Particle-based mesoscale modeling of flow and transport in complex fluids

The dynamic behavior of complex liquids and soft materials is of great importance in a wide range of disciplines. Computational studies of these phenomena are particularly demanding because of the presence of disparate length and energy scales, and the complicated coupling between the embedded objects and the hydrodynamic flow field. The goal of this dissertation is to contribute to the understanding of these systems through the development and application of robust, quantitative mesoscale simulation techniques which incorporate both hydrodynamic interactions and thermal fluctuations. The work involves the further development of a specific particle-based mesoscale algorithm---stochastic rotation dynamics---which solves the hydrodynamic equations by following the discrete time dynamics of particles with continuous coordinates and velocities, using efficient multi-particle collisions. A detailed study of the long length- and time-scale properties of the algorithm, which involves analytical derivations of hydrodynamic equations, Green-Kubo relations, and transport coefficients is presented. Extensive simulations are performed to verify these results. The original algorithm is generalized to model dense fluids and binary mixtures. The equation of state and analytical expressions for the transport coefficients are derived. It is also shown that the non-ideal model exhibits an order-disorder transition and caging in the limit of large collision frequencies. The phase diagram of the entropically driven de-mixing transition of the binary mixture is presented, the surface tension for a droplet is calculated, and a detailed analysis of the capillary wave spectrum is performed. Finally, the algorithm is extended to amphiphilic mixtures in order to be able to study microemulsions and micelle formation. We have also developed a constrained dynamics algorithm for modeling the dynamical behavior of wormlike chains embedded in a mesoscale solvent. Rigorously enforced bond-length constraints permit the use of longer time steps, resulting in increased computational efficiency. It also eliminates high frequency degrees of freedom which often complicate comparison with theory and experiment. Finally, in order to provide guidance for experiments, we have modeled the behavior of thermally driven microtubules and simulated sources of experimental error that affect curvature distribution measurements used to understand the physical basis of microtubule bending in living cells.