Polypropylene Made with In‐Situ Supported Me<sub>2</sub>Si(Ind)<sub>2</sub>ZrCl<sub>2</sub> and Me<sub>2</sub>Si(2‐Me‐Ind)<sub>2</sub>ZrCl<sub>2</sub> Catalysts: Properties Comparison
Bibliographic record
Abstract
Abstract Summary: Propylene homopolymerizations were carried out using Me 2 Si(Ind) 2 ZrCl 2 and Me 2 Si(2‐Me‐Ind) 2 ZrCl 2 , MAO‐modified silica, and common alkylaluminum cocatalysts. Supported catalysts were prepared by the in‐situ immobilization technique. The effect of the type and concentration of alkylaluminum on propylene polymerization was evaluated using TEA (triethylaluminum), IPRA (isoprenylaluminum), and TIBA (triisobutylaluminum) as cocatalysts. The polymers were analyzed by gel permeation chromatography (GPC), differential scanning calorimetry (DSC), and scanning electronic microscopy (SEM). The effect of the type and concentration of alkylaluminum on the melting temperature and the molar mass of the polypropylene was the same for both catalysts. The polymers made with in‐situ supported catalyst had lower melting points and, in almost all polymerization conditions, higher molar masses than those produced by homogeneous polymerization. Polypropylene samples made with Me 2 Si(2‐Me‐Ind) 2 ZrCl 2 had higher melting temperatures and molar masses than those made with Me 2 Si(Ind) 2 ZrCl 2 . SEM micrographs showed that the polymers obtained with in‐situ supported systems had a well‐defined morphology, confirming that the polymerization indeed took place onto the silica support. SEM micrographs of polypropylene particles obtained with Me 2 Si(2‐Me‐Ind) 2 ZrCl 2 in the presence of IPRA. magnified image SEM micrographs of polypropylene particles obtained with Me 2 Si(2‐Me‐Ind) 2 ZrCl 2 in the presence of IPRA.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.005 | 0.005 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".