Characterization of an on-chip reconfigurable 3D optofluidic microlens by confocal laser scanning microscopy
Bibliographic record
Abstract
This research describes the design, fabrication and performance of an optofluidic 3D microlens reconfigurable by hydrodynamic flow rate adjustments. The microflow device is realized by standard single-layer micromachining of the photoresist SU-8 on a silicon substrate. On-chip waveguides and microgrooves designed for the insertion of multimode glass fibers are integrated to serve as optical interconnection for incident light coupling and detection. The laminar flow regime in the structured microchannel and the use of two transparent fluids with different refractive indices enable smooth optical interfaces useful for the creation of optofluidic elements. The inertial microfluidic effects occurring in the channels allow the generation of a multiconvex 3D microlens. By altering the input flow rates the lens shape with different lens radii in the lateral and normal direction is adjusted. To confirm the fluid dynamic simulations and to three-dimensionally characterize the microflow system we conducted confocal laser scanning and fluorescent sample measurements. The unique features of this optical chip offer a novel 3D light focusing system attractive for enhanced low-cost cell parameter screening without the use of bulky/expensive single photon counting units.
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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".