Magnetic polyelectrolyte microcapsules <i>via</i> water-in-water droplet microfluidics
Bibliographic record
Abstract
Polyelectrolyte microcapsules (PEMCs) have biocompatible microcompartments. Therefore, PEMCs are useful for applications in cosmetics, food, pharmaceutics, and other industries. The fabrication of PEMCs often involves the use of harsh chemicals or cytotoxic organic phases that make biomedical applications of the microcapsules challenging. In this report, we present an all-aqueous droplet microfluidics platform for the generation of magnetic PEMCs. In the platform, we use an aqueous-two-phase system (ATPS) of polyethylene glycol (PEG) and dextran (Dex), to generate water-in-water droplets, which are magnetically functionalized with ferrofluid. Strong polyelectrolytes (PEs) with opposite charges are used in each ATPS phase. We make emulsion templates of magnetic Dex, containing the polycations, in a continuous phase of PEG. We then apply a magnetic field to move the magnetic droplets to a second PEG phase, which contains the polyanions. By careful tuning of the fluxes of the two PEs in their respective phases, we trigger the formation of a shell at the droplet interface. Owing to the presence of the ferrofluid, the resulting microcapsules are magnetically responsive. We show that the magnetic PEMCs are capable of passive release of large pseudo-drugs as well as triggered release using external stimuli such as osmotic shock and pH change. We expect that magnetic PEMCs from this biocompatible all-aqueous platform will find utility in the fabrication of functionalized drug carriers for targeted drug delivery.
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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".