Mechanistic study of double boron–silicon exchange reactions between dibenzosiloles and boron tribromide
Bibliographic record
Abstract
This paper describes a mechanistic study on double boron-silicon exchange reactions between dibenzosiloles and boron tribromide. This type of reaction presents a safe and environmentally benign approach to convert electron-rich siloles into corresponding electron-deficient boroles and hence shows intriguing potential for the synthesis of boron-doped π-conjugated molecular materials. However, the detailed mechanisms for such reactions have not yet been established in the current literature. In this work, we performed density functional theory (DFT) calculations in conjunction with NMR analysis to unravel the reaction pathways and energy profiles for relevant boron-silicon exchange reactions where two dibenzolesiloles and a phenanthrosilole were employed as reactants, respectively. Our results have shown that excess boron tribromide provides beneficial microsolvation effects on key transition states and reactive intermediates to lower the activation energy barrier for the overall reaction. In the meantime, the substitution pattern at the bay region of the dibenzosilole framework exerts significant impacts on the potential energy surface of the reaction; increased steric hindrance at the bay region decelerates the second boron-silicon exchange step, while extended π-conjugation at the bay region makes the first boron-silicon exchange more challenging. Overall, our computational and experimental results provide an in-depth understanding of the reactivity and scope of this type of reaction, which in turn serves as useful guidance for ongoing research in the field of borole-based organic optoelectronic materials.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".