Numerical Simulation on Transient Electrophoretic Motion of a Circular Particle in a T-Shaped Slit Microchannel
Bibliographic record
Abstract
This paper considers the electrophoretic motion of a circular particle in a T-shaped slit microchannel, where the size of the channel is close to that of the particle. During the process, the electric field (i.e., the gradient of the electric potential) changes with the particle motion, which in return influences the flow field and the particle motion. Therefore, the electric field, the flow field and the particle motion are coupled together, and this is an unsteady process. The objective is to obtain a fundamental understanding of the characteristics of the particle motion in the complicated T-shaped junction region. Such influences on the electric field and the particle motion are investigated as the applied electric potentials, the geometry of the channel and the size of the particle. In the theoretical analysis, the liquid phase is divided into the inner region and the outer region. The inner region consists of the electrical double layers and the outer region consists of the remainder of the liquid. Under the assumption of thin electrical double layer, a mathematical model governing the inner region, the outer region and the particle motion is developed. A direct numerical simulation method using the finite element method is employed. In this method, a continuous hydrodynamic model is adopted. By this model, both the liquid phase in the outer region and the particle phase are governed by the same momentum equations. ALE method is used to track the surface of the particle at each time step. The numerical results show that the electric field is influenced by the applied electric potentials, the geometry of the channel and the particle suspension, and that the particle motion is mainly dominated by the local electric field. It is also found that the magnitude of the particle motion is dependent on its own size in the same 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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".