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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. 

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. 

 

Scientists at ORNL have developed a method that can track chemical changes in molten salt in real time — helping to pave the way for the deployment of molten salt reactors for energy production.

During his first visit to Oak Ridge National Laboratory, Energy Secretary Chris Wright compared the urgency of the Lab’s World War II beginnings to today’s global race to lead in artificial intelligence, calling for a “Manhattan Project 2.”

Researchers at Oak Ridge National Laboratory have developed a new automated testing capability for semiconductor devices, which is newly available to researchers and industry partners in the Grid Research Integration and Deployment Center.

Ryan Culler is the program manager at Oak Ridge National Laboratory, where he oversees the production of actinium-225, a promising treatment for cancer. Driven by a personal connection to cancer through his late brother, Culler is dedicated to advancing medical isotopes to help improve cancer care. 

During Hurricanes Helene and Milton, ORNL deployed drone teams and the Mapster platform to gather and share geospatial data, aiding recovery and damage assessments. ORNL's EAGLE-I platform tracked utility outages, helping prioritize recovery efforts. Drone data will train machine learning models for faster damage detection in future disasters. 

Researchers at ORNL are using microwave radar reflection to nondestructively detect and measure the moisture content of materials within walls without removing drywall or cladding. This also expedites the moisture identification process and enables mold growth to be treated in the early stages.

ORNL, as a partner in the DOE’s Stor4Build Consortium, is co-leading research with several national laboratories to develop thermal energy storage to complement electrical battery storage and recently hosted a two-day workshop focused on advancing these technologies.

The US focuses on nuclear nonproliferation, and ORNL plays a key role in this mission. The lab conducts advanced research in uranium science, materials analysis and nuclear forensics to detect illicit nuclear activities. Using cutting-edge tools and operational systems, ORNL supports global efforts to reduce nuclear threats by uncovering the history of nuclear materials and providing solutions for uranium removal.