(156e) Data Enabled Discovery in Soft Materials Discovery

The advent of new tools for ingestion and analysis of large volumes of data has created new and exciting opportunities for materials discovery and characterization. In the particular case of soft materials, including polymers, rapid advances are taking place on multiple fronts. In this presentation, I will discuss three examples, each of which serves to illustrate a different way in which data science can be used to extract detailed information about molecular processes or interactions. The first is concerned with the role of branching on polymer structure and dynamics, the second is concerned with development of coarse-grained models of conducting polymers, and the third focuses on the use of advanced sampling methods based on the use of concepts from machine learning.