![White car (Porsche Taycan) with the hood popped is inside the building with an american flag on the wall.](/sites/default/files/styles/featured_square_large/public/2024-06/2024-P09317.jpg?h=8f9cfe54&itok=m6sQhZRq)
Filter News
Area of Research
News Topics
- (-) National Security (7)
- 3-D Printing/Advanced Manufacturing (6)
- Advanced Reactors (2)
- Artificial Intelligence (14)
- Bioenergy (5)
- Biology (7)
- Biomedical (3)
- Biotechnology (2)
- Buildings (5)
- Chemical Sciences (3)
- Climate Change (5)
- Composites (2)
- Computer Science (9)
- Decarbonization (9)
- Education (1)
- Emergency (1)
- Energy Storage (2)
- Environment (7)
- Exascale Computing (4)
- Fossil Energy (2)
- Frontier (5)
- Fusion (4)
- Grid (4)
- High-Performance Computing (7)
- Isotopes (6)
- Machine Learning (4)
- Materials (7)
- Materials Science (9)
- Mathematics (1)
- Microscopy (2)
- Nanotechnology (1)
- Net Zero (3)
- Neutron Science (6)
- Nuclear Energy (4)
- Partnerships (8)
- Physics (3)
- Polymers (1)
- Quantum Computing (8)
- Quantum Science (12)
- Security (1)
- Simulation (8)
- Space Exploration (3)
- Summit (4)
- Sustainable Energy (9)
- Transportation (3)
Media Contacts
![Caption: Participants gather for a group photo after discussing securing AI systems for critical national security data and applications. Photo by Liz Neunsinger/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2024-05/Picture1.jpg?h=1758acef&itok=hu9V4GaE)
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.
![Joon-Seok Kim Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2024-05/joon-seok.jpg?h=d9b3a08b&itok=qiPgBrWQ)
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.
![Quietly making noise: Measuring differential privacy could balance meaningful analytics and identity protection](/sites/default/files/styles/list_page_thumbnail/public/2024-04/AdobeStock_599537692.jpeg?h=8059516b&itok=oDcA1WvL)
To balance personal safety and research innovation, researchers at ORNL are employing a mathematical technique known as differential privacy to provide data privacy guarantees.
![Credit: Tyler Spano/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2024-04/liz.jpg?h=ab2675cd&itok=jVO3_Ggr)
Nuclear nonproliferation scientists at ORNL have published the Compendium of Uranium Raman and Infrared Experimental Spectra, a public database and analysis of structure-spectral relationships for uranium minerals. This first-of-its-kind dataset and corresponding analysis fill a key gap in the existing body of knowledge for mineralogists and actinide scientists.
![A multidirectorate group from ORNL attended AGU23 and came away inspired for the year ahead in geospatial, earth and climate science](/sites/default/files/styles/list_page_thumbnail/public/2024-02/MicrosoftTeams-image%20%2815%29%20%281%29.png?h=a5eb5da0&itok=gY269KaC)
ORNL scientists and researchers attended the annual American Geophysical Union meeting and came away inspired for the year ahead in geospatial, earth and climate science.
![Prasanna Balaprakash, who leads ORNL’s AI Initiative, participated in events hosted by the White House Office of Science and Technology Policy and the Task Force on American Innovation to discuss the challenges and opportunities posed by AI. Credit: Brian Mosley/Computing Research Association](/sites/default/files/styles/list_page_thumbnail/public/2024-01/01_tfai_decon_ai_20_-_10-26-23_0.jpg?h=411c976c&itok=kRKOW1KH)
In summer 2023, ORNL's Prasanna Balaprakash was invited to speak at a roundtable discussion focused on the importance of academic artificial intelligence research and development hosted by the White House Office of Science and Technology Policy and the U.S. National Science Foundation.
![ORNL intern Jack Orebaugh holds the drone used in his research to help locate human remains. Credit: Lena Shoemaker/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2024-01/jack.jpg?h=0261ddcd&itok=yZ9N5dAh)
Jack Orebaugh, a forensic anthropology major at the University of Tennessee, Knoxville, has a big heart for families with missing loved ones. When someone disappears in an area of dense vegetation, search and recovery efforts can be difficult, especially when a missing person’s last location is unknown. Recognizing the agony of not knowing what happened to a family or friend, Orebaugh decided to use his internship at the Department of Energy’s Oak Ridge National Laboratory to find better ways to search for lost and deceased people using cameras and drones.