Effect of Dry Oxidation on the Optical Response and Morphology of Mesoporous Hybrid Structures
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide This work presents a detailed experimental and theoretical investigation of periodic and quasiperiodic hybrid photonic structures composed of porous silicon (PS) and thermally oxidized porous Si–SiO 2 . Designed with a Fibonacci sequence and embedded between asymmetric Bragg mirrors, the structures were fabricated via electrochemical etching on p-type (100)-oriented silicon wafers with distinct doping levels (P + and P ++ ). A two-step dry oxidation process (350 °C and 800 °C) was employed to stabilize the porous network and transform PS into a robust hybrid Si–SiO 2 matrix. SEM and EDS analyses revealed that wafer doping significantly affects morphology, oxide growth, and silicon retention, with P + -based structures maintaining smoother surfaces and higher Si content postoxidation. Optical transmission spectra revealed that oxidation induces substantial blue shifts in localized defect modes, resulting from changes in refractive index and optical path length. Notably, porous Si–SiO 2 structures fabricated from P + wafers exhibit sharper and less attenuated localized modes compared to those from P ++ wafers, due to reduced Rayleigh scattering losses. Scattering loss estimations corroborate these findings. This study uniquely correlates morphology, doping, and oxidation kinetics to optical performance, demonstrating that dry oxidation can be strategically employed to enhance light confinement and reduce optical losses in mesoporous Fibonacci-based photonic structures. These results position porous Si–SiO 2 hybrid systems as promising platforms for low-loss photonic devices, sensors, and microcavity-based applications.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".