Copper(II) Ethylene Polymerization Catalysts: Do They Really Exist?
Bibliographic record
Abstract
The reactions of two types of copper(II) ethylene polymerization catalysts, [(sal)CuCl] 2 (sal = 2-{C(H)═N(2,6- i Pr 2 -C 6 H 3 )}-4,6- t Bu 2 -phenoxide) and (α-diimine)CuCl 2 (α-diimine = [(2,6- i Pr 2 -C 6 H 3 )N═C(Me)] 2 ), with methylaluminoxane (MAO) and trimethylaluminum (TMA) have been investigated. In both examples, facile and irreversible ligand (L) transfer from copper to TMA present in MAO was observed, resulting in formation of the corresponding (sal)AlMe 2 and (imino-amido)AlMe 2 complexes. The (imino-amido)AlMe 2 complex is formed by α-diimine ligand transfer to aluminum followed by alkylation of one imino moiety in the ligand backbone. Both aluminum complexes were active catalysts for ethylene polymerization with activities similar to their Cu(II) precursors. Simple addition of a neutral salicylaldimine or α-diimine ligand to MAO in the absence of any copper species resulted in the formation of the corresponding LAlMe 2 complexes, which are again active for ethylene polymerization. These results indicate that ethylene polymerization does not occur by a migratory insertion mechanism at the copper center, but is the result of ligand transfer to aluminum, and it is the resulting LAlMe 2 /LAlMe + complexes that are likely the active species.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".