How CO2 gas accelerates water nucleation at low temperature
Bibliographic record
Abstract
We conducted homogeneous nucleation experiments for dilute binary H2O-CO2 mixtures in Ar-N2 carrier gas with different CO2/H2O ratios at temperatures of 57 and 75 K and total pressures of ∼40 and 70 Pa, respectively. Direct experimental information on the number and type of molecules in the clusters and on the cluster number concentration is obtained by mass spectrometric detection of nucleating clusters that form in the uniform region of Laval expansions. Only homo-molecular water clusters are observed in the mass spectra. However, as the CO2/H2O ratio increases, a significant increase in the nucleation rate is observed. A simple kinetic model suggests that this acceleration of nucleation is due to the formation of short-lived, transient hetero-molecular H2O-CO2 dimers. Comparison with homogeneous binary nucleation of toluene-CO2 and unary nucleation of H2O shows that nucleation becomes more efficient in systems with stronger intermolecular interactions and a larger number of degrees of freedom. Such studies at the molecular level will improve our understanding of homogeneous nucleation mechanisms in atmospheric and industrial processes.
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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) | 0.001 | 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 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".