Electronic Band Structure and Material Gain of Dilute Nitride Quantum Wells Grown on InP Substrate
Bibliographic record
Abstract
The eight-band kp Hamiltonian is applied to calculate electronic band structure and material gain in dilute nitride quantum wells (QWs) grown on InP substrate. Three N-containing QW materials (GaInNAs, GaNAsSb, and GaNPSb) and different N-free barriers (GaInAs, GaAsSb, GaPSb, AlGaInAs, GaInPAs, AlGaAsSb, GaPAsSb, and AlGaPSb) lattice matched to InP are analyzed. It is shown that Ga0.17In0.83NyAs1-y-QWs with Ga0.47In0.53As, Al0.23Ga0.24In0.53As, or Ga0.17In0.83P0.63As0.37barriers are a very good gain medium for long-wavelength lasers grown on InP substrates. For N-free QWs the transverse electric (TE) mode of the material gain develops at 2.1 μm. This gain peak shifts toward longer wavelengths upon the incorporation of nitrogen and reaches the wavelength of ~2.8 Mm for 3% N. For GaNyAs0.26-ySb0.74-QWs no quantum confinement or very weak quantum confinement exist for electrons in N-free QWs with the ternary barrier (i.e., GaAs0.51Sb0.49) and quaternary (Al0.23Ga0.77As0.51Sb0.49and GaP0.25As0.15Sb0.60) barriers, respectively. However, the quantum confinement in the conduction band strongly increases after incorporation of nitrogen. For GaNyAs0.26-ySb0.74-QWs with 3% N gain peak for TE mode exists at 3.2 μm. Very similar changes in electronic band structure and material gain are noticed for GaNyP0.26-ySb0.74-QWs with GaP0.35Sb0.65, Al0.23Ga0.77As0.52Sb0.48, and GaP0.25As0.15Sb0.60barriers. In that case gain peak (TE mode) for GaN0.03P0.23Sb0.74-QW with GaP0.35Sb0.65barrier is at 3.6 μm. The intensity and the shape of material gain spectra in the three QW system vary with changes of the nitrogen concentration and the barrier content. At carrier concentration of 5 × 1018cm-3, the largest material gain exists for Ga0.17In0.83NyAs1-y-QWs with Al0.23Ga0.24In0.53As and Ga0.17In0.83As0.37Ga0.63barriers.
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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".