Numerical Simulation on the Electrophoretic Motion of Multiple Particles in Microchannels
Bibliographic record
Abstract
This paper considers the electrophoretic motion of multiple spheres in an aqueous electrolyte solution in a straight rectangular microchannel, where the size of the channel is close to that of the particles. This is a complicated 3-D transient process where the electric field, the flow field and the particle motion are coupled together. The objective is to numerically investigate how one particle influences the electric field and the flow field surrounding the other particle and the particle moving velocity. It is also aimed to investigate and demonstrate that the effects of particle size and electrokinetic properties on particle moving velocity. Under the assumption of thin electrical double layers, the electroosmotic flow velocity is used to describe the flow in the inner region. The model governing the electric field and the flow field in the outer region and the particle motion is developed. A direct numerical simulation method using the finite element method is adopted to solve the model. The numerical results show that the presence of one particle influences the electric field and the flow field adjacent to the other particle and the particle motion, and that this influences weaken when the separation distance becomes bigger. The particle motion is dependent on its size, with the smaller particle moving a little faster. In addition, the zeta potential of particle has an effective influence on the particle motion. For a faster particle moving from behind a slower one, numerical results show that the faster moving particle will climb and then pass the slower moving particle then two particles’ centers are not located on a line parallel to the electric field.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".