Application of Axiomatic Design Theory to a Microfluidic Device for the Production of Uniform Water-in-Oil Microspheres Adapting an Integration Method
Bibliographic record
Abstract
This work describes a novel microfluidic method to generate uniform water-in-oil (W/O) microspheres using the phase separation technique. Axiomatic design theory (ADT) was employed for the conceptual design of microchannel systems, and ADT verified that the proposed microfluidic system is a decoupled design. The integration of hydrodynamic flow focusing method and crossflow method is realized in a microfluidic device with oil phase and aqueous phase. The immiscible fluids are fed by continuous air pressure. By the hydrodynamic flow focusing method, the width of the dispersed focused aqueous phase is controlled. The focused flow enters T-junction geometry downstream, and the crossflow interferes with the focused flow. By varying the applied pressure to the crossflow, the W/O microspheres are formed at the T-junction. Based on this approach, the size of the W/O microspheres can be successfully controlled from 16 μm to 35 μm in diameter within about 5% of variation. The present method has advantages such as good sphericity, few satellite droplets, active control of the microsphere diameter, and high throughput with the simple and low cost process. To achieve the promising results, this integrating method reveals high potential for production of polymer based microspheres.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".