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Record W1984687380 · doi:10.1021/ma800194z

Properties of Water in Prestretched Recast Nafion

2008· article· en· W1984687380 on OpenAlexaff
Jun Lin, Pin-Han Wu, Ryszard Wycisk, Peter N. Pintauro, Zhiqing Shi

Bibliographic record

VenueMacromolecules · 2008
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsBC Innovation CouncilNational Research Council Canada
Fundersnot available
KeywordsNafionMaterials scienceMembraneWater transportConductivityMethanolAnalytical Chemistry (journal)Gravimetric analysisChemical engineeringChromatographyChemistryWater flowOrganic chemistryPhysical chemistryElectrochemistry

Abstract

fetched live from OpenAlex

Uniaxially prestretched recast Nafion membranes exhibited an unusual combination of properties (a proton conductivity equal to that of commercial Nafion but with a lower methanol permeability) which make them ideal candidates for use in a direct liquid methanol fuel cell. To better understand the function and underlying morphology of the prestretched membranes, water uptake and mobility data were collected and analyzed for draw ratios ranging from 1 to 7. Macroscopic (gravimetric) water uptake and the water self-diffusion coefficient (measured by NMR) were found to be invariant with membrane elongation and essentially identical to those measured in a commercial Nafion 117 film (a similar behavior was observed for proton conductivity). The ratio of freezable/nonfreezable water in prestretched recast Nafion, the water electro-osmotic drag coefficient, and the spin−lattice relaxation time constant of deuterated water, however, decreased with increasing film elongation, up to a draw ratio of 4. The functional dependence of these properties on draw ratio was similar to that observed for methanol permeability. The combined water results indicated that there were a greater number of smaller ionic/hydrophilic domains in prestretched recast Nafion as compared to commercial Nafion. Transmission electron microscopy of membrane cross sections confirmed this conclusion.

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 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 score0.005
Threshold uncertainty score0.217

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 head0.014
GPT teacher head0.171
Teacher spread0.158 · 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 teacher head, 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

Citations64
Published2008
Admission routes1
Has abstractyes

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