Maria Chan's Talk: AI for Materials and Chemistry скачать в хорошем качестве

Maria Chan's Talk: AI for Materials and Chemistry

Advances in AI are rapidly transforming how we understand, characterize, and design materials and chemistry for energy applications including energy storage and catalysis. In this talk, I will discuss key challenges and some efforts in applying AI towards materials and chemistry, including integration of theory-guided modeling with AI/ML approaches to interpret complex experimental characterization data (from electron and x-ray microscopy to spectroscopy) enabling “seeing the invisible” at atomic scales. I discuss strategies for property prediction, autonomous experimentation, the extraction of microscopy and spectroscopy data from scientific literature, and the development of data standards and infrastructure that make experimental data AI-ready. The talk draws on research funded by the US Department of Energy such as a DOE Early Career award, Energy Storage Research Alliance (ESRA), Midwest Integrated Center for Computational Materials (MICCoM), and the Integrated Scientific Agentic AI for Catalysis (ISAAC) project under the Genesis Mission.