Structural phases of colloids interacting via a flat-well potential

Abstract

Using Langevin dynamics simulations we investigate the self-assembly of colloidal particles in two dimensions interacting via an isotropic potential, which comprises both a hard-core repulsion and an additional softened square-well potential of controllable width α. In dilute concentrations, the particles assemble in small clusters with a well-defined crystalline order. For small values of α the particles form triangular lattices. As α is increased, more particles can be captured by the potential well giving rise to different crystalline symmetries and the structural phase transitions between them. The main structures observed are triangular, square, and a mixture of square and triangular cells forming an Archimedean tiling. In the concentrated regime the particles form a single percolated cluster with essentially the same orderings at the same ranges of α values as observed in the dilute regime, thus showing that cluster boundary effects have a minor influence on the cluster crystal symmetry. By using energy analysis and geometry arguments we discuss how the different observed structures minimize the system energy at different values of α.

Structural orderings of anisotropically confined colloids interacting via a quasi-square-well potential

“…Due to the large presence of defects, as well as the presence of fringes on the edge of the cluster, the £ parameter was not effective in identifying this phase. Note that the quasicrystalline phase could also be found in our previous work [43] in which colloids were unconfined.…”

“…(2a), (2b), and (2c), is an extension of the potential treated in Ref. [43], In this reference, the interaction potential is given solely by the sum of the two first terms f /HC(r,7 ) and t / pw'(r7 ). It will be demonstrated, in the following sections, that the Gaussian term ( / c (r,7) plays a crucial role on the self-assembly process of trapped colloids and gives rise to a wide variety of configurational orders.…”

“…In Ref. [43], where a system containing nonrepulsive colloids was considered, the different microscopic states, that is, the triangular, squared, and Archimedean tiling patterns, were characterized successfully by using the symmetry parameter §.…”

Machine learning for crystal identification and discovery

“…Experimentally, crystal structures with tunable properties can be created through anisotropic colloidal building blocks, DNA‐coated nanoparticles, or a host of other interactions . In computational studies of colloidal matter, various simple, as well as complex, phases can be formed through systematic modification of entropic or enthalpic interparticle interactions . For exploratory studies of these parameter spaces, the design process is difficult: after the computationally expensive undertaking of performing simulations, each data set must also be analyzed—a procedure that is often manual, repetitive, and labor‐intensive in the case of crystal structure identification.…”

Two-dimensional crystals of star polymers: a tale of tails

“…In the past decade, extensive computer simulations have revealed that a plethora of non-hexagonal crystals and quasicrystals can also be formed by particles that interact through isotropic po- 15 , whereas a double well leads to the formation of decagonal and dodecagonal two-dimensional quasicrystals 16 . More complex and designed potentials featuring multiple attractive minima and repulsive regions, can give rise to the sought-after honeycomb lattice 17 , which exhibits unique electronic and photonic properties 3,18 .…”