Bibliographic record
Abstract
The electro-osmotic pumping and pressure-driven manipulation of fluids are considered as the most common strategies in microfluidic devices. However, both of them exhibit major disadvantages such as hard integration and high reagent consumption, and they are destructive methods for detection and photo bleaching. In this paper, an electric field-effect flow control approach, combining the electro-osmotic pumping force and the pressure-driven pumping force, was developed to generate the induced pressure-driven flow in a T-shaped microfluidic chip. Electro-osmotic flow between the T-intersection and two reservoirs was demonstrated, and it provided a stable, continuous, and electric field-free flow in the section of the microchannel without the electrodes. The velocity of the induced pressure-driven flow was linearly proportional to the applied voltages. Both numerical and experimental investigations were conducted to prove the concept, and the experimental results showed good agreement with the numerical simulations. In comparison to other induced pressure pumping methods, this approach can induce a high and controllable pressure drop in the electric field-free segment, subsequently causing an induced pressure-driven flow for transporting particles or biological cells. In addition, the generation of bubbles and the blocking of the microchannel are avoided.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.315 | 0.543 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".