Synthesis, Characterization, Thermomechanical and Rheological Properties of Long Chain Branched Metallocene Polyolefins
Bibliographic record
Abstract
The objectives of this research were to prepare model long chain branched polyolefin samples with controlled molecular weights and chain structural properties, and to elucidate the effects of long chain branching on the rheological and mechanical properties of polyethylene and polypropylene using a variety of synthesis and characterization techniques. Significant long chain branch (LCB) formation was found by ¹³C NMR measurements in polyethylene (PE) samples produced using the homogeneous catalyst bis(cyclopentadienyl) zirconium dichloride in a semi-batch slurry polymerization. Enhanced levels of LCB were attributed to the in-situ reaction of ethylene macromonomer and the encapsulation of active centres by precipitated polymer chains. PE samples with controlled levels of LCB were synthesized using a two-stage polymerization process. Narrowly dispersed poly( ethylene-co-propylene) (EPR) macromonomer was first produced in a continuous stirred tank reactor (CSTR). The macromonomer was subsequently copolymerized with ethylene in a semi-batch reactor using the constrained geometry catalyst (CGC-Ti). The two-stage reaction process was also employed to synthesize polypropylene (PP) with EPR long chain branches using the catalyst system rac-dimethylsilylenebis(2-ethylbenz[e]indenyl)zirconium dichloride / MMAO. It was found that the stoichiometry of the macromonomer could be used to efficiently control the long chain branch frequency (LCBF) of the copolymers without greatly influencing the copolymer molecular weight. It was also possible to control the long chain branch length by varying the molecular weight of the macromonomer. The rheological properties of various long chain branched polyolefins were measured. These polymers exhibited significantly higher zero shear viscosities (110) and displayed greater shear thinning than linear polymers with similar molecular weights. It was observed that the branch MN had to be greater than 7000 g/mol in order to form sufficient entanglements to significantly influence the rheological responses. The 110 was found to be a sensitive indicator of branch frequency and branch length. Increasing the branch MN led to enhanced values of 110, improved shear-thinning, and elevated flow activation energies. Long chain branching played a significant role in the dynamic mechanical behaviour of polyolefins. Increasing the frequency of branching increased the stiffness of polyethylene, as reflected by the storage modulus. Long chain branching also served to enhance the damping or energy dissipation of PE, shown by increased values of the loss modulus. The dynamic mechanical behaviour of polypropylenes with EPR long chain branches was also characterized. There appeared to be a critical EPR branch length at a MN of approximately 6000 g/mol. When the branch length was below this critical MN, a homogenous system resulted. If this critical MN was exceeded, a two-phase system developed, with fine rubbery domains dispersed in a PP matrix. When a two-phase system developed, it enhanced the loss modulus of the copolymer in a manner similar to impact modified PP.
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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".