Numerical and experimental evaluation of microfluidic sorting devices
Bibliographic record
Abstract
The development of lab-on-a-chip devices calls for the isolation or separation of specific bioparticles or cells. The design of a miniaturized cell-sorting device for handheld operation must follow the strict parameters associated with lab-on-a-chip technology. The limitations include applied voltage, high efficiency of cell-separation, reliability, size, flow control, and cost, among others. Currently used designs have achieved successful levels of cell isolation; however, further improvements in the microfluidic chip design are important to incorporate into larger systems. This study evaluates specific design modifications that contribute to the reduction of required applied potential aiming for developing portable devices, improved operation reliability by minimizing induced pressure disturbance when electrokinetic pumping is employed, and improved flow control by incorporating directing streams achieving dynamic sorting and counting. The chip designs fabricated in glass and polymeric materials include asymmetric channel widths for sample focusing, nonuniform channel depth for minimizing induced pressure disturbance, directing streams to assist particle flow control, and online filters for reducing channel blockage. Fluorescence-based visualization experimental results of electrokinetic focusing, flow field phenomena, and dynamic sorting demonstrate the advantages of the chip design. Numerical simulations in COMSOL are validated by the experimental data and used to investigate the effects of channel geometry and fluid properties on the flow field.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".