Nucleation and growth of crystals inside polyethylene nano-droplets.

Polymer crystallization is a long-standing interesting problem both in fundamental polymer physics and in polymer manufacturing. Fundamentally, the connectivity of the macromolecules provides a unique feature for the study of nucleation and growth of crystals in contrast to the crystallization of smaller molecules. In addition, understanding the crystallization in polymers is industrially important due to the necessity of its control to achieve mechanically durable plastic materials. Molecular dynamics simulations offer a suitable way of studying this phenomenon due to their capability to probe the small time and length scales that are characteristic of nucleation. In this paper, we use a long alkane chain model to study nucleation and the growth of polyethylene crystals both within bulk and nano-droplets whose diameters range from about 6 to 11 nm. It is found that the droplets approach being more spherical during the nucleation whereas they deviate from this shape during the growth regime. Strikingly, a mean first passage time analysis indicates that the nucleation rate per unit volume decreases as the droplet size is increased. Finally, visual inspection of the simulation snapshots suggests that nuclei majorly emerged from the surface of the droplets.

Size-dependent thermodynamic structural selection in colloidal crystallization.

Nucleation and growth of crystalline phases play an important role in a variety of physical phenomena, ranging from freezing of liquids to assembly of colloidal particles. Understanding these processes in the context of colloidal crystallization is of great importance for predicting and controlling the structures produced. In many systems, crystallites that nucleate have structures differing from those expected from bulk equilibrium thermodynamic considerations, and this is often attributed to kinetic effects. In this work, we consider the self-assembly of a binary mixture of colloids in two dimensions, which exhibits a structural transformation from a non-close-packed to a close-packed lattice during crystal growth. We show that this transformation is thermodynamically driven, resulting from size dependence of the relative free energy between the two structures. We demonstrate that structural selection can be entirely thermodynamic, in contrast to previously considered effects involving growth kinetics or interaction with the surrounding fluid phase.

Assembly of three-dimensional binary superlattices from multi-flavored particles.

Binary superlattices constructed from nano- or micron-sized colloidal particles have a wide variety of applications, including the design of advanced materials. Self-assembly of such crystals from their constituent colloids can be achieved in practice by, among other means, the functionalization of colloid surfaces with single-stranded DNA sequences. However, when driven by DNA, this assembly is traditionally premised on the pairwise interaction between a single DNA sequence and its complement, and often relies on particle size asymmetry to entropically control the crystalline arrangement of its constituents. The recently proposed "multi-flavoring" motif for DNA functionalization, wherein multiple distinct strands of DNA are grafted in different ratios to different colloids, can be used to experimentally realize a binary mixture in which all pairwise interactions are independently controllable. In this work, we use various computational methods, including molecular dynamics and Wang-Landau Monte Carlo simulations, to study a multi-flavored binary system of micron-sized DNA-functionalized particles modeled implicitly by Fermi-Jagla pairwise interactions. We show how self-assembly of such systems can be controlled in a purely enthalpic manner, and by tuning only the interactions between like particles, demonstrate assembly into various morphologies. Although polymorphism is present over a wide range of pairwise interaction strengths, we show that careful selection of interactions can lead to the generation of pure compositionally ordered crystals. Additionally, we show how the crystal composition changes with the like-pair interaction strengths, and how the solution stoichiometry affects the assembled structures.

Binary Superlattice Design by Controlling DNA-Mediated Interactions.

Most binary superlattices created using DNA functionalization rely on particle size differences to achieve compositional order and structural diversity. Here we study two-dimensional (2D) assembly of DNA-functionalized micron-sized particles (DFPs), and employ a strategy that leverages the tunable disparity in interparticle interactions, and thus enthalpic driving forces, to open new avenues for design of binary superlattices that do not rely on the ability to tune particle size (i.e., entropic driving forces). Our strategy employs tailored blends of complementary strands of ssDNA to control interparticle interactions between micron-sized silica particles in a binary mixture to create compositionally diverse 2D lattices. We show that the particle arrangement can be further controlled by changing the stoichiometry of the binary mixture in certain cases. With this approach, we demonstrate the ability to program the particle assembly into square, pentagonal, and hexagonal lattices. In addition, different particle types can be compositionally ordered in square checkerboard and hexagonal-alternating string, honeycomb, and Kagome arrangements.

Assembly of multi-flavored two-dimensional colloidal crystals.

We systematically investigate the assembly of binary multi-flavored colloidal mixtures in two dimensions. In these mixtures all pairwise interactions between species may be tuned independently. This introduces an additional degree of freedom over more traditional binary mixtures with fixed mixing rules, which is anticipated to open new avenues for directed self-assembly. At present, colloidal self-assembly into non-trivial lattices tends to require either high pressures for isotropically interacting particles, or the introduction of directionally anisotropic interactions. Here we demonstrate tunable assembly into a plethora of structures which requires neither of these conditions. We develop a minimal model that defines a three-dimensional phase space containing one dimension for each pairwise interaction, then employ various computational techniques to map out regions of this phase space in which the system self-assembles into these different morphologies. We then present a mean-field model that is capable of reproducing these results for size-symmetric mixtures, which reveals how to target different structures by tuning pairwise interactions, solution stoichiometry, or both. Concerning particle size asymmetry, we find that domains in this model's phase space, corresponding to different morphologies, tend to undergo a continuous "rotation" whose magnitude is proportional to the size asymmetry. Such continuity enables one to estimate the relative stability of different lattices for arbitrary size asymmetries. Owing to its simplicity and accuracy, we expect this model to serve as a valuable design tool for engineering binary colloidal crystals from multi-flavored components.