Jump to main content
Jump to site search


Universal self-assembly of one-component three-dimensional dodecagonal quasicrystals

Abstract

Using molecular dynamics simulations, we study computational self-assembly of one-component three-dimensional dodecagonal (12-fold) quasicrystals in systems with two-length-scale potentials. Existing criteria for three-dimensional quasicrystal formation are quite complicated and rather inconvenient for particle simulations. So to localize numerically the quasicrystal phase, one should usually simulate over a wide range of system parameters. We show how to universally localize the parameters values at which dodecagonal quasicrystal order may appear for a given particle system. For that purpose, we use a criterion recently proposed for predicting decagonal quasicrystal formation in one-component two-length-scale systems. The criterion is based on two dimensionless effective parameters describing the fluid structure which are extracted from radial distribution function. The proposed method allows reducing the time spent for searching the parameters favoring certain solid structure for a given system. We show that the method works well for dodecagonal quasicrystals; this results is verified on four systems with different potentials: Dzugutov potential, oscillating potential which mimics metal interactions, repulsive shoulder potential describing effective interaction for core/shell model of colloids and embedded-atom model potential for aluminum. Our results suggest that mechanism of dodecagonal quasicrystal formation is universal for both metallic and soft-matter systems and it is based on competition between interparticle scales.

Back to tab navigation

Publication details

The article was received on 03 May 2017, accepted on 13 Jun 2017 and first published on 14 Jun 2017


Article type: Paper
DOI: 10.1039/C7SM00883J
Citation: Soft Matter, 2017, Accepted Manuscript
  •   Request permissions

    Universal self-assembly of one-component three-dimensional dodecagonal quasicrystals

    R. Ryltsev and N. Chtchelkatchev, Soft Matter, 2017, Accepted Manuscript , DOI: 10.1039/C7SM00883J

Search articles by author

Spotlight

Advertisements