Bright photoluminescence from ordered arrays of SiGe nanowires grown on Si(111)
Bibliographic record
Abstract
We report on the optical properties of SiGe nanowires (NWs) grown by molecular beam epitaxy (MBE) in ordered arrays on SiO2/Si(111) substrates. The production method employs Au catalysts with self-limited sizes deposited in SiO2-free sites opened-up in the substrate by focused ion beam patterning for the preferential nucleation and growth of these well-organized NWs. The NWs thus produced have a diameter of 200 nm, a length of 200 nm, and a Ge concentration x = 0.15. Their photoluminescence (PL) spectra were measured at low temperatures (from 6 to 25 K) with excitation at 405 and 458 nm. There are four major features in the energy range of interest (980-1120 meV) at energies of 1040.7, 1082.8, 1092.5, and 1098.5 meV, which are assigned to the NW-transverse optic (TO) Si-Si mode, NW-transverse acoustic (TA), Si-substrate-TO and NW-no-phonon (NP) lines, respectively. From these results the NW TA and TO phonon energies are found to be 15.7 and 57.8 meV, respectively, which agree very well with the values expected for bulk Si1- x Ge x with x = 0.15, while the measured NW NP energy of 1099 meV would indicate a bulk-like Ge concentration of x = 0.14. Both of these concentrations values, as determined from PL, are in agreement with the target value. The NWs are too large in diameter for a quantum confinement induced energy shift in the band gap. Nevertheless, NW PL is readily observed, indicating that efficient carrier recombination is occurring within the NWs.
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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".