Filter News
Area of Research
News Topics
- (-) Artificial Intelligence (4)
- (-) Bioenergy (13)
- (-) Cybersecurity (3)
- (-) Exascale Computing (3)
- (-) Grid (2)
- (-) Machine Learning (4)
- (-) Mercury (1)
- (-) Nuclear Energy (3)
- (-) Security (2)
- 3-D Printing/Advanced Manufacturing (2)
- Big Data (4)
- Biology (16)
- Biomedical (3)
- Biotechnology (2)
- Buildings (4)
- Chemical Sciences (4)
- Clean Water (2)
- Climate Change (21)
- Composites (1)
- Computer Science (9)
- Coronavirus (3)
- Decarbonization (14)
- Energy Storage (2)
- Environment (25)
- Frontier (4)
- Fusion (4)
- High-Performance Computing (7)
- Hydropower (3)
- Isotopes (1)
- ITER (1)
- Materials (8)
- Materials Science (4)
- Microscopy (7)
- Nanotechnology (3)
- National Security (7)
- Net Zero (2)
- Neutron Science (3)
- Partnerships (1)
- Physics (2)
- Polymers (1)
- Quantum Computing (5)
- Quantum Science (3)
- Simulation (3)
- Summit (4)
- Sustainable Energy (13)
- Transportation (3)
Media Contacts
A team of scientists led by the Department of Energy’s Oak Ridge National Laboratory and the Georgia Institute of Technology is using supercomputing and revolutionary deep learning tools to predict the structures and roles of thousands of proteins with unknown functions.