Analyses of Nucleation Rates from Molecular Dynamics Simulations

Bartell, Lawrence S.

doi:10.1021/jp020382q

Cited by 14 publications

(15 citation statements)

References 6 publications

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“…Changing the threshold volumes where nucleation is assumed to have occured does change the estimated nucleation rates somewhat, but the overall trends observed were not greatly impacted by these threshold values. To obtain nucleation rates, we consider that the N 0 different simulation boxes with volumes V box are parts of a larger volume V. [30][31][32][33] When a nucleation event occurs in a simulation box, the volume available for nucleation decreases to V-V box . The rate of change of the number of simulation boxes that have not yet nucleated ͑N͒ is given by…”

Section: B Nucleation Times and Ratesmentioning

confidence: 99%

Comparison of heterogeneous and homogeneous bubble nucleation using molecular simulations

2007

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NPT and NP zz T molecular dynamics simulations of Lennard-Jones atoms were used to compare homogeneous and heterogeneous nucleation. In the heterogeneous cases, the attraction between the fluid and a smooth fcc ͑100͒ surface was varied. Multiple simulations were used to determine nucleation times from which nucleation rates were estimated using a transient nucleation model. Calculations demonstrated a clear enhancement in nucleation rates in the heterogeneous cases compared to the homogeneous case. To obtain homogeneous nucleation rates similar to the heterogeneous cases required temperatures about 10 K higher. It was also found that void formation was favored as the attraction between the liquid and solid was decreased. Varying the system size, thermostatting method, and barostat time constant affected quantitative results, but not the qualitative trends.

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Section: B Nucleation Times and Ratesmentioning

confidence: 99%

Comparison of heterogeneous and homogeneous bubble nucleation using molecular simulations

2007

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“…To account for the appreciable statistical uncertainties associated with the stochastic nature of the hypothetical nucleation events when 0 is small, a weighted least-squares procedure was carried out to determine and 0 . Details are given in our previous report [8]. Figure 2 displays images of a nanoparticle at various times during the annealing run from one of the 18 particles with different thermal histories.…”

Section: Estimation Of Recrystallization Ratementioning

confidence: 99%

Recrystallization from a Three-Grain Crystalline Iron

Zhao

Chen

Huang

et al. 2015

Journal of Solid State Physics

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The solid state recrystallization and grain boundary migrations in an iron nanoparticle Fe 2616 with three grains were studied by a molecular dynamics simulation. It was found that nucleation rates could be determined as the smaller grains were consumed by the larger ones. Moreover, the grain disorder was more important than the misorientation angle in governing the rates. Suggestions about the critical nuclei for the recrystallization are proposed. No obvious interaction between the grain boundaries was observed in the example studied in this report.

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“…Although the study of the freezing of glasses offered the most direct way to characterize transient nucleation, in principle, analyses of the problem indicated that thousands of independent stochastic data points ͑sets of times at which nuclei materialize͒ are needed to yield a statistically reliable portrayal of the transient regime. 13,14 Such large sets of data have yet to be generated in laboratory experiments. The need for such a large number of points is mainly due to the correlation between the three principal parameters to characterize the transient regime ͑see below͒.…”

Section: Introductionmentioning

confidence: 99%

A new procedure for analyzing the nucleation kinetics of freezing in computer simulation

Bartell

2006

The Journal of Chemical Physics

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A new method for deriving the size of the critical nucleus and the Zeldovich factor directly from kinetic data is presented. Moreover, in principle, the form of G(n), the free energy of formation of nuclei consisting of n molecules, can be inferred. The method involves measuring times of first appearance of nuclei of size n in the transient regime and applying the Becker-Doring theory. Times of first appearance exhibit the same characteristics as the conventional times associated with N(n,t), the number of nuclei of at least size n per unit volume that have materialized at time t. That is, they are well represented by three nucleation parameters, the reduced moment, the time lag, and the steady state nucleation rate. But unlike the conventional steady state rate which is independent of n, the steady state times of first appearance vary with n. In order to characterize the three nucleation parameters with precision, however, thousands of independent stochastic events with known n are required. Such sets of data are readily generated in molecular dynamic simulations but, so far, not in laboratory experiments. Results are illustrated by an analysis of simulations of the spontaneous freezing of large clusters of SeF6.

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Analyses of Nucleation Rates from Molecular Dynamics Simulations

Cited by 14 publications

References 6 publications

Comparison of heterogeneous and homogeneous bubble nucleation using molecular simulations

Comparison of heterogeneous and homogeneous bubble nucleation using molecular simulations

Recrystallization from a Three-Grain Crystalline Iron

A new procedure for analyzing the nucleation kinetics of freezing in computer simulation

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