Copolymerization of Propylene with Poly(ethylene-<i>co</i>-propylene) Macromonomer and Branch Chain-Length Dependence of Rheological Properties
Bibliographic record
Abstract
A series of isotactic polypropylene (PP) samples with poly(ethylene- co -propylene) long chain branching were produced by a semibatch copolymerization of poly(ethylene- co -propylene) macromonomer (EPR), prepared in a high-temperature continuous stirred tank reactor (CSTR), and propylene using rac -dimethylsilylenebis(2-methylbenz[ e ]indenyl) zirconium dicholoride/modified methylaluminoxane. The branch frequency and branch length of the copolymers were controlled by varying the stoichiometry and molecular weight of the EPR macromonomer, respectively. Long chain branch frequencies of up to 2.8 branches per chain were achieved, while the branch length was varied from 2500 to 17 000 g/mol. The effects of macromonomer concentration, macromonomer molecular weight, and reaction temperature on the copolymer chain properties were investigated. The rheological responses of the EPR-branched PP were determined. Branches below 7000 g/mol had little influence on the rheological behavior of the polymers. The zero shear viscosity, shear thinning property, and loss and storage moduli were found to be dependent on the branch length and branch frequency when the branch M n was above 7000 g/mol. Elevated flow activation energies were observed with measured values of up to 51 kJ/mol. The physical and chemical properties of the copolymers were analyzed by gel permeation chromatography (GPC), FTIR, parallel-plate rheometry, and 13 C NMR.
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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".