Direct Arylation of Silicon Nanocrystals with Hexadehydro‐Diels–Alder‐Derived Benzynes
Bibliographic record
Abstract
Colloidal silicon nanocrystals (SiNCs) have garnered significant interest in optoelectronics and biomedical applications. Direct arylation provides pathways to enhance the solution processability of particles and manipulate the photophysical and electronic properties of SiNCs. Unfortunately, existing methods employed to prepare aryl-functionalized SiNCs are based on organometallic coupling or transition-metal-catalyzed strategies, which require metal-based reagents for preactivation or the precursors and complicated post-treatment processes for product purification. Herein, we demonstrate a metal-free method that directly functionalizes SiNCs with aryl-based ligands. We design a series of benzyne derivatives formed from the thermal cyclization of predesigned alkynes, allowing efficient arylation on hydride-terminated silicon surfaces under mild conditions. These aryl-functionalized SiNCs exhibit strong blue emissions with nanosecond-scaled decay, suggesting the formation of a new radiative recombination channel on SiNC surfaces.
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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".