Analysis of Electrokinetic Mixing Techniques Using Comparative Mixing Index
Bibliographic record
Abstract
The performance of micro-mixers is evaluated in terms of deviations from perfectly mixed state and mixing length (i.e., device length required to achieve perfect mixing). Different variations of T-mixer are reported for improved mixing performance, including geometric constrictions/obstacles embedded in the channel wall, heterogeneously charged walls, grooves on channel base, etc. Most of the reported designs provide improved mixing at the expense of reduced flow rate; there exists therefore a tradeoff between mixing and transport. The reduced flow rate, which affects species residence time, is unfortunately not taken into account in most micro-mixing performance analyses. This issue is addressed by the comparative mixing index (CMI), which evaluates mixing performance more appropriately by normalizing the effect of residence time among different designs. In this study, the performance of several mixing strategies are evaluated based on the CMI; these are mixer designs that incorporate (a) physical constrictions, (b) induced charge electro-osmotic (ICEO) effects, and (c) heterogeneously charged walls. The present analysis clearly identifies conditions under which a given mixer design is superior to a T-mixer.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".