Comparison of the Reactivities of Dimethylsilylene (SiMe<sub>2</sub>) and Diphenylsilylene (SiPh<sub>2</sub>) in Solution by Laser Flash Photolysis Methods
Bibliographic record
Abstract
Laser flash photolysis studies have been carried out with the goal of comparing the reactivities of dimethyl- and diphenylsilylene (SiMe 2 and SiPh 2, respectively) toward a comprehensive series of representative substrates in hexane solution under common conditions. The silylenes are generated using dodecamethylcyclohexasilane ( 1 ) and 1,1,3,3-tetramethyl-2,2-diphenyl-1,2,3-trisilacyclohexane ( 9 ), respectively, as photochemical precursors. The reactions examined include O−H, O−Si, and M−H (M = Si, Ge, Sn) bond insertions, Lewis acid−base complexation with tetrahydrofuran, (1+2) cycloaddition to C C and C⋮C multiple bonds, chlorine atom abstraction from CCl 4, and reaction with molecular oxygen; the kinetic data for SiPh 2 are accompanied by product studies in most cases. Further insight into the mechanisms of these reactions is provided by the identification of reaction intermediates and/or transient products in some cases; notable examples include the reactions of SiPh 2 with methoxytrimethylsilane, carbon tetrachloride, and molecular oxygen. With several of the substrates that were studied, comparison of the kinetic data for SiPh 2 to previously reported rate constants for reaction of dimesitylsilylene in cyclohexane allows an assessment of the role of steric effects in affecting silylene reactivity. Rate constants could also be determined for quenching of tetramethyldisilene (Si 2 Me 4 ) with molecular oxygen, CCl 4, and several other reagents that were studied.
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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 | 0.000 | 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) | 0.002 | 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".