Quantifying microdroplet contact-line friction using atomic force microscope
Bibliographic record
Abstract
Abstract Controlling the wetting and spreading of microdroplets is key to technologies such as microfluidics, ink-jet printing, and surface coating. Contact angle goniometry is commonly used to characterize surface wetting by droplets, but the technique is ill-suited for sub-millimetric droplets. Here, we attach a micrometric-sized droplet to an Atomic Force Microscope (AFM) cantilever to directly quantify contact-line friction on different surfaces (superhydrophobic and underwater superoleophobic) with sub-nanonewton force resolutions. We demonstrate the versatility of our approach by performing friction measurements using different liquids (water and oil droplets) and under different ambient environments (in air and under water). Finally, we show that underwater superoleophobic surfaces can be qualitatively different from superhydrophobic surfaces: contact-line friction is highly sensitive to contact-line speeds for the former but not for the latter surface.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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 teacher head, 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".