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Media Contacts
Jinghui Yuan, an R&D staff member in the Applied Research for Mobility Systems group at the Department of Energy’s Oak Ridge National Laboratory, has been elevated to a senior member of the Institute of Electrical and Electronics Engineers.
Lætitia H. Delmau, a distinguished researcher and radiochemist at Oak Ridge National Laboratory, has received the 2024 Glenn T. Seaborg Actinide Separations Award.
Robert Wagner, associate laboratory director for ORNL's Energy Science and Technology Directorate, has been selected to receive the George Westinghouse Gold Medal from the American Society of Mechanical Engineers, or ASME. The award recognizes his work to advance state-of-the-art clean power generation systems through research on combustion, fuel technologies and controls.
Researchers set a new benchmark for future experiments making materials in space rather than for space. They discovered that many kinds of glass have similar atomic structure and arrangements and can successfully be made in space. Scientists from nine institutions in government, academia and industry participated in this 5-year study.
Students from the first class of ORNL and Pellissippi State Community College's joint Chemical Radiation Technology Pathway toured isotope facilities at ORNL.
A team of researchers including a member of the Quantum Science Center at ORNL has published a review paper on the state of the field of Majorana research. The paper primarily describes four major platforms that are capable of hosting these particles, as well as the progress made over the past decade in this area.
Researchers at the Department of Energy’s Oak Ridge National Laboratory met recently at an AI Summit to better understand threats surrounding artificial intelligence. The event was part of ORNL’s mission to shape the future of safe and secure AI systems charged with our nation’s most precious data.
ORNL scientists are working on a project to engineer and develop a cryogenic ion trap apparatus to simulate quantum spin liquids, a key research area in materials science and neutron scattering studies.
Researchers at ORNL are using a machine-learning model to answer ‘what if’ questions stemming from major events that impact large numbers of people. By simulating an event, such as extreme weather, researchers can see how people might respond to adverse situations, and those outcomes can be used to improve emergency planning.
To balance personal safety and research innovation, researchers at ORNL are employing a mathematical technique known as differential privacy to provide data privacy guarantees.