A Density Functional Study of Ethylene Insertion into the M‐methyl (M = Ti, Zr) Bond for Different Catalysts, with a QM/MM Model for the Counterion, B(C<sub>6</sub>F<sub>5</sub>)<sub>3</sub>CH<sub>3</sub><sup>−</sup>
Bibliographic record
Abstract
Abstract Single site homogeneous catalysts have been studied extensively in recent years as alternatives to traditional heterogeneous catalysts. The current theoretical study uses density functional theory to study the insertion process of the ethylene monomer into the titanium‐carbon chain for contact ion‐pair systems of the type [L1L2TiCH3‐μ‐CH3‐B(C6F5)3], where L1, L2, are Cp, NPH3, and other ligands. Different modes of approach cis and trans to the μ‐CH3 bridge were considered. The counterion, B(C6F5)3CH3−, was modeled by QM/MM methods. The value of ΔHtot—the total barrier to insertion—was found to be positive (in the range of 4–15 kcal/mol). The ability of the ancillary ligands, L1 and L2, to stabilize the ion‐pair was found to be an important factor in determining the value of δHtot. On replacing the titanium metal center with zirconium, the ΔHtot values were found to be lowered (in the range of 2–9 kcal/mol), indicating that they would be better catalysts than their titanium analogues. The size of the ligands L1 and L2 was increased by replacing hydrogens in the ligands with tertiary butyl groups. The value of ΔHtot was found to increase (in the range of 10–28 kcal/mol) in contrast to the simple systems, for both the cis and trans cases of approach, with the cis mode of approach giving lower values of ΔHtot. Solvent effects were incorporated with cyclohexane (ε = 2.023) as the solvent, and were found to have a minor influence, ±(0.5–1.5) kcal/mol) on the insertion barrier for all the cases studied.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".