Bibliographic record
Abstract
Formation of liquid films through the deposition of droplets and spray onto a solid surface was studied experimentally. Experiments were done to observe the coalescence of highly viscous liquid droplets (87 wt% glycerin-in-water solutions) deposited onto a flat, solid steel plate. Droplets were deposited sequentially in straight lines or square droplet arrays. Droplet center-to-center distance was varied and the final dimensions of lines and sheets measured from photographs. When overlapping droplets were deposited surface tension forces pulled impacting droplets towards those already on the surface, a phenomena known as drawback. At large overlaps droplets deposited in a line or square array coalesced to form a circular film. When the droplet center-to-center distance increased, leading to less interaction, long, thin lines and square sheets were formed. As overlap was further decreased lines and sheets became discontinuous. A simple model was developed to predict the conditions under which rupture occurred. The lowest droplet overlap ratio (defined as droplet overlap distance divided by droplet spread diameter) at which a continuous liquid film could be formed was 位 = 0.293. Further studies with a pneumatic droplet generator that put down multiple droplets simultaneously confirmed this finding. In addition, spray experiments also exhibited the drawback effect during droplet coalescence and showcased the need to spray small droplets with large overlap in order to form a uniform thin film. Bubble entrapment and escape from sprayed paint films of different thickness was analyzed and the number, diameter and velocity of air bubbles were determined. Bubbles were observed to escape from both upward and downwards facing surfaces. Concentration gradients due to solvent evaporation in a paint film create surface tension variations that drive Marangoni flows, which bring bubbles to the paint surface. An analytical one-dimensional model of solvent diffusion was used to calculate solvent concentration variations in the paint film and the Marangoni number.
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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) | 0.007 | 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".