Large scale molecular dynamics simulations of homogeneous nucleation
J Diemand and R Angelil and KK Tanaka and H Tanaka, JOURNAL OF CHEMICAL PHYSICS, 139, 074309 (2013).
We present results from large-scale molecular dynamics (MD) simulations of homogeneous vapor-to-liquid nucleation. The simulations contain between 1 x 10(9) and 8 x 10(9) Lennard-Jones (LJ) atoms, covering up to 1.2 mu s (56 x 10(6) time-steps). They cover a wide range of supersaturation ratios, S similar or equal to 1.55-10(4), and temperatures from kT = 0.3 to 1.0 epsilon (where epsilon is the depth of the LJ potential, and k is the Boltzmann constant). We have resolved nucleation rates as low as 10(17) cm(-3) s(-1) (in the argon system), and critical cluster sizes as large as 100 atoms. Recent argon nucleation experiments probe nucleation rates in an overlapping range, making the first direct comparison between laboratory experiments and molecular dynamics simulations possible: We find very good agreement within the uncertainties, which are mainly due to the extrapolations of argon and LJ saturation curves to very low temperatures. The self- consistent, modified classical nucleation model of Girshick and Chiu J. Chem. Phys. 93, 1273 (1990) underestimates the nucleation rates by up to 9 orders of magnitudes at low temperatures, and at kT = 1.0 epsilon it overestimates them by up to 10(5). The predictions from a semi- phenomenological model by Laaksonen et al. Phys. Rev. E 49, 5517 (1994) are much closer to our MD results, but still differ by factors of up to 104 in some cases. At low temperatures, the classical theory predicts critical clusters sizes, which match the simulation results (using the first nucleation theorem) quite well, while the semi- phenomenological model slightly underestimates them. At kT = 1.0 epsilon, the critical sizes from both models are clearly too small. In our simulations the growth rates per encounter, which are often taken to be unity in nucleation models, lie in a range from 0.05 to 0.24. We devise a new, empirical nucleation model based on free energy functions derived from subcritical cluster abundances, and find that it performs well in estimating nucleation rates. (C) 2013 AIP Publishing LLC.
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