Literature DB >> 27566403

Generic phase diagram of binary superlattices.

Alexei V Tkachenko1.   

Abstract

Emergence of a large variety of self-assembled superlattices is a dramatic recent trend in the fields of nanoparticle and colloidal sciences. Motivated by this development, we propose a model that combines simplicity with a remarkably rich phase behavior applicable to a wide range of such self-assembled systems. Those systems include nanoparticle and colloidal assemblies driven by DNA-mediated interactions, electrostatics, and possibly, controlled drying. In our model, a binary system of large and small hard spheres (L and S, respectively) interacts via selective short-range ("sticky") attraction. In its simplest version, this binary sticky sphere model features attraction only between S and L particles. We show that, in the limit when this attraction is sufficiently strong compared with [Formula: see text], the problem becomes purely geometrical: the thermodynamically preferred state should maximize the number of [Formula: see text] contacts. A general procedure for constructing the phase diagram as a function of system composition f and particle size ratio r is outlined. In this way, the global phase behavior can be calculated very efficiently for a given set of plausible candidate phases. Furthermore, the geometric nature of the problem enables us to generate those candidate phases through a well-defined and intuitive construction. We calculate the phase diagrams for both 2D and 3D systems and compare the results with existing experiments. Most of the 3D superlattices observed to date are featured in our phase diagram, whereas several more are predicted for future discovery.

Keywords:  colloids; self-assembly; sticky spheres; superlattices

Year:  2016        PMID: 27566403      PMCID: PMC5027423          DOI: 10.1073/pnas.1525358113

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  24 in total

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Journal:  Nano Lett       Date:  2012-04-06       Impact factor: 11.189

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Authors:  Robert J Macfarlane; Byeongdu Lee; Matthew R Jones; Nadine Harris; George C Schatz; Chad A Mirkin
Journal:  Science       Date:  2011-10-14       Impact factor: 47.728

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Authors:  A-P Hynninen; M E Leunissen; A van Blaaderen; M Dijkstra
Journal:  Phys Rev Lett       Date:  2006-01-04       Impact factor: 9.161

5.  DNA-guided crystallization of colloidal nanoparticles.

Authors:  Dmytro Nykypanchuk; Mathew M Maye; Daniel van der Lelie; Oleg Gang
Journal:  Nature       Date:  2008-01-31       Impact factor: 49.962

6.  Designing DNA-grafted particles that self-assemble into desired crystalline structures using the genetic algorithm.

Authors:  Babji Srinivasan; Thi Vo; Yugang Zhang; Oleg Gang; Sanat Kumar; Venkat Venkatasubramanian
Journal:  Proc Natl Acad Sci U S A       Date:  2013-10-28       Impact factor: 11.205

7.  Design rule for colloidal crystals of DNA-functionalized particles.

Authors:  Francisco J Martinez-Veracoechea; Bianca M Mladek; Alexei V Tkachenko; Daan Frenkel
Journal:  Phys Rev Lett       Date:  2011-07-20       Impact factor: 9.161

8.  Binary nanoparticle superlattices of soft-particle systems.

Authors:  Alex Travesset
Journal:  Proc Natl Acad Sci U S A       Date:  2015-07-20       Impact factor: 11.205

9.  Dielectric effects in the self-assembly of binary colloidal aggregates.

Authors:  Kipton Barros; Erik Luijten
Journal:  Phys Rev Lett       Date:  2014-07-01       Impact factor: 9.161

10.  Crystallization of DNA-coated colloids.

Authors:  Yu Wang; Yufeng Wang; Xiaolong Zheng; Étienne Ducrot; Jeremy S Yodh; Marcus Weck; David J Pine
Journal:  Nat Commun       Date:  2015-06-16       Impact factor: 14.919

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  3 in total

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Authors:  Evan Pretti; Hasan Zerze; Minseok Song; Yajun Ding; Nathan A Mahynski; Harold W Hatch; Vincent K Shen; Jeetain Mittal
Journal:  Soft Matter       Date:  2018-08-01       Impact factor: 3.679

2.  Using symmetry to elucidate the importance of stoichiometry in colloidal crystal assembly.

Authors:  Nathan A Mahynski; Evan Pretti; Vincent K Shen; Jeetain Mittal
Journal:  Nat Commun       Date:  2019-05-02       Impact factor: 14.919

3.  A Deep Learning Framework Discovers Compositional Order and Self-Assembly Pathways in Binary Colloidal Mixtures.

Authors:  Runfang Mao; Jared O'Leary; Ali Mesbah; Jeetain Mittal
Journal:  JACS Au       Date:  2022-07-19
  3 in total

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