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Record W1976128962 · doi:10.1002/pen.11367

Polymer blend de‐mixing and morphology development of immiscible polymer blends during tube flow

2000· article· en· W1976128962 on OpenAlexaff
Askar Karami, S. T. Balke

Bibliographic record

VenuePolymer Engineering and Science · 2000
Typearticle
Languageen
FieldMaterials Science
TopicPolymer crystallization and properties
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMaterials sciencePolypropyleneExtrusionShear ratePlastics extrusionPolymer blendPolymerMixing (physics)PolyethyleneCoalescence (physics)Composite materialViscosityCopolymer

Abstract

fetched live from OpenAlex

Abstract This work is an investigation of morphology and de‐mixing of polymer blends during melt flow through a tube. Morphology is the relative size, shape and location of each distinguishable phase present in a polymer blend. De‐mixing is the shear‐induced migration of different types of polymers away from each other during the flow. The ability to tailor de‐mixing during extrusion can potentially result in a new family of plastics waste recycling processes with mixed waste entering an extruder and separate streams of different polymer types leaving it. Also, control of morphology development can lead to the formation of layered structures without the need for two or more extruders and co‐extrusion. This work is directed at elucidating morphology development and de‐mixing of polymer blends in the most simple process design: melt flow through a tube. Shear‐induced migration was quantitatively shown in various polyethylene‐polypropylene, polypropylene‐nylon 6 and polyethylene‐nylon 6 blends. The migration observed was in accord with the hypothesis that the system tends to minimize its rate of energy dissipation for a fixed flow rate. The ratio of the viscosity of the dispersed phased to that of the continuous phase greatly influenced the morphology of polypropylene‐nylon 6 and polyethylenenylon 6 blends: a droplet‐dispersed phase structure occurred at a high viscosity ratio, whereas a multi‐layer structure resulted at viscosity ratios near unity. Shear‐induced deformation and coalescence contributed to formation of the multi‐layer structure.

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 score0.762

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)0.0010.000

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 head0.008
GPT teacher head0.203
Teacher spread0.195 · 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

Citations12
Published2000
Admission routes1
Has abstractyes

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