Abstract
The bottom-up prediction of complex behaviors of materials to serve the needs of materials design and prediction of their performance is a grand challenge due to the prohibitive computational times of atomistic simulations. Mesoscale modeling is thus necessary to bridge the spatiotemporal scales for making progress on this problem. This chapter provides an overview of theoretical framework of mesoscale modeling and the state-of-the-art coarse-graining methods that allow for simulation and prediction of complex materials at extended time- and length-scales beyond the atomistic modeling. This chapter covers several popular scale-bridging and coarse-graining methods, including both generic and chemistry-specific coarse-grained modeling, along with applications to soft and polymeric materials as demonstrative examples. In the end, we also discuss several issues and challenges in the mesoscale modeling, which need to be resolved in the future.