Effect of intermixing on bulk and interface Raman modes in GaAs:AlAs superlattice waveguide structures
Bibliographic record
Abstract
Spatially resolved Raman spectroscopy at room temperature is used to study quantum well intermixing in GaAs:AlAs superlattice structures. Phonon modes are probed from the side facet along the [110] direction. The intermixing leads to the appearance of interfacial alloy modes and degraded the intensity of the superlattice interface (IF) modes, which can be used as a sensitive indicator of superlattice quality. These changes in the Raman spectra, along with spatially resolved photoluminescence, are used to distinguish the degree of intermixing in samples intermixed by impurity free vacancy diffusion at 850–950 °C, and to investigate the bandgap modulation in a periodically intermixed bandgap grating fabricated using ion implantation induced disordering. The shift of the GaAs-transverse optic mode to the GaAs-like transverse optic alloy mode and the degradation of the GaAs-IF mode are shown to provide the best indication of the extent of intermixing. Due to the large contrast in the GaAs-IF mode intensity between as-grown and intermixed superlattice, using IF modes is found to be a promising route for characterizing the resolution of the superlattice bandgap grating.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".