Filter News
Area of Research
- (-) Nuclear Science and Technology (36)
- (-) Supercomputing (44)
- Advanced Manufacturing (3)
- Biology and Environment (14)
- Clean Energy (28)
- Computational Biology (1)
- Computational Engineering (1)
- Computer Science (6)
- Electricity and Smart Grid (1)
- Fuel Cycle Science and Technology (1)
- Functional Materials for Energy (1)
- Fusion and Fission (30)
- Fusion Energy (10)
- Isotope Development and Production (1)
- Isotopes (4)
- Materials (35)
- Materials for Computing (1)
- National Security (22)
- Neutron Science (11)
- Nuclear Systems Modeling, Simulation and Validation (1)
- Sensors and Controls (1)
News Topics
- (-) Artificial Intelligence (36)
- (-) Nuclear Energy (39)
- (-) Partnerships (1)
- (-) Security (5)
- 3-D Printing/Advanced Manufacturing (8)
- Advanced Reactors (12)
- Big Data (19)
- Bioenergy (9)
- Biology (11)
- Biomedical (19)
- Biotechnology (2)
- Buildings (4)
- Chemical Sciences (5)
- Climate Change (17)
- Computer Science (96)
- Coronavirus (14)
- Critical Materials (3)
- Cybersecurity (9)
- Decarbonization (5)
- Energy Storage (8)
- Environment (22)
- Exascale Computing (22)
- Frontier (28)
- Fusion (9)
- Grid (5)
- High-Performance Computing (38)
- Isotopes (6)
- Machine Learning (14)
- Materials (15)
- Materials Science (19)
- Mathematics (1)
- Microscopy (7)
- Molten Salt (5)
- Nanotechnology (11)
- National Security (8)
- Net Zero (1)
- Neutron Science (17)
- Physics (9)
- Polymers (2)
- Quantum Computing (19)
- Quantum Science (24)
- Simulation (14)
- Software (1)
- Space Exploration (8)
- Summit (42)
- Sustainable Energy (10)
- Transformational Challenge Reactor (3)
- Transportation (6)
Media Contacts
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
Researchers have developed high-fidelity modeling capabilities for predicting radiation interactions outside of the reactor core—a tool that could help keep nuclear reactors running longer.
Scientists have demonstrated a new bio-inspired material for an eco-friendly and cost-effective approach to recovering uranium from seawater.
In a step toward advancing small modular nuclear reactor designs, scientists at Oak Ridge National Laboratory have run reactor simulations on ORNL supercomputer Summit with greater-than-expected computational efficiency.
Oak Ridge National Laboratory scientists are evaluating paths for licensing remotely operated microreactors, which could provide clean energy sources to hard-to-reach communities, such as isolated areas in Alaska.
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.
Oak Ridge National Laboratory is using ultrasonic additive manufacturing to embed highly accurate fiber optic sensors in heat- and radiation-resistant materials, allowing for real-time monitoring that could lead to greater insights and safer reactors.
OAK RIDGE, Tenn., March 4, 2019—A team of researchers from the Department of Energy’s Oak Ridge National Laboratory Health Data Sciences Institute have harnessed the power of artificial intelligence to better match cancer patients with clinical trials.