Why Do <i>C</i><sub>1</sub>-Symmetric <i>ansa</i>-Zirconocene Catalysts Produce Lower Molecular Weight Polymers for Ethylene/Propylene Copolymerization than for Ethylene/Propylene Homopolymerization?
Bibliographic record
Abstract
We have carried out a combined QM/MM study to rationalize the factors that can affect the performance of C 1 -symmetric ansa -zirconocene catalysts that contain bridged cyclopentadienyl (Cp) and fluorenyl (Flu) ligands in olefin homo- and copolymerization. Two growing chains with different β-C (tertiary or secondary) and two olefins (propene and ethylene) have been used for this purpose. Our calculations indicate that chain transfer has a higher barrier than chain propagation in EE (ethylene homopolymerization), PP (propylene homopolymerization), and PE (propylene complexation to a metal with a propyl chain) systems. However, the two processes are competitive in EP (ethylene complexation to a metal with a 2-methylpropyl chain) system. Substituents on the carbon in a C−H link weaken the C−H bond. This in turn determines the order EP < EE < PP < PE for the heat of reaction of the β-hydrogen transfer process, giving rise to the chain termination, where the process with the most negative reaction heat is the more thermodynamically favorable. It is further argued that the barriers for the termination process must follow the same order of EP < EE < PP < PE. For the insertion process the barrier increases with the number of substituents on the olefin and the C β atom of the growing chain as PP > PE ∼ EP > EE. The different propensity of the four systems for termination and propagation results in the higher barrier of termination for EE, PP, and PE, whereas the barriers are similar for EP. Our analysis explains why ethylene/propylene homopolymerization affords high molecular weight polymers, whereas ethylene/propylene copolymerization affords low molecular weight polymers.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".