Bis-aminocyclopropenylidene carbene borane catalyzed imine hydrogenation
Bibliographic record
Abstract
Certain borenium cations supported by carbenes can function as hydrogenation catalysts for imines. While many carbenes have been explored, variation of the other groups on boron has been less common. We have investigated several carbene-borane adducts in an attempt to understand the ability of a bis-amino cyclopropenylidene (BAC) carbene dicyclohexylborane adduct to hydrogenate relatively sterically unhindered benzyl imines. As an additional variant, a BAC carbene adduct of diphenylborane was prepared. A convenient preparation of diphenylboron fluoride via a potassium fluoroborinate salt was employed in this chemistry. Reaction of diphenylboron fluoride with a BAC carbene afforded a modest yield of a carbene-fluoroborane adduct. Reaction between the fluoroborinate salt and a lithium tetrafluoroborate adduct of the carbene provided the adduct in much improved yield and cleanliness, and the product was structurally characterized. The fluoroborate could be converted to a boron hydride through fluoride-hydride exchange with dimethylchlorosilane. The boron hydride adduct was also structurally characterized. Unlike the BAC carbene dicyclohexylborane adduct, the BAC carbene diphenylborane adduct showed essentially no activity in hydrogenation of imines or enamines.
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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".