Mechanistic Aspects of Bond Activation with Perfluoroarylboranes
Bibliographic record
Abstract
In the mid-1990s, it was discovered that tris(pentafluorophenyl)borane, B(C(6)F(5))(3), was an effective catalyst for hydrosilylation of a variety of carbonyl and imine functions. Mechanistic studies revealed a counterintuitive path in which the function of the borane was to activate the silane rather than the organic substrate. This was the first example of what has come to be known as "frustrated Lewis pair" chemistry utilizing this remarkable class of electrophilic boranes. Subsequent discoveries by the groups of Stephan and Erker showed that this could be extended to the activation of dihydrogen, initiating an intense period of activity in this area in the past 5 years. This article describes the early hydrosilylation chemistry and its subsequent applications to a variety of transformations of importance to organic and inorganic chemists, drawing parallels with the more recent hydrogen activation chemistry. Here, we emphasize the current understanding of the mechanism of this process rather than focusing on the many and emerging applications of hydrogen activation by fluoroarylborane-based frustrated Lewis pair systems.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".