Experimental investigation of interfacial energy transport in an evaporating sessile droplet for evaporative cooling applications
Bibliographic record
Abstract
In this paper we experimentally examine evaporation flux distributions and modes of interfacial energy transport for continuously fed evaporating spherical sessile water droplets in a regime that is relevant for applications, particularly for evaporative cooling systems. The contribution of the thermal conduction through the vapor phase was found to be insignificant compared to the thermal conduction through the liquid phase for the conditions we investigated. The local evaporation flux distributions associated with thermal conduction were found to vary along the surface of the droplet. Thermal conduction provided a majority of the energy required for evaporation but did not account for all of the energy transport, contributing 64±3%, 77±3%, and 77±4% of the energy required for the three cases we examined. Based on the temperature profiles measured along the interface we found that thermocapillary flow was predicted to occur in our experiments, and two convection cells were consistent with the temperature distributions for higher substrate temperatures while a single convection cell was consistent with the temperature distributions for a lower substrate temperature.
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 | 0.000 | 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) | 0.001 | 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".