Filter News
Area of Research
- (-) Functional Materials for Energy (1)
- (-) Fusion and Fission (6)
- (-) National Security (15)
- (-) Supercomputing (46)
- Advanced Manufacturing (8)
- Biology and Environment (43)
- Building Technologies (2)
- Clean Energy (93)
- Computational Biology (1)
- Computational Engineering (1)
- Computer Science (8)
- Electricity and Smart Grid (1)
- Energy Sciences (1)
- Fusion Energy (2)
- Materials (41)
- Materials for Computing (9)
- Neutron Science (10)
- Nuclear Science and Technology (1)
- Quantum information Science (1)
News Topics
- (-) Artificial Intelligence (45)
- (-) Composites (1)
- (-) Polymers (2)
- (-) Sustainable Energy (15)
- 3-D Printing/Advanced Manufacturing (9)
- Advanced Reactors (8)
- Big Data (22)
- Bioenergy (12)
- Biology (15)
- Biomedical (18)
- Biotechnology (3)
- Buildings (5)
- Chemical Sciences (9)
- Climate Change (20)
- Computer Science (104)
- Coronavirus (16)
- Critical Materials (4)
- Cybersecurity (23)
- Decarbonization (8)
- Energy Storage (13)
- Environment (26)
- Exascale Computing (23)
- Fossil Energy (1)
- Frontier (29)
- Fusion (24)
- Grid (13)
- High-Performance Computing (41)
- Isotopes (2)
- ITER (6)
- Machine Learning (23)
- Materials (18)
- Materials Science (20)
- Mathematics (1)
- Microscopy (8)
- Molten Salt (1)
- Nanotechnology (12)
- National Security (35)
- Net Zero (2)
- Neutron Science (16)
- Nuclear Energy (34)
- Partnerships (7)
- Physics (9)
- Quantum Computing (19)
- Quantum Science (25)
- Security (14)
- Simulation (17)
- Software (1)
- Space Exploration (3)
- Summit (42)
- Transportation (10)
Media Contacts
A team of researchers from the Department of Energy’s Oak Ridge National Laboratory has married artificial intelligence and high-performance computing to achieve a peak speed of 20 petaflops in the generation and training of deep learning networks on the