Microlens Arrays for Optoelectronic Devices.
Bibliographic record
Abstract
This paper reports on an improved method of fabricating microlens arrays using a low cost replication process. An accurate negative reproduction ("mold") of an existing high quality lens surface (master) is made in a soft silicone elastomer. This mold is formed by thermally curing Sylgard® 182 silicone elastomer (made by Dow Corning®) on the lens surface. To prevent distortion of the replica surface, the mold is made on a rigid backing plate. Dispensing a commercial epoxy ‘Polyset’ PCX 28-91B into the mold and curing it under UV radiation generates a replica lens array. The epoxy material is chosen to have minimal shrinkage upon curing. The epoxy material is also chosen to have lower intrinsic loss and have a refractive index tailored to the application. In addition, we have developed a procedure to enable the incorporation of commercially available SiO2 nanoparticles (Nissan IPA-ST-S, 9-11nm) into this epoxy material. The incorporation of nanoparticles allows the epoxide to be harder, have a refractive index closer to SiO2, have even smaller shrinkage while maintaining low intrinsic loss because of the small size of the SiO2 particles.
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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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".