Optical and Electronic Propreties of GeSn and GeSiSn Heterostructures and Nanowires
Bibliographic record
Abstract
The first part of this work reports on detailed studies of the influence of both strain and composition on the band structure of GeSiSn ternary alloys. First, we developed a simple yet rigorous semi-empirical second nearest neighbors tight binding sp3s* method that incorporates the effect of substitutional disorder. We have found that the composition of α-Sn at the direct to indirect crossover of the ternary alloy decreases from 11% in a fully relaxed alloy to 7% in tensile strained alloy (for a strain value of 0.71%). In the latter case, we have considered a thin GeSiSn layer is epitaxialy grown on a thin Ge substrate. The last section of this work addresses the behavior of GeSn/Ge core-shell nanowires. Herein, we have solved the effective mass Hamiltonian in cylindrical coordinates using a finite difference technique for the core-shell nanowires where the core and the shell are made of different alloys. We have found that above a critical doping concentration of 5×1016 cm-3 and below a core radius of 20 nm, the electron density is localized in the Ge shell for the Ge0.9Sn0.1/Ge core-shell nanowire system.
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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".