Heterogeneous Surface Charge Enhanced Micromixing for Electrokinetic Flows
Why this work is in the frame
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Bibliographic record
Abstract
Enhancing the species mixing in microfluidic applications is key to reducing analysis time and increasing device portability. The mixing in electroosmotic flow is usually diffusion-dominated. Recent numerical studies have indicated that the introduction of electrically charged surface heterogeneities may augment mixing efficiencies by creating localized regions of flow circulation. In this study, we experimentally visualized the effects of surface charge patterning and developed an optimized electrokinetic micromixer applicable to the low Reynolds number regime. Using the optimized micromixer, mixing efficiencies were improved between 22 and 68% for the applied potentials ranging from 70 to 555 V/cm when compared with the negatively charged homogeneous case. For producing a 95% mixture, this equates to a potential decrease in the required mixing channel length of up to 88% for flows with Péclet numbers between 190 and 1500.
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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