About

Solutions to societal challenges in areas as diverse as energy, healthcare, aerospace, or sustainable engineering call for multifunctional material systems with novel and unprecedented property combinations. To realize these novel material systems requires new approaches to discover, synthesize, analyze, and process materials. Data science, coupled with methods of machine learning, holds the promise to transform our understanding of “how materials work” and to dramatically accelerate the process of developing the material systems that will drive future innovations. To harness this potential requires building of the knowledge base and resources that enable the integration of data-driven design into materials research.

The Center for Data-Driven Design of Multifunctional Material Systems (D3OM2S) leverages the strengths and talents of Carnegie Mellon University and the Air Force Research Laboratory in materials and computer research to establish a pipeline of research talent with expertise in artificial intelligence (AI) and materials science, and to advance the materials science field by integrating AI into materials research and design.