Rapid mixing of colliding picoliter liquid droplets delivered through-space from piezoelectric-actuated pipettes characterized by time-resolved fluorescence monitoring
Bibliographic record
Abstract
Rapid mixing of aqueous solutions is a crucial first step to study the kinetics of fast biochemical reactions with high temporal resolution. Remarkable progress toward this goal has been made through the development of advanced stopped-flow mixing techniques resulting in reduced dead times, and thereby extending reaction monitoring capabilities to numerous biochemical systems. Concurrently, piezoelectric actuators for through-space liquid droplet sample delivery have also been applied in several experimental systems, providing discrete picoliter sample volume delivery and precision sample deposition onto a surface, free of confinement within microfluidic devices, tubing, or other physical constraints. Here, we characterize the inertial mixing kinetics of two aqueous droplets (130 pl) produced by piezoelectric-actuated pipettes, following droplet collision in free space and deposition on a surface in a proof of principle experiment. A time-resolved fluorescence system was developed to monitor the mixing and fluorescence quenching of 5-carboxytetramethylrhodamine (5-Tamra) and N-Bromosuccinimide, which we show to occur in less than 10 ms. In this respect, this methodology is unique in that it offers millisecond mixing capabilities for very small quantities of discrete sample volumes. Furthermore, the use of discrete droplets for sample delivery and mixing in free space provides potential advantages, including the elimination of the requirement for a physical construction as with microfluidic systems, and thereby makes possible and extends the experimental capabilities of many systems.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".