Generic phase diagram of binary superlattices

• Published in: Proceedings of the National Academy of Sciences - PNAS Vol. 113; no. 37; pp. 10269 - 10274
• Main Author: Tkachenko, Alexei V.
• Format: Journal Article
• Language: English
• Published: United States National Academy of Sciences 13-09-2016
• Subjects: Binary system; Electrostatics; Nanoparticles; Physical Sciences; Thermodynamics; self-assembly; colloids; sticky spheres; superlattices
• ISSN: 0027-8424; 1091-6490
• DOI: 10.1073/pnas.1525358113

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 kT, the problem becomes purely geometrical: the thermodynamically preferred state should maximize the number of LS 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.