Filter News
Area of Research
News Type
News Topics
- (-) Composites (1)
- (-) Environment (30)
- (-) Frontier (9)
- (-) Space Exploration (1)
- (-) Summit (5)
- (-) Transformational Challenge Reactor (2)
- 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)
- Clean Water (2)
- Climate Change (23)
- Computer Science (15)
- Coronavirus (5)
- Critical Materials (1)
- Cybersecurity (7)
- Decarbonization (19)
- Element Discovery (1)
- Energy Storage (17)
- Exascale Computing (6)
- Fossil Energy (1)
- Fusion (7)
- Grid (8)
- High-Performance Computing (10)
- Hydropower (3)
- Isotopes (3)
- ITER (2)
- Machine Learning (7)
- 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)
- Quantum Science (7)
- Security (4)
- Simulation (3)
- Sustainable Energy (18)
- Transportation (8)
Media Contacts
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.
Energy and sustainability experts from ORNL, industry, universities and the federal government recently identified key focus areas to meet the challenge of successfully decarbonizing the agriculture sector
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.