Induced charge electro osmotic mixer: Obstacle shape optimization
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Bibliographic record
Abstract
Efficient mixing is difficult to achieve in miniaturized devices due to the nature of low Reynolds number flow. Mixing can be intentionally induced, however, if conducting or nonconducting obstacles are embedded within the microchannel. In the case of conducting obstacles, vortices can be generated in the vicinity of the obstacle due to induced charge electro-osmosis (ICEO) which enhances mixing of different streams: the obstacle shape affects the induced zeta potential on the conducting surface, which in turn influences the flow profile near the obstacle. This study deals with optimization of the geometric shape of a conducting obstacle for the purpose of micromixing. The obstacle boundary is parametrically represented by nonuniform rational B-spline curves. The optimal obstacle shape, which maximizes the mixing for given operating conditions, is found using genetic algorithms. Various case studies at different operating conditions demonstrated that the near right triangle shape provides optimal mixing in the ICEO flow dominant regime, whereas rectangular shape is the optimal shape in diffusion dominant regime. The tradeoff between mixing and transport is examined for symmetric and nonsymmetric obstacle shapes.
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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 | 0.001 |
| 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