Polymer blend de‐mixing and morphology development of immiscible polymer blends during tube flow
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".