All News

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.

Researchers at Georgia State University used the Summit supercomputer to study an elaborate molecular pathway called nucleotide excision repair. Decoding NER’s sophisticated sequence of events and the role of PInC in the pathway could provide key insights into developing novel treatments and preventing conditions that lead to premature aging and certain types of cancer.

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.

P&G is using simulations on the ORNL Summit supercomputer to study how surfactants in cleaners cause eye irritation. By modeling the corneal epithelium, P&G aims to develop safer, concentrated cleaning products that meet performance and safety standards while supporting sustainability goals.

Scientists designing the world’s first controlled nuclear fusion power plant, ITER, needed to solve the problem of runaway electrons, negatively charged particles in the soup of matter in the plasma within the tokamak, the magnetic bottle intended to contain the massive energy produced. Simulations performed on Summit, the 200-petaflop supercomputer at ORNL, could offer the first step toward a solution.

A research partnership between two Department of Energy national laboratories has accelerated inspection of additively manufactured nuclear components, and the effort is now expanding to inspect nuclear fuels. 

Researchers at Stanford University, the European Center for Medium-Range Weather Forecasts, or ECMWF, and ORNL used the lab’s Summit supercomputer to better understand atmospheric gravity waves, which influence significant weather patterns that are difficult to forecast. 

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.