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SYBD: Symposium Big data driven materials science

SYBD 1: Big Data Driven Materials Science

SYBD 1.1: Hauptvortrag

Dienstag, 17. März 2020, 09:30–10:00, HSZ 02

Materials innovation driven by data and knowledge systems — •Surya Kalidindi — Georgia Institute of Technology, Atlanta, USA

Emerging concepts and toolsets in Data science and Cyberinfrastructure can be strong enablers for systematic mining and capture of Materials Knowledge needed to guide efficient and possibly autonomous explorations of the unimaginably large materials and process design spaces, while synergistically leveraging all available experimental and simulation data. The ongoing efforts in my research group are aimed at accelerating materials innovation through the development of (i) a new mathematical framework that allows a systematic and consistent parametrization of the extremely large spaces in the representations of the material hierarchical structure (spanning multiple length/structure scales) and governing physics across a broad range of materials classes and phenomena, (ii) a new formalism that evaluates all available next steps in a given materials innovation effort (i.e., various multiscale experiments and simulations) and rank-orders them based on their likelihood to produce the desired knowledge (expressed as PSP linkages), and (iii) novel higher-throughput experimental assays that are specifically designed to produce the critically needed fundamental materials data for calibrating the numerous parameters typically present in multiscale materials models. I will present and discuss ongoing research activities in my group.