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1 - 10 of 308 Results

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.

Van Graves, an engineering manager at ORNL, is celebrating 40 years of dedicated service leading a diverse range of prominent engineering projects at ORNL and internationally.

Using the Frontier supercomputer, a team of researchers from the Massachusetts Institute of Technology conducted large-scale calculations to chart the isospin density of a neutron star across a range of conditions. Their work provides new insights into how pressure and density interact within neutron stars, offering important predictions about their inner workings.

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.
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 and the University of Cincinnati achieved a breakthrough in understanding the vulnerability of microbes to the butanol they produce during fermentation of plant biomass. The discovery could pave the way for more efficient production of domestic fuels, chemicals and materials.

In collaboration with the U.S. Department of Homeland Security’s Science and Technology Directorate, researchers at ORNL are evaluating technology to detect compounds emitted by pathogens and pests in agricultural products at the nation’s border.
Professionals from government and industry gathered at ORNL for the Nondestructive Assay Holdup Measurements Training Course for Nuclear Criticality Safety, a hands-on training in nondestructive assay, a technique for detecting and quantifying holdup without disturbing operations.