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Record W2054603855 · doi:10.1021/ie0512035

Diffusive Permeability and Selectivity of Nanocomposite Membranes

2006· article· en· W2054603855 on OpenAlexafffund
Reghan J. Hill

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2006
Typearticle
Languageen
FieldEngineering
TopicMembrane Separation and Gas Transport
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsPenetrant (biochemical)Volume fractionMembranePermeability (electromagnetism)Thermal diffusivityPolymerSelectivityMaterials scienceChemical physicsNanocompositeHomogeneousMicrostructureSynthetic membranePolymer nanocompositeChemical engineeringPolymer chemistryChemistryNanotechnologyThermodynamicsComposite materialPhysicsOrganic chemistry

Abstract

fetched live from OpenAlex

The permeability of certain polymer membranes with impenetrable nanoinclusions increases with the particle volume fraction (Merkel et al. Science 2002, 296, 519−522). This intriguing discovery contradicts even qualitative expectations based on Maxwell's classical theory of conduction/diffusion in composites with homogeneous phases. This paper describes a theoretical model that captures the observed dependence of the bulk permeability and selectivity on the inclusion size and volume fraction, thereby providing a straightforward connection between membrane microstructure and performance. An essential feature of the theory is a polymer-segment depletion layer at the inclusion−polymer interface. The accompanying increase in free volume leads to a significant increase in the local penetrant diffusivity, which, in turn, increases the bulk permeability and selectivity.

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 score0.017
Threshold uncertainty score0.712

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 integrity0.0000.001
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 head0.034
GPT teacher head0.275
Teacher spread0.241 · 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

Citations29
Published2006
Admission routes2
Has abstractyes

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