The area of computational and data-driven design of materials has been garnering significant interest due to the increasing need for high-performance materials in electronics, energy and structural applications, and extreme environments. The research on the computational design of materials and its integration into advanced manufacturing techniques will potentially be leveraged in the future to develop new-generation composites, alloys, ceramics, and other materials for extreme environments such as hypersonics applications, adaptive thermal response materials, energetic composites in fuel cells, thermal energy harvesting in satellites, and materials for green energy applications.

In this talk, Dr. Acar will present an overview of the computational and data-driven methods developed by her research group to design metallic alloys under the effects of uncertainty. The mechanical performance of these materials is enhanced by modeling them in terms of micro-scale (~10-6 m) features. The talk will also discuss the impact of manufacturing-related uncertainty arising from the imperfections and defects during processing on the reliability and performance of these materials. Additional topics will cover the integration of Artificial Intelligence (AI)/Machine Learning (ML) techniques into physics-based and physics-informed material models to accelerate the design of different material systems processed with conventional and additive manufacturing techniques.