Synthesis of Si<sub><i>x</i></sub>Ge<sub>1–<i>x</i></sub> Nanocrystals Using Hydrogen Silsesquioxane and Soluble Germanium Diiodide Complexes
Bibliographic record
Abstract
We report an investigation into the formation of Si x Ge 1– x alloy nanocrystals (64 < x < 100) synthesized from mixing GeI 2:PR 3 adducts with hydrogen silsesquioxane (HSQ). The use of trialkylphosphine adducts allows GeI 2 and HSQ to be homogeneously coprecipitated, improving control over the size and composition of the resulting Si x Ge 1– x nanocrystals. This approach yields oxide-embedded and freestanding materials with near-infrared photoluminescence (PL) comparable in quantum efficiency to similarly prepared Si nanocrystals. The formation of bimodal populations of Si-rich and Ge-rich nanocrystals was observed, with homogeneous distribution of Ge within each population. Through changes to precursor stoichiometry and annealing temperature and time, control over particle size and composition was demonstrated. The impact of these factors on the near-IR PL was evaluated. We propose a multistep formation mechanism to account for the formation of separate Si-rich and Ge-rich populations and present indirect evidence for the participation of Ge in the emission process. Materials were analyzed using Fourier transform infrared spectroscopy, Raman spectroscopy, powder X-ray diffraction, PL spectroscopy, high-resolution transmission electron microscopy and spatially resolved energy-dispersive X-ray spectroscopy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 teacher head, 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".