News & Media
Secretary of Energy Advisory Board (SEAB) Report Recognizes PNNL Contributions
Report features how PNNL’s computing capabilities are affecting the nation’s security, science, and energy missions
Contributions from researchers across Pacific Northwest National Laboratory (PNNL) were recognized in the preliminary findings of a Secretary of Energy Advisory Board (SEAB) report from a working group dedicated to the U.S. Department of Energy’s (DOE’s) capabilities and future in artificial intelligence (AI) and machine learning. PNNL researchers’ expertise is prominent throughout DOE’s AI efforts, particularly in the areas of data sciences and national security.
Based largely on input from DOE sponsors, the report features how PNNL’s computing capabilities are affecting the nation’s security, science, and energy missions. Key highlights include:
- Studying how AI affects the global landscape for securing nuclear materials, potentially using deep learning to enhance physical and digital protections against material concealment, delivery, theft, and sabotage.
- Describing how the United States and its partners might employ deep learning to combat attack efforts for enhanced nuclear security.
- Designing advanced deep learning models to characterize operations with buildings, using electrical signatures on power lines, enabling new designs for energy-efficient buildings in addition to enhanced security features for nuclear facilities.
- Leading the nuclear explosive monitoring project with data scientists working to significantly lower detection thresholds of low-yield, evasive underground nuclear explosions without increasing time-to-detection or the amount of human analysis.
- Co-design of advanced accelerator, memory and data movement concepts to support convergence of AI and machine learning methods with other forms of data analytics and traditional scientific high performance computing (HPC).
The report highlights PNNL’s support to the National Nuclear Security Administration, featuring joint laboratory collaborations between PNNL and others, including the Y-12 National Security Complex, Sandia National Laboratories, Lawrence Livermore National Laboratory, Los Alamos National Laboratory, and Oak Ridge National Laboratory. Additionally, PNNL is working as part of DOE’s comparative advantages in AI, providing the Office of Energy Efficiency and Renewable Energy access to AI subject matter experts.
Improving nuclear waste storage models by studying the chemistry of material interactions
WastePD EFRC research on the glass-steel interface was published in Nature Materials
New research unravels the chemistry of how materials in the waste packages used for the disposal of high-level radioactive waste interact in deep geologic repository environments. Having a better understanding of the interactions between materials under various conditions provides more information to make waste storage performance models more robust.
“Many performance models use conservative approaches such as assuming that the steel canister walls don’t even exist or that they dissolve very fast. This study provides the opportunity to better incorporate the canister barrier in the models,” said Joseph Ryan, a PNNL materials scientist and coauthor on the paper, “Self-accelerated corrosion of nuclear waste forms at material interfaces,” published in Nature Materials.
The United States is converting highly radioactive nuclear waste, also known as high-level waste, into glass. The molten glass is poured into steel canisters for long-term storage and ultimate disposal in a geologic repository. The goal is to design waste storage and disposal systems that would remain safe for hundreds of thousands of years to come, even if they are exposed to water. Because of the extensive time span of waste storage, researchers turn to cutting-edge science to project what will happen during that time period. The data is used to inform extensive safety analyses—helping make sure the system is engineered to be compatible with the natural system so that waste remains separate from the environment.
“We can’t just do a test on a material and say, ‘That material corroded this much in 30 days and extrapolate that to a million years.’ It doesn’t work that way,” Ryan said. “At the most basic level, we try to understand the underlying chemistry of corrosion. Then, we feed that information into computer models to calculate the expected release over time.”
In this study, led by the WastePD Energy Frontier Research Center based at Ohio State University, researchers unpacked the chemistry that occurs when two materials are close together, focusing on glass-steel along with ceramic-steel interactions. This chemical situation could occur when water has percolated into the repository and has breached the steel canister, exposing the glass-steel interface to water.
When water finally breaches the waste package container, it will fill the microscopic space that forms between the solid glass and the steel canister. Chemical reactions that happen in localized and tiny microenvironments such as these can be quite different than those happening in a more open setting. In this case, this localized area can have a different chemistry than the surrounding solution, causing more corrosion than would be expected.
The researchers tested their theory in the laboratory. They pressed glass and steel together in salty liquid and kept it at 90° C (194° F) for a month. At the end of the experiment, they found differences in the width of thin layers that indicated higher corrosion between the glass-steel couple interface than in a control sample.
Why it matters: This research allows scientists to improve models that project how a disposal canister could perform in a deep geologic environment. Having a better understanding of the interactions between materials under various conditions provides more information to make the models more robust. Currently, some models project what happens to waste under the assumption that the steel canister walls do not exist. Operating under this pretext can result in higher projections of waste degradation than would likely occur when taking a conservative approach. But better understanding the chemistry of how the solid waste and the steel canister interact allows a scientifically based understanding of how the canisters behave and interact with the glass to be included in performance assessment models.
Summary: High-level waste is immobilized as glass in stainless steel canisters. On cooling, a confined crevice space forms at the stainless steel-glass interface. If the disposal canister is breached and if water can enter the steel-glass interface, it could result in anodic dissolution of the stainless steel, generating metal cations, which hydrolyze to form protons and strongly increase the local acidity. This acidic environment may locally enhance the corrosion of both the stainless steel and the glass, which leads to the release of cations from the glass. Further, the coupled corrosion may trigger the precipitation of additional secondary phases that may impact subsequent canister corrosion or nuclear glass durability.
What’s Next: While this study sheds light on the chemical interactions that occur at the stainless steel-glass interface, there are more interactions to explore. Ultimately, a better understanding of different chemical mechanisms will improve the overall performance model.
Sponsors: This work was supported as part of the Center for Performance and Design of Nuclear Waste Forms and Containers, an Energy Frontier Research Center funded by the US Department of Energy, Office of Science, Basic Energy Sciences under Award no. DESC0016584.
Research Team: Xiaolei Guo, Gerald S. Frankel, Gopal Viswanathan, Tianshu Li (Ohio State University); Stéphane Gin (CEA, France); Penghui Lei, Tiankai Yao, Jie Lian (Rensselaer Polytechnic Institute); Hongshen Liu, Dien Ngo, Seong H. Kim (Pennsylvania State University); Daniel K. Schreiber, John D. Vienna, Joseph V. Ryan (PNNL); Jincheng Du (University of North Texas)