Effect of layer separation, InAs thickness, and rapid thermal annealing on the optical emission from a multi-layer quantum wire structure
Bibliographic record
Abstract
Multi-layer InAs quantum wire stacks with different layer separations (8, 15, and 25 nm) and InAs thicknesses (3, 4, 5, and 7 monolayers [ML]) were grown on and embedded in In0.53Ga0.27Al0.20As barrier/spacer layers lattice-matched to an InP substrate. For the samples with 4 ML of InAs and different layer separations, double peak photoluminescence was observed from quantum wire stacks separated by 8 nm, and with a 15 nm spacer layer a long wavelength component was observed extending from the main peak. Only a single peak was found as the spacer layer thickness was increased to 25 nm. For the quantum wire stacks with different InAs layer thicknesses and a separation of 8 nm, double peak photoluminescence spectra were observed in the sample with 4 ML of InAs, and a main peak with a long wavelength component was obtained from the sample with 3 ML of InAs. Only a single peak was detectable for the InAs layer thicknesses of 5 and 7 ML. The optical emission features were studied via temperature and excitation laser power dependent photoluminescence. Based on the photoluminescence and transmission electron microscopy observations, photoluminescence spectral features can be attributed to a bi-modal height distribution in certain samples. In order to extend the optical emission to room temperature, the sample with 5 ML of InAs and an 8 nm spacer layer was subjected to post-growth rapid thermal annealing at different temperatures. The emission wavelength was tunable from 1.63 to 1.72 μm at room temperature.
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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 | 0.000 | 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 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".