Front structure and dynamics in dense colonies of motile bacteria: Role of active turbulence.

We study the spreading of a bacterial colony undergoing turbulentlike collective motion. We present two minimalistic models to investigate the interplay between population growth and coherent structures arising from turbulence. Using direct numerical simulation of the proposed models we find that turbulence has two prominent effects on the spatial growth of the colony: (a) the front speed is enhanced, and (b) the front gets crumpled. Both these effects, which we highlight by using statistical tools, are markedly different in our two models. We also show that the crumpled front structure and the passive scalar fronts in random flows are related in certain regimes.

Basis function sampling: a new paradigm for material property computation.

Wang-Landau sampling, and the associated class of flat histogram simulation methods have been remarkably helpful for calculations of the free energy in a wide variety of physical systems. Practically, convergence of these calculations to a target free energy surface is hampered by reliance on parameters which are unknown a priori. Here, we derive and implement a method built upon orthogonal functions which is fast, parameter-free, and (importantly) geometrically robust. The method is shown to be highly effective in achieving convergence. An important feature of this method is its ability to attain arbitrary levels of description for the free energy. It is thus ideally suited to in silico measurement of elastic moduli and other material properties related to free energy perturbations. We demonstrate the utility of such applications by applying our method to calculate the Frank elastic constants of the Lebwohl-Lasher model of liquid crystals.

Measuring liquid crystal elastic constants with free energy perturbations.

A first principles method is proposed to calculate the Frank elastic constants of nematic liquid crystals. These include the constants corresponding to standard splay, twist and bend deformations, and an often-ignored surface-like contribution known as saddle-splay. The proposed approach is implemented on the widely studied Gay-Berne (3, 5, 2, 1) model [J. G. Gay and B. J. Berne, J. Chem. Phys., 1981, 74, 3316], and the effects of temperature and system size on the elastic constants are examined in the nematic phase. The results of simulations for splay, twist, and bend elastic constants are consistent with those from previous literature reports. The method is subsequently applied to the saddle-splay elastic constant k24 which is found to exist at the limits of the Ericksen inequalities governing positive definite free energy. Finally, extensions of the method are discussed that present a new paradigm for in silico measurements of elastic constants.

Surface Adsorption in Nonpolarizable Atomic Models.

Many ionic solutions exhibit species-dependent properties, including surface tension and the salting-out of proteins. These effects may be loosely quantified in terms of the Hofmeister series, first identified in the context of protein solubility. Here, our interest is to develop atomistic models capable of capturing Hofmeister effects rigorously. Importantly, we aim to capture this dependence in computationally cheap "hard" ionic models, which do not exhibit dynamic polarization. To do this, we have performed an investigation detailing the effects of the water model on these properties. Though incredibly important, the role of water models in simulation of ionic solutions and biological systems is essentially unexplored. We quantify this via the ion-dependent surface attraction of the halide series (Cl, Br, I) and, in so doing, determine the relative importance of various hypothesized contributions to ionic surface free energies. Importantly, we demonstrate surface adsorption can result in hard ionic models combined with a thermodynamically accurate representation of the water molecule (TIP4Q). The effect observed in simulations of iodide is commensurate with previous calculations of the surface potential of mean force in rigid molecular dynamics and polarizable density-functional models. Our calculations are direct simulation evidence of the subtle but sensitive role of water thermodynamics in atomistic simulations.

Liquid-crystal mediated nanoparticle interactions and gel formation.

Colloidal particles embedded within nematic liquid crystals exhibit strong anisotropic interactions arising from preferential orientation of nematogens near the particle surface. Such interactions are conducive to forming branched, gel-like aggregates. Anchoring effects also induce interactions between colloids dispersed in the isotropic liquid phase, through the interactions of the pre-nematic wetting layers. Here we utilize computer simulation using coarse-grained mesogens to perform a molecular-level calculation of the potential of mean force between two embedded nanoparticles as a function of anchoring for a set of solvent conditions straddling the isotropic-nematic transition. We observe that strong, nontrivial interactions can be induced between particles dispersed in mesogenic solvent, and explore how such interactions might be utilized to induce a gel state in the isotropic and nematic phases.

Modeling of formation of nanoparticles in reverse micellar systems: Ostwald ripening of silver halide particles.

There are many possible size enhancement processes that affect the formation of nanoparticles in reverse micelles, such as coagulation and Ostwald ripening, and different physical systems are likely to follow one or more of these mechanisms depending upon the properties of the system. It has been suggested that silver halide particles, prepared from a reverse micellar system of AgNO3 and KCl in NP-6/cyclohexane solution, increase in size due to Ostwald ripening (Kimijima, K.; Sugimoto, T. J. Phys. Chem. B 2004, 108, 3735), which occurs due to the dependence of the solubility of the particles on the particle size so that the larger particles grow at the expense of smaller particles. This study provides a modeling framework to quantitatively analyze the ripening process of nanoparticles produced in reverse micellar systems.