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Illustration of oscillating UCI3 bonds

Researchers for the first time documented the specific chemistry dynamics and structure of high-temperature liquid uranium trichloride salt, a potential nuclear fuel source for next-generation reactors. 

Oak Ridge National Laboratory building and sign for the Computing and Computational Sciences Directorate.

The contract will be awarded to develop the newest high-performance computing system at the Oak Ridge Leadership Computing Facility.

This photo is of four men standing in front of a wall of monitors that are showing a tree looking image.

To better predict long-term flooding risk, scientists at the Department of Energy’s Oak Ridge National Laboratory developed a 3D modeling framework that captures the complex dynamics of water as it flows across the landscape. The framework seeks to provide valuable insights into which communities are most vulnerable as the climate changes, and was developed for a project that’s assessing climate risk and mitigation pathways for an urban area along the Southeast Texas coast.

Man in a blue polo is standing over blue water

ORNL researchers completed successful testing of a gallium nitride transistor for use in more accurate sensors operating near the core of a nuclear reactor. This is an important technical advance particularly for monitoring new, compact.

Jiafu Mao, left, and Yaoping Wang discuss their analysis of urban and rural vegetation resilience across the United States in the EVEREST visualization lab at ORNL. Credit: Carlos Jones, ORNL/U.S. Dept. of Energy

Scientists at ORNL completed a study of how well vegetation survived extreme heat events in both urban and rural communities across the country in recent years. The analysis informs pathways for climate mitigation, including ways to reduce the effect of urban heat islands.

The illustration depicts ocean surface currents simulated by MPAS-Ocean. Credit: Los Alamos National Laboratory, E3SM, U.S. Dept. of Energy

A team from DOE’s Oak Ridge, Los Alamos and Sandia National Laboratories has developed a new solver algorithm that reduces the total run time of the Model for Prediction Across Scales-Ocean, or MPAS-Ocean, E3SM’s ocean circulation model, by 45%. 

Sam Hollifield displays a prototype of the Secure Hijack, Intrusion and Exploit Layered Detector, or SHIELD, the device monitoring the cybersecurity of the semi-truck. Credit: Lena Shoemaker/ORNL, U.S. Dept. of Energy

As vehicles gain technological capabilities, car manufacturers are using an increasing number of computers and sensors to improve situational awareness and enhance the driving experience.

When exposed to radiation, electrons produced within molten zinc chloride, or ZnCl2, can be observed in three distinct singly occupied molecular orbital states, plus a more diffuse, delocalized state. Credit: Hung H. Nguyen/University of Iowa

In a finding that helps elucidate how molten salts in advanced nuclear reactors might behave, scientists have shown how electrons interacting with the ions of the molten salt can form three states with different properties. Understanding these states can help predict the impact of radiation on the performance of salt-fueled reactors.

The Department of Energy’s Oak Ridge National Laboratory announced the establishment of its Center for AI Security Research, or CAISER, to address threats already present as governments and industries around the world adopt artificial intelligence and take advantage of the benefits it promises in data processing, operational efficiencies and decision-making. Credit: Rachel Green/ORNL, U.S. Dept. of Energy

The Department of Energy’s Oak Ridge National Laboratory announced the establishment of the Center for AI Security Research, or CAISER, to address threats already present as governments and industries around the world adopt artificial intelligence and take advantage of the benefits it promises in data processing, operational efficiencies and decision-making.

ZEISS Head of Additive Manufacturing Technology Claus Hermannstaedter, left, and ORNL Interim Associate Laboratory Director for Energy Science and Technology Rick Raines sign a licensing agreement that allows ORNL’s machine-learning algorithm, Simurgh, to be used for rapid evaluations of 3D-printed components with industrial X-ray computed tomography, or CT. Using machine learning in CT scanning is expected to reduce the time and cost of inspections of 3D-printed parts by more than ten times.

A licensing agreement between the Department of Energy’s Oak Ridge National Laboratory and research partner ZEISS will enable industrial X-ray computed tomography, or CT, to perform rapid evaluations of 3D-printed components using ORNL’s machine