High‐efficiency InGaN/GaN quantum well structures on large area silicon substrates
Bibliographic record
Abstract
Abstract The growth techniques which have enabled the realization of InGaN‐based multi‐quantum‐well (MQW) structures with high internal quantum efficiencies (IQE) on 150 mm (6‐in.) silicon substrates are reviewed. InGaN/GaN MQWs are deposited onto GaN templates on large‐area (111) silicon substrates, using AlGaN strain‐mediating interlayers to inhibit thermal‐induced cracking and wafer‐bowing, and using a SiN x interlayer to reduce threading dislocation densities in the active region of the MQW structure. MQWs with high IQE approaching 60% have been demonstrated. Atomic resolution electron microscopy and EELS analysis have been used to study the nature of the important interface between the Si(111) substrate and the AlN nucleation layer. We demonstrate an amorphous SiN x interlayer at the interface about 2 nm wide, which does not, however, prevent good epitaxy of the AlN on the Si(111) substrate.
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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".