Formation free energy of clusters in vapor-liquid nucleation: A Monte Carlo simulation study

Oh, Kwang Jin; Zeng, Xiao Cheng

doi:10.1063/1.478331

Cited by 69 publications

(39 citation statements)

References 33 publications

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“…In contrast, the NVT simulations have mostly been performed on small systems so as to result in the formation of a single droplet and the size of the droplet and density of the surrounding vapor is then a function of the size of the simulation cell. One exception is the work of Oh and Zeng [6,36] which was done using relatively large systems. Comparison to their work will be made below.…”

Section: B Comparison To Simulationmentioning

confidence: 99%

“…For this reason, the process of homogeneous nucleation of bubbles in a superheated fluid and of droplets in a supersaturated vapor has a long history going all the way back to the fundamental paper of van der Waals [1,2,3]. Recent years have seen tremendous progress in the development of simulation methods that circumvent the time and size limitations of simulations to allow for the study of rare events, such as homogeneous nucleation [4,5,6,7]. In parallel, various approaches to a theoretical description of nucleation have been formulated with varying degrees of success [8,9,10].…”

Section: Introductionmentioning

confidence: 99%

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Density functional theory of inhomogeneous liquids. III. Liquid-vapor nucleation

Lutsko

2008

The Journal of Chemical Physics

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The process of nucleation of vapor bubbles from a superheated liquid and of liquid droplets from a supersaturated vapor is investigated using the Modified-Core van der Waals model Density Functional Theory (Lutsko, JCP 128, 184711 (2008)). A novel approach is developed whereby nucleation is viewed as a transition from a metastable state to a stable state via the minimum free energy path which is identified using the nudged elastic-band method for exploring free energy surfaces. This allows for the unbiased calculation of the properties of sub-and super-critical clusters, as well as of the critical cluster. For Lennard-Jones fluids, the results compare well to simulation and support the view that even at high supersaturation nucleation proceeds smoothly rather than via spinodal-like instabilities as has been suggested recently.

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Section: B Comparison To Simulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Density functional theory of inhomogeneous liquids. III. Liquid-vapor nucleation

Lutsko

2008

The Journal of Chemical Physics

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“…It may be shown that (6) which shifts attention to the free energy difference F (j)− F (j − 1) associated with the addition of a molecule to a (j − 1)-cluster. Computing these differences is the basis of an approach has been used extensively in calculations of cluster free energies [17][18][19][20][21][22][23]. But nucleation is actually controlled by the properties of clusters near the critical size, and one drawback of computing the differences F (j)−F (j −1) is that the predicted nucleation rate could be susceptible to the accumulation of errors in evaluating such a sequence.…”

Section: Introductionmentioning

confidence: 99%

Free energies of molecular clusters determined by guided mechanical disassembly

Tang

Ford

2015

Phys. Rev. E

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The excess free energy of a molecular cluster is a key quantity in models of the nucleation of droplets from a metastable vapour phase; it is often viewed as the free energy arising from the presence of an interface between the two phases. We show how this quantity can be extracted from simulations of the mechanical disassembly of a cluster using guide particles in molecular dynamics. We disassemble clusters ranging in size from 5 to 27 argon-like Lennard-Jones atoms, thermalised at 60 K, and obtain excess free energies, by means of the Jarzynski equality, that are consistent with previous studies. We only simulate the cluster of interest, in contrast to approaches that require a series of comparisons to be made between clusters differing in size by one molecule. We discuss the advantages and disadvantages of the scheme and how it might be applied to more complex systems.

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“…This results in massive discrepancies between the nucleation rates predicted by CNT and those measured in laboratory experiments [6][7][8][9][10][11][12][13][14][15] and molecular dynamics 13,[16][17][18][19][20][21][22][23][24][25][26] or Monte Carlo simulations. [27][28][29][30][31][32][33][34] More recent nucleation theories have made significant improvements since the introduction of the CNT. Density functional theory (DFT) 35 and the extended modified liquid drop model take into account the extended transition rea) Electronic mail: diemand@physik.uzh.ch; URL: http://www.physik.uzh.ch/~diemand/ gion from liquid to vapor, sometimes referred to as the the "corona," and match MD results far better than the CNT.…”

Section: Introductionmentioning

confidence: 99%

Large scale molecular dynamics simulations of homogeneous nucleation

Diemand

Angélil

Tanaka

et al. 2013

The Journal of Chemical Physics

118

163

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We present results from large-scale molecular dynamics (MD) simulations of homogeneous vapor-to-liquid nucleation. The simulations contain between 1 × 109 and 8 × 109 Lennard-Jones (LJ) atoms, covering up to 1.2 s (56 × 106 time-steps). They cover a wide range of supersaturation ratios, S = 1.55-104, and temperatures from kT = 0.3 to 1.0 (where is the depth of the LJ potential, and k is the Boltzmann constant). We have resolved nucleation rates as low as 1017 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 it overestimates them by up to 105. 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 , 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. We present results from large-scale molecular dynamics (MD) simulations of homogeneous vapor-toliquid nucleation. The simulations contain between 1 × 10 9 and 8 × 10 9 Lennard-Jones (LJ) atoms, covering up to 1.2 μs (56 × 10 6 time-steps). They cover a wide range of supersaturation ratios, S 1.55-10 4 , and temperatures from kT = 0.3 to 1.0 (where 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 l...

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Formation free energy of clusters in vapor-liquid nucleation: A Monte Carlo simulation study

Cited by 69 publications

References 33 publications

Density functional theory of inhomogeneous liquids. III. Liquid-vapor nucleation

Density functional theory of inhomogeneous liquids. III. Liquid-vapor nucleation

Free energies of molecular clusters determined by guided mechanical disassembly

Large scale molecular dynamics simulations of homogeneous nucleation

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