Optical Manipulation of Microparticles in an SU-8/PDMS Hybrid Microfluidic Chip Incorporating a Monolithically Integrated On-Chip Lens Set
Bibliographic record
Abstract
An SU-8/PDMS microfluidic chip incorporating a monolithically integrated on-chip lens set for transport and manipulation of microparticles is developed. The components, including the on-chip lens set, the microfluidic channel, and the fiber grooves, are defined in a single layer of SU-8 by one-step photolithography. The design of the on-chip lens set and the fabrication of the microfluidic chip are fully described. The influence of the beam-waist radius on the manipulation performance is theoretically analyzed and experimentally verified for the first time. In the cross-type optofluidic architecture, the evaluation is performed by measuring the particle displacement with different beam-waist radii under different fluid-flow rates. The on-chip lens set is designed to have a specific dimension to achieve the required beam-waist radius. It is revealed that the particle displacement is counter-proportional to the beam-waist radius. An experiment is performed. The results show that the particle displacement is increased by reducing the beam-waist radius. The optical manipulation of microparticles is also demonstrated by using two counter-propagating light beams that are perpendicular to the fluid-flow direction with the beam-waist radius determined by two on-chip lens sets placed on the two sides of the microfluidic channel. The proposed architecture could be used to enhance the performance in particle transport, separation, and concentration.
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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) | 0.000 | 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".