Cluster Formation at Extreme Supersaturations: Nucleation versus Barrierless Transition
Bibliographic record
Abstract
We study the process of cluster formation at extreme supersaturations and identify the temperature-supersaturation domain where evaporation can be neglected resulting in a barrierless process with kinetics dominated by the dimer formation. The cluster size distribution obeys the coalescence equation with the pressure–temperature-dependent association rate coefficients ki, j. In view of the crucial role played by kinetics under these extreme conditions, the values of these coefficients calculated within the free molecular collision model are insufficient for the prediction of the nucleation rate and cluster distribution. An alternative is the use of ki, j obtained from the ab initio calculations. We apply these considerations to the analysis of recent water nucleation experiments in the postnozzle flow of a Laval nozzle. Theoretical predictions of nucleation rate are in an excellent agreement with experiment. At the same time, there is a discrepancy in the densities of small clusters. The latter can be attributed to the difference in ki, j extracted from the experimental data and those resulted from the ab initio calculations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".