Photonic band gap templating using optical interference lithography
Bibliographic record
Abstract
We describe the properties of three families of inversion-symmetric, large photonic band-gap (PBG) template architectures defined by iso-intensity surfaces in four beam laser interference patterns. These templates can be fabricated by optical interference (holographic) lithography in a suitable polymer photo-resist. PBG materials can be synthesized from these templates using two stages of infiltration and inversion, first with silica and second with silicon. By considering point and space group symmetries to produce laser interference patterns with the smallest possible irreducible Brillouin zones, we obtain laser beam intensities, directions, and polarizations which generate a diamond-like (fcc) crystal, a novel body-centered cubic (bcc) architecture, and a simple-cubic (sc) structure. We obtain laser beam parameters that maximize the intensity contrasts of the interference patterns. This optimizes the robustness of the holographic lithography to inhomogeneity in the polymer photo-resist. When the optimized iso-intensity surface defines a silicon to air boundary (dielectric contrast of 11.9 to 1), the fcc, bcc, and sc crystals have PBG to center frequency ratios of 25%, 21%, and 11%, respectively. A full PBG forms for the diamond-like crystal when the refractive index contrast exceeds 1.97 to 1. We illustrate a non-inversion symmetric PBG architecture that interpolates between a simple fcc structure and a diamond network structure. This crystal exhibits two distinct and complete photonic band gaps. We also describe a generalized class of tetragonal photonic crystals that interpolate between and extrapolate beyond the diamond-like crystal and the optimized bcc crystal. We demonstrate the extent to which the resulting PBG materials are robust against perturbations to the laser beam amplitudes and polarizations, and template inhomogeneity. The body centered cubic structure exhibits the maximum robustness overall.
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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) | 0.001 | 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".