Issue 7, 2016

The relationship between local density and bond-orientational order during crystallization of the Gaussian core model

Abstract

Whether nucleation is triggered by density or by bond-orientational order is one of the most hotly debated issues in recent investigations of the crystallization process. Here, we present a numerical study of the relationship between them for soft particles within the isothermal–isobaric ensemble. We compress the system and thus obtain the fluid-solid transition. By investigating locally dense-packed particles and particles with a relatively high bond-orientational order in the compressing process, we find a sharp increase of the spatial correlations for both densely packed particles and highly bond-orientational ordered particles at the phase transition point, which provide new characterization methods for the liquid–crystal transition. We also find that it is the bond-orientational order rather than density that triggers the nucleation process. The relationship between the local density and the bond-orientational order parameter is strongly affected by the characterization methods used. The local bond order parameter (q6) shows clear correlation with the local density (ρ) in the fluid stage, while the coarse-grained form ([q with combining macron]6) does not correlate with ρ at all, owing to the comparable spatial scales of q6 and ρ. Nevertheless, [q with combining macron]6 shows an obvious advantage in distinguishing between solid and liquid particles in our work. These results may elevate our understanding of the mechanism of the crystallization process.

Graphical abstract: The relationship between local density and bond-orientational order during crystallization of the Gaussian core model

Supplementary files

Article information

Article type
Paper
Submitted
03 Nov 2015
Accepted
28 Dec 2015
First published
06 Jan 2016

Soft Matter, 2016,12, 2009-2016

Author version available

The relationship between local density and bond-orientational order during crystallization of the Gaussian core model

Y. Li and Z. Sun, Soft Matter, 2016, 12, 2009 DOI: 10.1039/C5SM02712H

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