Surface excess properties from energy transport measurements during water evaporation
Bibliographic record
Abstract
When water evaporates at high rates, recent studies indicate thermal conduction to the interface does not provide enough energy to evaporate water at the observed rate and that it is perhaps thermocapillary convection that transports the remaining energy. This possibility is examined by applying the Gibbs dividing-surface approximation to develop an expression for the energy transported along the interface. When this energy transport rate is compared with that required to evaporate the liquid at the observed rate, it is found that a Gibbs excess property, the "surface-thermal capacity," can be evaluated. A series of 19 evaporation experiments has been conducted under conditions for which there was no buoyancy-driven convection and for which the evaporation rate was progressively increased. For Marangoni numbers, (Ma) less than approximately 100, the interface was quiescent and thermal conduction (the Stefan condition) correctly predicted the energy transport rate to the surface. For experiments with 100 22,000, the interfacial flow was turbulent and viscous dissipation became important.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".