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Equipment in Maik Lang's lab

Glass Structure May Be Key to Safer Nuclear Waste

Demand for nuclear power has increased steadily since the first commercial nuclear power station came online in the 1950s. Nuclear energy is now responsible for approximately 11 percent of all power generated in the world. Due to this growing popularity, greater emphasis has been put on areas of research relating to the generation of nuclear power, specifically the materials used in and around reactors, and the waste those materials generate.

Safe disposal of nuclear waste is of primary concern, given its potential effects on the environment and surrounding communities should a leak occur. One of the methods used to combat this possibility is vitrification—the conversion of waste into a stable glass. The glass serves as a safe containment method for the spent fuel over hundreds of thousands of years. However, the effects of radiation, one of the key drivers of microstructural evolution of these types of glass, are not fully understood. This is where Maik Lang, associate professor of nuclear engineering and Pietro F. Pasqua Fellow, and his JDRD team come in.

The goal of Lang’s JDRD project is to develop an understanding of the structure of these glasses using ORNL’s Spallation Neutron Source (SNS) and Integrated Computational Environment–Modeling and Analysis for Neutrons, or ICE-MAN. In its second year, Lang’s team has pivoted to focus their modeling efforts on the nuclear fuel itself. 

“In the renewal, we shifted away from glasses to nuclear fuel materials,” he said. “The overall goal is still to understand the glass structure, but we think we first have to understand defect formation in crystalline materials. Once we have a good handle on that, we can move on to the more complicated glass system, which is an aperiodic material.”

Lang’s team is working alongside ORNL’s Anibal Ramirez-Cuesta, Chemical Spectroscopy Group leader, and Matt Tucker, Diffraction Group leader, to further develop the ICE-MAN platform as well as making use of it to decode their data. In turn, Lang’s data is serving as a test bed for the platform itself, setting the stage for future collaborations.