Katy Bradford: Cassette approach offers compelling construction solution
Filter News
Area of Research
- (-) Electricity and Smart Grid (1)
- (-) National Security (4)
- (-) Supercomputing (20)
- Biology and Environment (10)
- Clean Energy (22)
- Computational Biology (1)
- Computer Science (1)
- Functional Materials for Energy (2)
- Fusion and Fission (4)
- Isotopes (3)
- Materials (26)
- Materials for Computing (3)
- Neutron Science (13)
News Topics
- (-) Energy Storage (3)
- (-) Frontier (7)
- (-) Nanotechnology (3)
- (-) Neutron Science (2)
- (-) Space Exploration (1)
- (-) Summit (7)
- 3-D Printing/Advanced Manufacturing (1)
- Artificial Intelligence (9)
- Big Data (4)
- Bioenergy (3)
- Biology (7)
- Biomedical (4)
- Biotechnology (1)
- Buildings (3)
- Chemical Sciences (2)
- Climate Change (7)
- Computer Science (14)
- Coronavirus (4)
- Critical Materials (1)
- Cybersecurity (5)
- Decarbonization (2)
- Environment (4)
- Exascale Computing (6)
- Grid (5)
- High-Performance Computing (9)
- Machine Learning (8)
- Materials (8)
- Materials Science (5)
- Microscopy (2)
- National Security (13)
- Partnerships (1)
- Physics (2)
- Quantum Computing (7)
- Quantum Science (4)
- Security (4)
- Simulation (5)
- Sustainable Energy (2)
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.