Extraction of monomer-cluster association rate constants from water nucleation data measured at extreme supersaturations
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Bibliographic record
Abstract
We utilize recently reported data for water nucleation in the uniform postnozzle flow of pulsed Laval expansions to derive water monomer association rates with clusters. The nucleation experiments are carried out at flow temperatures of 87.0 K and 47.5 K and supersaturations of lnS ∼ 41 and 104, respectively. The cluster size distributions are measured at different nucleation times by mass spectrometry coupled with soft single-photon ionization at 13.8 eV. The soft ionization method ensures that the original cluster size distributions are largely preserved upon ionization. We compare our experimental data with predictions by a kinetic model using rate coefficients from a previous ab initio calculation with a master equation approach. The prediction and our experimental data differ, in particular, at the temperature of 87.0 K. Assuming cluster evaporation to be negligible, we derive association rate coefficients between monomer and clusters purely based on our experimental data. The derived dimerization rate lies 2-3 orders of magnitude below the gas kinetic collision limit and agrees with the aforementioned ab initio calculation. Other than the dimerization rate, however, the derived rate coefficients between monomer and cluster j (j ≥ 3) are on the same order of magnitude as the kinetic collision limit. A kinetic model based on these results confirms that coagulation is indeed negligible in our experiments. We further present a detailed analysis of the uncertainties in our experiments and methodology for rate derivation and specify the dependency of the derived rates on uncertainties in monomer and cluster concentrations.
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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 | 0.001 | 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)
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Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
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