Mass and heat transfer resistivities at liquid–vapor interfaces: Beyond the ideal gas
Bibliographic record
Abstract
The classical Hertz–Knudsen–Schrage (HKS) model for non-equilibrium mass and heat transfer across liquid–vapor interfaces is extended to account for real gas effects and non-linearity. Specifically, the HKS relations are re-derived for a temperature and velocity dependent condensation coefficient (Tsuruta et al., 1999) and combined with real gas property relations derived from the Enskog–Vlasov (EV) equation (Struchtrup and Frezzotti, 2022). The resulting non-linear Tsuruta–EV–HKS model is valid for mass and heat transfer up to the critical point. The resulting interfacial resistivities exhibit marked dependence on temperature, with resistivities strongly decreasing towards the critical point, as well as non-linear dependence on mass and heat flux. • Hertz–Knudsen–Schrage model extended to real gas vapors and non-linear transport. • Evaporation and heat transfer resistivities vanish towards the critical point. • Non-linearities affect interface resistance. • Molecular Dynamics simulations show similar trends. • Marked temperature dependence and non-linearity affect experiments and simulations.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".