Filter News
Area of Research
- Advanced Manufacturing (1)
- Biology and Environment (28)
- Biology and Soft Matter (1)
- Clean Energy (20)
- Computer Science (1)
- Electricity and Smart Grid (1)
- Functional Materials for Energy (1)
- Fusion and Fission (10)
- Isotopes (1)
- Materials (11)
- Materials for Computing (2)
- National Security (13)
- Neutron Science (12)
- Supercomputing (15)
News Topics
- (-) Advanced Reactors (4)
- (-) Artificial Intelligence (14)
- (-) Climate Change (26)
- (-) Grid (13)
- (-) Neutron Science (12)
- (-) Nuclear Energy (10)
- (-) Security (4)
- (-) Sustainable Energy (25)
- 3-D Printing/Advanced Manufacturing (12)
- Big Data (9)
- Bioenergy (19)
- Biology (28)
- Biomedical (6)
- Biotechnology (3)
- Buildings (16)
- Chemical Sciences (15)
- Clean Water (5)
- Composites (3)
- Computer Science (20)
- Coronavirus (9)
- Critical Materials (4)
- Cybersecurity (7)
- Decarbonization (21)
- Element Discovery (1)
- Energy Storage (25)
- Environment (36)
- Exascale Computing (8)
- Fossil Energy (1)
- Frontier (10)
- Fusion (7)
- High-Performance Computing (16)
- Hydropower (8)
- Irradiation (1)
- Isotopes (4)
- ITER (2)
- Machine Learning (10)
- Materials (37)
- Materials Science (16)
- Mercury (1)
- Microscopy (13)
- Nanotechnology (9)
- National Security (17)
- Net Zero (2)
- Partnerships (8)
- Physics (10)
- Polymers (5)
- Quantum Computing (7)
- Quantum Science (9)
- Simulation (6)
- Space Exploration (4)
- Summit (7)
- Transformational Challenge Reactor (2)
- Transportation (10)
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.
A new version of the Energy Exascale Earth System Model, or E3SM, is two times faster than an earlier version released in 2018.
A novel method to 3D print components for nuclear reactors, developed by the Department of Energy’s Oak Ridge National Laboratory, has been licensed by Ultra Safe Nuclear Corporation.
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.
A research team from Oak Ridge National Laboratory has identified and improved the usability of data that can help accelerate innovation for the growing bioeconomy.