Nickel-Catalyzed C–H Silylation of Arenes with Vinylsilanes: Rapid and Reversible β-Si Elimination
Bibliographic record
Abstract
The reaction of C 6 F 5 H and H 2 C═CHSiMe 3 with catalytic [ i Pr 2 Im]Ni(η 2 -H 2 C═CHSiMe 3 ) 2 ( 1b ) exclusively forms the C–H silylation product C 6 F 5 SiMe 3 with ethylene as a byproduct ([ i Pr 2 Im] = 1,3-di(isopropyl)imidazole-2-ylidene). Catalytic C–H bond silylation is facile with partially fluorinated aromatic substrates containing two ortho fluorine substituents adjacent to the C–H bond and 1,2,3,4-tetrafluorobenzene. Less fluorinated substrates react slower. Under the same reaction conditions, catalytic [IPr]Ni(η 2 -H 2 C═CHSiMe 3 ) 2 ( 1a ) ([IPr] = 1,3-bis[2,6-diisopropylphenyl]-1,3-dihydro-2H-imidazol-2-ylidene) provided only the alkene hydroarylation product C 6 F 5 CH 2 CH 2 SiMe 3 . Mechanistic studies reveal that the C–H activation and β-Si elimination steps are reversible under catalytic conditions with both catalysts 1a and 1b . With catalytic 1a, reversible ethylene loss after β-Si elimination was also observed despite its inability to catalyze C–H silylation; the reductive elimination step to form the silylation product is much slower than reductive elimination to form the alkene hydroarylation product. Reversible ethylene loss was not observed with 1b, which suggests that the rate-limiting step in the reaction is neither C–H activation nor β-Si elimination but either ethylene loss or reductive elimination of cis-disposed aryl and SiMe 3 moieties.
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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) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".