Highly selective monosubstitution of symmetrical dialkoxysilanes in continuous flow: Kinetics and mechanisms research
Bibliographic record
Abstract
Abstract Monosubstituted symmetrical dialkoxysilanes, intermediates in the production of numerous well‐known materials, present challenges for selective monosubstitution due to the presence of two alkoxy groups in similar chemical environments. Notably, kinetic studies on this phenomenon have not been documented. In addressing this knowledge gap, we developed a continuous flow system to the reaction kinetics between diethoxydimethylsilane and vinyl magnesium chloride, enhancing our understanding of these reactions. We initially analyzed the reaction order, pre ‐exponential factors, and activation energies systematically. The kinetic investigation revealed that the partial reaction order for diethoxydimethylsilane was first‐order, the partial reaction order for vinyl magnesium chloride was also first‐order, and the overall reaction order was second‐order. The activation energy of the main reaction was 39.21 kJ/mol, and the activation energy of the side reaction was 59.72 kJ/mol. Therefore, precise control of the reaction conditions is essential for improving the yield. This kinetic investigation identified a potential reaction mechanism, which was later confirmed through a series of experiments. These experiments accurately determined the applicable concentration and temperature ranges for our kinetic model. Further, simulations of the model assessed the influences of reaction temperature and molar ratios on the monosubstitution selectivity, aiming to achieve controlled reaction outcomes. This study provides new insights into the reaction kinetics of Grignard reagents with symmetrical dialkoxysilanes and offers valuable guidance for optimizing reaction conditions in industrial applications. This study demonstrates selective monosubstitution of symmetrical dialkoxysilanes in a laminar flow reactor. Compared to traditional batch processes, the laminar flow reactor achieved milder conditions and higher selectivity, reaching 99.5% selectivity and 97.9% yield through kinetic studies and model simulations.
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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) | 0.000 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".