Droplet impact and flow into a gap between parallel plates
Bibliographic record
Abstract
Droplet impact on irregular, rough, or porous substrates can lead to inertia driven liquid penetration during droplet spread, air entrapment in voids, and triple-phase contact line pinning. This work focuses on inertia driven flow inside of a model long, narrow pore. We impacted 2 mm diameter water drops on long narrow gaps, photographing the impact and penetration with a high-speed camera, to understand how the flow develops and behaves inside these gaps. The experimental conditions varied were the velocity of impact (0.06–1.5 m/s) and the gap spacing between the plates (50–150 µm). The influence of inertia on the flow between the plates is negligible for impact velocities less than 0.5 m/s and can be predicted using a simple analytical model. Drops flow into larger gaps faster than smaller gaps at all impact velocities. Drops flow faster into gaps as impact velocity increases, but this has diminishing returns: at sufficiently high impact velocity the drop will cleave, which prevents a significant portion of the drop from flowing into the gap. Analytical models are presented to predict conditions under which the droplet will cleave and the rate of liquid penetration into the gap due to capillary forces.
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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 | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".