Filter News
Area of Research
News Type
News Topics
- (-) Clean Water (2)
- (-) Climate Change (23)
- (-) Composites (1)
- (-) Grid (8)
- (-) Machine Learning (7)
- (-) Nuclear Energy (10)
- (-) Quantum Science (7)
- (-) Sustainable Energy (18)
- 3-D Printing/Advanced Manufacturing (7)
- Advanced Reactors (3)
- Artificial Intelligence (9)
- Big Data (5)
- Bioenergy (15)
- Biology (23)
- Biomedical (4)
- Biotechnology (3)
- Buildings (7)
- Chemical Sciences (13)
- Computer Science (15)
- Coronavirus (5)
- Critical Materials (1)
- Cybersecurity (7)
- Decarbonization (19)
- Element Discovery (1)
- Energy Storage (17)
- Environment (30)
- Exascale Computing (6)
- Fossil Energy (1)
- Frontier (9)
- Fusion (7)
- High-Performance Computing (10)
- Hydropower (3)
- Isotopes (3)
- ITER (2)
- Materials (24)
- Materials Science (12)
- Mercury (1)
- Microscopy (10)
- Nanotechnology (7)
- National Security (14)
- Net Zero (2)
- Neutron Science (10)
- Partnerships (7)
- Physics (9)
- Polymers (4)
- Quantum Computing (7)
- Security (4)
- Simulation (3)
- Space Exploration (1)
- Summit (5)
- Transformational Challenge Reactor (2)
- Transportation (8)
Media Contacts
Drilling with the beam of an electron microscope, scientists at ORNL precisely machined tiny electrically conductive cubes that can interact with light and organized them in patterned structures that confine and relay light’s electromagnetic signal.
A rapidly emerging consensus in the scientific community predicts the future will be defined by humanity’s ability to exploit the laws of quantum mechanics.
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.