Enhanced bandgap blue-shift in InGaAsP multiple-quantum-well laser structures by low-temperature-grown InP
Bibliographic record
Abstract
Quantum well intermixing (QWI) in an InGaAsP multiple-quantum-well (MQW) laser structure is demonstrated using an InP epitaxial layer grown at 300 °C, by gas source molecular beam epitaxy, followed by rapid thermal annealing. Photoluminescence is used to compare the magnitude of the QWI process between low-temperature (LT)- and normal-temperature (NT, 470 °C)-grown InP layers as a function of both anneal temperature and time. For example, after an anneal at 780 °C, a large bandgap blue-shift of ~197 nm is observed in MQW structures capped with LT-InP as compared to an ~35 nm shift in identical structures capped with NT-InP. Also, the effect of the LT-InP capping is compared to NT-InP, capped with a dielectric (~100 nm of SiO 2 ), following anneal at 800 °C for 60 s. This shows blue-shifts of ~243 and ~142 nm, 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".