Tailor‐made controlled rheology polypropylenes from metallocene and Ziegler–Natta resins
Bibliographic record
Abstract
Production of controlled rheology polypropylenes (CRPPs) is practiced industrially by modifying existing commodity Ziegler–Natta resins through peroxide‐induced β‐scission reactions, resulting in materials with controlled rheological properties and accompanying narrower molecular weight distributions (MWDs). In this work, this methodology was studied using both metallocene‐based polypropylenes (mPPs) and Ziegler–Natta‐based polypropylenes (ZN‐PPs). Numerical simulations based on a previously proposed kinetic model indicated that the nature of the starting resin has a significant effect on the control of MWD polydispersity index (PDI) and weight‐average molecular weight () of the resulting CRPP. Based on these observations, experiments were carried out to demonstrate the feasibility of producing CRPP with targeted molecular and rheological characteristics. Commercial mPP and ZN‐PP resins were selected to produce CRPP with similar or melt flow rates (MFRs) but varying PDIs. The rheological properties and MWDs of these materials were evaluated through oscillatory shear and gel permeation chromatography (GPC) measurements and their extrusion behavior was briefly studied and assessed with respect to these properties. POLYM. ENG. SCI., 59:1114–1121 2019. © 2019 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".