Quantum precision reached in modeling molten salt behavior
Strengthening the competitiveness of the U.S. transportation industry depends on developing domestic EV batteries that combine rapid charging with long-range performance — two goals that often conflict. Researchers at ORNL have addressed this challenge by redesigning a key battery component, enabling fast, 10-minute charging while improving energy density and reducing reliance on copper.
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.
Daniel Jacobson, distinguished research scientist in the Biosciences Division at ORNL, has been elected a Fellow of the American Institute for Medical and Biological Engineering, or AIMBE, for his achievements in computational biology.
Dave Weston studies how microorganisms influence plant health and stress tolerance, using the Advanced Plant Phenotyping Laboratory to accelerate research on plant-microbe interactions and develop resilient crops for advanced fuels, chemicals and
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.”
Using the Frontier supercomputer at ORNL, researchers have developed a new technique that predicts nuclear properties in record detail. The study revealed how the structure of a nucleus relates to the force that holds it together. This understanding could advance efforts in quantum physics and across a variety of sectors, from to energy production to national security.
A workshop led by scientists at ORNL sketched a road map toward a longtime goal: development of autonomous, or self-driving, next-generation research laboratories.