Effects of dc-dielectrophoretic force on particle trajectories in microchannels
Bibliographic record
Abstract
A method of controlling the particle trajectory in a microchannel is demonstrated. The method utilizes the dc-dielectrophoretic (dc-DEP) force created around an insulating hurdle in a microchannel under an applied dc electric field. This method does not require a complicated electrode array which is commonly used in the conventional ac-DEP system. The “proof-of-principle” experiments were carried out using a straight microchannel with a rectangle-shaped hurdle in the middle. The experiments showed that the trajectories of the micron-sized particles can be controlled by the DEP force under electric-field strengths of 5–20kV∕m. To compare with the experimental results, the particle motion was simulated using the Lagrangian tracking method, taking into consideration of the electrophoretic force, the dielectrophoretic force, and the dielectric interaction between the particle and the channel wall. The numerical simulation based on the finite-element method showed a reasonable agreement with the experimental data.
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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 | 0.001 |
| 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 | 0.000 | 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 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".