Balaprakash chosen for Tennessee’s new AI advisory council
Filter News
Area of Research
- (-) Biology and Environment (34)
- (-) Neutron Science (10)
- Advanced Manufacturing (1)
- Biology and Soft Matter (1)
- Clean Energy (19)
- Computational Biology (1)
- Electricity and Smart Grid (1)
- Functional Materials for Energy (1)
- Fusion and Fission (3)
- Isotopes (1)
- Materials (16)
- Materials for Computing (2)
- National Security (10)
- Supercomputing (16)
News Topics
- (-) Biomedical (2)
- (-) Environment (25)
- (-) Frontier (2)
- (-) Machine Learning (3)
- (-) Neutron Science (10)
- (-) Polymers (1)
- (-) Sustainable Energy (9)
- 3-D Printing/Advanced Manufacturing (3)
- Advanced Reactors (1)
- Artificial Intelligence (5)
- Big Data (1)
- Bioenergy (15)
- Biology (27)
- Biotechnology (3)
- Buildings (1)
- Chemical Sciences (6)
- Clean Water (2)
- Climate Change (16)
- Composites (2)
- Computer Science (4)
- Coronavirus (2)
- Critical Materials (1)
- Cybersecurity (1)
- Decarbonization (9)
- Energy Storage (6)
- Exascale Computing (1)
- Grid (2)
- High-Performance Computing (4)
- Hydropower (5)
- Materials (7)
- Materials Science (4)
- Mercury (1)
- Microscopy (6)
- Nanotechnology (2)
- National Security (2)
- Net Zero (1)
- Nuclear Energy (1)
- Partnerships (3)
- Physics (1)
- Quantum Science (1)
- Security (2)
- Simulation (1)
- Space Exploration (1)
- Summit (3)
- Transformational Challenge Reactor (1)
- Transportation (1)
Media Contacts
Three ORNL scientists have been elected fellows of the American Association for the Advancement of Science, or AAAS, the world’s largest general scientific society and publisher of the Science family of journals.
Energy and sustainability experts from ORNL, industry, universities and the federal government recently identified key focus areas to meet the challenge of successfully decarbonizing the agriculture sector
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.