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.
Oxide interfaces in disarray
Exploration of disorder at material interfaces could lead to better device performance
The structure of an interface at which two materials meet helps determine the performance of the computers and other devices we use every day. However, understanding and controlling interface disorder at the atomic level is a difficult materials science challenge.
A research team at PNNL and Texas A&M University combined cutting edge imaging and numerical simulations to examine disordering processes in widely used oxide materials. They found that certain oxide interface configurations remain stable in extreme environments, suggesting ways to build better performing, more reliable devices for fuel cells, space-based electronics, and nuclear energy.
Visualizing the disordering process
As reported in Advanced Materials Interfaces (“Asymmetric Lattice Disorder Induced at Oxide Interfaces,” DOI: 10.1002/admi.201901944) the team set out to examine interfaces between pyrochlore-like and perovskite oxides, two common classes of functional materials used in energy and computing technologies. While most past work has focused on individual bulk materials, less attention has been paid to interfaces connecting them, as would be the case in a device. In particular, it is not clear how interface features, such as composition, bonding, and possible defects, govern disordering processes.
Funded by PNNL’s Nuclear Process Science Initiative (NPSI), the team employed experimental and theoretical methods to study the interface at different stages of disorder introduced through ion irradiation. They imaged the local structure of the material using high-resolution scanning transmission electron microscopy and convergent beam electron diffraction, which showed that the bulk of the two materials disordered (amorphized) before the interface. After further irradiating the material, they found that a band region near the interface had remained crystalline, while the rest of the structure had become amorphous.
To understand this behavior, the team turned to a technique called electron energy loss spectroscopy, which allowed them to examine the atomic-scale chemistry and defects formed at the interface. Their measurements revealed the presence of substantial amounts of defects called oxygen vacancies, which can greatly affect properties such as magnetism and conductivity. Based on these observations, the team constructed a theoretical model of the interface and explored the effect of different interface configurations on the tendency to form vacancies.
“In our model we are able to systematically vary interface features, such as crystal structure, intermixing, and strain, to see their effect on defect formation. We found that the structure of the materials on both sides of the interface can influence where defects are likely to form first,” explained Steven R. Spurgeon, a PNNL materials scientist. “Our model suggests that by selecting appropriate crystal structures and controlling how they connect, it may be possible to dictate the sequence of defect formation, which would allow us to enhance the properties of these materials.”
The team is exploring other interface structures and chemistries, with an eye toward improving the performance of oxides used in extreme environments.
The study was conducted as part of the NPSI project, “Damage Mechanisms and Defect Formation in Irradiated Model Systems,” led by Spurgeon.