Janus Droplets and Droplets with Multiple Heterogeneous Surface Strips Generated with Nanoparticles under Applied Electric Field
Bibliographic record
Abstract
A novel method of fabricating Janus droplets and droplets with heterogeneous strips is presented in this article. These droplets were made by covering the surfaces of oil droplets with different nanoparticles under an electric field in a microfluidic chip. The microfluidic chip was used to control the delivery of nanoparticles, and the electric field was employed to assemble the nanoparticles adhering on the droplet. By controlling the delivery of nanoparticles in the microfluidic chip under the electric field, different nanoparticles accumulate on the droplet surface and the desired Janus droplets and droplets with heterogeneous strips can be formed. Because of the presence of charged nanoparticles on droplets’ surfaces, the Janus droplets and droplets with heterogeneous strips have unique electrokinetic properties. The electro-osmotic flow fields around Janus droplets and droplets with heterogeneous strips in different pH solutions were visualized, and the electrokinetic velocities of these droplets in a microchannel were measured as a function of the electrical field. On the basis of their specific electrokinetic properties, two applications of the droplets coated with nanoparticles were developed: flow focusing and microvalve. The experimental demonstrations indicate that the Janus droplets and droplets with heterogeneous strips offer great potential in sensing, actuating, and controlling fluid flow.
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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".