Despite the vast design space of composites, there are significant gaps between the performance, economic, and environmental targets and current design and manufacturing approaches. The current experimental or analytical material screening approach relies heavily on known material architectures and is a trial-and-error process, which largely hinders the material design exploration and optimization capabilities. Such gaps indicate the necessity of a new approach to composite design and manufacturing that enables both the discovery of new composites materials forms and relevant new manufacturing methodologies.

 

The mission of this center, which consists of a multi-disciplinary team of experimentalists, computational researchers, and computer scientists, is to build an AI-enabled inverse design approach for fundamental understanding and integrated material-manufacturing design of advanced polymer composites. While uncovering these fundamental insights, this center also aims to build Inverse Design Software (InDeS) tools that accelerate the discovery of advanced polymer composites for improved performance and energy-efficient manufacturing, thereby enabling a smaller carbon footprint, lower structural weight, and lower cost.