Filter News
Area of Research
- (-) Biology and Environment (29)
- (-) Materials (30)
- (-) National Security (18)
- Advanced Manufacturing (1)
- Biological Systems (1)
- Clean Energy (69)
- Computational Biology (1)
- Computational Engineering (1)
- Computer Science (3)
- Fusion and Fission (7)
- Fusion Energy (1)
- Isotopes (4)
- Materials for Computing (7)
- Neutron Science (22)
- Nuclear Science and Technology (7)
- Quantum information Science (5)
- Supercomputing (74)
News Type
News Topics
- (-) Advanced Reactors (3)
- (-) Biomedical (17)
- (-) Buildings (4)
- (-) Machine Learning (19)
- (-) Mathematics (3)
- (-) Quantum Science (11)
- (-) Summit (12)
- (-) Transportation (9)
- 3-D Printing/Advanced Manufacturing (22)
- Artificial Intelligence (25)
- Big Data (12)
- Bioenergy (42)
- Biology (60)
- Biotechnology (11)
- Chemical Sciences (30)
- Clean Water (10)
- Climate Change (35)
- Composites (7)
- Computer Science (42)
- Coronavirus (13)
- Critical Materials (8)
- Cybersecurity (19)
- Decarbonization (22)
- Energy Storage (28)
- Environment (80)
- Exascale Computing (6)
- Frontier (5)
- Fusion (6)
- Grid (9)
- High-Performance Computing (24)
- Hydropower (5)
- Isotopes (11)
- ITER (1)
- Materials (62)
- Materials Science (56)
- Mercury (6)
- Microscopy (25)
- Molten Salt (2)
- Nanotechnology (32)
- National Security (34)
- Net Zero (3)
- Neutron Science (31)
- Nuclear Energy (15)
- Partnerships (15)
- Physics (26)
- Polymers (11)
- Quantum Computing (2)
- Renewable Energy (2)
- Security (11)
- Simulation (13)
- Space Exploration (1)
- Sustainable Energy (30)
- Transformational Challenge Reactor (3)
Media Contacts
Researchers at ORNL are teaching microscopes to drive discoveries with an intuitive algorithm, developed at the lab’s Center for Nanophase Materials Sciences, that could guide breakthroughs in new materials for energy technologies, sensing and computing.
ORNL researchers used the nation’s fastest supercomputer to map the molecular vibrations of an important but little-studied uranium compound produced during the nuclear fuel cycle for results that could lead to a cleaner, safer world.
A team of researchers has developed a novel, machine learning–based technique to explore and identify relationships among medical concepts using electronic health record data across multiple healthcare providers.
ORNL scientists had a problem mapping the genomes of bacteria to better understand the origins of their physical traits and improve their function for bioenergy production.
Every day, hundreds of thousands of commuters across the country travel from houses, apartments and other residential spaces to commercial buildings — from offices and schools to gyms and grocery stores.
ORNL, TVA and TNECD were recognized by the Federal Laboratory Consortium for their impactful partnership that resulted in a record $2.3 billion investment by Ultium Cells, a General Motors and LG Energy Solution joint venture, to build a battery cell manufacturing plant in Spring Hill, Tennessee.
A team of scientists led by the Department of Energy’s Oak Ridge National Laboratory and the Georgia Institute of Technology is using supercomputing and revolutionary deep learning tools to predict the structures and roles of thousands of proteins with unknown functions.
A team led by the ORNL has found a rare quantum material in which electrons move in coordinated ways, essentially “dancing.”
Improved data, models and analyses from ORNL scientists and many other researchers in the latest global climate assessment report provide new levels of certainty about what the future holds for the planet
Scientists at ORNL and the University of Wisconsin–Madison have discovered that genetically distinct populations within the same species of fungi can produce unique mixes of secondary metabolites, which are organic compounds with applications in