Classifying dynamic contact line modes in drying drops
Bibliographic record
Abstract
Although the evaporation mode of sessile droplets is almost universally characterized as either constant contact radius (CCR) or constant contact angle (CCA), here we investigate two alternatives where the contact line speed is either constant or inversely proportional to the droplet radius. We present supporting evidence from our experiments on poly(ethylene oxide) (PEO) polymer solutions and blood, and from literature on pure and binary liquids, colloidal suspensions, soft substrates, reactive dewetting and hole nucleation. We introduce the use of novel "clock-drop" images to visualize droplet evolution and dimensionless height-radius plots to characterize the evaporative pathways. Combining these with a simple scaling argument, we show that receding speed is inversely proportional to the three-phase contact radius R, with a constant of proportionality A, which is dependent on the drying conditions and drop shape, but independent of drop volume. We have shown that this is equivalent to a linear decrease in contact area with time. By varying only A, which we achieved experimentally by choosing solutions whose precipitate constricts after deposition, the evaporation mode can be altered continuously to include the two established modes CCR and CCA, and two new modes which we term "slowly receding" and "rapidly receding", which are characterised by fully dried "doughnut" and "pillar" deposits respectively.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".