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Cited by 498

The DOI matches its Crossref record; 22 of the 22 references it cites were found in a registry or an index.

Random packings of spheres and spherocylinders simulated by mechanical contraction

Open access
Williams, S. R., Philipse, A. P.·2003·Physical Review E

Abstract

We introduce a simulation technique for creating dense random packings of hard particles. The technique is particularly suited to handle particles of different shapes. Dense amorphous packings of spheres have been formed, which are consistent with the existing work on random sphere packings. Packings of spherocylinders have also been simulated out to the large aspect ratio of alpha=160.0. Our method packs randomly oriented spherocylinders to densities that reproduce experimental results on anisotropic powders and colloids very well. Interestingly, the highest packing density of phi=0.70 is achieved for very short spherocylinders rather than spheres. This suggests that slightly changing the shapes of the particles forming a hard sphere glass could cause it to melt. Comparisons between the equilibrium phase diagram for hard spherocylinders and the densest possible amorphous packings have interesting implications on the crystallization of spherocylinders as a function of aspect ratio.

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Crossref · 10.1103/physreve.67.051301

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Metadata

Authors
Williams, S. R., & Philipse, A. P.
Venue
Physical Review E
Published
2003-05-07
Volume
67
Issue
5
Pages
051301-051301
ISSN
  • 1063-651X (ISSN-L)
  • 1095-3787
OpenAlex
W1996959238
Cited by
498
References
22
FWCI
8.27
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Random packings of spheres and spherocylinders simulated by mechanical contraction. https://app.cochat.ai/papers/10.1103/physreve.67.051301
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Williams, S. R., & Philipse, A. P. (2003). Random packings of spheres and spherocylinders simulated by mechanical contraction. Physical Review E. https://doi.org/10.1103/physreve.67.051301

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.