Electrokinetic motion of a spherical micro particle at an oil−water interface in microchannel
Bibliographic record
Abstract
The electrokinetic motion of a negatively charged spherical particle at an oil-water interface in a microchannel is numerically investigated and analyzed in this paper. A three-dimensional (3D) transient numerical model is developed to simulate the particle electrokinetic motion. The channel wall, the surface of the particle and the oil-water interface are all considered negatively charged. The effects of the direct current (DC) electric field, the zeta potentials of the particle-water interface and the oil-water interface, and the dynamic viscosity ratio of oil to water on the velocity of the particle are studied in this paper. In addition, the influences of the particle size are also discussed. The simulation results show that the micro-particle with a small value of negative zeta potential moves in the same direction of the external electric field. However, if the zeta potential value of the particle-water interface is large enough, the moving direction of the particle is opposite to that of the electric field. The velocity of the particle at the interface increases with the increase in the electric field strength and the particle size, but decreases with the increase in the dynamic viscosity ratio of oil to water, and the absolute value of the negative zeta potentials of both the particle-water interface and the oil-water interface. This work is the first numerical study of the electrokinetic motion of a charged particle at an oil-water interface in a microchannel.
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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 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".