Electronic band structure and material gain of III-V-Bi quantum wells grown on GaSb substrate and dedicated for mid-infrared spectral range
Bibliographic record
Abstract
The 8-band kp Hamiltonian is applied to calculate electronic band structure and material gain in III-V-Bi quantum wells (QWs) grown on GaSb substrates. We analyzed three Bi-containing QWs (GaSbBi, GaInSbBi, and GaInAsSbBi) and different Bi-free barriers (GaSb and AlGaInAsSb), lattice matched to GaSb. Bi-related changes in the electronic band structure of III-V host incorporated into our formalism are based on recent ab-initio calculations for ternary alloys (III-Ga-Bi and III-In-Bi) [Polak et al., Semicond. Sci. Technol. 30, 094001 (2015)]. When compared to Bi-free QWs, the analyzed Bi-containing structures show much better quantum confinement in the valence band and also larger redshift of material gain peak per percent of compressive strain. For 8 nm thick GaInSb/GaSb QWs, material gain of the transverse electric (TE) mode is predicted at 2.1 μm for the compressive strain of ε = 2% (32% In). The gain peak of the TE mode in 8 nm thick GaSbBi/GaSb QW reaches this wavelength for compressive strain of 0.15% that corresponds to about 5% Bi. It has also been shown that replacing In atoms by Bi atoms in GaInSbBi/GaSb QWs while keeping the same compressive strain (ε = 2%) in QW region enhances and shifts gain peak significantly to the longer wavelengths. For 8 nm wide GaInSbBi/GaSb QW with 5% Bi, the gain peak is predicted at around 2.6 μm, i.e., is redshifted by about 400 nm compared to Bi-free QW. For 8 nm wide GaInAsSbSb QWs (80% In, 5% Bi, and ε = 2%) with proper AlGaInAsSb barriers, it is possible to achieve large material gain even at 4.0 μm.
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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".