Filter News
Area of Research
News Topics
- (-) Artificial Intelligence (6)
- (-) Materials Science (4)
- 3-D Printing/Advanced Manufacturing (2)
- Big Data (2)
- Biology (1)
- Biomedical (2)
- Buildings (1)
- Chemical Sciences (1)
- Clean Water (1)
- Climate Change (2)
- Computer Science (19)
- Coronavirus (1)
- Energy Storage (2)
- Environment (8)
- Exascale Computing (1)
- High-Performance Computing (6)
- Isotopes (1)
- Materials (2)
- Microscopy (1)
- Nanotechnology (2)
- Neutron Science (2)
- Nuclear Energy (5)
- Physics (1)
- Quantum Computing (1)
- Quantum Science (2)
- Security (1)
- Space Exploration (2)
- Summit (6)
- Sustainable Energy (2)
- Transportation (2)
Media Contacts
A team led by the U.S. Department of Energy’s Oak Ridge National Laboratory demonstrated the viability of a “quantum entanglement witness” capable of proving the presence of entanglement between magnetic particles, or spins, in a quantum material.
A multidisciplinary team of scientists at ORNL has applied a laser-interference structuring, or LIS, technique that makes significant strides toward eliminating the need for hazardous chemicals in corrosion protection for vehicles.
An ORNL-led team comprising researchers from multiple DOE national laboratories is using artificial intelligence and computational screening techniques – in combination with experimental validation – to identify and design five promising drug therapy approaches to target the SARS-CoV-2 virus.
At the Department of Energy’s Oak Ridge National Laboratory, scientists use artificial intelligence, or AI, to accelerate the discovery and development of materials for energy and information technologies.
On Feb. 18, the world will be watching as NASA’s Perseverance rover makes its final descent into Jezero Crater on the surface of Mars. Mars 2020 is the first NASA mission that uses plutonium-238 produced at the Department of Energy’s Oak Ridge National Laboratory.
Students often participate in internships and receive formal training in their chosen career fields during college, but some pursue professional development opportunities even earlier.
Artificial intelligence (AI) techniques have the potential to support medical decision-making, from diagnosing diseases to prescribing treatments. But to prioritize patient safety, researchers and practitioners must first ensure such methods are accurate.
Materials scientists, electrical engineers, computer scientists, and other members of the neuromorphic computing community from industry, academia, and government agencies gathered in downtown Knoxville July 23–25 to talk about what comes next in
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.