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Media Contacts
Matthew R. Ryder, a researcher at the Department of Energy’s Oak Ridge National Laboratory, has been named the 2020 Foresight Fellow in Molecular-Scale Engineering.
Oak Ridge National Laboratory researchers have discovered a better way to separate actinium-227, a rare isotope essential for an FDA-approved cancer treatment.
Scientists have tapped the immense power of the Summit supercomputer at Oak Ridge National Laboratory to comb through millions of medical journal articles to identify potential vaccines, drugs and effective measures that could suppress or stop the
Oak Ridge National Laboratory researchers have developed a thin film, highly conductive solid-state electrolyte made of a polymer and ceramic-based composite for lithium metal batteries.
For the second year in a row, a team from the Department of Energy’s Oak Ridge and Los Alamos national laboratories led a demonstration hosted by EPB, a community-based utility and telecommunications company serving Chattanooga, Tennessee.
Researchers at Oak Ridge National Laboratory demonstrated a 20-kilowatt bi-directional wireless charging system on a UPS plug-in hybrid electric delivery truck, advancing the technology to a larger class of vehicles and enabling a new energy storage method for fleet owners and their facilities.
Suman Debnath, a researcher at ORNL, has been elevated to the grade of senior member of the Institute of Electrical and Electronics Engineers (IEEE).
Researchers at the Department of Energy’s Oak Ridge National Laboratory have used Summit, the world’s most powerful and smartest supercomputer, to identify 77 small-molecule drug compounds that might warrant further study in the fight
Researchers at ORNL demonstrated that sodium-ion batteries can serve as a low-cost, high performance substitute for rechargeable lithium-ion batteries commonly used in robotics, power tools, and grid-scale energy storage.
Oak Ridge National Laboratory will partner with Cincinnati Children’s Hospital Medical Center to explore ways to deploy expertise in health data science that could more quickly identify patients’ mental health risk factors and aid in