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Record W2072629763 · doi:10.1002/aic.690490418

Core–shell structure and segregation effects in composite droplet polymer blends

2003· article· en· W2072629763 on OpenAlexaff
Joël Reignier, Basil D. Favis

Bibliographic record

VenueAIChE Journal · 2003
Typearticle
Languageen
FieldMaterials Science
TopicPolymer crystallization and properties
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsPolystyreneMaterials scienceComposite numberShell (structure)Radius of gyrationMethyl methacrylateComposite materialPhase (matter)PolymerViscoelasticityCore (optical fiber)Morphology (biology)Polymer blendViscosityCopolymerChemistry

Abstract

fetched live from OpenAlex

Abstract Core–shell morphology formation within the dispersed phase was studied for composite droplet polymer‐blend systems comprising a high‐density polyethylene matrix, polystyrene shell and different molecular weights of poly(methyl methacrylate) core material. The blends were prepared in the melt using an internal mixer, and the morphology was analyzed by electron microscopy. Changing the viscoelastic properties of the core in the dispersed phase dramatically affects PS‐PMMA segregation within the dispersed composite droplet itself. A high‐molecular‐weight‐PMMA core contains a large quantity of occluded PS inclusions, while the low‐molecular‐weight PMMA results in a perfectly segregated PS shell and PMMA core. These phenomena were attributed to the viscosity of the PMMA. Using the latter system, a direct microscopic study of the shell formation process demonstrates unambiguously that under conditions of perfect segregation, the onset of complete shell formation corresponds to a shell thickness that is close to two times the radius of gyration of polystyrene. Thus, the thinnest possible shell in such a system possesses a molecular‐scale thickness. The system with the high‐molecular‐weight‐PMMA core demonstrates an onset of complete shell formation that is displaced to higher concentrations due to the poor segregation effect. By counterbalancing the effects of viscosity ratio and interfacial effects on the composite droplet size, it is possible to generate perfectly segregated core–shell dispersed‐phase morphologies of almost identical size with a controlled shell thickness ranging from 40 to 300 nm.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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 integrity0.0000.000
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 head0.015
GPT teacher head0.238
Teacher spread0.223 · 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 source (direct Gemma or distilled Codex), 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

Citations42
Published2003
Admission routes1
Has abstractyes

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