Monte Carlo computer simulation of chain formation from nanoparticles

Spontaneous assembly of long chains of nanoparticles (NPs) has been experimentally observed for many different materials including nanocolloids of semiconductors, metal oxides, and metals. While the origin of dipole moment in various colloids can be different, a universal explanation of chain assembly can be provided by the hypothesis of dipole-dipole attraction of nanocolloids. In this paper, we describe the application of the Monte Carlo method for modeling of self-organization of large ensembles of NPs. As the first approximation, the Derjaguin-Landau-Verwey-Overbeek (DLVO) theory provides an adequate description of self-organization of several hundreds of NPs. Unlike microscale colloids that served as a classical model for DLVO, we used a distance-dependent media dielectric constant. The simulated chains are morphologically and geometrically similar to those observed experimentally. This establishes the fundamentally important ability of NPs to self-assemble due to their intrinsic anisotropy. Thermodynamic analysis of Monte Carlo results reveals the role of partial removal of the stabilizer shell in CdTe nanocolloids necessary for reduction of interparticle repulsion. Analysis of the field distribution around short chains demonstrates that the growth of linear agglomerates is kinetically controlled by a high activation barrier for NPs approaching from all of the directions except one end of the chain. The presented algorithm can be applied to other interparticle interactions, such as induced dipoles, which can stimulate chain formation in the absence of permanent dipole moment. It can also serve as a theoretical foundation for the understanding of the large complex superstructures forming from anisotropic and anisometric NPs. Monte Carlo simulation of nanoscale dipoles can also be extended to the interactions of NP with proteins, and related biological systems important for a variety of applications in medicine.