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Record W2002105145 · doi:10.1002/pen.11087

Morphology and rheological properties of polypropylene/reactive elastomer blends

2002· article· en· W2002105145 on OpenAlexaff
Frédérique Marguerat, Pierre J. Carreau, Alain Michel

Bibliographic record

VenuePolymer Engineering and Science · 2002
Typearticle
Languageen
FieldMaterials Science
TopicPolymer crystallization and properties
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsMaterials scienceElastomerViscoelasticityRheologyPolypropyleneComposite materialPolymer blendPhase (matter)Morphology (biology)ViscosityCopolymerScanning electron microscopePolymerOrganic chemistryChemistry

Abstract

fetched live from OpenAlex

Abstract The relation of morphology to the linear viscoelastic properties for polymer blends consisting of an inert polypropylene and an elastomeric dispersed phase, made of two miscible copolymers, EVA and EMA, was investigated. The rheological properties of the elastomeric phase were modified by crosslinking in presence of an organometallic catalyst. The activation energy for the transesterification reaction taking place between EVA and EMA has been determined by following the increases of the complex viscosity with time and temperature. The Palierne model has been used to describe the linear viscoelastic behavior of the blends, and to estimate the interfacial tension between the immiscible components. The model was shown to describe relatively well the linear viscoelastic properties of reactive and nonreactive blends containing 30% or less elastomer. In parallel, the morphology of reactive and nonreactive blends (i.e. without catalyst in the elastomeric phase), before and after rheological experiments, has been determined using scanning electron microscopy. The size of the dispersed elastomeric particles for reactive blends prepared using an internal mixer was found to be, in most cases, much smaller than that for nonreactive blends.

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 score0.011
Threshold uncertainty score0.338

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 studies0.0000.001
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 head0.022
GPT teacher head0.201
Teacher spread0.180 · 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

Citations11
Published2002
Admission routes1
Has abstractyes

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