Topological "Shape" in Micellar Dynamics.

For micelles, "shape" is prominent in rheological computations of fluid flow, but this "shape" is often expressed too informally to be useful for rigorous analyses. We formalize topological "shape equivalence" of micelles, both globally and locally, to enable visualization of computational fluid dynamics. Although topological methods in visualization provide significant insights into fluid flows, this opportunity has been limited by the known difficulties in creating representative geometry. We present an agile geometric algorithm to represent the micellar shape for input into fluid flow visualizations. We show that worm-like and cylindrical micelles have formally equivalent shapes, but that visualization accentuates unexplored differences. This global-local paradigm is extensible beyond micelles.

Structural relaxation dynamics of colloidal nanotrimers.

By Molecular Dynamics simulation, we investigate the dynamics of isotropic fluids of colloidal nanotrimers whose interactions are described by varying the strength of attractive and repulsive terms of the Mie potential. To provide a consistent comparison between the systems described by different force fields, we determine the phase diagram and critical points of each system, characterize the morphology of high-density liquid phases at the same reduced temperature and density, and finally investigate their long-time relaxation dynamics. In particular, we detect an especially complex dynamics that reveals the existence of slow and fast nanotrimers and the resulting occurrence of non-Gaussianity, which develops at intermediate timescales. Deviations from Gaussianity are temporary and vanish within the timescales of the system's density fluctuations decay, when a Fickian-like diffusion regime is eventually observed.

The Role of Chemical Heterogeneity in Surfactant Adsorption at Solid-Liquid Interfaces.

Chemical heterogeneity of solid surfaces disrupts the adsorption of surfactants from the bulk liquid. While its presence can hinder the performance of some formulations, bespoke chemical patterning could potentially facilitate controlled adsorption for nanolithography applications. Although some computational studies have investigated the impact of regularly patterned surfaces on surfactant adsorption, in reality, many interesting surfaces are expected to be stochastically disordered and this is an area unexplored via simulations. In this paper, we describe a new algorithm for the generation of randomly disordered chemically heterogeneous surfaces and use it to explore the adsorption behavior of four model nonionic surfactants. Using novel analysis methods, we interrogate both the global surface coverage (adsorption isotherm) and behavior in localized regions. We observe that trends in adsorption characteristics as surfactant size, head/tail ratio, and surface topology are varied and connect these to underlying physical mechanisms. We believe that our methods and approach will prove useful to researchers seeking to tailor surface patterns to calibrate nonionic surfactant adsorption.

Efficient Algorithm for the Topological Characterization of Worm-like and Branched Micelle Structures from Simulations.

Many surfactant-based formulations are utilized in industry as they produce desirable viscoelastic properties at low concentrations. These properties are due to the presence of worm-like micelles (WLMs), and as a result, understanding the processes that lead to WLM formation is of significant interest. Various experimental techniques have been applied with some success to this problem but can encounter issues probing key microscopic characteristics or the specific regimes of interest. The complementary use of computer simulations could provide an alternate route to accessing their structural and dynamic behavior. However, few computational methods exist for measuring key characteristics of WLMs formed in particle simulations. Further, their mathematical formulations are challenged by WLMs with sharp curvature profiles or density fluctuations along the backbone. Here, we present a new topological algorithm for identifying and characterizing WLMs in particle simulations, which has desirable mathematical properties that address shortcomings in previous techniques. We apply the algorithm to the case of sodium dodecyl sulfate micelles to demonstrate how it can be used to construct a comprehensive topological characterization of the observed structures.

Microscopic Origin of the Hofmeister Effect in Gelation Kinetics of Colloidal Silica.

The gelation kinetics of silica nanoparticles is a central process in physical chemistry, yet it is not fully understood. Gelation times are measured to increase by over 4 orders of magnitude, simply changing the monovalent salt species from CsCl to LiCl. This striking effect has no microscopic explanation within current paradigms. The trend is consistent with the Hofmeister series, pointing to short-ranged solvation effects not included in the standard colloidal (DLVO) interaction potential. By implementing a simple form for short-range repulsion within a model that relates the gelation timescale to the colloidal interaction forces, we are able to explain the many orders of magnitude difference in the gelation times at fixed salt concentration. The model allows us to estimate the magnitude of the non-DLVO hydration forces, which dominate the interparticle interactions on the length scale of the hydrated ion diameter. This opens the possibility of finely tuning the gelation time scale of nanoparticles by just adjusting the background electrolyte species.

Flow-induced aggregation and breakup of particle clusters controlled by surface nanoroughness.

Interactions between colloidal particles are strongly affected by the particle surface chemistry and composition of the liquid phase. Further complexity is introduced when particles are exposed to shear flow, often leading to broad variation of the final properties of formed clusters. Here we discover a new dynamical effect arising in shear-induced aggregation where repeated aggregation and breakup events cause the particle surface roughness to irreversibly increase with time, thus decreasing the bond adhesive energy and the resistance of the aggregates to breakup. This leads to a pronounced overshoot in the time evolution of the aggregate size, which can only be explained with the proposed mechanism. This is demonstrated by good agreement between time evolution of measured light-scattering data and those calculated with a population-balance model taking into account the increase in the primary particle nanoroughness caused by repeated breakup events resulting in the decrease of bond adhesive energy as a function of time. Thus, the proposed model is able to reproduce the overshoot phenomenon by taking into account the physicochemical parameters, such as pH, till now not considered in the literature. Overall, this new effect could be exploited in the future to achieve better control over the flow-induced assembly of nanoparticles.