End-faced waveguide mediated optical propulsion of microspheres and single cells in a microfluidic device
Bibliographic record
Abstract
Single cell transport in microfluidic devices is a topic of interest as their utility is becoming appreciated by cell and molecular biologist. Cell transport should minimize mechanical stress due to friction or pressure gradients. Optical forces have the advantage of applying their forces across the cell volume and not only at the cell membrane and are thus preferable. Optical pushing by scattering force is a suitable candidate so highly dependent on the photon irradiance field inside the propagation capillary which in turn is determined by the waveguide properties delivering the radiation pressure. Here we present a numerical approach to predict the optical scattering force, speed and trajectory of cells as a function of waveguide and propagation capillary geometry. Experimental verification of the simulation approach is demonstrated using polystyrene microspheres and leukemia cells. Effects of optical fibre to waveguide alignment, capillary wall angle and temperature on the dynamic viscosity on speed and position of the microspheres and cells inside the propagation capillary are demonstrated.
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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".