Numerical investigation of air mediated droplet bouncing on flat surfaces
Bibliographic record
Abstract
A liquid droplet can bounce off a flat substrate independent of surface wettability if the impact occurs at low velocities, i.e., We of less than seven. In this case, the droplet spreads on a sub-micrometer air layer and rebounds subsequently without any direct contact with the surface. We have numerically investigated the process of air layer formation beneath the droplet. The numerical simulations are validated using experimental results available in the literature based on morphology of the droplet interface and thickness of the air layer. Numerical results revealed that the formation of a high pressure zone at the center of impact deforms the droplet to a kink shape at the moment of impact. The deformation leads to displacement of high pressure zone from center to kink edge of the droplet interface. Further investigation of pressure and velocity of air beneath the droplet divulged that high pressure region at the kink edge suppresses air flow at the inner region while accelerating flow at the outer region. In addition, it is demonstrated that fluid flow at the kink edge where droplet interface has the minimum distance from the substrate resembles Couette flow. It is demonstrated that the deformation of droplet along with displacement of high pressure region from the center to kink edge are responsible for stabilizing the air layer beneath the droplet and consequently spreading and receding of droplet over a thin air cushion.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".