Microfluidic Generation of Particle-Stabilized Water-in-Water Emulsions
Bibliographic record
Abstract
Herein, we present a microfluidic platform that generates particle-stabilized water-in-water emulsions. The water-in-water system that we use is based on an aqueous two-phase system of polyethylene glycol (PEG) and dextran (DEX). DEX droplets are formed passively, in the continuous phase of PEG and carboxylated particle suspension at a flow-focusing junction inside a microfluidic device. As DEX droplets travel downstream inside the microchannel, carboxylated particles that are in the continuous phase partition to the interface of the DEX droplets due to their affinity to the interface of PEG and DEX. As the DEX droplets become covered with carboxylated particles, they become stabilized against coalescence. We study the coverage and stability of the emulsions, while tuning the concentration and the size of the carboxylated particles, downstream inside the reservoir of the microfluidic device. These particle-stabilized water-in-water emulsions showcase good particle adsorption under shear, while being flowed through narrow microchannels. The intrinsic biocompatibility advantages of particle-stabilized water-in-water emulsions make them a good alternative to traditional particle-stabilized water-in-oil emulsions. To illustrate a biotechnological application of this platform, we show a proof-of-principle of cell encapsulation using this system, which with further development may be used for immunoisolation of cells for transplantation purposes.
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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".