Filter News
Area of Research
- (-) National Security (17)
- Advanced Manufacturing (3)
- Biological Systems (1)
- Biology and Environment (66)
- Clean Energy (61)
- Climate and Environmental Systems (1)
- Computational Biology (2)
- Computational Engineering (1)
- Computer Science (3)
- Fusion and Fission (29)
- Fusion Energy (13)
- Isotopes (7)
- Materials (40)
- Materials for Computing (8)
- Neutron Science (60)
- Nuclear Science and Technology (28)
- Nuclear Systems Modeling, Simulation and Validation (1)
- Supercomputing (41)
- Transportation Systems (2)
News Topics
- (-) Big Data (6)
- (-) Biology (3)
- (-) Biomedical (1)
- (-) Neutron Science (2)
- (-) Nuclear Energy (2)
- (-) Security (6)
- (-) Transportation (1)
- 3-D Printing/Advanced Manufacturing (1)
- Artificial Intelligence (6)
- Bioenergy (2)
- Biotechnology (1)
- Buildings (1)
- Climate Change (4)
- Computer Science (11)
- Coronavirus (2)
- Cybersecurity (9)
- Decarbonization (2)
- Energy Storage (1)
- Environment (4)
- Grid (5)
- High-Performance Computing (3)
- Machine Learning (8)
- Materials (1)
- Materials Science (2)
- Nanotechnology (1)
- National Security (23)
- Partnerships (1)
- Quantum Science (1)
- Simulation (1)
- Summit (2)
- Sustainable Energy (2)
Media Contacts
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.
Digital twins are exactly what they sound like: virtual models of physical reality that continuously update to reflect changes in the real world.
Stephen Dahunsi’s desire to see more countries safely deploy nuclear energy is personal. Growing up in Nigeria, he routinely witnessed prolonged electricity blackouts as a result of unreliable energy supplies. It’s a problem he hopes future generations won’t have to experience.
When the COVID-19 pandemic stunned the world in 2020, researchers at ORNL wondered how they could extend their support and help
It’s a simple premise: To truly improve the health, safety, and security of human beings, you must first understand where those individuals are.
ORNL researchers used the nation’s fastest supercomputer to map the molecular vibrations of an important but little-studied uranium compound produced during the nuclear fuel cycle for results that could lead to a cleaner, safer world.
A team of researchers has developed a novel, machine learning–based technique to explore and identify relationships among medical concepts using electronic health record data across multiple healthcare providers.
Tackling the climate crisis and achieving an equitable clean energy future are among the biggest challenges of our time.
ORNL scientists had a problem mapping the genomes of bacteria to better understand the origins of their physical traits and improve their function for bioenergy production.
Deborah Frincke, one of the nation’s preeminent computer scientists and cybersecurity experts, serves as associate laboratory director of ORNL’s National Security Science Directorate. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy