Why this work is in the frame
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Bibliographic record
Abstract
We experimentally investigate the dynamics of viscous droplets impacting on rough surfaces under a broad range of Weber number ( 2 ≤ We ≤ 1 , 194 ), Ohnesorge number ( 0 . 002 ≤ Oh ≤ 2 . 630 ), and average surface roughness ( 9 . 7 μ m ≤ R a ≤ 19 . 5 μ m ). Three primary impact outcomes—jetting, spreading, and splashing—are observed. Our findings reveal that surface roughness promotes splashing by amplifying perturbations, while liquid viscosity counters this effect by dissipating the kinetic energy of the advancing lamella. We empirically describe the splashing threshold with the relation as Oh Re χ ( R a ) = K ( R a ) , where the fitting parameter K ( R a ) increases and χ ( R a ) decreases with greater surface roughness. Moreover, the maximum spreading factor ( β m ), defined as the ratio of the droplet’s maximum spreading diameter to its initial diameter, shows a pronounced dependence on surface roughness in low-viscosity conditions ( Oh < 0 . 050 ), but this dependence diminishes in high-viscosity regimes ( Oh ≥ 0 . 050 ). This trend results from the interplay between viscous dissipation induced by surface roughness and the intrinsic liquid viscosity. In the low-viscosity regime, the experimental β m is consistent with the empirical scaling law of β m = a ( We / Oh ) b , with the fitting constants, a and b , varying with surface roughness and liquid properties. In the regime of 0 . 050 < Oh < 1 , β m approximates ( We / Oh ) 1 / 6 . These findings elucidate the significant role of surface roughness and liquid viscosity in governing droplet impact dynamics and spreading.
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.
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 it