The School of Mechanical and Materials Engineering Seminar Series, “Advancing materials innovation with artificial intelligence” Presented by Dr. Ram Devanathan

About the event

Advancing materials innovation with artificial intelligence

Presented by:

Ram Devanathan, Director, Energy Processes & Materials Division, Pacific Northwest National Lab

Abstract:

 Artificial intelligence (AI) offers the tantalizing possibility of accelerating materials discovery, optimization, and deployment.  AI can standardize synthesis and characterization experiments, curate data and knowledge autonomously, and help automate tasks that are hazardous, repetitive, or typically error prone. AI can also support efficient data analysis and information extraction from large data streams typical of beam line experiments and high throughput computation. It is possible to analyze material microstructures rapidly using AI. When combined with physical laws and practical constraints, AI can generate insights from complex datasets, enhance the depth of analysis, and uncover subtle trends in the data. Physics-informed AI is an important step to make models more transparent and explainable. However, there are several challenges to the widespread use of AI in materials research, such as limited availability of relevant high-quality data with metadata, the need to quantify uncertainty, complex relationships, and sloppy use of AI. The talk will highlight recent progress in this field at PNNL and highlight a path to move from Ai and automation to autonomous experiments.

Biography:

Ram Devanathan is the Director of the Energy Processes & Materials Division in the Energy & Environment Directorate at Pacific Northwest National Laboratory (PNNL) in Richland, Washington. He is passionate about advancing US energy leadership, artificial intelligence, and advanced manufacturing. Devanathan’s technical interests include the design of materials for extreme environments, multiscale modeling, and machine learning for materials discovery. He serves as an active volunteer with the American Chemical Society, Materials Research Society, The Minerals, Metals & Materials Society, and the Mid-Columbia Science Fair. He is on the advisory board of PNNL’s Center for AI and the Great Lakes Energy Institute. He is a recipient of the US Department of Energy’s Outstanding Mentor Award for his efforts to involve high school, undergraduate, and graduate students in computational materials science, and the American Ceramic Society’s Richard M. Fulrath Award. Devanathan is a Fellow of the American Association for the Advancement of Science, the American Ceramic Society, the American Chemical Society, and the Oppenheimer Science and Energy Leadership Program.