Experimental Investigation of Microparticle Focusing in SiO2 Nanofluids Inside Curvilinear Microchannels
Bibliographic record
Abstract
Abstract Curvilinear microchannels have enabled high throughput sized-based separation and manipulation of microparticles. Real life applications usually deal with fluid’s non-Newtonian behavior, where particles dynamics are altered compared to Newtonian mediums. Despite multiple reports on particle manipulation in shear-thinning fluids, no fundamental experimental investigation has been reported on microparticle focusing behavior inside shear-thickening fluids such as metallic oxide nanofluids in water (e.g., SiO 2 -water). These nanofluids pose unique thermal characteristics and exhibit a drastic increase in viscosity as the shear rate rises in the microchannel. Here, we investigate the particle focusing behavior of co-flows of SiO 2 nanofluids inside curved microchannels with various channel widths and radii of curvature. We also report on the effect of nanofluid concentration, fluid axial velocity, and the particle size on particle migration. We observed a behavioral change in particle migration in SiO 2 nanofluids, where the shear-dependent effect could enhance the particle focusing at lower flow rates. Moreover, the dominance of Dean drag at higher axial velocities would dominate the particle migration and transfer them towards two focusing peaks close to the sidewalls. A thorough investigation of particle behavior in nanofluids inside curved microchannels could enable future applications in heat exchangers, solar energy collectors, and nanoplastic detection.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".