Mechanism of droplet-formation in a supersonic microfluidic spray device
Bibliographic record
Abstract
Spray drying is an approach employed in automotive, food, and pharmaceutical industries as a robust and cost efficient liquid atomization technique offering direct control over droplet dimensions. The majority of commercially available spray nozzles are designed for large throughput spray drying applications or uniform surface coating, but microfluidic nebulizers have recently been developed as small scale alternatives. Here, we explore the physical parameters that define the droplet size and formation under supersonic flow conditions commonly found in microfluidic spray drying systems. We examined the spray nozzle operation using high speed imaging and laser scattering measurements, which allowed us to describe the spray regimes and droplet size distributions. It was determined that by using this spray nozzle device, droplets with diameters of 4–8 μm could be generated. Moreover, we show that the supersonic de Laval nozzle model can be used to predict the average droplet size. Our approach can be used as a platform for interfacing fluid microprocessing with gas phase detection and characterization.
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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".