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In a bold step toward transforming how nuclear infrastructure is built, the Department of Energy鈥檚 Manufacturing Demonstration Facility at Oak Ridge National Laboratory, in partnership with Kairos Power, has successfully developed and validated large-scale, 3D-printed polymer composite forms for casting complex, high-precision concrete structures that would be technically challenging and costly to produce using conventional methods.
The Department of Energy鈥檚 Oak Ridge National Laboratory had a major presence at the second annual AI+ Expo for National Competitiveness in Washington, D.C. The event, hosted by the Special Competitive Studies Project, showcased prominent players in technology, academia and government as they navigate the rapid growth of artificial intelligence.
The Department of Energy鈥檚 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.
DOE鈥檚 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鈥檚 energy needs and accelerate nuclear energy via AI.
Six entrepreneurs comprise the next cohort of Innovation Crossroads, a DOE Lab-Embedded Entrepreneurship Program node based at ORNL. The program provides energy-related startup founders from across the nation with access to ORNL鈥檚 unique scientific resources and capabilities, as well as connect them with experts, mentors and networks to accelerate their efforts to take their world-changing ideas to the marketplace.
United Rare Earths has licensed two innovative technologies from Oak Ridge National Laboratory aimed at reducing dependence on critical rare earth elements.
A former intern for ORNL was selected to represent Tennessee presenting his research at the National Junior Science and Humanities Symposium. Langalibalele 鈥淟anga鈥 Lunga, a senior at Farragut High School in Knoxville, Tennessee, interned with ORNL working on deep learning for fast scanning microscopy, a technique for capturing microscopic images more rapidly than traditional methods.
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.
ORNL鈥檚 Biological Monitoring and Abatement Program, or BMAP, is marking 40 years of helping steward the DOE鈥檚 33,476 acres of land on which some of the nation鈥檚 most powerful science and technology missions are carried out.
Researchers at ORNL have developed a tool that gives builders a quick way to measure, correct and certify level foundations. FLAT, or the Flat and Level Analysis Tool, examines a 360-degree laser scan of a construction site using ORNL-developed segmentation algorithms and machine learning to locate uneven areas on a concrete slab.