Investigation of splashing phenomena during the impact of molten sub-micron gold droplets on solid surfaces
Bibliographic record
Abstract
The dynamics of splashing accompanying the impact of molten 800 nm diameter gold droplets on silicon, gold coated silicon, gold coated glass and polished solid gold surfaces has been studied. A novel method based on laser induced forward transfer has been developed to generate single submicron molten gold droplets. Splashing morphology has been characterized using Scanning Electron Microscopy (SEM) and Focused Ion Beam (FIB) techniques. It is found that the splashing of submicron gold droplets upon impact is enhanced by high droplet impact energy achieved by reducing the droplet flight distance and that an air layer resulting in a bubble becomes trapped under the impacting droplets even when the size of the droplet is less than one micron. Our results show that, under these conditions, heat transfer between the submicron droplet and the solid substrate is more important than surface roughness and surface tension in the evolution of splashing. A theoretical model has been developed to simulate the splashing characteristics of submicron gold droplets during impact. Both the experimental data and the analytical model show that splashing is enhanced by high heat transfer rates to the surface.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".