Mechanical Filtration of Particles in Electrowetting on Dielectric Devices
Bibliographic record
Abstract
A passive mechanical method for the filtration of particles in electrowetting on dielectric (EWOD) devices is presented. Analytical and experimental results show that droplets actuated by EWOD cannot pass physical obstructions unaided at the scales considered here. However, it was possible to pull droplets past the same obstructions using a second droplet. The two droplets approach the obstruction from opposite sides and merge within the pore of the obstruction. The interface on the enabling side of the amalgamated droplet is then actuated to pull fluid through the obstruction. This technique was successful for pore sizes between half and two orders of magnitude below the confined droplet height. This wide range of viable pore sizes will allow for the filtration of particles by size in EWOD devices. It can also be used to filter large particles traditionally used in microfluidic immunoassays or allow for the use of smaller particles to increase sensitivity. Success at pore sizes as small as 2 μm also suggests that filtration of animal cells in EWOD devices is possible. The proposed process is performed without the use of surfactants, which may make it more attractive for applications using biological material.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".