Is the Polymerization of Linear α-Olefins by Transition-Metal Carbene Complexes a Viable Process? A Theoretical Study Based on Density Functional Theory
Bibliographic record
Abstract
Gradient-corrected density functional theory has been used to study the mechanism of α-olefin polymerization catalyzed by transition-metal carbene complexes. Taking the [CH 2 Re(NO) 2 (PMe 3 )] + complex as an example, we investigated the possible elementary steps of the polyethylene formation. This “carbene-to-metallacycle” style mechanism based on a pure carbene intermediate starts with the coordination of the ethylene. Then ethylene reacts with the carbene complex by a [2 + 2] addition. Metallacyclobutane decomposition to a new carbene complex takes place by an α-hydrogen transfer reaction. We have also investigated the possible side reactions for the metallacyclobutane decomposition by metathesis reaction, cyclization, and β-hydride transfer reactions. Calculations have been performed on the monomer and carbene complexes, on the possible intermediates, ethylene π-complexes, metallacyclobutanes, cyclopropyl complexes, cyclopropyl hydride complexes, propylidene complexes, propene π-complexes, allyl−hydride intermediates, and transition states. The results show that when the [CH 2 Re(NO) 2 (PMe 3 )] + complex is used as a catalyst, the β-hydride transfer is both kinetically and thermodynamically favored over the α-hydride transfer reaction; therefore, ethylene polymerization is not viable. Modifying the catalyst by changing the metal center does not change the preference for the β-elimination products. However, the application of strongly electron donating ligands can make the metal center sufficiently electron rich to stabilize the new propylidene ligand over the formation of an olefin π-complex.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".