Filter News
Area of Research
- (-) Fusion Energy (2)
- (-) Supercomputing (12)
- Advanced Manufacturing (3)
- Biology and Environment (24)
- Biology and Soft Matter (1)
- Clean Energy (32)
- Climate and Environmental Systems (2)
- Computational Engineering (1)
- Computer Science (5)
- Fusion and Fission (1)
- Materials (18)
- Materials for Computing (1)
- National Security (7)
- Neutron Science (6)
- Nuclear Science and Technology (2)
- Quantum information Science (1)
- Transportation Systems (1)
News Topics
- (-) Environment (4)
- (-) Machine Learning (2)
- (-) Materials Science (5)
- (-) Space Exploration (2)
- (-) Transportation (1)
- 3-D Printing/Advanced Manufacturing (1)
- Advanced Reactors (4)
- Artificial Intelligence (7)
- Big Data (5)
- Bioenergy (2)
- Biology (4)
- Biomedical (4)
- Buildings (1)
- Climate Change (3)
- Computer Science (21)
- Coronavirus (2)
- Critical Materials (1)
- Decarbonization (1)
- Energy Storage (1)
- Exascale Computing (3)
- Frontier (3)
- Fusion (3)
- High-Performance Computing (5)
- Materials (4)
- Microscopy (1)
- Nanotechnology (3)
- National Security (1)
- Neutron Science (1)
- Nuclear Energy (5)
- Quantum Computing (5)
- Quantum Science (4)
- Simulation (4)
- Summit (11)
- Sustainable Energy (1)
Media Contacts
ORNL researchers are deploying their broad expertise in climate data and modeling to create science-based mitigation strategies for cities stressed by climate change as part of two U.S. Department of Energy Urban Integrated Field Laboratory projects.
A team of researchers has developed a novel, machine learning–based technique to explore and identify relationships among medical concepts using electronic health record data across multiple healthcare providers.
A study led by researchers at ORNL could help make materials design as customizable as point-and-click.
A study by researchers at the ORNL takes a fresh look at what could become the first step toward a new generation of solar batteries.
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.
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
Students often participate in internships and receive formal training in their chosen career fields during college, but some pursue professional development opportunities even earlier.
The type of vehicle that will carry people to the Red Planet is shaping up to be “like a two-story house you’re trying to land on another planet.
Using additive manufacturing, scientists experimenting with tungsten at Oak Ridge National Laboratory hope to unlock new potential of the high-performance heat-transferring material used to protect components from the plasma inside a fusion reactor. Fusion requires hydrogen isotopes to reach millions of degrees.