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Media Contacts
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.
U2opia Technology has licensed Situ and Heartbeat, a package of technologies from the Department of Energy’s Oak Ridge National Laboratory that offer a new method for advanced cybersecurity monitoring in real time.
Distinguished materials scientist Takeshi Egami has spent his career revealing the complex atomic structure of metallic glass and other liquids — sometimes sharing theories with initially resistant minds in the scientific community.
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.
ORNL’s Matthew Loyd will receive a Department of Energy Office of Science Early Career Research award.
After retiring from Y-12, Scott Abston joined the Isotope Science and Engineering Directorate to support isotope production and work with his former manager. He now leads a team maintaining critical equipment for medical and space applications. Abston finds fulfillment in mentoring his team and is pleased with his decision to continue working.
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.
ORNL is the lead partner on five research collaborations with private fusion companies in the 2024 cohort of the Innovation Network for FUSion Energy, or INFUSE, program. These collaborative projects are intended to resolve technical hurdles and develop enabling technologies to accelerate fusion energy research in the private sector.