Emission energy tuning of InAs-quantum dots for fabrication of broadband superluminescent diodes
Bibliographic record
Abstract
Multiple layers of InAs quantum dots (QDs) where the dots height was tuned from one layer to another have been grown and characterized. The desired dots height within one layer was controlled by the thickness of the GaAs cap layer grown at low temperature (@510°C) before annealing the dots to 610°C. Four combined layers of QDs where the thickness of the cap layer was varied from 2.8 nm to 6.5 nm resulted in a photoluminescence spectrum with full width at half maximum of 125 nm at peak wavelength energy of 1.06 ¿m. Overlapping several layers of QDs of different heights is a reliable and predictable approach that can be used to engineer the bandwidth emission spectrum for fabrication of 1 ¿m broadband superluminescent diodes. 3 dB and 10 dB bandwidth of 100 nm and 230 nm were obtained under 200 mA injection current in CW operation mode at 55 K, respectively.
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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".