Statistical Mechanical Paradigms for Next-Generation Coarse-Grained Modeling

Since nature is intrinsically multiscale, a successful multiscale model must be able to deliver a consistent description across different length and time scales. In particular, molecular soft matter is relevant to many interdisciplinary fields in terms of multiscale modeling from materials to biology. Yet, it is challenging to develop a consistent multiscale approach to explain the chemical and physical changes that span the molecular to the macroscopic, which are often tightly coupled. This talk presents the new paradigms for understanding the principles of statistical mechanics underlying bottom-up coarse-grained modeling and for the faithful construction of multiscale models of molecular soft matter. Here, a systematic approach is presented to tackle the multiscale challenge from three microscopic-driven perspectives: design principles, model universality, and model fidelity. By constructing a multiscale model from microscopic-driven design principles, I will demonstrate that systematic bottom-up coarse-grained models derived from molecular-scale information can deliver consistent physical descriptions at different scales (universality) with accurate recapitulation of structure and dynamics (fidelity). These findings illustrate how rigorous, physics-driven coarse-grained modeling can facilitate the efficient simulation of complex molecular soft matter and guide the future era of multiscale modeling.