Challenge of the Copolymerization of Olefins with N-Containing Polar Monomers. Systematic Screening of Nickel(II) and Palladium(II) Catalysts with Brookhart and Grubbs Ligands. 2. Chain-Propagation Barriers, Intrinsic Regioselectivity, and Curtin-Hammett Reactivity
Bibliographic record
Abstract
The second level of a computational screening of late-transition-metal catalysts and nitrogen-containing polar monomers toward an incorporation of amines and nitriles in the polymer chain of polyolefins is reported. The structures and energies of the transition states for the insertion of the C C bond of ethylene, propylene, acrylonitrile, and vinylamine into the metal−carbon bond of generic models for Ni(II) and Pd(II) complexes with diimine (Brookhart) and salicylaldiminato (Grubbs) ligands have been calculated using density functional theory. The calculations reveal the general trend that the activation energies for the ethylene, propylene, and acrylonitrile insertion in the Brookhart systems are similar, whereas the activation energies for the vinylamine insertion are much higher. The nickel systems show lower insertion barriers than do their palladium counterparts. For the chain propagation with the Grubbs catalysts, a Curtin−Hammett-type energy profile involving cis−trans isomerization and subsequent C−C insertion is predicted. The regioselectivity of the propylene, acrylonitrile, and vinylamine insertion is rationalized by the analysis of the frontier orbitals of the free monomers.
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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) | 0.002 | 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".