Oxidant-Activated Reactions of Nucleophiles with Silicon Nanocrystals
Bibliographic record
Abstract
The oxidant-activated reactivity of Si toward nucleophiles was evaluated for Si nanocrystals (Si-NCs) of differing diameters, d . In the presence of ferrocenium as a one-electron, outer-sphere oxidant, d ≥ 8 nm Si-NCs readily reacted with nucleophiles, including methanol, butanol, butylamine, butanoic acid, butylthiol, and diethylphosphine. However, d < 8 nm Si-NCs did not undergo such reactions, and stronger oxidants such as acetylferrocenium or 1,1′-diacetylferrocenium were required. Butylamine-, butylthiol-, and butanol-functionalized d ≥ 8 nm Si-NCs were partially oxidized and exhibited photoluminescence originating from defect states. In contrast, butanoic acid-functionalized Si-NCs were minimally oxidized and displayed core emission resulting from the excitation and relaxation of electrons across the Si-NC bandgap. Diethylphosphine-functionalized Si-NCs were stable only under inert conditions and showed core emission, with the Si–P bonds being highly susceptible to oxidation and rapidly decomposing upon exposure to ambient conditions. The general reactivity is consistent with the redox potential of the one-electron oxidant and the valence band edge position of the Si-NCs. The trends in reactivity thus provide an example of differential chemical reactions of nanoparticles relative to bulk materials, reflecting the differences in electronic structure and the continuum of electronic properties between variously sized Si nanoparticles and bulk Si samples.
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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".