Argon nucleation in a cryogenic nucleation pulse chamber

Iland, Kristina; Wölk, Judith; Strey, R.; Kashchiev, Dimo

doi:10.1063/1.2764486

Cited by 82 publications

(87 citation statements)

References 55 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The temperature scaling of nucleation rates relative to MCNT seems to be qualitatively different: the simulations show an increasing discrepancy with the classical nucleation rate predictions as the temperature is lowered (see Figure 11 and also earlier simulation results 13,22 and the NPC argon experiment 60 ). In the SSN experiment, this discrepancy is nearly constant or even slightly decreasing towards lower temperatures (see Figure 8 in Sinha et al 61 ).…”

Section: Comparison With the Argon Ssn Experimentsmentioning

confidence: 91%

See 1 more Smart Citation

Large scale molecular dynamics simulations of homogeneous nucleation

Diemand

Angélil

Tanaka

et al. 2013

The Journal of Chemical Physics

118

163

View full text Add to dashboard Cite

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...

show abstract

Section: Comparison With the Argon Ssn Experimentsmentioning

confidence: 91%

“…Most laboratory measurements of argon nucleation probe nucleation rates lower than 10 9 cm −3 s −1 (e.g., Iland et al 60 ). The recent development of Laval SSN nucleation experiments 61 has increased the accessible rates enormously, by almost 10 orders of magnitude.…”

Section: Comparison With the Argon Ssn Experimentsmentioning

confidence: 99%

Large scale molecular dynamics simulations of homogeneous nucleation

Diemand

Angélil

Tanaka

et al. 2013

The Journal of Chemical Physics

118

163

View full text Add to dashboard Cite

show abstract

“…The circles depict the argon atoms, while the diamond represents the position of all of the guides at the origin of the cell. [28,29], as well as the experimental studies of Iland et al [30].…”

Section: A Preliminariesmentioning

confidence: 99%

Free energies of molecular clusters determined by guided mechanical disassembly

Tang

Ford

2015

Phys. Rev. E

View full text Add to dashboard Cite

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.

show abstract

“…One notable example is the condensation of Argon, a noble gas, where reports of theoretical and experimentally measured nucleation rates can differ even by 26 orders of magnitude [3][4][5].…”

Section: Introductionmentioning

confidence: 99%

Crystal nucleation as the ordering of multiple order parameters

Russo

Tanaka

2016

The Journal of Chemical Physics

107

View full text Add to dashboard Cite

Nucleation is an activated process in which the system has to overcome a free energy barrier in order for a first-order phase transition between the metastable and the stable phases to take place. In the liquid-to-solid transition the process occurs between phases of different symmetry, and it is thus inherently a multi-dimensional process, in which all symmetries are broken at the transition. In this Focus Article, we consider some recent studies which highlight the multi-dimensional nature of the nucleation process. Even for a single-component system, the formation of solid crystals from the metastable melt involves fluctuations of two (or more) order parameters, often associated with the decoupling of positional and orientational symmetry breaking. In other words, we need at least two order parameters to describe the free-energy of a system including its liquid and crystalline states. This decoupling occurs naturally for asymmetric particles or directional interactions, focusing here on the case of water, but we will show that it also affects spherically symmetric interacting particles, such as the hard-sphere system. We will show how the treatment of nucleation as a multi-dimensional process has shed new light on the process of polymorph selection, on the effect of external fields on the nucleation process, and on glass-forming ability.

show abstract

Argon nucleation in a cryogenic nucleation pulse chamber

Cited by 82 publications

References 55 publications

Large scale molecular dynamics simulations of homogeneous nucleation

Large scale molecular dynamics simulations of homogeneous nucleation

Free energies of molecular clusters determined by guided mechanical disassembly

Crystal nucleation as the ordering of multiple order parameters

Contact Info

Product

Resources

About