Artificial intelligence tools secure tomorrow’s electric grid
Filter News
Area of Research
- (-) Materials (55)
- (-) Neutron Science (16)
- (-) Supercomputing (56)
- Advanced Manufacturing (10)
- Biology and Environment (8)
- Clean Energy (50)
- Climate and Environmental Systems (1)
- Computational Engineering (1)
- Computer Science (10)
- Fusion and Fission (1)
- Fusion Energy (4)
- Materials for Computing (3)
- National Security (8)
- Nuclear Science and Technology (5)
- Quantum information Science (4)
- Transportation Systems (1)
News Topics
- (-) 3-D Printing/Advanced Manufacturing (12)
- (-) Composites (1)
- (-) Computer Science (54)
- (-) Materials Science (51)
- Advanced Reactors (4)
- Artificial Intelligence (11)
- Big Data (12)
- Bioenergy (10)
- Biology (1)
- Biomedical (15)
- Chemical Sciences (2)
- Clean Water (2)
- Climate Change (1)
- Coronavirus (10)
- Critical Materials (2)
- Cybersecurity (3)
- Decarbonization (1)
- Energy Storage (15)
- Environment (16)
- Exascale Computing (4)
- Frontier (3)
- Fusion (3)
- Grid (3)
- High-Performance Computing (2)
- Isotopes (2)
- Machine Learning (5)
- Materials (2)
- Mathematics (1)
- Microscopy (10)
- Molten Salt (2)
- Nanotechnology (20)
- National Security (1)
- Neutron Science (46)
- Nuclear Energy (13)
- Physics (12)
- Polymers (7)
- Quantum Science (17)
- Security (2)
- Space Exploration (2)
- Summit (22)
- Sustainable Energy (13)
- Transformational Challenge Reactor (2)
- Transportation (10)
Media Contacts
A team of scientists led by Oak Ridge National Laboratory used machine learning methods to generate a high-resolution map of vegetation growing in the remote reaches of the Alaskan tundra.
Jon Poplawsky, a materials scientist at the Department of Energy’s Oak Ridge National Laboratory, develops and links advanced characterization techniques that improve our ability to see and understand atomic-scale features of diverse materials
Scientists at Oak Ridge National Laboratory and Hypres, a digital superconductor company, have tested a novel cryogenic, or low-temperature, memory cell circuit design that may boost memory storage while using less energy in future exascale and quantum computing applications.