Silyl Esters as Reactive Intermediates in Organic Synthesis
Bibliographic record
Abstract
Abstract Silyl esters have been exploited as metastable reaction intermediates, both purposefully and unintentionally, since at least the 1960s. Their reactivity is broadly related to the substituents on the silicon, and in this way their properties can be readily modulated. Silyl esters have unique reactivity profiles that have been used to generate downstream products of a range of functionalities, and because of this many excellent methods for the synthesis of a variety of value-added chemicals have been developed. Furthermore, because of the frequent use of hydrosilanes as terminal reductants in catalytic processes, silyl ester intermediates are likely more commonly utilized by synthetic chemists than currently realized. This review comprehensively summarizes the reactions known to take advantage of reactive silyl ester intermediates and discusses examples of catalytic reactions that proceed in an unanticipated manner through silyl ester intermediates. 1 Introduction 2 Synthesis of Silyl Esters 3 Making Amides from Silyl Esters 3.1 Amidation Using Chlorosilanes 3.2 Amidation Using Azasilanes 3.3 Amidation Using Oxysilanes 3.4 Amidation Using Hydrosilanes 3.5 Amine Formation via Amidation/Reduction 3.6 Miscellaneous 4 Mechanistic Investigations of Amidation 4.1 Mechanism of Amidation Using Chlorosilanes 4.2 Mechanism of Amidation Using Hydrosilanes 4.3 Mechanism of Amidation Using Oxy- or Azasilanes 5 Making Esters from Silyl Esters 6 Making Aldehydes, Alcohols, Amines, and Alkanes via Reduction 6.1 Aldehyde Synthesis by Metal-Free Reduction 6.2 Aldehyde Synthesis by Metal-Mediated Reduction 6.3 Alcohol Synthesis by Metal-Mediated Reduction 6.4 Amine Synthesis 6.5 Alkane Synthesis by Metal-Free Reduction 7 Making Acid Chlorides from Silyl Esters 8 In Situ Generated Silyl Esters and Ramifications for Catalysis 9 Conclusion
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".