DFT Study of Ethylene and Propylene Copolymerization over a Heterogeneous Catalyst with a Coordinating Lewis Base
Bibliographic record
Abstract
The copolymerization of ethylene and propylene over a heterogeneous Ti(III) catalyst containing tetrahydrofuran (THF) as a Lewis base and MgCl 2 as a support has been studied by means of DFT. Two feasible models of active sites have been examined thoroughly, and one of them turned out to be favorable in terms of both catalytic activity and the microstructure of the resulting polymer. The external barriers of olefin insertion for this model range from 3.1 to 16.0 kcal/mol and are influenced by a variety of factors, such as the structure of the growing polymer chain and the nature of the incoming olefin as well as the orientation of the ligands around the titanium atom. Stochastic simulations performed on the basis of insertion and termination barriers provided us with the insight into the composition and microstructure of the copolymer as well as its molecular weight as a function of comonomer partial pressures. It is demonstrated that the reactivity of ethylene in the copolymerization process is significantly higher than that of propylene, which is consistent with known experimental data. Our results also indicate moderate regiospecificity and stereoselectivity toward propylene, depending on the partial pressures of the comonomers.
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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) | 0.001 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".