Filter News
Area of Research
- Advanced Manufacturing (1)
- Biology and Environment (80)
- Biology and Soft Matter (1)
- Clean Energy (111)
- Climate and Environmental Systems (2)
- Computational Biology (1)
- Computer Science (2)
- Electricity and Smart Grid (1)
- Fusion and Fission (12)
- Fusion Energy (1)
- Isotopes (2)
- Materials (49)
- Materials for Computing (6)
- National Security (26)
- Neutron Science (20)
- Nuclear Science and Technology (6)
- Sensors and Controls (1)
- Supercomputing (59)
News Type
News Topics
- (-) Advanced Reactors (18)
- (-) Artificial Intelligence (82)
- (-) Energy Storage (73)
- (-) Environment (140)
- (-) Grid (41)
- (-) Security (23)
- (-) Software (1)
- (-) Transportation (52)
- 3-D Printing/Advanced Manufacturing (85)
- Big Data (36)
- Bioenergy (74)
- Biology (81)
- Biomedical (47)
- Biotechnology (19)
- Buildings (35)
- Chemical Sciences (57)
- Clean Water (17)
- Climate Change (74)
- Composites (18)
- Computer Science (146)
- Coronavirus (34)
- Critical Materials (16)
- Cybersecurity (31)
- Decarbonization (65)
- Education (4)
- Element Discovery (1)
- Emergency (2)
- Exascale Computing (38)
- Fossil Energy (5)
- Frontier (41)
- Fusion (45)
- High-Performance Computing (76)
- Hydropower (5)
- Isotopes (48)
- ITER (4)
- Machine Learning (35)
- Materials (102)
- Materials Science (98)
- Mathematics (7)
- Mercury (9)
- Microelectronics (4)
- Microscopy (36)
- Molten Salt (4)
- Nanotechnology (42)
- National Security (63)
- Net Zero (11)
- Neutron Science (99)
- Nuclear Energy (83)
- Partnerships (48)
- Physics (55)
- Polymers (20)
- Quantum Computing (32)
- Quantum Science (58)
- Renewable Energy (2)
- Simulation (41)
- Space Exploration (15)
- Statistics (2)
- Summit (52)
- Sustainable Energy (78)
- Transformational Challenge Reactor (7)
Media Contacts
Researchers at the Department of Energy’s Oak Ridge National Laboratory and partner institutions have launched a project to develop an innovative suite of tools that will employ machine learning algorithms for more effective cybersecurity analysis of the U.S. power grid.
Power companies and electric grid developers turn to simulation tools as they attempt to understand how modern equipment will be affected by rapidly unfolding events in a complex grid.
The contract will be awarded to develop the newest high-performance computing system at the Oak Ridge Leadership Computing Facility.
To better predict long-term flooding risk, scientists at the Department of Energy’s Oak Ridge National Laboratory developed a 3D modeling framework that captures the complex dynamics of water as it flows across the landscape. The framework seeks to provide valuable insights into which communities are most vulnerable as the climate changes, and was developed for a project that’s assessing climate risk and mitigation pathways for an urban area along the Southeast Texas coast.
In the wet, muddy places where America’s rivers and lands meet the sea, scientists from the Department of Energy’s Oak Ridge National Laboratory are unearthing clues to better understand how these vital landscapes are evolving under climate change.
ORNL's Guang Yang and Andrew Westover have been selected to join the first cohort of DOE’s Advanced Research Projects Agency-Energy Inspiring Generations of New Innovators to Impact Technologies in Energy 2024 program. The program supports early career scientists and engineers in their work to convert disruptive ideas into impactful energy technologies.
Researchers at ORNL have successfully demonstrated the first 270-kW wireless power transfer to a light-duty electric vehicle. The demonstration used a Porsche Taycan and was conducted in collaboration with Volkswagen Group of America using the ORNL-developed polyphase wireless charging system.
Prasanna Balaprakash, a national leader in artificial intelligence, or AI, spoke to some of the highest achieving students in the country at the National Science Bowl in Washington D.C.
ORNL researchers and communications specialists took part in the inaugural AI Expo for National Competitiveness in Washington D.C, May 7 and 8, to showcase and provide insight into how the lab is leading the way for utilizing the vast possibilities of AI.
John Lagergren, a staff scientist in Oak Ridge National Laboratory’s Plant Systems Biology group, is using his expertise in applied math and machine learning to develop neural networks to quickly analyze the vast amounts of data on plant traits amassed at ORNL’s Advanced Plant Phenotyping Laboratory.