Rapid thermal annealing of InAs∕GaAs quantum dots with a low-temperature-grown InGaP cap layer
Bibliographic record
Abstract
A single layer of self-assembled InAs quantum dots was grown on a GaAs (001) substrate by gas source molecular-beam epitaxy. The quantum dots were overgrown with 65nm GaAs, 25nm InGaP, and a 10nm GaAs etch-stop layer. This was either uncapped or capped with 100nm of low-temperature (LT)-grown, lattice-matched InGaP (LT-InGaP) or with a SiO2 layer or Al2O3 layer. Photoluminescence (PL) measurements were made on samples before and after rapid thermal annealing at 550–900°C and for 15–120s at 650°C. Samples capped with LT-InGaP showed a significant blueshift of the PL peak wavelength for anneals above 575°C. By comparison, for the SiO2-capped and uncapped samples, the net blueshift only becomes significant for anneals >700°C, while an Al2O3 cap actually reduces the blueshift and suppresses the intermixing. It appears that the best conditions for spatially controlling the quantum dot intermixing occur with annealing at low temperatures (600–650°C).
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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".