Quantum precision reached in modeling molten salt behavior
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.
From decoding plant genomes to modeling microbial behavior, computational biologist Priya Ranjan builds computational tools that turn extensive biological datasets into real-world insights. These tools transform the way scientists ask and answer complex biological questions that advance biotechnology breakthroughs and support cultivation of better crops for energy and food security.
Members of the Quantum Science Center, or QSC, gathered at an all-hands meeting in Baton Rouge, Louisiana, in mid-May to reflect on the remarkable accomplishments from the past five years and to prepare for what members hope to be the next five years of the center.
ORNL’s Biological Monitoring and Abatement Program, or BMAP, is marking 40 years of helping steward the DOE’s 33,476 acres of land on which some of the nation’s most powerful science and technology missions are carried out.
Paul is exploring the next frontier: bridging quantum computing with neutron science. His research aims to integrate quantum algorithms with neutron scattering experiments, opening new possibilities for understanding materials at an atomic level.
The fifth annual Quantum Science Center, or QSC, Summer School at Purdue University, held Apr. 21 through Apr. 25, 2025, welcomed its largest group of students to date. Experts from industry, academia and national laboratories gathered at the Purdue Quantum Science and Engineering Institute to share their research in multiple areas of quantum science.
UT-Battelle has contributed up to $475,000 for the purchase and installation of advanced manufacturing equipment to support a program at Tennessee’s Oak Ridge High School that gives students direct experience with the AI- and robotics-assisted workplace of the future.
Scientists at ORNL have developed a vacuum-assisted extrusion method that reduces internal porosity by up to 75% in large-scale 3D-printed polymer parts. This new technique addresses the critical issue of porosity in large-scale prints but also paves the way for stronger composites.
The University of Oklahoma and Oak Ridge National Laboratory, the Department of Energy’s largest multi-program science and energy laboratory, have entered a strategic collaboration to establish a cutting-edge additive manufacturing center.
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.