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ORNL received more than $5 million from DOE;s Technology Commercialization Fund to advance research in grid security, artificial intelligence, nuclear energy and advanced manufacturing, helping move lab innovations toward industry use.
Army Major Mike Ecklund is currently embedded at ORNL through the Army’s Training with Industry program. At the lab, he works with scientists to study the behavior of nuclear materials in long-term storage, translating research findings into practical insights.
Researchers at ORNL will share their discoveries and innovations at DOE’s Advanced Research Projects Agency-Energy Energy Innovation Summit in San Diego, California.
A 2003 cascading power failure left more than 50 million people without electricity and exposed vulnerabilities in interconnected infrastructure. Twenty years later, ORNL researcher Nasir Ahmad is using simulations to assess risks and help prevent similar widespread outages.
ORNL researchers have developed Photon, a framework that accelerates the discovery of vulnerabilities in artificial intelligence models by scaling testing across the Frontier exascale supercomputer. The system uses coordinated, automated attack strategies to identify and refine weaknesses in AI models, helping improve their security and reliability in critical applications.
Industry leaders met at ORNL to discuss research and technology pathways for securely integrating AI data centers with the electric grid. The workshop focused on grid integration, power systems, supply chains and security.
ORNL is announcing the creation of the Institute for Next-Generation Data Centers, a new national institute dedicated to advancing the design, operation and integration of artificial intelligence data centers into the United States’ energy system.
Experiments conducted between 2002 and 2012 at ORNL studied 31 tin isotopes with varying numbers of neutrons to examine how neutrons affect nuclear stability and nuclear properties. The combined results contributed to identifying tin-132 as a doubly magic nucleus and improved theoretical models of nuclear structure.
Researchers at ORNL have developed a deep learning algorithm that analyzes drone, camera and sensor data to reveal unusual vehicle patterns that may indicate illicit activity, including the movement of nuclear materials.
Researchers at ORNL are breathing new life into the scientific understanding of neptunium, a unique, radioactive, metallic element — and a key precursor for production of the plutonium-238 that fuels exploratory spacecraft. The team’s research arrives during a period of increased national interest in the use of Pu-238 in radioisotope thermoelectric generators.