Artificial intelligence tools secure tomorrow’s electric grid
Filter News
Area of Research
News Topics
- (-) Biomedical (7)
- (-) Cybersecurity (9)
- (-) Decarbonization (30)
- (-) Energy Storage (21)
- (-) Frontier (19)
- (-) Isotopes (11)
- (-) Materials (59)
- (-) Mercury (2)
- (-) Microscopy (7)
- (-) Space Exploration (4)
- 3-D Printing/Advanced Manufacturing (20)
- Advanced Reactors (3)
- Artificial Intelligence (26)
- Big Data (10)
- Bioenergy (22)
- Biology (29)
- Biotechnology (6)
- Buildings (14)
- Chemical Sciences (24)
- Clean Water (5)
- Climate Change (31)
- Composites (6)
- Computer Science (23)
- Coronavirus (4)
- Critical Materials (6)
- Education (3)
- Emergency (1)
- Environment (43)
- Exascale Computing (15)
- Fossil Energy (2)
- Fusion (9)
- Grid (16)
- High-Performance Computing (33)
- Hydropower (3)
- Irradiation (2)
- Machine Learning (15)
- Materials Science (16)
- Mathematics (2)
- Microelectronics (2)
- Molten Salt (1)
- Nanotechnology (7)
- National Security (21)
- Net Zero (5)
- Neutron Science (32)
- Nuclear Energy (21)
- Partnerships (24)
- Physics (14)
- Polymers (4)
- Quantum Computing (12)
- Quantum Science (9)
- Renewable Energy (2)
- Security (3)
- Simulation (29)
- Software (1)
- Summit (9)
- Sustainable Energy (17)
- Transportation (18)
Media Contacts
ORNL researchers have identified a mechanism in a 3D-printed alloy – termed “load shuffling” — that could enable the design of better-performing lightweight materials for vehicles.
The word “exotic” may not spark thoughts of uranium, but Tyler Spano’s investigations of exotic phases of uranium are bringing new knowledge to the nuclear nonproliferation industry.