Filter News
Area of Research
- (-) Sensors and Controls (1)
- (-) Supercomputing (32)
- Advanced Manufacturing (1)
- Biology and Environment (11)
- Clean Energy (15)
- Computer Science (1)
- Fusion and Fission (4)
- Fusion Energy (1)
- Isotopes (2)
- Materials (12)
- Materials for Computing (1)
- National Security (11)
- Neutron Science (4)
- Nuclear Science and Technology (2)
News Topics
- (-) Artificial Intelligence (12)
- (-) Climate Change (3)
- (-) Frontier (12)
- (-) Quantum Computing (5)
- (-) Security (5)
- 3-D Printing/Advanced Manufacturing (3)
- Big Data (1)
- Bioenergy (6)
- Biology (4)
- Biomedical (5)
- Biotechnology (1)
- Buildings (1)
- Chemical Sciences (3)
- Computer Science (31)
- Coronavirus (5)
- Cybersecurity (6)
- Decarbonization (1)
- Energy Storage (5)
- Environment (3)
- Exascale Computing (7)
- Grid (3)
- High-Performance Computing (11)
- Isotopes (1)
- Machine Learning (5)
- Materials (8)
- Materials Science (6)
- Microscopy (5)
- Molten Salt (1)
- Nanotechnology (5)
- National Security (5)
- Neutron Science (7)
- Nuclear Energy (1)
- Partnerships (1)
- Physics (4)
- Quantum Science (10)
- Simulation (1)
- Space Exploration (1)
- Summit (14)
- Sustainable Energy (5)
- Transportation (2)
Media Contacts
OAK RIDGE, Tenn., Feb. 12, 2019—A team of researchers from the Department of Energy’s Oak Ridge and Los Alamos National Laboratories has partnered with EPB, a Chattanooga utility and telecommunications company, to demonstrate the effectiveness of metro-scale quantum key distribution (QKD).
Brixon, Inc., has exclusively licensed a multiparameter sensor technology from the Department of Energy’s Oak Ridge National Laboratory. The integrated platform uses various sensors that measure physical and environmental parameters and respond to standard security applications.
A team of researchers from the Department of Energy’s Oak Ridge National Laboratory has married artificial intelligence and high-performance computing to achieve a peak speed of 20 petaflops in the generation and training of deep learning networks on the