A Modified Disjoining Pressure Model for Thin Film Evaporation of Water
Bibliographic record
Abstract
In the present work, a modified model to predict the disjoining pressure for thin film evaporation of water is presented. There has been some controversy about disjoining pressure modeling, especially for the case of polar liquids such as water. The conventional models for prediction of disjoining pressure, such as non-polar, logarithmic and exponential models, lead to different values of pressure and physically invalid thicknesses of the thin film near the non-evaporating region. In the present work, a modified disjoining pressure model is introduced based on multiplying a stretching function with the van der Waals component of disjoining pressure to consider the other intermolecular and surface effects such as structural forces and hydrogen bonds. Comparison of the present model with conventional ones shows that it can account for the effect of water molecules polarity over the entire extended meniscus. Also, the non-evaporating region thickness can be appropriately evaluated by this model, unlike the conventional ones. Moreover, the simple formulation of this model makes it suitable for analytical investigations of water thin film evaporation. Finally the effects of superheat, wall temperature and far field meniscus radius on the heat and mass transfer and fluid flow characteristic of thin film region are investigated and compared for the different disjoining pressure models.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".