Acoustofluidic generation of droplets with tunable chemical concentrations
Bibliographic record
Abstract
The dynamic control of the chemical concentration within droplets is required in numerous droplet microfluidic applications. Here, we propose an acoustofluidic method for the generation of a library of aqueous droplets with the desired chemical concentrations in a continuous oil phase. Surface acoustic waves produced by a focused interdigital transducer interact with two parallel laminar streams with different chemical compositions. Coupling the acoustic waves with the flow streams results in the controlled acoustofluidic mixing of the aqueous solutions through the formation of acoustic streaming flow-induced microvortices. The mixed streams are split at a bifurcation, and one of the streams with a precisely controlled chemical concentration is fed into a T-junction to produce droplets with tunable chemical concentrations. The periodic acoustofluidic mixing of the aqueous streams enables the generation of a droplet library with a well-defined inter-droplet concentration gradient. The proposed method is a promising tool for the on-chip dynamic control of in-droplet chemical concentrations and for next-generation droplet microfluidic applications.
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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".