Synthesis and Photoluminescent Properties of Size-Controlled Germanium Nanocrystals from Phenyl Trichlorogermane-Derived Polymers
Bibliographic record
Abstract
We report the preparation of luminescent oxide-embedded germanium nanocrystals (Ge-NC/GeO2) by the reductive thermal processing of polymers derived from phenyl trichlorogermane (PTG, C6H5GeCl3). Sol-gel processing of PTG yields air-stable polymers with a Ge:O ratio of 1:1.5, (C6H5GeO1.5)n, that thermally decompose to yield a germanium rich oxide (GRO) network. Thermal disproportionation of the GRO results in nucleation and initial growth of oxide-embedded Ge-NC, and subsequent reaction of the GeO2 matrix with the reducing atmosphere results in additional nanocrystal growth. This synthetic method affords quantitative yields of composite powders in large quantities and allows for Ge-NC size control through variations of the peak thermal processing temperature and reaction time. Freestanding germanium nanocrystals (FS-Ge-NC) are readily liberated from Ge-NC/GeO2 composite powders by straightfoward dissolution of the oxide matrix in warm water. Composites and FS-Ge-NC were characterized using thermogravimetric analysis (TGA), Fourier transform infrared spectroscopy (FTIR), Raman spectroscopy, X-ray powder diffraction (XRD), X-ray photoelectron spectroscopy (XPS), transmission electron microscopy (TEM), selected area electron diffraction (SAED), energy dispersive X-ray spectroscopy (EDX), and photoluminescence (PL) spectroscopy.
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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) | 0.000 | 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".