Direct-Gap Photoluminescence from a Si-Ge Multilayer Super Unit Cell Grown on Si<sub>0.4</sub>Ge<sub>0.6</sub>
Bibliographic record
Abstract
Both Si and Ge possess indirect band gaps, which makes them very inefficient light emitters. One way to overcome this limitation is through bandgap engineering. M. d'Avezac et al. predicted in 2012 that a strained SiGe 2 Si 2 Ge 2 SiGe n super unit cell on Si 0.4 Ge 0.6 would have a direct and dipole-allowed gap of 0.863 eV, which is suited for optical fiber applications. Here we report on the epitaxial growth of such a structure and its optical properties, for which purpose two similar samples were prepared by molecular beam epitaxy and solid phase epitaxy. Photoluminescence (PL) spectra were obtained at low temperatures (6–25 K) with excitation at wavelengths of 405 and 458 nm, which emphasize the light emission from the sample superstructure. A strong low-energy PL quadruplet is seen, with peaks near 727, 758, 792 and 822 meV at 6 K, together with a much weaker peak at 871 meV. The ratio of intensities of the strong and weak peaks is the same in both samples. The weak peak at 871 meV is assigned to the dipole-allowed direct-gap transition associated with the super unit cell. The four strong peaks are attributed to dislocation related emission lines of the thick relaxed Si 0.4 Ge 0.6 transition layer.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".