Strong near-infrared photoluminescence and absorption from Si/Si1−xGex type-II multiple quantum wells on bulk crystal SiGe substrates
Bibliographic record
Abstract
We report a study of photoluminescence (PL) and optical absorption in high-quality tensile-strained Si type-II multiple quantum wells (QWs) grown on bulk crystal SiGe substrates by using low-temperature ultrahigh-vacuum chemical vapor deposition. Detailed PL experiments, as a function of excitation density together with applied uniaxial stress, were performed to study the band alignment and to help elucidate the origin of the observed PL peaks. Spatially direct and indirect transitions of the Si QWs and an intense broad subgap PL were observed. With increasing excitation power, the PL lines of Si QWs shift to lower energies, whereas the broad PL shifts to higher energy. The applied [110] compressive stress results in a redshift of the substrate PL lines, as expected, but a blueshift of both the Si QW PL and the broad PL lines. The optical absorption data also show strong absorption in the near-infrared region where the broad PL was observed. Near the absorption edge (Eg), the energy dependence obeys a square law rather than a square root law, suggesting that Eg is associated with a quasi-direct transition. The Eg value deduced according to the square law agrees well with the broad PL peak energy provided that temperature-dependent Eg, excitonic binding energy, and exciton localization energy, as well as quantum confinement are considered.
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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".