Asymptotic regimes in elastohydrodynamic and stochastic leveling on a\n viscous film
Bibliographic record
Abstract
Thin viscous films are ubiquitous in Nature and biology and they are indispensable in industrial applications through lubrication and coating. In order to utilize the potential of thin viscous films on the micro and nano scale, detailed understanding and models of the mechanisms that govern the flow dynamics is necessary.\nIn the presented thesis, I investigate how the flow dynamics are influenced by small scale effects using mathematical and numerical modelling. More specifically, small scale flow phenomena driven by elastic bending, thermal fluctuations and surface tensions forces are studied. A main objective was to identify time and length scales on which characteristic thin film flow features such as perturbation levelling and film rupture/de-wetting occur. This has great practical implications as it can be used to improve a films stability and provide estimates of the system's total surface energy. Moreover, thermal fluctuations are demonstrated to be able to influence these time scales to a great extent.\nFurthermore, I investigate how wetting droplets on conical structures can self-propell due to a mismatch in the droplets front and trailing contact angle. The latter has significant potential to create passively coated structures and to enhance water transport in fog nets.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".