Stereoregularity, Regioselectivity, and Dormancy in Polymerizations Catalyzed by<i>C</i><sub>1</sub>-Symmetric Fluorenyl-Based Metallocenes. A Theoretical Study Based on Density Functional Theory
Bibliographic record
Abstract
C s -Symmetric propylene polymerization catalysts 1 with a bridged cyclopentadienyl and fluorenyl architecture are known to produce syndiotactic polymers. On the other hand, related C 1 -symmetric catalysts, such as 2, that are obtained from 1 by the introduction of a bulky substituent ( tert -butyl) on the cyclopentadienyl ring afford isotactic polymers. In this study we employ DFT calculations in order to analyze several aspects of olefin polymerizations catalyzed by the fluorenyl-based C 1 -symmetric zirconocene 2 . Modeling of the propagation in naked cationic systems, disregarding the noncoordinating counterion, yields information on the factors that affect streoselectivity (and ultimately stereoregularity), regioselectivity, and reactivity of the “crowded” site of the zirconocene relative to the “open” one. Several hypotheses are investigated, with the aim to rationalize the experimental observation that 2 affords isotactic polymers whereas 1 gives rise to syndiotactic polymers. We provide in addition an analysis of the stability of dormant species 5 produced from 2,1 propylene mis-insertions. For this task, the need to include explicitly the counterion in the modeling seems to be inevitable. Comparative studies of the energetics of β-H elimination to the metal or β-H transfer to the monomer, relative to insertion into a Zr−secondary C bond, indicate that dormant species 5 are prone to β-H elimination.
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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".