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Record W2047056548 · doi:10.1002/cjce.5450850103

Mass Transport Through PDMS/Clay Nanocomposite Membranes

2007· article· en· W2047056548 on OpenAlexvenueno aff
Quan Liu, D. De Kée

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2007
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Nanocomposites and Properties
Canadian institutionsnot available
FundersForskningsrådet om Hälsa, Arbetsliv och VälfärdNational Aeronautics and Space Administration
KeywordsMembraneNanocompositeDiffusionPermeationMaterials sciencePolymerDeformation (meteorology)Chemical engineeringParticle (ecology)Mass transportComposite materialPolymer chemistryChemistryThermodynamics

Abstract

fetched live from OpenAlex

Abstract Poly(dimethylsiloxane)/clay nanocomposite membranes have been synthesized and mass transport properties through those nanocomposite membranes have been investigated. The effect of mechanical deformation on the transport properties of the PDMS (nanocomposite) membranes has also been studied. With the introduction of clay particles into the polymer matrix, mass transport is reduced, likely due to the longer diffusion path, which slows the diffusion process. The effect of membrane extension on diffusion is more complicated. Under small deformation, the permeation flux decreases, but under high deformation, it shows an enhanced diffusion. As the clay particle concentration increased, the effect of external deformation is reduced, and an enhanced diffusion is observed.

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)0.001
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 score0.006
Threshold uncertainty score0.369

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.009
GPT teacher head0.194
Teacher spread0.185 · 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

Citations10
Published2007
Admission routes1
Has abstractyes

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