Investigation of Particle Electrophoretic Motion in Converging-Diverging Microchannels
Bibliographic record
Abstract
We studied experimentally the particle electrophoretic motion in converging-diverging microchannels on a poly(dimethylsiloxane) (PDMS) chip. The whole process of particle acceleration and deceleration was visualized through traditional optical microscopy, with which the accelerated particle electrophoretic separation is demonstrated. The effects of electric field, particle size, particle moving passage, and channel configuration on particle electrophoretic motion are examined individually. We find that the ratio of particle velocity in the throat to that in the straight channel is insensitive to both the particle moving passage and the length of converging/diverging channel, but increased for smaller particles moving through symmetric converging-diverging channels under lower electric fields. Moreover, we find that the particle velocity ratio in electrically driven flows is significantly lower than the cross-sectional area ratio of the straight channel to the throat. We have attributed this discrepancy to the particle-induced distortion in the electric potential distribution. The computed contour of electric field in a converging-diverging microchannel has revealed that the electric field is locally higher around the two poles of a particle than all other regions inside the channel.
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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".