Thermodynamics of heterogeneous multicomponent condensation on mixed nuclei
Bibliographic record
Abstract
We consider a nucleating center consisting of both an insoluble core and soluble species and develop the thermodynamics of isothermal formation of a droplet on such a nucleus in a multicomponent vapor mixture. Two different approaches to the derivation of the free energy of droplet formation within the framework of the capillarity approximation are considered. If condensation is not barrierless, the free energy of formation describes a multidimensional free-energy surface having a “well” point and a “saddle” point. It is shown that in a strict theory, taking account of surface enrichment effects, the compositions of droplets corresponding to these two points are equal and can be found without knowing the surface tension of the droplet. For the case of no surfactants in the droplet, we extend the Kuni method of investigating the behavior of the free energy of droplet formation to the case of heterogeneous multicomponent condensation on mixed nuclei, which makes it possible to find out all the main features of the free-energy surface without explicitly knowing the free-energy itself. The theoretical results are illustrated by numerical calculations for the water–methanol condensation on mixed nuclei.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".