Transition Metal-Free Hydrosilylation and Hydroboration of Unsaturated Carbon-Heteroatom Bonds
Bibliographic record
Abstract
The hydrosilylation or hydroboration of unsaturated C-O and C-N bonds yields valuable reagents and intermediates for organic synthesis. Traditionally, these reactions have been carried out by transition metal catalysts which are generally expensive and toxic, or stoichiometric reagents which produce a significant amount of waste. As such, transition metal-free catalytic alternatives have steadily gained popularity as a more sustainable alternative. This thesis presents the use of cheap and readily available simple alkali metal bases such as KOtBu and nBuLi as powerful catalysts for the reduction of carbonyls and imines. Notably, aldehydes can be selectively obtained through the reduction of tertiary amides and esters, and amines can be produced from nitriles using a similar method. These conversions have previously been relegated to the domain of late transition metal catalysts. Variation of the silane or borane was found to be highly influential in adjusting the chemoselectivity. For example, in the conversion of amides to aldehydes, use of (EtO)3SiH resulted in overreduction to the amine product, whereas (EtO)2MeSiH allowed for selective reduction to the aldehyde equivalent. In this work, we discuss our investigations into the scope and selectivity of this straightforward yet effective system. Additionally, we introduce a new approach for achieving long-term precise control of reaction conditions at low temperatures.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".