Vacuum evaporated porous silicon photonic interference filters
Bibliographic record
Abstract
Porous materials with nanometer-scale structure are important in a wide variety of applications including electronics, photonics, biomedicine, and chemistry. Recent interest focuses on understanding and controlling the properties of these materials. Here we demonstrate porous silicon interference filters, deposited in vacuum with a technique that enables continuous variation of the refractive index between that of bulk silicon and that of the ambient (n approximately 3.5 to 1). Nanometer-scale oscillations in porosity were introduced with glancing angle deposition, a technique that combines oblique deposition onto a flat substrate of glass or silicon in a high vacuum with computer control of substrate tilt and rotation. Complex refractive index profiles were achieved including apodized filters, with Gaussian amplitude modulations of a sinusoidal index variation, as well as filters with index matching antireflection regions. A novel quintic antireflection coating is demonstrated where the refractive index is smoothly decreased to that of the ambient, reducing reflection over a broad range of the infrared spectrum. Optical transmission characterstics of the filters were accurately predicted with effective medium modeling coupled with a calibration performed with spectroscopic ellipsometry.
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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) | 0.000 | 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 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".