Digital Twins for New Materials Discovery

Traditional methods of material discovery and development are often time-consuming, costly, and rely heavily on trial-and-error approaches. Additionally, understanding the intricate relationships between a material's structure, properties, and performance at various scales remains a significant challenge. This student team will work to address a pressing need for a more efficient and precise approach to accelerate materials innovation. This student team will work to address the critical issue of expediting materials innovation through the implementation of digital twin technology. This student team will work to create virtual replicas of materials, encompassing both their physical attributes and functional behavior, and will aim to revolutionize the process of material discovery. This student team will work to conduct research that establishes the foundational frameworks and methodologies required to construct and continuously update digital twins, offering a promising avenue for enhancing the efficiency and effectiveness of new material development. This student team will work to create a framework that can be used to create digital twins of a wide range of materials, including metals, ceramics, polymers, and composites. The framework the student team is working to create can also be used to simulate the behavior of materials under a variety of conditions, such as during manufacturing, processing, and use. Students will work to create virtual replicas of materials, conduct tests, make virtual changes, etc. and to better understand the industry environment. Ultimately, this student team will work to create virtual replicas of materials, as well as process documentation of how to construct and continuously update digital twins, test data, lessons learned, and will work to provide next step recommendations.

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