DFT Study of Olefin versus Nitrogen Bonding in the Coordination of Nitrogen-Containing Polar Monomers to Diimine and Salicylaldiminato Nickel(II) and Palladium(II) Complexes. Implications for Copolymerization of Olefins with Nitrogen-Containing Polar Monomers
Bibliographic record
Abstract
An initial screening of late-transition-metal catalysts and nitrogen-containing polar monomers toward an incorporation of amines or nitriles in the polymer chain of polyolefins has been performed using density functional theory. Substrates of the type CH 2 CH(CH 2 ) n X (X = polar group) can bind either with the N-containing polar group or with the π moiety to the metal center of the catalyst. Monomer−catalyst combinations favoring the π complex over the N complex are promising, because the π-binding mode can subsequently lead to polymer growth. The stabilization energies for the π and N complexes of monomers of the type CH 2 CH(CH 2 ) n CN, CH 2 CH(CH 2 ) n NH 2, and CH 2 CH(CH 2 ) n N(CH 3 ) 2 with generic models for the recently reported nickel(II) and palladium(II) catalysts with diimine (“Brookhart”) and salicylaldiminato (“Grubbs”) ligands have been calculated. While the investigated polar monomers have been shown to form very strong metal−nitrogen bonds with the Brookhart nickel catalysts, the enamine prefers the π binding mode in its complexes with all model catalysts. Promising results have also been obtained for the coordination of nitriles and amines with the Grubbs nickel catalysts. The palladium systems show an even larger preference for π coordination than their nickel counterparts. An energy-decomposition scheme has been used to rationalize the relative strength of the catalyst−monomer bonds.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".