Porous silicon-based UV microcavities (Conference Presentation)
Bibliographic record
Abstract
The theoretical and experimental study of porous silicon-based UV microcavities is discussed in this work. The obtaining of CMs in the Ultraviolet range expands the field of research of porous silicon photonic structures. The porous silicon microcavities (PSM) consisted of two Bragg reflectors (BRs) with a defect between them. It was fabricated by electrochemical etching. Microcavities (MCs) were subjected to dry oxidation process (DOP). In this way we obtained an oxidized porous silicon (OPS) that induces a shift of the response to the ultraviolet (UV) region on both, the minimum peak of the reflectance spectrum and the maximum peak of the transmittance spectrum; two UV microcavities showed maximum transparency in the UV of 67 %. The shift is explained as due to the formation of silicon dioxide (SiO₂); this wavelength shift shows a logarithm-like function of oxidation times. It was used a theoretical model to predict the refractive index of the MCs that contains two components (Si and air) and tree component (Si, SiO₂, and air). Moreover, a photonic model was used to obtain the photonic band gap structure and the defect modes of different MCs in the UV-Visible range. The theoretical results showed that the experimental peaks within the UV photonic bandgap are indeed defect modes. Characterization of MCs was performed by SEM, FTIR and UV-Vis-NIR spectroscopy before and after the DOP. These results open the possibility to create silicon-based photonic structures within the UV range where usually silicon or porous silicon either strongly absorb or scatter light.
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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) | 0.004 | 0.001 |
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".