Studies on the Organocatalytic Enantioselective Michael Addition of Cyclic Ketones and α,α-Disubstituted Aldehydes to α-Nitrostyrenes
Bibliographic record
Abstract
Background: The catalytic asymmetric Michael addition of carbonyl compounds to nitrostyrenes is of interest because the reaction establishes two adjacent stereocenters in one step and the product γ-nitrocarbonyl compounds are synthetically useful intermediates. This reaction has been exhaustively investigated with β-nitrostyrenes as the Michael acceptors but the use of α-nitrostyrenes, for establishing nonadjacent stereocenters in the product, is not well studied. Objective: The aim of this study was to investigate the organocatalytic asymmetric, enamine mediated, Michael addition of cyclic ketones and α,α-disubstituted aldehydes to in situ generated α- nitrostyrenes and to optimize the diastereoselectivity and the enantioselectivity of the reaction. Method: The Michael addition reactions of a series of ketones and aldehydes with a variety of α- nitrostyrenes, that were generated in situ form nitroacetates, were conducted in a selection of solvents in the presence of chiral pyrrolidine catalysts and protic acid additives. Conditions that provided the highest asymmetric induction were identified. Results: Under optimized conditions, γ-nitroketones (up to 99% ee) and γ-nitroaldehydes (up to 79% ee) were obtained. The synthetic utility of the γ-nitroladehydes was demonstrated by converting a representative Michael adduct into a functionalized pyrrolidine. Conclusion: The enamine mediated Michael addition of cyclic ketones and α,α-disubstituted aldehydes to in situ generated α-nitrostyrenes proceeds with moderate to good levels of 1,3-asymmetric induction. The methodology complements the well-known Michael addition reactions of β- nitrostyrene, and provides access to enantiomerically enriched γ-aryl-γ-nitro ketones and γ-aryl-γ-nitro aldehydes. Keywords: Aldehydes, ketones, Michael addition, organocatalysis, α-nitrostyrene, carbonyl compounds.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".