Filter News
Area of Research
- (-) Supercomputing (35)
- Biological Systems (1)
- Biology and Environment (64)
- Biology and Soft Matter (1)
- Clean Energy (43)
- Climate and Environmental Systems (1)
- Computational Biology (1)
- Electricity and Smart Grid (1)
- Fusion and Fission (20)
- Fusion Energy (4)
- Isotopes (6)
- Materials (17)
- Materials for Computing (2)
- National Security (11)
- Neutron Science (9)
- Nuclear Science and Technology (16)
- Quantum information Science (4)
News Topics
- (-) Bioenergy (3)
- (-) Biomedical (7)
- (-) Climate Change (12)
- (-) Grid (1)
- (-) Nuclear Energy (2)
- (-) Quantum Science (10)
- (-) Space Exploration (1)
- (-) Sustainable Energy (3)
- 3-D Printing/Advanced Manufacturing (2)
- Artificial Intelligence (21)
- Big Data (13)
- Biology (6)
- Biotechnology (1)
- Buildings (2)
- Chemical Sciences (1)
- Computer Science (45)
- Coronavirus (7)
- Cybersecurity (2)
- Decarbonization (3)
- Energy Storage (1)
- Environment (13)
- Exascale Computing (12)
- Frontier (13)
- High-Performance Computing (20)
- Machine Learning (7)
- Materials (4)
- Materials Science (8)
- Mathematics (1)
- Microscopy (2)
- Nanotechnology (5)
- National Security (3)
- Net Zero (1)
- Neutron Science (6)
- Physics (3)
- Quantum Computing (10)
- Security (1)
- Simulation (10)
- Software (1)
- Summit (21)
- Transportation (3)
Media Contacts
A team from the ORNL has conducted a series of experiments to gain a better understanding of quantum mechanics and pursue advances in quantum networking and quantum computing, which could lead to practical applications in cybersecurity and other areas.
The type of vehicle that will carry people to the Red Planet is shaping up to be “like a two-story house you’re trying to land on another planet.
Scientists at the Department of Energy’s Oak Ridge National Laboratory are working to understand both the complex nature of uranium and the various oxide forms it can take during processing steps that might occur throughout the nuclear fuel cycle.
Using artificial neural networks designed to emulate the inner workings of the human brain, deep-learning algorithms deftly peruse and analyze large quantities of data. Applying this technique to science problems can help unearth historically elusive solutions.
By analyzing a pattern formed by the intersection of two beams of light, researchers can capture elusive details regarding the behavior of mysterious phenomena such as gravitational waves. Creating and precisely measuring these interference patterns would not be possible without instruments called interferometers.