Bibliographic record
Abstract
Manipulating the flow of light is critical in the design and fabrication of light-based devices ranging from solar cells, smart cameras, liquid crystal display (LCD) screens, projectors and light emitting diodes (LEDs). Thin films configured with spatial patterns or modulations in refractive index exhibit strong and richly varied interactions with light beams. In this thesis, we show that embedding planar films with specific geometries of waveguide lattices allows precise control over the inflow and outflow of light. Specifically, we demonstrate the fabrication of a new class of waveguide-encoded polymer films that are generated through a single-step, room temperature technique. Here, waveguide encoded lattices with a range of symmetries are spontaneously inscribed in photopolymerizable resins by self-trapped beams of incandescent light. We describe the generation of lattices consisting of five intersecting arrays of waveguides, which confer a range of unprecedented properties including a large, panoramic field of view (FOV) infinite depth of field and multiple imaging functionalities including focusing and inversion. We have also fabricated lattices inspired by natural arthropodal compound eyes, which comprise a radial distribution of waveguide and in turn impart a continuous, enhanced FOV. We demonstrate the application of these films in controlling the beam profiles of LEDs including their divergence and convergence. Finally, we show that thin films patterned with a periodic array of planar waveguides serve as effective beam steering coatings, which deflect light away from the metallic front contacts of commercially available solar cells and in this way, increase their efficiency.
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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".