Wetting at the nanoscale: A molecular dynamics study
Bibliographic record
Abstract
A novel method to calculate the solid-liquid contact angle is introduced in this study. Using the 3D configuration of a liquid droplet on a solid surface, this method calculates the contact angle along the contact line and provides an angular distribution. Although this method uses the 3D configuration of liquid droplets, it does not require the calculation of the 3D density profile to identify the boundaries of the droplet. This decreases the computational cost of the contact angle calculation greatly. Moreover, no presumption about the shape of the liquid droplet is needed when using the method introduced in this study. Using this method, the relationship between the size and the contact angle of water nano-droplets on a graphite substrate was studied. It is shown that the contact angle generally decreases by increasing the size of the nano-droplet. The microscopic contact angle of 83.0° was obtained for water on graphite which is in a good agreement with previous experimental and numerical studies. Neglecting other nanoscale effects which may influence the contact angle, the line tension of SPC/E (extended simple point charge model) water was calculated to be 3.6×10−11 N, which is also in good agreement with the previously calculated values.
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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) | 0.002 | 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".