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1 - 10 of 291 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.

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.

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.

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 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.
To help reduce the likelihood of losing future cultivated crops to drought and other seasonal hardships, researchers from ORNL, Budapest and Hungary are using neutrons, light microscopy and transmission electron microscopy to study the 'Never Never' plant, known for its ability to endure periods of little to no rain.