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Morphology and Linear Viscoelasticity of Poly[ethylene-co-(1-octene)]/Layered Silicate Nanocomposites

2002· article· en· W1992770859 on OpenAlexaff
Wei Feng, A. Aı̈t-Kadi, Bernard Riedl

Bibliographic record

VenueMacromolecular Rapid Communications · 2002
Typearticle
Languageen
FieldMaterials Science
TopicSilicone and Siloxane Chemistry
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsMaterials scienceOrganoclayNanocompositeOcteneSilicateComposite materialEthyleneMorphology (biology)MicrostructureTransmission electron microscopyMontmorilloniteViscoelasticityIntercalation (chemistry)Dynamic mechanical analysisPolymerChemical engineeringCopolymerNanotechnologyChemistry

Abstract

fetched live from OpenAlex

Poly[ethylene-co-(1-octene)] nanocomposites with different microstructures were prepared with two kinds of organoclay by melt intercalation. X-ray diffraction and transmission electron microscopy were used to characterize the morphology of the composites. Linear storage moduli of the composites in the melt state were found to increase greatly with increasing the extent of dispersion of silicate layers and showed an obvious sensitivity to the morphologies of the composites.

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 score0.010
Threshold uncertainty score0.951

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.030
GPT teacher head0.270
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

Citations17
Published2002
Admission routes1
Has abstractyes

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