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The Department of Energy’s Oak Ridge National Laboratory and artificial intelligence company Atomic Canyon signed a memorandum of understanding to streamline the licensing process for nuclear power plants with artificial intelligence for license application reviews.

ORNL set a new milestone in nuclear component �鶹Ӱ��, successfully testing two 3D-printed stainless steel experimental capsules at the lab’s High Flux Isotope Reactor. This achievement marks an important step in demonstrating that additively manufactured components can meet the rigorous safety standards required in nuclear applications. 

DOE’s Argonne, Idaho, and Oak Ridge National Laboratories co-hosted the AI x Nuclear Energy Executive Summit: Unleashing the Power for AI. It brought together leaders from national labs, tech companies and the nuclear energy industry to discuss how to meet AI’s energy needs and accelerate nuclear energy via AI.

More than a year ago, ORNL computational scientists raised concerns about the accuracy of using a 2-femtosecond time step in liquid water simulations. A new study confirms and deepens those concerns, revealing even greater potential for error than previously thought.

Scientists have developed a new machine learning approach that accurately predicted critical and difficult-to-compute properties of molten salts, materials with diverse nuclear energy applications. 

Analyzing massive datasets from nuclear physics experiments can take hours or days to process, but researchers are working to radically reduce that time to mere seconds using special software being developed at the Department of Energy’s Lawrence Berkeley and Oak Ridge national laboratories.  

Researchers at Oak Ridge National Laboratory have developed a modeling method that uses machine learning to accurately simulate electric grid behavior while protecting proprietary equipment details. The approach overcomes a key barrier to accurate grid modeling, helping utilities plan for future demand and prevent blackouts. 

 

ORNL researchers helped introduce college students to quantum computing for the first time during the 2025 Winter Classic Invitational, providing hands-on access to real quantum hardware and training future high-performance computing users through a unique challenge that bridged classical and quantum technologies.

A team from ORNL, joined by university students, recently traveled to the Ohio State University Research Reactor to conduct a novel experiment on nuclear thermal rocket fuel coatings — one that could help propel NASA’s astronauts to Mars faster and more efficiently. 

Jairus Hines, an electronics and unmanned systems technician at ORNL, works with airborne, waterborne and ground-based drones. As part of the lab’s Autonomous Systems group, he applies "low and slow" drone technology to radiation detection for national security missions.