Investigation of an electro-osmotic micromixer with heterogeneous zeta-potential distribution at the wall
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Bibliographic record
Abstract
Abstract In this study, the effects of zeta-potential, Debye-Huckel parameter and Reynolds number on electrokinetic mixing through heterogeneous microchannels are investigated. In previous studies, relatively complicated approaches were applied to examine the electrokinetically produced vortices; on the other hand, a relatively simple innovative micromixer consisted of a non-homogeneous rectangular microchannel with the prescribed arrangements of zeta-potential at the walls is considered in this paper. In other words, the mentioned microchannel has heterogeneous zeta-potential distribution at its wall, while other surface properties are assumed to be uniform and homogenous. Moreover, in order to investigate the mixing efficiency of microfluidic devices based on the electroosmotic flow is proposed. Actually, in the electroosmotic phenomenon, the fluid flow is caused by applying a potential across the microchannel. To achieve the electro-osmotic mixing, the Navier-Stokes, Nernst-Planck, Laplace and convection-diffusion equations are solved numerically for the velocity field, ions distribution, electrical potential, and concentration field, sequentially. Having examined the results, one can easily figure out that the performance of electro-osmotic micromixers intensively depends on the wall zeta-potential value and its distribution. Moreover, it can be inferred that the mixing efficiency is really dependent on Debye-Huckel or Reynolds number so that it will increase as soon as theses mentioned parameters decreases. One of the most important achievements of this paper is that a better mixing performance can be attained by the asymmetric charge pattern. In other words, it is really essential to arrange the charge pattern more asymmetric to achieve the highest mixing efficiency.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| 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 it