The effect of thin gap insertion layer on InP nanostructure grown by metal–organic vapour phase epitaxys
Bibliographic record
Abstract
Abstract The effect of thin GaP insertion layers on the structural and optical properties of InP/In0.49Ga0.51P self‐assembled quantum dots (SAQDs) on GaAs (001) substrate grown by metal–organic vapour phase epitaxy has been reported. The properties of InP/In0.49Ga0.51P SAQDs are modified when a thin (1–4 ML) GaP layer is inserted underneath the InP quantum dots (QDs). Deposition of the GaP insertion layer affects the dot dimension and improves the size uniformity. The density, dimension and uniformity of InP QDs strongly depend on the GaP insertion layer thickness. This variation in QD size is a result of a material nucleation effect caused by atomic intermixing between the InP QDs and underlying GaP insertion layer and surface energy. The insertion of GaP layer led to tuning the emission wavelength and narrowing of full width at half maximum (FWHM) when they are characterised by PL measurements at room temperature. © 2012 Canadian Society for Chemical Engineering
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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".