Nanocavities and germanium nanocrystals produced by Ge ion implantation in fused silica
Bibliographic record
Abstract
High-resolution SEM images of germanium nanocrystals (Ge-nc) synthesized by ion implantation in fused silica samples annealed at temperatures below and above the melting point of Ge show a strong size-selective depth-distribution of nanostructures, as evidenced by the correlation between the dimension of the observed objects and the local concentration of implanted Ge measured by Rutherford backscattering spectroscopy (RBS). Whereas the Ge-nc nucleation seems to obey the Ostwald ripening process in samples annealed below 900 °C, Ge desorption effects, non-uniform in depth, in conjunction with the formation of large and spherical nanocavities, become dominant for annealing performed above the solid-liquid phase transition of Ge. Measurements for different annealing times at 1050 °C show two distinct processes in the Ge desorption dynamics: the first is related to direct Ge outgassing effects during the nucleation of Ge-nc, which occurs within the first minutes of the thermal annealing, while the second is due to the release of Ge from Ge-nc, associated with the formation of nanocavities. The formation rate of these nanocavities is more efficient at greater depth than in the vicinity of the sample surface. It appears to be strongly dependent on the local concentration of defects, responsible for the reduction of the Ge diffusion, and to be related to the breaking of Ge-O and Si-Ge bonds at the Ge-nc/SiO(2) interface.
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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 | 0.000 | 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 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".