Using film nanostructure to control photoluminescence angular emission profiles
Bibliographic record
Abstract
Luminescent thin films are used for many applications, including light-emitting diodes, lasers and flat panel displays. Glancing angle deposition (GLAD) is a physical vapor deposition technique which relies on highly oblique flux angles to create porous thin films. When combined with real-time substrate motion control and measurement of deposition rates, it is possible to produce high quality nanostructered thin films. A rugate filter uses a sinusoidally varying index profile to produce a stop band. Using the GLAD technique, it is possible to produce a rugate filter from a single material. The central wavelength, depth and width of the stop band can be designed by adjusting the film nanostructure. In this paper, rugates composed of Y2O3:Eu are used to control the angular emission profiles of the photoluminescent thin film. Confined, annular and isotropic emission profiles film is nearly uniform for emission angles between ~ -60° and ~60°.
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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".