Controlled group V intermixing in InGaAsP quantum well structures and its application to the fabrication of two section tunable lasers
Bibliographic record
Abstract
We report the technique of controlled group V quantum well intermixing (QWI) in a compressively strained In0.76Ga0.24As0.85P0.15/In0.76Ga0.24As0.52P0.48 multiquantum well laser structure and its application to the fabrication of two-section tunable lasers. The blueshift of the band-gap energy was enhanced by capping the samples with films of SiO2 or low-temperature grown InP, while suppressed by a SixNy film with a refractive index of about 2.1. Spatially selective band-gap tuning was achieved by patterning the dielectric film into dot and strip arrays with different surface coverage. Time-of-flight secondary ion mass spectra showed that the enhanced blueshift was caused by the interdiffusion of group V atoms between the quantum wells and barriers. A group V interstitial interdiffusion mechanism is proposed for the sample capped with SiO2 and this is supported by the even more efficient intermixing induced by low-temperature InP, which contains a high concentration of excess phosphorus. A two-section tunable laser operating around 1.55 μm was fabricated using this QWI technology. A tuning range of about 10 nm was demonstrated by simply changing the current injected into the phase tuning section.
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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 | 0.001 | 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".