Microlens array fabricated by a low-cost grayscale lithography maskless system
Bibliographic record
Abstract
This work presents the fabrication of a contiguous f/#=f/15 Fresnel microlens array (MLA) by employing a low-cost home-built maskless exposure lithographic system based on a digital light projector technology by using Texas Instruments’ digital micromirror device chip. A continuous diffractive phase relief structure was generated on a photoresist-coated silicon wafer, replicated in polydimethylsiloxane (PDMS) and electrostatically bonded to a glass substrate. The whole exposure time takes 10.8 min to expose a 2.4×2.4 mm MLA, with a resolution of 2.5 μm. This exposure time is relatively short, enabling high throughput or fast prototyping. Optical characterization was carried out using a He-Ne laser source (λ=633 nm ), by evaluating the maximum intensity of each spot generated at the MLA focal plane, Imax, as well as its sharpness by measuring their full width at half maximum (FWHM) intensity values. The resulting FWHM and maximum intensity spot average values were FWHM AVG =20±8% μm and Imax AVG =0.71±7% a.u. , respectively. The quality of replication was evaluated by profile characterization of the resulting mold and replica based on step height measurement along 180 μm. The maximum obtained difference was 32 nm, corresponding to 2.5% of the total mold height or λ/20 . AFM measurements were also carried out to quantify the roughness quality between mold and replica. The resulting RMS roughness was 4.73 nm (λ/130 ) and 6.66 nm (λ/95 ) for mold and replica, respectively. A comparison between theoretical and measured intensity profiles at the MLA focal plane was also carried out. A good correspondence between the results was found. Such an MLA can be applied as a Shack–Hartmann wavefront sensor in optical interconnects and to enhance the efficiency of detector arrays.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".