Catalytic Enantioselective Allyl- and Crotylboration of Aldehydes Using Chiral Diol•SnCl<sub>4</sub> Complexes. Optimization, Substrate Scope and Mechanistic Investigations
Bibliographic record
Abstract
We report a novel class of C2-symmetric chiral diols derived from the hydrobenzoin skeleton. The combination of these diols with SnCl4 under Yamamoto's concept of Lewis acid assisted Brønsted acidity (LBA catalysis) leads to high levels of asymmetric induction in the allylboration of aldehydes by commercially available allylboronic acid pinacol ester 1a. The corresponding homoallylic alcohol products of synthetically useful aliphatic aldehydes are obtained in excellent yields with up to 98:2 er. This combined acid manifold is also efficient in catalyzing the diastereo- and enantioselective crotylboration of aldehydes, thus providing the propionate units in >95:5 dr and up to 98:2 er. The X-ray crystal structure of the optimal diol x SnCl4 complex, Vivol (4m) x SnCl4, unambiguously shows the Brønsted acidic character of this LBA catalyst and its highly dissymmetrical environment. Further controls have ruled out a possible boron trans-esterification mechanism with the chiral diol and point to LBA catalyst-derived activation of the pinacol allylic boronates 1. Due to slow dissociation of the diol x SnCl4 complex, a small excess of diol is required in order to suppress a competing racemic cycle catalyzed by free SnCl4.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".