Filter News
Area of Research
News Topics
- (-) 3-D Printing/Advanced Manufacturing (12)
- (-) ITER (2)
- (-) Machine Learning (10)
- Advanced Reactors (4)
- Artificial Intelligence (14)
- Big Data (9)
- Bioenergy (19)
- Biology (28)
- Biomedical (6)
- Biotechnology (3)
- Buildings (16)
- Chemical Sciences (15)
- Clean Water (5)
- Climate Change (26)
- 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)
- Grid (13)
- High-Performance Computing (16)
- Hydropower (8)
- Irradiation (1)
- Isotopes (4)
- Materials (37)
- Materials Science (16)
- Mercury (1)
- Microscopy (13)
- Nanotechnology (9)
- National Security (17)
- Net Zero (2)
- Neutron Science (12)
- Nuclear Energy (10)
- Partnerships (8)
- Physics (10)
- Polymers (5)
- Quantum Computing (7)
- Quantum Science (9)
- Security (4)
- Simulation (6)
- Space Exploration (4)
- Summit (7)
- Sustainable Energy (25)
- Transformational Challenge Reactor (2)
- Transportation (10)
Media Contacts
Oak Ridge National Laboratory researchers recently used large-scale additive manufacturing with metal to produce a full-strength steel component for a wind turbine, proving the technique as a viable alternative to
Scientists have developed a novel approach to computationally infer previously undetected behaviors within complex biological environments by analyzing live, time-lapsed images that show the positioning of embryonic cells in C. elegans, or roundworms. Their published methods could be used to reveal hidden biological activity.
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.