Optimized photoluminescence of Si nanocrystals produced by ion implantation
Bibliographic record
Abstract
We have produced Si nanocrystals by implanting Si ions at 90 keV into 430 nm thick SiO<sub>2</sub> films, to fluences from 6 x 10<sup>16</sup> to 1.4 x 10<sup>17</sup> ions/cm<sup>2</sup> (or 9 - 20 at. % excess Si). High temperature anneals at 1100°C and 1200°C in an N<sub>2</sub> ambient followed, to coalesce the excess silicon into nanocrystalline precipitates. Samples were further annealed for 1 hr at 450°C in a 5% H2 95% N<sub>2</sub> ambient to passivate dangling bonds and reduce non-radiative electron-hole recombinations. The films were then characterized by Photoluminescence (PL), and the PL intensity is maximized at 17 at. % excess silicon. This suggests that quantum confinement and/or the total number of nanocrystals is optimized at a Si excess of 17 at. % for high temperature annealing conditions. Annealing at 1100°C results in a greater number of smaller nanocrystals than annealing at 1200°C, and consequently a greater PL intensity. The peak wavelength of light emission reaches equilibrium after a much shorter annealing time than does the PL intensity, suggesting that the nanocrystals attain their final size before the film reaches equilibrium. Positron Annihilation Spectroscopy (PAS) was used to investigate defects in the film. The majority of defects introduced by ion implantation annealed away very quickly, in correlation with the rapid equilibration of the peak wavelength of PL emission.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".