Selective transmittance of linearly polarized light in thin films rationally designed by FDTD and FDFD theories and fabricated by glancing angle deposition
Bibliographic record
Abstract
Columnar thin films exhibiting linear polarization selectivity have been theoretically investigated and fabricated using the glancing angle deposition (GLAD) technique. The film structure employed an s-shaped columnar morphology that may be either smoothly bent or composed of discrete segments. Finite-difference time-domain and frequency-domain methods have been used to model these thin film structures numerically. Simulation results have yielded optimal geometries in which the films exhibit either a single frequency band with polarization-selective transmittance or two separated frequency bands each transmitting one of two orthogonal linearly polarized modes. Based on these designs, a series of TiO2 films were grown by GLAD with continuous and discrete s-shaped columnar morphology. Experimental measurements by spectrophotometry verified the presence of selectivity for the orthogonal linearly polarized modes. Films with more then 24 periods were found to have polarization selectivity approaching unity. The agreement between the simulation and experimental results demonstrates the potential for future theoretical development of highly selective polarization filters based on GLAD thin films.
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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".