The precise and accurate production of millimetric water droplets using a superhydrophobic generating apparatus
Bibliographic record
Abstract
The production of millimetric liquid droplets has importance in a wide range of applications both in the laboratory and industrially. As such, much effort has been put forth to devise methods to generate these droplets on command in a manner which results in high diameter accuracy and precision, well-defined trajectories followed by successive droplets and low oscillations in droplet shape throughout their descents. None of the currently employed methods of millimetric droplet generation described in the literature adequately addresses all of these desired droplet characteristics. The reported methods invariably involve the cohesive separation of the desired volume of liquid from the bulk supply in the same step that separates the single droplet from the solid generator. We have devised a droplet generation device which separates the desired volume of liquid within a tee-apparatus in a step prior to the generation of the droplet which has yielded both high accuracy and precision of the diameters of the final droplets produced. Further, we have engineered a generating tip with extreme antiwetting properties which has resulted in reduced adhesion forces between the liquid droplet and the solid tip. This has yielded the ability to produce droplets of low mass without necessitating different diameter generating tips or the addition of surfactants to the liquid, well-defined droplet trajectories, and low oscillations in droplet volume. The trajectories and oscillations of the droplets produced have been assessed and presented quantitatively in a manner that has been lacking in the current literature.
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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".