Reaction Optimization, Scalability, and Mechanistic Insight on the Catalytic Enantioselective Desymmetrization of 1,1‐Diborylalkanes via Suzuki–Miyaura Cross‐Coupling
Bibliographic record
Abstract
A method for enantioselective desymmetrization of 1,1-diborylalkanes through a stereoselective Pd-catalyzed Suzuki-Miyaura cross-coupling has been thoroughly optimized. The most effective ligand was found to be a α,α,α,α-tetra-aryl-1,3-dioxolane-4,5-dimethanol (TADDOL)-derived phosphoramidite. Results show that in order to achieve high selectivity, a suitable balance between the sterics of the aryl groups and the amino group on the ligand must be achieved. While the base has been known to facilitate transmetallation in cross-coupling reactions, mechanistic studies on this desymmetrization process reveal that the base, in the presence of KHF2, likely plays an additional role in the hydrolysis of the pinacol boronates to the corresponding boronic acids. Through an in depth optimization of the chiral ligand and mechanistic studies, it was possible to obtain ee values over 90% for several aryl bromides and to develop a reliably scalable process (up to one gram of 1,1-diborylalkane substrate).
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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 | 0.001 | 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 | 0.001 |
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".