Asymmetric Csp <sup>3</sup> –Csp <sup>3</sup> Bond Formation via Ni-Catalyzed Regio- and Enantioselective Hydroalkylation of Linear 1,3-Diene through Carbonyl Umpolung
Bibliographic record
Abstract
Asymmetric Csp 3 –Csp 3 bond formation has been a grand pursuit in synthetic chemistry. The regioselective and enantioselective hydroalkylation of 1,3-diene has emerged as an appealing approach for constructing chiral allylic Csp 3 –Csp 3 bonds. However, this method is presently confined to the use of stabilized Csp 3 nucleophilic substrates. Herein, we present a nickel-catalyzed asymmetric hydroalkylation of 1,3-dienes with simple unstabilized alkyl carbanion enabled by naturally abundant carbonyls’ umpolung under mild reaction conditions. A range of simple alkylated chiral allylic compounds were generated in good to high yields (up to 96%), with an enantiomeric ratio (er) of up to 98:2 to form the Csp 3 –Csp 3 bond. The protocol is applicable to heterocycles, polyenes, and unsaturated hydrazones as well as late-stage functionalization of various complex pharmaceuticals. Density functional theory calculations elucidated the mechanism and enantioselectivity of the reaction. An enantiocontrol model is also proposed, emphasizing the crucial role of a chiral NHC ligand in facilitating this asymmetric reaction, as revealed by the two-layer two-dimensional (2D) contour maps.
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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) | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".