Density Functional Study of Neutral Salicylaldiminato Nickel(II) Complexes as Olefin Polymerization Catalysts
Bibliographic record
Abstract
The recent discovery of the ability of salicylaldiminato Ni(II) complexes to promote ethylene polymerization creates a potential for a new class of olefin polymerization catalysts. The major advantage of this type of catalyst is that they produce a neutral active center and thereby avoid the ion-pairing problems encountered with the homogeneous single-site catalysts in current use. The present DFT study investigates the polymerization mechanism of these neutral complexes as well as the electronic and steric effects of various substituents on the catalyst backbone. The addition of electron-withdrawing or -releasing substituents on the 5 position of the salicylaldiminato ring was found to result in small changes in the energies of the reactions in the polymerization mechanism. This is most likely due to the substituents' remoteness from the active center. Changing the electronic nature of the donor atoms resulted in larger shifts in energy. Finally, bulky substituents such as 2,6-diisopropylphenyl and 9-anthracenyl groups were found to have the largest effect on the reaction barriers and enthalpies in a direction that should substantially increase catalyst activity.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".