Abstract

There has been rapidly growing demand of polymeric materials coming from different aspects of modern life because of the highly diverse physical and chemical properties of polymers. Polymer informatics is an interdisciplinary research field of polymer science, computer science, information science and machine learning that serves as a platform to exploit existing polymer data for efficient design of functional polymers. In this study, we present two cases studies of successful discovery of new functional polymers using a data-driven approach. The design process involves an interplay between expert knowledge, computer simulation, and machine learning. The proposed method is shown to be superior than the conventional design approach.