Toward realization of photonic bandgap materials with glancing angle deposition
Bibliographic record
Abstract
A modern challenge of materials science and physics is the creation and understanding of photonic crystals. Glancing Angle Deposition (GLAD) enables the growth of thin film materials with designable morphological structure on the scale of tens of nanometers, similar to proposed geometries of photonic crystals. Here we present recent progress toward the realization of photonic crystals with GLAD. Square spiral films of silicon were fabricated with GLAD, and were analyzed with scanning electron microscopy (SEM) and spectroscopic ellipsometry. The SEM images clearly show a periodic and spiral structure, similar to that recently predicted to have a robust three-dimensional bandgap. Ellipsometric analysis is ongoing, with as yet no distinct features that might suggest photonic bandgaps. To measure and control the in-plane ordering of silicon thin films, we have deposited and characterized pillar microstructures, producing an indirect measurement of film porosity with varying flux incidence. Two dimensional Fourier transforms were applied to plan view SEM images of porous pillar microstructures, showing no regular lattice but a broad ring that suggests a short range average spacing. In-plane periodicities were observed up to 100nm. Ongoing research is toward fabricating and analyzing photonic crystal structures at visible and infrared wavelengths.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".