstract

fetched live from OpenAlex

To understand proton-exchange membrane fuel cells (PEMFCs) better, researchers have used several techniques to visualize their internal operation. This Concept outlines the advantages of using 1H NMR microscopy, that is, magnetic resonance imaging, to monitor the distribution of water in a working PEMFC. We describe what a PEMFC is, how it operates, and why monitoring water distribution in a fuel cell is important. We will focus on our experience in constructing PEMFCs, and demonstrate how 1H NMR microscopy is used to observe the water distribution throughout an operating hydrogen PEMFC. Research in this area is briefly reviewed, followed by some comments regarding challenges and anticipated future developments.

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 score0.212
Threshold uncertainty score0.740

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 head0.019
GPT teacher head0.231
Teacher spread0.212 · 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