Epitaxial SiGeSn grown on Si by ion implantation
Bibliographic record
Abstract
We have formed SixGe1−x−ySny compounds on Si substrates by ion implantation and annealing and investigated their concentration profiles, crystallization, and optical properties. Ge and Sn ions were implanted in the range (2.5–10) × 1016 Ge/cm2 at 65 keV, and (1.0–4.0) × 1016 Sn/cm2 at 100 keV, resulting in a peak implant dose at a depth of 50 nm for both species. Epitaxially regrown SixGe1−x−ySny layers (110 nm thick) were produced with Ge and Sn contents that allowed bandgap tuning in the (0.88–1.1) eV range. Shifts in photoelectron binding energies (Si 2p, Ge 3d, and Sn 3d) were consistent with ternary compound formation. Sn segregation was observed for annealing temperatures ≥600 °C. A significant increase in the optical absorption coefficient (×104 cm−1 for λ = (800–1700) nm) was observed for SiGe, SiSn, and SiGeSn alloys, with SiGeSn having coefficients several orders of magnitude higher than for Si. Contributions of segregated Sn to these properties were observed. Metastable SixGe1−x−ySny layers were achieved, which may point to a promising route to mitigate Sn incorporation challenges for near-infrared detectors.
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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".