Characterizing Soft Matter Self‐Assembly and Material Properties with Advanced Molecular Dynamics and Data‐Driven Methods

Abstract

Sampling of potential energy surfaces (PES) lies at the core of soft matter self-assembly and material property characterization using molecular simulations. Yet, PES roughness and poor sampling efficiency must be overcome with advanced molecular dynamics (MD) techniques. We introduce the PES concept and detail the current PES-sampling progress using multiscale simulations, including methods in quantum mechanics, all-atomistic MD, and coarse-grained MD. Advanced techniques such as data-driven, machine-learned, and statistical-modeling methods are also introduced. We then focus on several enhanced sampling methods to accurately characterize the PES for probing the material properties of supramolecular soft matter. A variety of simulation software is also showcased to guide hands-on implementation. Finally, we summarize some recent characterization of soft material phenomena using MD methods with enhanced PES sampling. This chapter overviews methods for PES sampling and aims to stimulate broader accessibility of enhanced PES sampling of soft matter self-assembly and characterization.