Filter News
Area of Research
- Advanced Manufacturing (5)
- Biology and Environment (36)
- Biology and Soft Matter (1)
- Clean Energy (48)
- Climate and Environmental Systems (1)
- Computer Science (1)
- Electricity and Smart Grid (1)
- Functional Materials for Energy (1)
- Fusion and Fission (23)
- Fusion Energy (4)
- Isotopes (19)
- Materials (29)
- Materials for Computing (3)
- National Security (25)
- Neutron Science (11)
- Nuclear Science and Technology (20)
- Supercomputing (41)
News Type
News Topics
- (-) 3-D Printing/Advanced Manufacturing (53)
- (-) Climate Change (54)
- (-) Cybersecurity (20)
- (-) Fossil Energy (4)
- (-) Frontier (26)
- (-) Isotopes (33)
- (-) Machine Learning (23)
- (-) Molten Salt (2)
- (-) Nuclear Energy (65)
- (-) Space Exploration (13)
- Advanced Reactors (13)
- Artificial Intelligence (53)
- Big Data (25)
- Bioenergy (55)
- Biology (63)
- Biomedical (32)
- Biotechnology (10)
- Buildings (22)
- Chemical Sciences (32)
- Clean Water (14)
- Composites (10)
- Computer Science (97)
- Coronavirus (21)
- Critical Materials (2)
- Decarbonization (46)
- Education (1)
- Emergency (2)
- Energy Storage (43)
- Environment (114)
- Exascale Computing (26)
- Fusion (37)
- Grid (26)
- High-Performance Computing (53)
- Hydropower (5)
- Irradiation (1)
- ITER (3)
- Materials (71)
- Materials Science (63)
- Mathematics (5)
- Mercury (7)
- Microelectronics (2)
- Microscopy (28)
- Nanotechnology (28)
- National Security (41)
- Net Zero (9)
- Neutron Science (59)
- Partnerships (20)
- Physics (34)
- Polymers (13)
- Quantum Computing (22)
- Quantum Science (34)
- Renewable Energy (1)
- Security (13)
- Simulation (34)
- Software (1)
- Summit (32)
- Sustainable Energy (51)
- Transformational Challenge Reactor (4)
- Transportation (37)
Media Contacts
Three staff members in ORNL’s Fusion and Fission Energy and Science Directorate have moved into newly established roles facilitating communication and program management with sponsors of the directorate’s Nuclear Energy and Fuel Cycle Division.
A key industrial isotope, iridium-192, has not been produced in the U.S. in almost 20 years. DOE's Isotope Program and QSA Global Inc. announced a joint product development agreement to initiate U.S. production of iridium-192.
New computational framework speeds discovery of fungal metabolites, key to plant health and used in drug therapies and for other uses.
In summer 2023, ORNL's Prasanna Balaprakash was invited to speak at a roundtable discussion focused on the importance of academic artificial intelligence research and development hosted by the White House Office of Science and Technology Policy and the U.S. National Science Foundation.
The 21st Symposium on Separation Science and Technology for Energy Applications, Oct. 23-26 at the Embassy Suites by Hilton West in Knoxville, attracted 109 researchers, including some from Austria and the Czech Republic. Besides attending many technical sessions, they had the opportunity to tour the Graphite Reactor, High Flux Isotope Reactor and both supercomputers at ORNL.
Researchers at ORNL became the first to 3D-print large rotating steam turbine blades for generating energy in power plants.
Nuclear engineering students from the United States Military Academy and United States Naval Academy are working with researchers at ORNL to complete design concepts for a nuclear propulsion rocket to go to space in 2027 as part of the Defense Advanced Research Projects Agency DRACO program.
A 19-member team of scientists from across the national laboratory complex won the Association for Computing Machinery’s 2023 Gordon Bell Special Prize for Climate Modeling for developing a model that uses the world’s first exascale supercomputer to simulate decades’ worth of cloud formations.
A team of eight scientists won the Association for Computing Machinery’s 2023 Gordon Bell Prize for their study that used the world’s first exascale supercomputer to run one of the largest simulations of an alloy ever and achieve near-quantum accuracy.
Lee's paper at the August conference in Bellevue, Washington, combined weather and power outage data for three states – Texas, Michigan and Hawaii – and used a machine learning model to predict how extreme weather such as thunderstorms, floods and tornadoes would affect local power grids and to estimate the risk for outages. The paper relied on data from the National Weather Service and the U.S. Department of Energy’s Environment for Analysis of Geo-Located Energy Information, or EAGLE-I, database.