Complex Drop Impact Morphology
Bibliographic record
Abstract
The aim of this work is to understand the changes in the observed phenomena during particle-laden drop impact. The impact of millimeter-size drops was investigated onto hydrophilic (glass) and hydrophobic (polycarbonate) substrates. The drops were dispersions of water and spherical and nearly iso-dense hydrophobic particles with diameters of 200 and 500 μm. The impact was studied by side and bottom view images in the range 150 ≤ We ≤ 750 and 7100 ≤ Re ≤ 16400. The particles suppressed the appearance of singular jetting and drop partial rebound but promoted splashing, receding breakup, and rupture. The drops with 200 μm particles spread in two phases: fast and slow, caused by inertial and capillary forces, respectively. Also, the increase in volume fraction of 200 μm particle led to a linear decrease in the maximum spreading factor caused by the inertia force on both hydrophilic and hydrophobic substrates. The explanation of this reduction was argued to be the result of energy dissipation through frictional losses between particles and the substrate.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".