Multiscale Modeling of Soft Materials and Related Biological Responses.

다국어 초록 (Multilingual Abstract)

Liquids, polymers, gels, foams and a number of biological materials are soft materials, which can be easily deformed by thermal stress or thermal fluctuations. Predominant physical behaviors of these soft materials occur at energy scale comparable with room temperature thermal energy. These behaviors cannot be, or are not easily, directly predicted from its atomic or molecular constituents. This is because the soft materials are always self-assemble into mesoscopic structures, which are much larger than the microscopic scale (the scale of atoms and molecules), and yet much smaller than the macroscopic (overall) scale of these materials. Especially, the mechanical and physical properties of soft materials originate from the interplay of phenomena at different spatial and temporal scales. Simultaneously considering these behaviors at different scales is a forbidden challenge, even with the state-of-the-art supercomputer. As such, it is necessary to adopt multiscale techniques when dealing with soft materials in order to account for all important mechanisms.
We start with studying the structure and dynamics of polymeric materials. Using the Iterative Boltzmann Inversion method, both the static structures and dynamic behavior of all-atomistic models of polymers (such as polyisoprene and polyethylene) can be reproduced by a simple coarse-grained model, which bridges the scale from micro to meso. On this coarse-grained level, the entangled network of polymer chains is described via a primitive path analysis, which allows us to extraction of the tube diameter and primitive chain length, quantities required to bridge the scale from meso to macro. Furthermore, by making the affine-deformation assumption, a continuum constitutive law for polymeric materials has been developed from the tube model of primitive paths, which can be applied to study mechanical behaviors of polymeric materials. In this way, the different scales are crossed by using different bridging laws, which enable us to directly predict the viscoelastic properties of polymeric materials using a bottom-up approach. Our predicted dynamic moduli, zero-rate shear viscosities, and relaxation moduli of polyisoprene and polyethylene polymers are found to be in excellent agreement with experimental results.
We then investigated the structure and dynamics of polymer nanocomposites through multiscale modeling, by considering the different volume fractions of fillers. When highly entangled polymer chains are confined between fillers, their conformation and entanglement network are dramatically changed, in contrast to their unentangled counterparts. The entangled polymer chains are found to be significantly disentangled and flattened during increment of the volume fractions of spherical nonattractive fillers. A critical volume fraction is found to control the crossover from polymer chain entanglements to "nanoparticle entanglements", below which the polymer chain relaxation accelerates upon filling.
These results provide a microscopic understanding of the dynamics of entangled polymer chains inside their composites, and offer an explanation for the unusual rheological properties of polymer composites.
The endocytosis of polymer grafted (PEGylated) nanoparticles is studied by using the large scale dissipative particle dynamics simulations and self-consistent field theory. The free energy change of grafted polyethylene glycol (PEG) polymers, before and after endocytosis, is identified to have an effect which is comparable to, or even larger than, the bending energy of the membrane during endocytosis. By incorporating the free energy change of PEG, the critical ligand-receptor binding strength for PEGylated NPs to be internalized can be correctly predicted by a simple analytical equation. Without considering this free energy change, it turns out impossible to predict whether the PEGylated NPs will be delivered into the diseased cells. These simulation results and theoretical analysis not only provide new insights into the endocytosis process of PEGylated NPs, but also shed light on the underlying physical mechanisms, which can be utilized for designing efficient PEGylated NP-based therapeutic carriers with improved cellular targeting and uptake.
The contributions of this dissertation are threefold: (1) establishing a multiscale modeling framework to predict macroscopic behaviors of polymers with molecular information, (2) utilizing the multiscale modeling technique to provide mechanisms underpinning the design of polymer nanocomposites, (3) rapid computational prototyping and testing of polymer grafted drug carriers for targeted drug delivery.