Wei Chen, Northwestern University
Design of advanced material systems imposes challenges in integrating knowledge and representation from multiple disciplines and domains such as materials, manufacturing, structural mechanics, and design optimization. While most of the existing methods are trial-and-error based, we are proposing data-driven systematic computational design methods that provide a seamless integration of the aforementioned domains through advances in design representation, evaluation, and synthesis. In this talk, we will introduce the state-of-the-art computational design methods for designing heterogeneous nano- and microstructural materials and metamaterial systems such as polymer nanocomposites, light-weight composite structures, microelectronic materials, and solar cells. Research developments in microstructure characterization and reconstruction, deep machine learning of key structure features, mixed-variable Gaussian Process Modeling and Bayesian optimization, and multiscale uncertainty quantification will be introduced. Challenges and opportunities in designing engineered material systems will be discussed.