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Record W2067952283 · doi:10.1021/ma048262z

Pressure−Volume−Temperature Dependence of Polypropylene/Organoclay Nanocomposites

2004· article· en· W2067952283 on OpenAlexaff
L. A. Utracki, Robert Simha

Bibliographic record

VenueMacromolecules · 2004
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Nanocomposites and Properties
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsOrganoclayPolypropyleneVolume fractionNanocompositeCrystallinityMaterials sciencePolymerVolume (thermodynamics)Polymer chemistryComposite materialPolymer nanocompositeMethacrylateChemical engineeringThermodynamicsCopolymerPhysics

Abstract

fetched live from OpenAlex

The pressure−volume−temperature ( PVT ) dependencies of commercial polypropylene melt (PP) and its nanocomposites containing X wt % of organoclay (Cloisite-15A, or C15) and 2 X wt % of a compatibilizer were determined at T = 450−530 K and P = 0.1−190 MPa. C15 was used at concentrations: X = 0, 2, and 4 wt %. Three functionalized PP's were used as compatibilizers: two maleated and one grafted with glycidyl methacrylate. Incorporation of X = 2 wt % C15 into PP resulted in reduction of specific volume by Δ V ≈ 1%, but that of free volume (hole) fraction by Δ h ≈ 5%. The latter quantity was computed from the Simha−Somcynsky lattice−hole equation of state. Furthermore, at constant T and P the hole fraction was found to be linearly related to the bulk-average energetic interaction parameter and to be a sensitive indicator of structural changes. In binary (polymer + organoclay) systems Δ h is linearly related to the interlayer spacing, d 001 . So, where statements from the previous paper are repeated or there are similarities, this is done for purposes of comparison. In three-component systems (with a compatibilizer) the proportionality has been preserved, but large changes of Δ h result in relatively small changes of d 001 . Mechanical properties hardly correlate with either Δ h or d 001, as polymer/compatibilizer morphology and crystallinity complicate the behavior.

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 score0.008
Threshold uncertainty score0.853

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 science0.0010.000
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 head0.006
GPT teacher head0.210
Teacher spread0.204 · 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

Citations47
Published2004
Admission routes1
Has abstractyes

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