Filter News
Area of Research
- Advanced Manufacturing (3)
- Biology and Environment (28)
- Building Technologies (1)
- Clean Energy (44)
- Climate and Environmental Systems (1)
- Computational Biology (1)
- Computational Engineering (3)
- Computer Science (15)
- Fusion and Fission (4)
- Fusion Energy (2)
- Isotopes (1)
- Materials (62)
- Materials for Computing (14)
- Mathematics (1)
- National Security (22)
- Neutron Science (106)
- Nuclear Science and Technology (6)
- Quantum information Science (6)
- Supercomputing (113)
News Topics
- (-) Computer Science (189)
- (-) Exascale Computing (37)
- (-) Neutron Science (131)
- (-) Polymers (33)
- 3-D Printing/Advanced Manufacturing (122)
- Advanced Reactors (34)
- Artificial Intelligence (91)
- Big Data (55)
- Bioenergy (92)
- Biology (99)
- Biomedical (58)
- Biotechnology (22)
- Buildings (57)
- Chemical Sciences (65)
- Clean Water (29)
- Climate Change (100)
- Composites (26)
- Coronavirus (46)
- Critical Materials (26)
- Cybersecurity (35)
- Decarbonization (80)
- Education (4)
- Element Discovery (1)
- Emergency (2)
- Energy Storage (109)
- Environment (195)
- Fossil Energy (6)
- Frontier (42)
- Fusion (55)
- Grid (63)
- High-Performance Computing (85)
- Hydropower (11)
- Irradiation (3)
- Isotopes (53)
- ITER (7)
- Machine Learning (48)
- Materials (144)
- Materials Science (141)
- Mathematics (9)
- Mercury (12)
- Microelectronics (3)
- Microscopy (51)
- Molten Salt (8)
- Nanotechnology (60)
- National Security (63)
- Net Zero (14)
- Nuclear Energy (109)
- Partnerships (44)
- Physics (61)
- Quantum Computing (34)
- Quantum Science (69)
- Renewable Energy (2)
- Security (24)
- Simulation (48)
- Software (1)
- Space Exploration (25)
- Statistics (3)
- Summit (57)
- Sustainable Energy (126)
- Transformational Challenge Reactor (7)
- Transportation (97)
Media Contacts
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.
Oak Ridge National Laboratory scientists have developed a method leveraging artificial intelligence to accelerate the identification of environmentally friendly solvents for industrial carbon capture, biomass processing, rechargeable batteries and other applications.
Researchers used quantum simulations to obtain new insights into the nature of neutrinos — the mysterious subatomic particles that abound throughout the universe — and their role in the deaths of massive stars.
In May, the Department of Energy’s Oak Ridge and Brookhaven national laboratories co-hosted the 15th annual International Particle Accelerator Conference, or IPAC, at the Music City Center in Nashville, Tennessee.
Anuj J. Kapadia, who leads the Advanced Computing in Health Sciences Section at the Department of Energy’s Oak Ridge National Laboratory, was named a 2024 Fellow by the American Association of Physicists in Medicine.
Researchers at ORNL and the University of Maine have designed and 3D-printed a single-piece, recyclable natural-material floor panel tested to be strong enough to replace construction materials like steel.
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.
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.
Researchers set a new benchmark for future experiments making materials in space rather than for space. They discovered that many kinds of glass have similar atomic structure and arrangements and can successfully be made in space. Scientists from nine institutions in government, academia and industry participated in this 5-year study.
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.