Short-wavelength laser diodes based on AlInAs/AlGaAs self-assembled quantum dots
Bibliographic record
Abstract
Self-assembled quantum dots (QDs) of highly strained InAlAs have been grown by molecular beam epitaxy in separate-confinement p–i–n heterostructures on (001) GaAs substrates. Results from a systematic study of samples with varying amounts of deposited material relates the observed emission peaks with QD levels, wetting layer states, or barrier materials. For samples with high-QD concentration, lasing is observed in the upper-QD shells. A sample with contact layers improving carrier and optical confinement operates up to room temperature and displays lowered threshold current densities. A threshold current density of ∼4 A/cm2 is measured for this structure at T=5 K and continuous-wave operation is obtained up to T∼77 K. A material gain larger than 1.7×104 cm−1 is measured for this single-layer structure. Lasing is observed in the upper-QD shells for small gain media, and progresses towards the QD lower states for longer cavity lengths representing an emission shift of 45 meV. A minor dependence of the threshold on QD density is found for samples having densities between 20 and hundreds of QDs per micron squared. For samples with multiple QD layers displaying vertical self-assembling, an increase in the emission linewidth is observed compared with single-layer samples and multilayer samples with uncorrelated growth.
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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".