Filter News
Area of Research
- (-) Neutron Science (10)
- (-) Supercomputing (14)
- Advanced Manufacturing (6)
- Biology and Environment (5)
- Building Technologies (1)
- Clean Energy (48)
- Computer Science (2)
- Energy Sciences (1)
- Fuel Cycle Science and Technology (1)
- Fusion and Fission (4)
- Fusion Energy (3)
- Isotopes (2)
- Materials (33)
- Materials for Computing (4)
- National Security (5)
- Nuclear Science and Technology (23)
- Nuclear Systems Modeling, Simulation and Validation (1)
- Quantum information Science (1)
News Topics
- (-) 3-D Printing/Advanced Manufacturing (5)
- (-) Artificial Intelligence (6)
- (-) Bioenergy (5)
- (-) Cybersecurity (1)
- (-) Energy Storage (1)
- (-) Nuclear Energy (2)
- (-) Physics (6)
- Advanced Reactors (1)
- Big Data (8)
- Biology (1)
- Biomedical (12)
- Chemical Sciences (1)
- Climate Change (1)
- Composites (1)
- Computer Science (34)
- Coronavirus (10)
- Critical Materials (1)
- Decarbonization (1)
- Environment (5)
- Exascale Computing (2)
- Frontier (1)
- Fusion (1)
- Grid (2)
- High-Performance Computing (2)
- Isotopes (1)
- Machine Learning (4)
- Materials (2)
- Materials Science (12)
- Mathematics (1)
- Microscopy (2)
- Molten Salt (1)
- Nanotechnology (9)
- National Security (1)
- Neutron Science (30)
- Polymers (3)
- Quantum Science (11)
- Security (1)
- Summit (15)
- Sustainable Energy (4)
- Transportation (4)
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