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Media Contacts
Building innovations from ORNL will be on display in Washington, D.C. on the National Mall June 7 to June 9, 2024, during the U.S. Department of Housing and Urban Development’s Innovation Housing Showcase. For the first time, ORNL’s real-time building evaluator was demonstrated outside of a laboratory setting and deployed for building construction.
Momentum for manufacturing innovation in the United States got a boost during the inaugural MDF Innovation Days, held recently at the U.S. Department of Energy Manufacturing Demonstration Facility at Oak Ridge National Laboratory.
Vanderbilt University and ORNL announced a partnership to develop training, testing and evaluation methods that will accelerate the Department of Defense’s adoption of AI-based systems in operational environments.
ORNL researchers used electron-beam additive manufacturing to 3D-print the first complex, defect-free tungsten parts with complex geometries.
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 researchers have produced the most comprehensive power outage dataset ever compiled for the United States. This dataset, showing electricity outages from 2014-22 in the 50 U.S. states, Washington D.C. and Puerto Rico, details outages at 15-minute intervals for up to 92% of customers for the eight-year period.
Mohamad Zineddin hopes to establish an interdisciplinary center of excellence for nuclear security at ORNL, combining critical infrastructure assessment and protection, risk mitigation, leadership in nuclear security, education and training, nuclear security culture and resilience strategies and techniques.
Four ORNL researchers traveled to Warsaw, Poland, during the first week of April to support the opening of Poland’s first Clean Energy Training Center, a regional hub dedicated to providing workforce development and training to expand new nuclear
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.