Filter News
Area of Research
- Advanced Manufacturing (22)
- Biology and Environment (16)
- Building Technologies (1)
- Clean Energy (82)
- Computer Science (1)
- Electricity and Smart Grid (1)
- Fusion and Fission (26)
- Fusion Energy (15)
- Materials (31)
- Materials for Computing (4)
- National Security (4)
- Neutron Science (7)
- Nuclear Science and Technology (12)
- Supercomputing (30)
News Topics
- (-) 3-D Printing/Advanced Manufacturing (128)
- (-) Exascale Computing (44)
- (-) Fusion (59)
- (-) Microelectronics (4)
- Advanced Reactors (35)
- Artificial Intelligence (102)
- Big Data (62)
- Bioenergy (92)
- Biology (101)
- Biomedical (61)
- Biotechnology (24)
- Buildings (67)
- Chemical Sciences (73)
- Clean Water (31)
- Climate Change (106)
- Composites (30)
- Computer Science (199)
- Coronavirus (46)
- Critical Materials (29)
- Cybersecurity (35)
- Decarbonization (85)
- Education (5)
- Element Discovery (1)
- Emergency (2)
- Energy Storage (112)
- Environment (201)
- Fossil Energy (6)
- Frontier (46)
- Grid (67)
- High-Performance Computing (94)
- Hydropower (11)
- Irradiation (3)
- Isotopes (57)
- ITER (7)
- Machine Learning (51)
- Materials (149)
- Materials Science (149)
- Mathematics (10)
- Mercury (12)
- Microscopy (51)
- Molten Salt (9)
- Nanotechnology (60)
- National Security (73)
- Net Zero (14)
- Neutron Science (139)
- Nuclear Energy (111)
- Partnerships (51)
- Physics (64)
- Polymers (33)
- Quantum Computing (38)
- Quantum Science (72)
- Renewable Energy (2)
- Security (26)
- Simulation (53)
- Software (1)
- Space Exploration (25)
- Statistics (3)
- Summit (61)
- Sustainable Energy (130)
- Transformational Challenge Reactor (7)
- Transportation (99)
Media Contacts
Advanced materials research to enable energy-efficient, cost-competitive and environmentally friendly technologies for the United States and Japan is the goal of a memorandum of understanding, or MOU, between the Department of Energy’s Oak Ridge National Laboratory and Japan’s National Institute of Materials Science.
Researchers at ORNL have developed the first additive manufacturing slicing computer application to simultaneously speed and simplify digital conversion of accurate, large-format three-dimensional parts in a factory production setting.
ORNL researchers completed successful testing of a gallium nitride transistor for use in more accurate sensors operating near the core of a nuclear reactor. This is an important technical advance particularly for monitoring new, compact.
A new study conducted on the Frontier supercomputer gave researchers new clues to improving fusion confinement. This research, in collaboration with General Atomics and UC San Diego, uncovered that the interaction between ions and electrons near the tokamak's edge can unexpectedly increase turbulence, challenging previous assumptions about how to optimize plasma confinement for efficient nuclear fusion.
Oak Ridge National Laboratory scientists ingeniously created a sustainable, soft material by combining rubber with woody reinforcements and incorporating “smart” linkages between the components that unlock on demand.
Building innovations from ORNL will be on display in Washington, D.C. on the National Mall June 7 to June 9, 2024, during the U.S. Department of Housing and Urban Development’s Innovation Housing Showcase. For the first time, ORNL’s real-time building evaluator was demonstrated outside of a laboratory setting and deployed for building construction.
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.
Momentum for manufacturing innovation in the United States got a boost during the inaugural MDF Innovation Days, held recently at the U.S. Department of Energy Manufacturing Demonstration Facility at Oak Ridge National Laboratory.
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.
When scientists pushed the world’s fastest supercomputer to its limits, they found those limits stretched beyond even their biggest expectations. In the latest milestone, a team of engineers and scientists used Frontier to simulate a system of nearly half a trillion atoms — the largest system ever modeled and more than 400 times the size of the closest competition.