Filter News
Area of Research
News Type
News Topics
- (-) Clean Water (2)
- (-) Cybersecurity (7)
- (-) Energy Storage (17)
- (-) Exascale Computing (6)
- (-) Machine Learning (7)
- (-) Quantum Science (7)
- (-) Summit (5)
- 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)
- Climate Change (23)
- Composites (1)
- Computer Science (15)
- Coronavirus (5)
- Critical Materials (1)
- Decarbonization (19)
- Element Discovery (1)
- Environment (30)
- Fossil Energy (1)
- Frontier (9)
- Fusion (7)
- Grid (8)
- 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)
- Nuclear Energy (10)
- Partnerships (7)
- Physics (9)
- Polymers (4)
- Quantum Computing (7)
- Security (4)
- Simulation (3)
- Space Exploration (1)
- Sustainable Energy (18)
- Transformational Challenge Reactor (2)
- Transportation (8)
Media Contacts
Spanning no less than three disciplines, Marie Kurz’s title — hydrogeochemist — already gives you a sense of the collaborative, interdisciplinary nature of her research at ORNL.
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.
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 rapidly emerging consensus in the scientific community predicts the future will be defined by humanity’s ability to exploit the laws of quantum mechanics.
To explore the inner workings of severe acute respiratory syndrome coronavirus 2, or SARS-CoV-2, researchers from ORNL developed a novel technique.
A new version of the Energy Exascale Earth System Model, or E3SM, is two times faster than an earlier version released in 2018.
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.