News & Media

Latest Stories

69 results found
Filtered by Electric Grid Modernization, Hydrogen & Fuel Cells, and Waste-to-Energy and Products

Secretary of Energy Advisory Board (SEAB) Report Recognizes PNNL Contributions

ML and AI

Report features how PNNL’s computing capabilities are affecting the nation’s security, science, and energy missions

August 25, 2020
August 25, 2020
Highlight

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.

View full preliminary findings of the Secretary of Energy Advisory Board (SEAB) report.

For more information about PNNL’s research contributions, contact Aaron Luttman

JULY 14, 2020
Web Feature

Turning the Tides

Their consistency and predictability makes tidal energy attractive, not only as a source of electricity but, potentially, as a mechanism to provide reliability and resilience to regional or local power grids.

Oxide interfaces in disarray

Microscope image, bright blue background with bright green oxides

Atomic-scale imaging informs interface models for oxygen defect formation during disordering of oxides used in energy and computing.

| PNNL

Exploration of disorder at material interfaces could lead to better device performance

March 3, 2020
March 3, 2020
Highlight

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.

Research Team

Steven Spurgeon (PNNL), Tiffany Kaspar (PNNL), Vaithiyalingam Shutthanandan (Environmental Molecular Sciences Laboratory at PNNL), Jonathan Gigax (Texas A&M), Lin Shao (Texas A&M), Michel Sassi (PNNL).
February 20, 2020
DECEMBER 11, 2019
Web Feature

PNNL to Lead New Grid Modernization Projects

PNNL will lead three new grid modernization projects funded by the Department of Energy. The projects focus on scalability and usability, networked microgrids, and machine learning for a more resilient, flexible and secure power grid.
NOVEMBER 26, 2019
Web Feature

Conquering Peak Power

PNNL’s Intelligent Load Control technology manages and adjusts electricity use in buildings when there’s peak demand on the power grid.
AUGUST 30, 2019
Web Feature

Optimize, not Oversize

Energy storage is slowly shifting utility planning practices from the current paradigm, which ensures grid reliability by building reserve generation resources, to ensuring grid reliability by optimizing grid services.
JULY 25, 2019
News Release

Containing Hydrogen in a Materials World

Researchers at the Department of Energy’s Pacific Northwest National Laboratory and Sandia National Laboratories have joined forces to reduce costs and improve the reliability of hydrogen fueling stations.