Filter News
Area of Research
- (-) Computational Engineering (3)
- (-) Neutron Science (24)
- Advanced Manufacturing (4)
- Biology and Environment (41)
- Building Technologies (1)
- Clean Energy (84)
- Climate and Environmental Systems (1)
- Computational Biology (1)
- Computer Science (15)
- Electricity and Smart Grid (3)
- Fuel Cycle Science and Technology (1)
- Functional Materials for Energy (1)
- Fusion and Fission (45)
- Fusion Energy (17)
- Isotope Development and Production (1)
- Isotopes (4)
- Materials (71)
- Materials for Computing (12)
- Mathematics (1)
- National Security (43)
- Nuclear Science and Technology (37)
- Nuclear Systems Modeling, Simulation and Validation (1)
- Quantum information Science (9)
- Sensors and Controls (1)
- Supercomputing (119)
News Topics
- (-) Computer Science (16)
- (-) Cybersecurity (1)
- (-) Fusion (1)
- (-) Machine Learning (4)
- (-) Microscopy (3)
- (-) Nuclear Energy (3)
- (-) Quantum Science (7)
- 3-D Printing/Advanced Manufacturing (6)
- Advanced Reactors (1)
- Artificial Intelligence (7)
- Big Data (3)
- Bioenergy (6)
- Biology (6)
- Biomedical (13)
- Biotechnology (1)
- Chemical Sciences (3)
- Clean Water (3)
- Climate Change (2)
- Composites (1)
- Coronavirus (8)
- Decarbonization (2)
- Energy Storage (6)
- Environment (9)
- Fossil Energy (1)
- Frontier (1)
- High-Performance Computing (3)
- Materials (14)
- Materials Science (23)
- Mathematics (2)
- Nanotechnology (10)
- National Security (2)
- Neutron Science (101)
- Physics (9)
- Polymers (1)
- Quantum Computing (1)
- Security (2)
- Space Exploration (3)
- Summit (7)
- Sustainable Energy (2)
- Transportation (5)
Media Contacts
Neutron experiments can take days to complete, requiring researchers to work long shifts to monitor progress and make necessary adjustments. But thanks to advances in artificial intelligence and machine learning, experiments can now be done remotely and in half the time.
Like most scientists, Chengping Chai is not content with the surface of things: He wants to probe beyond to learn what’s really going on. But in his case, he is literally building a map of the world beneath, using seismic and acoustic data that reveal when and where the earth moves.
Scientists at ORNL used neutron scattering to determine whether a specific material’s atomic structure could host a novel state of matter called a spiral spin liquid.
More than 50 current employees and recent retirees from ORNL received Department of Energy Secretary’s Honor Awards from Secretary Jennifer Granholm in January as part of project teams spanning the national laboratory system. The annual awards recognized 21 teams and three individuals for service and contributions to DOE’s mission and to the benefit of the nation.
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 team including researchers from the Department of Energy’s Oak Ridge National Laboratory has developed a digital tool to better monitor a condition known as Barrett’s esophagus, which affects more than 3 million people in the United States.
A team led by the U.S. Department of Energy’s Oak Ridge National Laboratory demonstrated the viability of a “quantum entanglement witness” capable of proving the presence of entanglement between magnetic particles, or spins, in a quantum material.
An ORNL-led team comprising researchers from multiple DOE national laboratories is using artificial intelligence and computational screening techniques – in combination with experimental validation – to identify and design five promising drug therapy approaches to target the SARS-CoV-2 virus.
The Department of Energy’s Office of Science has selected five Oak Ridge National Laboratory scientists for Early Career Research Program awards.
At the Department of Energy’s Oak Ridge National Laboratory, scientists use artificial intelligence, or AI, to accelerate the discovery and development of materials for energy and information technologies.