Mesoscale interaction parameter

Simulations of physical properties of realistic Pt/support nanoparticle systems can provide interaction parameters that are used by molecular-level simulations of self-organization in CL inks. Coarse-grained MD studies presented in the section Mesoscale Model of Self-Organization in Catalyst Layer Inks provide vital insights on structure formation. Information on agglomerate formation, pore space morphology, ionomer structure and distribution, and wettability of pores serves as input for parameterizations of structure-dependent physical properties, discussed in the section Effective Catalyst Layer Properties From Percolation Theory. CGMD studies can be applied to study the impact of modifications in chemical properties of materials and ink composition on physical properties and stability of CLs. 

In this chapter, we describe our recent mesoscale modeling studies of the interactions between spherical nanoparticles and model cell membranes [73-75]. Although these studies are not comprehensive, they demonstrate the techniques that could be used to further explore the mechanisms of nanoparticle-membrane interactions. Initially, we describe the use of hybrid selfconsistent field theory to study the phase behavior of small (radius Rp < 10 nm) spherical nanoparticles near a lipid bilayer. Depending on the nanoparticle size and interaction parameters... 

The mesoscale model consists of a set of crosslink nodes (i.e., junctions) connected via single finite-extensible nonlinear elastic (FENE) bonds (that can be potentially cross-linked and/or scissioned), which represent the chain segments between crosslinks. In addition, there is a repulsive Lennard-Jones interaction between all crosslink positions to simulate volume exclusion effects. The Eennard-Jones and FENE interaction parameters were adjusted and the degree of polymerization (p) for a given length of a FENE bond calibrated until the MWD computed from our network matched the experimental MWD of the virgin material [112]. 

Dissipative particle dynamics (DPD) is a technique for simulating the motion of mesoscale beads. The technique is superficially similar to a Brownian dynamics simulation in that it incorporates equations of motion, a dissipative (random) force, and a viscous drag between moving beads. However, the simulation uses a modified velocity Verlet algorithm to ensure that total momentum and force symmetries are conserved. This results in a simulation that obeys the Navier-Stokes equations and can thus predict flow. In order to set up these equations, there must be parameters to describe the interaction between beads, dissipative force, and drag. 

Block copolymer phase separation has first and foremost been studied in bulk. The mesoscale structure is determined by molecular parameters such as chain length (N), volume fractions of the components, interaction between the blocks (x) and temperature (Figure 2.6). In this Chapter, we will be concerned mainly with diblock copolymers,... 

This chapter is organized as follows. In section 1.1, we introduce our notation and present the details of the molecular and mesoscale simulations the expanded ensemble-density of states Monte Carlo method,and the evolution equation for the tensor order parameter [5]. The results of both approaches are presented and compared in section 1.2 for the cases of one or two nanoscopic colloids immersed in a confined liquid crystal. Here the emphasis is on the calculation of the effective interaction (i.e. potential of mean force) for the nanoparticles, and also in assessing the agreement between the defect structures found by the two approaches. In section 1.3 we apply the mesoscopic theory to a model LC-based sensor and analyze the domain coarsening process by monitoring the equal-time correlation function for the tensor order parameter, as a function of the concentration of adsorbed nanocolloids. We present our conclusions in Section 1.4. 

The dynamical behavior of macromolecules in solution is strongly affected or even dominated by hydrodynamic interactions [6,104,105]. Erom a theoretical point of view, scaling relations predicted by the Zimm model for, e.g., the dependencies of dynamical quantities on the length of the polymer are, in general, accepted and confirmed [106]. Recent advances in experimental single-molecule techniques provide insight into the dynamics of individual polymers, and raise the need for a quantitative theoretical description in order to determine molecular parameters such as diffusion coefficients and relaxation times. Mesoscale hydrodynamic simulations can be used to verify the validity of theoretical models. Even more, such simulations are especially valuable when analytical methods fail, as for more complicated molecules such as polymer brushes, stars, ultrasoft colloids, or semidilute solutions, where hydrodynamic interactions are screened to a certain degree. Here, mesoscale simulations still provide a full characterization of the polymer dynamics. 

In addition to the attempts to better understand the origin of mesoscale structures in dispersed two-phase flows by means of extremum principles and stabflity analyses, CFD simulations may provide guidance. One may therefore expect that simulations of particle behavior on the basis of a proper description of the fluid—particle interaction force reproduce the formation and dynamics of coherent structures and clusters (see also Capecelatro et al, 2015). After all, CFD simulations allow visualizations of 3D transient flow fields and make it possible to systematically investigate the effect of all types of variables (flow rates, physical properties, geometrical parameters) on flow fields to a degree not feasible experimentally. 

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