Microfluidic on-chip Production of Alginate Hydrogels Using Double Co-flow Geometry
Bibliographic record
Abstract
Abstract Microfluidic on-chip production of microgels employing external gelation has numerous biological and pharmaceutical applications, particularly for the encapsulation of delicate cargos, however, the on-chip production of microgels in microfluidic devices can be challenging due to problems such as clogging caused by accelerated progress in precursor solution viscosity. Here, we introduce a novel microfluidic design incorporating two consecutive co-flow geometries for microfluidic droplet generation. A shielding oil phase is employed to avoid emulsification and gelation stages from occurring simultaneously, thereby preventing clogging. The results revealed that the microfluidic device could generate highly monodispersed spherical droplets (coefficient of variation < 3%) with an average diameter in the range of 60–200 μm. Additionally, it was demonstrated that the device could appropriately create a shelter of the oil phase around the inner aqueous phase regardless of the droplet formation regime and flow conditions. The ability of the proposed microfluidic device in the generation of microgels was validated by producing alginate microgels utilizing an aqueous solution of calcium chloride as the continuous phase.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".