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Record W2317893483 · doi:10.1021/jp502081g

Surface Morphology and Properties of Ternary Polymer Blends: Effect of the Migration of Minor Components

2014· article· en· W2317893483 on OpenAlexafffund
Ahmad Rezaei Kolahchi, Abdellah Ajji, Pierre J. Carreau

Bibliographic record

VenueThe Journal of Physical Chemistry B · 2014
Typearticle
Languageen
FieldMaterials Science
TopicPolymer crystallization and properties
Canadian institutionsPolytechnique Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceTernary operationPolymerPolystyreneScanning electron microscopeMorphology (biology)Polymer blendChemical engineeringPolycaprolactonePEG ratioEthylene glycolPolyethylene terephthalatePolymer chemistryAdipateSurface energyComposite materialCopolymer

Abstract

fetched live from OpenAlex

In this work, the surface morphology and properties of ternary polymer blends and the migration of minor component molecules to the top surface layer of the films were studied. We used polystyrene (PS), poly(butylene adipate-co-terephthalate), polycaprolactone, poly(methyl methacrylate), and polylactide as second minor phases in a blend of polyethylene terephthalate-poly(ethylene glycol) (PET-PEG). The morphology of the ternary systems predicted using the spreading coefficient and relative interfacial energy concepts was confirmed by scanning electron microscopy images. The surface characterization results showed a higher rate of migration of PEG to the polymer-air interface in the systems with a nonwetting morphology and the highest in the PET-PS-PEG blend. Atomic force microscopy images suggested that the high surface hydrophilicity of the PET-PS-PEG blend is due to a dendritic pattern of PEG crystals on the film surface, which were not observed for the other samples.

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 score0.001
Threshold uncertainty score0.132

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 integrity0.0000.000
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 head0.012
GPT teacher head0.216
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

Citations29
Published2014
Admission routes2
Has abstractyes

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