Filter News
Area of Research
News Topics
- (-) 3-D Printing/Advanced Manufacturing (2)
- (-) Artificial Intelligence (6)
- (-) Nanotechnology (2)
- Big Data (3)
- Bioenergy (1)
- Biology (1)
- Biomedical (2)
- Buildings (1)
- Chemical Sciences (1)
- Clean Water (1)
- Climate Change (2)
- Computer Science (21)
- Coronavirus (1)
- Energy Storage (3)
- Environment (9)
- Exascale Computing (1)
- High-Performance Computing (6)
- Machine Learning (1)
- Materials (1)
- Materials Science (3)
- Microscopy (1)
- Neutron Science (8)
- Nuclear Energy (2)
- Physics (1)
- Quantum Computing (1)
- Quantum Science (2)
- Security (1)
- Space Exploration (1)
- Summit (6)
- Sustainable Energy (1)
- Transportation (1)
Media Contacts
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.
Twenty-seven ORNL researchers Zoomed into 11 middle schools across Tennessee during the annual Engineers Week in February. East Tennessee schools throughout Oak Ridge and Roane, Sevier, Blount and Loudon counties participated, with three West Tennessee schools joining in.
The ExOne Company, the global leader in industrial sand and metal 3D printers using binder jetting technology, announced it has reached a commercial license agreement with Oak Ridge National Laboratory to 3D print parts in aluminum-infiltrated boron carbide.
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.