Propylene Polymerization and Deactivation Processes with Isoselective {Cp/Flu} Zirconocene Catalysts
Bibliographic record
Abstract
Industrially relevant single-site precatalysts used to produce isotactic polypropylene (iPP) include C2-symmetric {SBI} and C1-symmetric {Cp/Flu} complexes of group 4 metals. While the latter can produce iPPs with a higher degree of isotacticity, they also suffer from poor productivity compared to their {SBI} counterparts. Several causes for this trend have been suggested—2,1-Regioinsertions are frequently pointed out, as they are suspected to drive the catalyst into a dormant state. While this event does not seem to significantly impact the productivity of {SBI} systems, the influence of these regioerror is poorly documented for isoselective {Cp/Flu} precatalysts. To address this issue, new Ph2X(Cp)(Flu) (Ph2X = Ph2C, FluC, Ph2Si) proligands (2a–k) and some of the corresponding dichlorozirconocenes (3a–h,k) were synthesized. These new compounds were characterized and tested in homogeneous propylene polymerization at 60 °C and the amounts of regioerrors in the resulting polymers were examined by 13C NMR spectroscopy. A possible correlation between poor productivity and a high number of regioerrors was investigated and is discussed. Furthermore, a C-H activation process in the bulky nBu3C substituent upon activation of 4c (the dimethylated analog of 3c) by B(C6F5)3 has been evidenced by NMR; DFT calculations support this C-H activation as a deactivation mechanism.
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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 | 0.001 |
| 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".