Microfluidic conformal coating of non-spherical magnetic particles
Bibliographic record
Abstract
We present the conformal coating of non-spherical magnetic particles in a co-laminar flow microfluidic system. Whereas in the previous reports spherical particles had been coated with thin films that formed spheres around the particles; in this article, we show the coating of non-spherical particles with coating layers that are approximately uniform in thickness. The novelty of our work is that while liquid-liquid interfacial tension tends to minimize the surface area of interfaces-for example, to form spherical droplets that encapsulate spherical particles-in our experiments, the thin film that coats non-spherical particles has a non-minimal interfacial area. We first make bullet-shaped magnetic microparticles using a stop-flow lithography method that was previously demonstrated. We then suspend the bullet-shaped microparticles in an aqueous solution and flow the particle suspension with a co-flow of a non-aqueous mixture. A magnetic field gradient from a permanent magnet pulls the microparticles in the transverse direction to the fluid flow, until the particles reach the interface between the immiscible fluids. We observe that upon crossing the oil-water interface, the microparticles become coated by a thin film of the aqueous fluid. When we increase the two-fluid interfacial tension by reducing surfactant concentration, we observe that the particles become trapped at the interface, and we use this observation to extract an approximate magnetic susceptibility of the manufactured non-spherical microparticles. Finally, using fluorescence imaging, we confirm the uniformity of the thin film coating along the entire curved surface of the bullet-shaped particles. To the best of our knowledge, this is the first demonstration of conformal coating of non-spherical particles using microfluidics.
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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 | 0.000 |
| 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 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".