Multiscale methods have been developed over the last decade to overcome a significant challenge for computer simulation and modeling - the broad span of time and length scales in biosystems, materials and flow problems. To describe and simulate properties or phenomena on scales that are not accessible to fully atomistic molecular dynamics (MD) or Monte Carlo (MC) simulations, coarse-graining techniques have recently attracted great interest for providing descriptions at a mesoscopic level of resolution that preserve fluid thermodynamic and transport behaviors with a reduced number of degrees of freedom and hence less computational demand. In this dissertation, we mainly focus on particle-based coarse-grained (CG) models, which are constructed from bottom-up, i.e. from fully atomistic systems, especially for flow problems.

One fundamental question arises: how well and to what extent can a bottom-up developed mesoscale model recover the physical properties of a molecular scale system? To answer this question, we explore systematically the properties of a CG model that is developed to represent an intermediate mesoscale model between the atomistic and continuum scales, and thus reduce the computational cost relative to an underlying reference all-atom (AA) Lennard-Jones (LJ) simulation. In Chapter 2, the thermodynamic properties are considered in detail while the transport properties are examined in the third chapter.

To coarse-grain, the iterative Boltzmann inversion (IBI) is used to determine a CG potential for a (1-phi)N mesoscale particle system, where phi is the degree of coarse-graining, so as to reproduce the radial distribution function (RDF) of an N atomic particle system and then propose a reformulation of IBI as a robust minimization procedure that enables simultaneous matching of the RDF and the fluid pressure. This new method also improves the isothermal compressibility relative to pure IBI. Unlike the RDF and the pressure, dynamical properties such as the self-diffusion coefficient and viscosity in a CG model cannot be matched during coarse-graining by modifying the pair interaction. Instead, removed degrees of freedom require a modification of the equations of motion to simulate their implicit effects on dynamics. A simple but approximate approach is to introduce a friction coefficient, gamma, and random forces for the remaining degrees of freedom, in which case gamma becomes an additional parameter in the coarse-grained model that can be tuned. We consider the non-Galilean-invariant Langevin and the Galilean-invariant dissipative particle dynamics (DPD) thermostats with CG systems in which we can systematically tune the fraction phi of removed degrees of freedom.

Finally, a multiscale problem is studied from a thermodynamic point of view using molecular dynamics simulations. We are interested in developing a fundamental understanding of the unusually long lifetime of surface nanobubbles, which is experimentally observed in several studies but does not follow predictions of classical macroscopic theory. We develop a novel free energy calculation technique that can estimate the interfacial properties of a nanobubble of various sizes and contact angles in the presence of a gas-enriched hydrophobic surface. Several characteristics of the system are reported including the hydrophobic wall properties and the density and pressure profiles of the two-phase system. To demonstrate the potentially unique contributions of water, we simulate the two-phase system using both LJ and SPC/E models for comparison. The preliminary results show that a small nanobubble can exist at a metastable state when the contact angle is small around 9 to 20 degrees, which agrees with the experimental results and this is distinctly observed when an explicit water model is used. Also, we conclude that the gas enrichment layer is responsible for the stability of nanobubble.