Filter News
Area of Research
- (-) Supercomputing (36)
- Biological Systems (1)
- Biology and Environment (19)
- Clean Energy (10)
- Computational Biology (1)
- Fusion and Fission (2)
- Isotopes (17)
- Materials (24)
- Materials for Computing (2)
- National Security (9)
- Neutron Science (9)
- Nuclear Science and Technology (3)
- Quantum information Science (4)
News Topics
- (-) Biomedical (7)
- (-) Cybersecurity (2)
- (-) Frontier (13)
- (-) Microscopy (2)
- (-) Physics (3)
- (-) Quantum Science (10)
- (-) Space Exploration (1)
- 3-D Printing/Advanced Manufacturing (2)
- Artificial Intelligence (21)
- Big Data (13)
- Bioenergy (3)
- Biology (6)
- Biotechnology (1)
- Buildings (2)
- Chemical Sciences (1)
- Climate Change (12)
- Computer Science (45)
- Coronavirus (7)
- Decarbonization (3)
- Energy Storage (1)
- Environment (13)
- Exascale Computing (12)
- Grid (1)
- High-Performance Computing (20)
- Machine Learning (7)
- Materials (4)
- Materials Science (8)
- Mathematics (1)
- Nanotechnology (5)
- National Security (3)
- Net Zero (1)
- Neutron Science (6)
- Nuclear Energy (2)
- Quantum Computing (10)
- Security (1)
- Simulation (10)
- Software (1)
- Summit (21)
- Sustainable Energy (3)
- Transportation (3)
Media Contacts
As the second-leading cause of death in the United States, cancer is a public health crisis that afflicts nearly one in two people during their lifetime.
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.
Scientists at have experimentally demonstrated a novel cryogenic, or low temperature, memory cell circuit design based on coupled arrays of Josephson junctions, a technology that may be faster and more energy efficient than existing memory devices.
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.
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.