Synthesis of Organosilanes and Investigation of Their Catalytic Activity for Direct Amide Bond Formation
Bibliographic record
Abstract
Amide synthesis is a fundamental reaction in synthetic chemistry due to the abundance of amides in biologically active molecules, synthetic polymers, and commercial products. Coupling reagents that activate the carboxylic acid have become the most well-studied method to direct amide bond formation. Amongst these, carbodiimides, uronium and phosphonium salts, and benzotriazoles are the most common. These reactions, however, are often limited by poor atom economy, and toxic and expensive reagents. Therefore, synthetic chemists need a better method to form amides safely and efficiently. Organosilanes have been reported as greener, efficient alternative amide coupling reagents. Current work in this field often requires a stoichiometric (or more) amount of the silane. While stoichiometric amide coupling reactions are generally the methods of choice for their efficiency and practicality, catalytic amide coupling can present a new step toward greener methodologies to make amides. This thesis explores novel organosilanes that are investigated as catalysts for direct amidation. The silane catalysts are designed to have enhanced reactivity by incorporating a hydrogen bond donor (HBD) to facilitate the formation of a silyl ester intermediate and nucleophilic attack at the carbonyl by the amine coupling partner. The synthesis of various organosilanes have been investigated, including silanes that have an amide or urea, hydroxy, or protonated amine as a HBD. The silanes that have been successfully synthesized were tested as catalysts in direct amidation. Aryl and alkyl silanes, and di- and trisubstituted silanes were used in stoichiometric silane-mediated amide synthesis to study how the substitution on the silicon effects amidation.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".