Morphology development of EPDM/PP uncross‐linked/dynamically cross‐linked blends
Bibliographic record
Abstract
Abstract Ethylene‐propylene‐diene‐terpolymer (EPDM) and polypropylene (PP)‐based uncross‐linked and dynamically cross‐linked blends were prepared both in an internal mixer and in a corotating twin‐screw extruder. The effects of composition, plasticization and mixing equipment on the morphology development and the final viscoelastic properties were studied. In the uncross‐linked blends, the plasticization resulted in a coarser morphology. Furthermore, it was shown that the majority of the plasticizer resided in the EPDM phase, enabling its deformation in the flow direction. In addition, the intensive mixing conditions inside the twin‐screw extruder resulted in a finer morphology. In the dynamically cross‐linked blends, the twin‐screw extrusion process resulted in a higher level of gel content with larger EPDM domains. The plasticization showed again a coarsening effect, resulting in interconnected cross‐linked EPDM domains. An interesting interfacial phenomenon was observed especially in the plasticized vulcanized blends where nanometer size occluded PP domains were stripped off and eroded into the EPDM phase. With the exception of the nonplasticized uncross‐linked blends, the viscoelastic properties of all other blending systems were found to be directly affected by the morphology, gel content (in the case of cross‐linked blends), and the presence of the plasticizer. POLYM. ENG. SCI., 2012. © 2011 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 | 0.000 |
| 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".