Organocatalytic Approaches to Asymmetric Oxidation: Epoxidation of α-Branched Enals and α-Benzoyloxylation of Carbonyl Compounds
Bibliographic record
Abstract
This work describes the development of enantioselective oxidation reactions of carbonyl compounds using covalent organocatalysis. In the first part, asymmetric epoxidation of α-branched α,β-unsaturated aldehydes with aqueous hydrogen peroxide is presented. An exceptionally synergistic combination of a primary cinchona alkaloid-derived amine and a chiral BINOL-derived phosphoric acid was found to promote the reaction with excellent enantiocontrol for a wide variety of α,β-disubstituted and α-monosubstituted enals. Conformational analysis of catalytically relevant intermediates using NMR and computational techniques enabled the rationalization of the absolute stereochemistry of products. The second part of this thesis describes a highly efficient direct catalytic asymmetric α-benzoyloxylation of cyclic ketones. The same primary amine paired with an inorganic acid was found to be an effective catalyst for a wide range of substrates. The methodology was applied to the first asymmetric synthesis of (+)-2β,4-dihydroxy-1,8-cineole, a predicted terpenoid metabolite in mammals. Preliminary investigations on the α-benzoyloxylation of α-branched aldehydes and α-branched enals using this catalytic system demonstrated significant potential of the method for the enantioselective formation of oxygenated quaternary stereocenters.
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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 | 0.001 |
| 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".