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Media Contacts
A new technology to continuously place individual atoms exactly where they are needed could lead to new materials for devices that address critical needs for the field of quantum computing and communication that cannot be produced by conventional means.
A study led by the Department of Energy’s Oak Ridge National Laboratory details how artificial intelligence researchers created an AI model to help identify new alloys used as shielding for housing fusion applications components in a nuclear reactor. The findings mark a major step towards improving nuclear fusion facilities.
Three transportation researchers at the Department of Energy’s Oak Ridge National Laboratory have been elevated to senior member grade of the Institute of Electrical and Electronics Engineers, or IEEE.
In a game-changing study, ORNL scientists developed a deep learning model — a type of artificial intelligence that mimics human brain function — to analyze high-speed videos of plasma plumes during a process called pulsed laser deposition.
For the first time, ORNL will run equipment developed at its research facilities on a commercially available quantum network at EPB Quantum Network powered by Qubitekk to help validate the technology's commercial viability.
ORNL has partnered with Western Michigan University to advance intelligent road infrastructure through the development of new chip-enabled raised pavement markers. These innovative markers transmit lane-keeping information to passing vehicles, enhancing safety and enabling smarter driving in all weather conditions.
A team led by scientists at ORNL identified and demonstrated a method to process a plant-based material called nanocellulose that reduced energy needs by a whopping 21%, using simulations on the lab’s supercomputers and follow-on analysis.
As a mechanical engineer in building envelope materials research at ORNL, Bryan Maldonado sees opportunities to apply his scientific expertise virtually everywhere he goes, from coast to coast. As an expert in understanding how complex systems operate, he’s using machine learning methods to control the process and ultimately optimize performance.
A research scientist with the Department of Energy’s Oak Ridge National Laboratory, Ayana Ghosh was named the 2024 Early Discovery Award winner by the American Ceramic Society. The award recognizes an early career member of the organization who has contributed to basic science in the field of glass and ceramics.
Researchers for the first time documented the specific chemistry dynamics and structure of high-temperature liquid uranium trichloride salt, a potential nuclear fuel source for next-generation reactors.