Filter News
Area of Research
News Type
News Topics
- (-) Advanced Reactors (3)
- (-) Artificial Intelligence (9)
- (-) Computer Science (15)
- (-) Energy Storage (17)
- (-) Materials Science (12)
- 3-D Printing/Advanced Manufacturing (7)
- Big Data (5)
- Bioenergy (15)
- Biology (23)
- Biomedical (4)
- Biotechnology (3)
- Buildings (7)
- Chemical Sciences (13)
- Clean Water (2)
- Climate Change (23)
- Composites (1)
- Coronavirus (5)
- Critical Materials (1)
- Cybersecurity (7)
- Decarbonization (19)
- Element Discovery (1)
- Environment (30)
- Exascale Computing (6)
- Fossil Energy (1)
- Frontier (9)
- Fusion (7)
- Grid (8)
- High-Performance Computing (10)
- Hydropower (3)
- Isotopes (3)
- ITER (2)
- Machine Learning (7)
- Materials (24)
- Mercury (1)
- Microscopy (10)
- Nanotechnology (7)
- National Security (14)
- Net Zero (2)
- Neutron Science (10)
- Nuclear Energy (10)
- Partnerships (7)
- Physics (9)
- Polymers (4)
- Quantum Computing (7)
- Quantum Science (7)
- Security (4)
- Simulation (3)
- Space Exploration (1)
- Summit (5)
- Sustainable Energy (18)
- Transformational Challenge Reactor (2)
- Transportation (8)
Media Contacts
More than 50 current employees and recent retirees from ORNL received Department of Energy Secretary’s Honor Awards from Secretary Jennifer Granholm in January as part of project teams spanning the national laboratory system. The annual awards recognized 21 teams and three individuals for service and contributions to DOE’s mission and to the benefit of the nation.
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.
Neuromorphic devices — which emulate the decision-making processes of the human brain — show great promise for solving pressing scientific problems, but building physical systems to realize this potential presents researchers with a significant