(Luminescence and Display Materials Division Centennial Outstanding Achievement Award) Band Gap Luminescence from Nanometer Thick Si/SiO<sub>2</sub> Quantum Wells
Bibliographic record
Abstract
In opto-electronics and photonics, the severe disadvantage of an indirect band gap has limited the application of elemental silicon. Amongst a number of diverse approaches to engineering efficient light emission in silicon nanostructures, one system that has received considerable attention has been Si/SiO2 quantum wells. Engineering such structures has not been easy, because to observe the desired quantum confinement effects, the quantum well thickness has to be less than 5 nm. Nevertheless, such ultra thin structures have now been produced by a variety of techniques. The SiO2 layers are amorphous, but the silicon layers can range from amorphous through nanocrystalline to single-crystal form. The fundamental band gap of the quantum wells has been measured primarily by optical techniques and strong confinement effects have been observed. A number of theories based primarily on ab initio approaches have been developed to explain these results with varying degrees of success. A detailed comparison is made between theoretical and experimental determinations of the band gap in Si/SiO2 quantum wells.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.128 | 0.080 |
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".