Title: "Combining Electron Microscopy and Machine Learning to Solve Nuclear Materials Problems."

Abstract
Both fission and fusion structural materials and fusion plasma facing materials will suffer significant degradation in their service environment. Expensive and time-consuming experiments, such as ion irradiation, in-pile irradiation, and plasma exposure, are used to emulate the damage expected in service. To extract the most scientific information possible from these experiments, we employ advanced electron microscopy methods.

This talk will outline recent advances in electron microscopy, such as high-throughput chemical and crystallographic mapping, and discuss how these methods provide new insight into the structure and performance of materials for nuclear environments. In particular, we will discuss how "big data" machine learning/data analytics methods are valuable to ensure that all possible scientific insight is extracted from the huge datasets produced by modern electron microscopes.

Through these examples, we will demonstrate how combining advanced experiments with data analytics can provide unique insight into the post-irradiation state of structural and plasma-facing materials and maximize the potential to gain valuable insight from the experimental campaigns.

Bio
Chad Parish received a PhD in Materials Science and Engineering from North Carolina State University in 2006. He was a post-doc at Sandia National Laboratories' Materials Characterization Department for two and half years, and then moved to Oak Ridge National Laboratory, Materials Science and Technology Division, where he has held positions of Weinberg Distinguished Early Career Fellow, Research and Development Associate, and Research and Development Staff Member. He received the Department of Energy Early Career Award (Fusion Energy Sciences) in 2015. His research emphasizes materials problem solving for nuclear systems using the methods of electron microscopy. He is the secretary of the Microanalysis Society and received the 2018 Fusion Power Associates Rose Award for Excellence in Fusion Engineering.