Nanoparticle and scalar mixing of magnetic colloids in microchannels—Prevalence of Kelvin body force over spin-up flow
Bibliographic record
Abstract
This study investigates the underlying mechanisms of active transverse mixing in dilute magnetic colloidal suspensions in microchannels , focusing on the interplay between the Kelvin Body Force (KBF) and spin-up flow under a rotating magnetic field (RMF). By studying the effects of KBF-induced flow on mixing, we identify the KBF as the dominant force that generates strong transverse motion, which significantly enhances the transverse mixing of scalar and nanoparticles . Using a Y-shaped microchannel model with one-sided injection of magnetic nanoparticles (MNPs), we show how the KBF disrupts the axial flow pattern, thereby promoting rapid mixing and reducing scalar field segregation. In comparison, the spin-up flow shows limited influence, suggesting the clear advantage of the KBF in optimizing mixing efficiency. These results highlight the potential of tuning RMF parameters to maximize KBF-driven mixing in microfluidic applications. On the other hand, further investigation of spin-up flow in the cluster regime could improve our understanding of the dynamics of KBF-driven mixing and provide new insights for microfluidic reactor design.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".