Filter News
Area of Research
- Biology and Environment (15)
- Clean Energy (34)
- Computational Biology (1)
- Computational Engineering (1)
- Computer Science (2)
- Electricity and Smart Grid (1)
- Fusion and Fission (4)
- Fusion Energy (3)
- Isotopes (2)
- Materials (7)
- Materials for Computing (4)
- Mathematics (1)
- National Security (4)
- Neutron Science (5)
- Nuclear Science and Technology (6)
- Nuclear Systems Modeling, Simulation and Validation (1)
- Sensors and Controls (1)
- Supercomputing (12)
- Transportation Systems (1)
News Type
News Topics
- (-) Advanced Reactors (14)
- (-) Artificial Intelligence (30)
- (-) Biomedical (26)
- (-) Clean Water (12)
- (-) Grid (19)
- (-) Machine Learning (13)
- (-) Transportation (28)
- 3-D Printing/Advanced Manufacturing (43)
- Big Data (22)
- Bioenergy (26)
- Biology (33)
- Biotechnology (8)
- Buildings (16)
- Chemical Sciences (15)
- Climate Change (28)
- Composites (8)
- Computer Science (63)
- Coronavirus (19)
- Critical Materials (6)
- Cybersecurity (4)
- Decarbonization (19)
- Education (1)
- Emergency (1)
- Energy Storage (30)
- Environment (64)
- Exascale Computing (11)
- Fossil Energy (3)
- Frontier (9)
- Fusion (21)
- High-Performance Computing (27)
- Isotopes (19)
- ITER (4)
- Materials (33)
- Materials Science (47)
- Mathematics (7)
- Mercury (4)
- Microscopy (13)
- Molten Salt (1)
- Nanotechnology (11)
- National Security (17)
- Net Zero (5)
- Neutron Science (30)
- Nuclear Energy (35)
- Partnerships (11)
- Physics (14)
- Polymers (7)
- Quantum Computing (11)
- Quantum Science (25)
- Security (6)
- Simulation (13)
- Space Exploration (8)
- Statistics (2)
- Summit (19)
- Sustainable Energy (55)
- Transformational Challenge Reactor (3)
Media Contacts
A team led by researchers at ORNL explored training strategies for one of the largest artificial intelligence models to date with help from the world’s fastest supercomputer. The findings could help guide training for a new generation of AI models for scientific research.
Researchers at the Department of Energy’s Oak Ridge National Laboratory met recently at an AI Summit to better understand threats surrounding artificial intelligence. The event was part of ORNL’s mission to shape the future of safe and secure AI systems charged with our nation’s most precious data.
ORNL researchers have teamed up with other national labs to develop a free platform called Open Energy Data Initiative Solar Systems Integration Data and Modeling to better analyze the behavior of electric grids incorporating many solar projects.
The BIO-SANS instrument, located at Oak Ridge National Laboratory’s High Flux Isotope Reactor, is the latest neutron scattering instrument to be retrofitted with state-of-the-art robotics and custom software. The sophisticated upgrade quadruples the number of samples the instrument can measure automatically and significantly reduces the need for human assistance.
Plans to unite the capabilities of two cutting-edge technological facilities funded by the Department of Energy’s Office of Science promise to usher in a new era of dynamic structural biology. Through DOE’s Integrated Research Infrastructure, or IRI, initiative, the facilities will complement each other’s technologies in the pursuit of science despite being nearly 2,500 miles apart.
Groundbreaking report provides ambitious framework for accelerating clean energy deployment while minimizing risks and costs in the face of climate change.
Scientists at Oak Ridge National Laboratory and six other Department of Energy national laboratories have developed a United States-based perspective for achieving net-zero carbon emissions.
The U.S. Environmental Protection Agency has approved the registration and use of a renewable gasoline blendstock developed by Vertimass LLC and ORNL that can significantly reduce the emissions profile of vehicles when added to conventional fuels.
Groundwater withdrawals are expected to peak in about one-third of the world’s basins by 2050, potentially triggering significant trade and agriculture shifts, a new analysis finds.
ORNL researchers modeled how hurricane cloud cover would affect solar energy generation as a storm followed 10 possible trajectories over the Caribbean and Southern U.S.