Understanding the morphology formation and properties of polyamide 6 and bio‐based poly(trimethylene terephthalate) blends
Bibliographic record
Abstract
The influence of processing conditions on bio‐based poly(trimethylene terephthalate) (PTT) and polyamide 6 (PA6) blends via twin‐screw extrusion was successfully investigated, bringing new knowledge on the physical interactions between two widely used thermoplastics. A 50/50 wt% blend ratio was selected since it is characteristic of its unpredictable morphology and as such can highlight the behavior of the PTT/PA6 system in general, relevant for all blend ratios. Moreover, those materials are the two most used fibers in carpet industries and this blend presents a possible reality for carpet recycling via melt processing. The effects of the processing conditions on blend morphology were highlighted on the material surface by atomic force microscopy (AFM), and in the bulk by scanning electron microscopy (SEM) after solvent etching of the PA6 phase. The domain size was strongly influenced by the processing temperature used, which was explained by existing theories of blending via measurement of rheology and interfacial tension. The mechanical properties highlighted the interest of controlled morphology through adaptation of the processing parameters for end‐product applications. POLYM. ENG. SCI., 58:2210–2218, 2018. © 2018 Society of Plastics Engineers
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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 | 0.001 |
| 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".