A Study of Homogeneous Condensation-Freezing Nucleation of Small Water Droplets in an Expansion Cloud Chamber

Volume nucleation rates for homogeneous freezing in supercooled water microdroplets: results from a combined experimental and modelling approach

“…We define the temperature at the mid-point of the curve, where the volume fraction of ice is 0.5, to be the homogeneous nucleation point. For each particle size, the nucleation temperature is approximately 236 K, in excellent agreement with values from previous work (Anderson et al, 1980;Cziczo and Abbatt, 1999;DeMott and Rogers, 1990). Errors in the volume fraction frozen range from 2 to 3% in the plateau regions, where the samples are predominantly supercooled droplets or ice, to 10% near the nucleation point, where the phase composition is most sensitive to small fluctuations in temperature.…”

Suppression of sub-surface freezing in free-standing thin films of a coarse-grained model of water

“…Therefore, both homogeneous and heterogeneous nucleation are important in determining cloud dynamics. On a molecular level, nucleation events-whether homogeneous or heterogeneous-generally occur at length (≈ 10 −9 m) and time (≈ 10 −9 s) scales that are not accessible to the existing experimental techniques, and there has only been success in measuring nucleation rates in narrow ranges of temperature without gaining any knowledge about the characteristics of the intermediate states [11][12][13][14][15][16][17][18][19][20][21][22].…”

Scaled models for nucleation

“…(25) and (26) serve as good predictors for lnS over a range of nucleation rates. Figure 1 shows experimental homogeneous vapor-to-liquid data for lnS cr /Ω 3/2 for a number of substances [32][33][34][35][36][37][38] using bulk values [28] for Ω. The data for ln S cr conform to the approximate scaling law in Eq.…”

“…(25) rather well in spite of the scatter in data and the approximation of Ω by the bulk value. In fact, the ln S cr data appear to be more linear in [ The linearity of the data of Katz , et al, [37] for toluene is particularly striking, and it is noteworthy that almost all of the Katz data [35][36][37][38] fit this linear dependence extremely well. In Figure 2 is plotted the J = 10 4 cm-3/sec expansion cloud chamber data of Miller,…”

“…Natural logarithm of the threshold (J = 1cm⁻³sec⁻¹) supersaturation ratio, S cr , divided by Ω 3/2 from diffusion chamber and nozzle beam experimental data. The data points are for toluene [37] ( ∆ ), nonane [36] (x ), water [32] ( □ ), n-butylbenzene [37] ( ◯ ), sulfur hexafluoride [11] ( + ) carbon tetrachloride [38] ( ▽ ), chloroform [38] ( ⊗ ), ethanol [35] ( ♢ ), octane [37] ( * ), argon [34] [taken from McGraw [12], Fig. 1] (▼) and acetic acid [33] ( ▲ ).…”