Contact Line Ice Nucleation Is the Dominant Freezing Mechanism for Water on Macro- and Microscopic Polypropylene Surfaces
Bibliographic record
Abstract
Ice nucleation on hydrophobic surfaces induces aircraft and wind turbine icing, the freezing of water in cryo-preservation, and atmospheric ice formation on micro- and nanoplastics. Yet, predicting the freezing mechanisms and temperatures for hydrophobic materials, such as plastics, remains difficult without understanding if freezing initiates at the plastic–water interface or at the plastic–water–air contact line. Here, we investigated the freezing of water droplets on macroscopic and microscopic polypropylene plastics to characterize their ice nucleation onset locations. First, the onset locations of freezing were measured with a high-speed camera (≥2100 frames per second) to differentiate between freezing initiating at the plastic–water interface and freezing initiating at the plastic–water–air contact line. Freezing at the contact line was the dominant mechanism for 10 μL droplets on flat polypropylene sheets, with ice nucleation observed at the contact line in 90% of the cases. Second, we investigated the change in the contact angles of the droplets during a cooling cycle. Interestingly, the contact angles decreased with cooling under a N 2 flow by up to 6.6°, suggesting a pinned contact line. This pinned contact line and the associated negative pressure at the contact line could have played a role in the freezing mechanism. Third, we analyzed polypropylene fibers in contact with 1 μL and 5 nL droplets and found that contact line nucleation dominated. For example, 5 nL droplets condensed onto polypropylene microfibers nucleated ice at the contact line 3.5 times more often than at the fiber–water interface. Overall, our measurements demonstrated that polypropylene sheets and fibers had a clear preference for initiating freezing at the three-phase contact line. As a consequence, understanding the thermodynamics governing the contact line might enable predictive capabilities of the freezing temperatures for plastic materials and other hydrophobic surfaces.
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 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 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".