Recent Advances on Design and Synthesis of Chiral Imidazolium Ionic Liquids and their Applications in Green Asymmetric Synthesis
Bibliographic record
Abstract
Over the past decade, catalysis by ionic liquids (ILs) has experienced a tremendous growth in the context of “Green Chemistry”, and there are numerous examples of a variety of catalytic reactions that have been successfully carried out in such neoteric media.The great enthusiasm for catalysis in ILs is not only driven by the curiosity of chemists, but also due to the growing awareness of developing greener reactions or process media in catalytic science and greener catalytic technologies due their advantages of unique physical and chemical properties as compared to traditional volatile organic solvents.Recently, development of chiral ionic liquids and their applications in asymmetric synthesis have attracted much attention as these reactions have widespread applications in the synthesis of chiral drugs and pharmaceutical industries. Asymmetric induction is mainly achieved by the use of chiral substrates or reagents, chiral catalysts or enzymes. Owing to the vast number of structurally different room temperature ILS that have been synthesized, this review focuses on imidazolium ionic liquids that possess chirality either in the imidazolium moiety or in the anion moiety. The aim of this review is to highlight the recent breakthrough of Chiral ILs in chirality transfer or chiral recognition when used as solvent or co-solvent: the case of task specific ionic liquids is beyond the scope of this review. In the first part, the synthesis of of CILs has been presented and the second part of the review has been devoted on the applications of such CILs in green asymmetric synthesis as well as various pharmaceutical industries.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".