Electron confinement and optical enhancement in<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:msub><mml:mrow><mml:mi mathvariant="normal">S</mml:mi><mml:mi mathvariant="normal">i</mml:mi><mml:mo>/</mml:mo><mml:mi mathvariant="normal">S</mml:mi><mml:mi mathvariant="normal">i</mml:mi><mml:mi mathvariant="normal">O</mml:mi></mml:mrow><mml:mrow><mml:mn>2</mml:mn></mml:mrow></mml:msub></mml:mrow></mml:math>superlattices
Bibliographic record
Abstract
We have performed first-principles calculations of $\mathrm{Si}/{\mathrm{SiO}}_{2}$ superlattices in order to examine their electronic states, confinement, and optical transitions, using linearized-augmented-plane-wave techniques and density-functional theory. Two atomic models having fairly simple interface structure are considered. They differ in the way dangling bonds at interfaces are satisfied. The real and imaginary parts of the dielectric function are calculated at the Fermi-golden-rule level and used to estimate the absorption coefficients. Confinement is demonstrated by the dispersionless character of the electronic band structures in the growth direction. Optical enhancement is shown to exist by comparing the direct and indirect transitions in the band structures with the related transitions in bulk Si. The role played by the interface on the optical properties is assessed by comparing the absorption coefficients from the two models.
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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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".