Filter News
Area of Research
- Advanced Manufacturing (2)
- Biology and Environment (31)
- Building Technologies (1)
- Clean Energy (45)
- Climate and Environmental Systems (1)
- Computational Biology (2)
- Computational Engineering (3)
- Computer Science (16)
- Electricity and Smart Grid (1)
- Functional Materials for Energy (1)
- Fusion and Fission (10)
- Fusion Energy (2)
- Isotopes (1)
- Materials (41)
- Materials for Computing (13)
- Mathematics (1)
- National Security (26)
- Neutron Science (20)
- Nuclear Science and Technology (2)
- Quantum information Science (6)
- Supercomputing (127)
News Topics
- (-) Artificial Intelligence (102)
- (-) Computer Science (199)
- (-) ITER (7)
- (-) Net Zero (14)
- (-) Polymers (33)
- (-) Summit (61)
- 3-D Printing/Advanced Manufacturing (128)
- Advanced Reactors (35)
- Big Data (62)
- Bioenergy (92)
- Biology (101)
- Biomedical (61)
- Biotechnology (24)
- Buildings (67)
- Chemical Sciences (73)
- Clean Water (31)
- Climate Change (106)
- Composites (30)
- Coronavirus (46)
- Critical Materials (29)
- Cybersecurity (35)
- Decarbonization (85)
- Education (5)
- Element Discovery (1)
- Emergency (2)
- Energy Storage (112)
- Environment (201)
- Exascale Computing (44)
- Fossil Energy (6)
- Frontier (46)
- Fusion (59)
- Grid (67)
- High-Performance Computing (94)
- Hydropower (11)
- Irradiation (3)
- Isotopes (57)
- Machine Learning (51)
- Materials (149)
- Materials Science (149)
- Mathematics (10)
- Mercury (12)
- Microelectronics (4)
- Microscopy (51)
- Molten Salt (9)
- Nanotechnology (60)
- National Security (73)
- Neutron Science (139)
- Nuclear Energy (111)
- Partnerships (51)
- Physics (64)
- Quantum Computing (38)
- Quantum Science (72)
- Renewable Energy (2)
- Security (26)
- Simulation (53)
- Software (1)
- Space Exploration (25)
- Statistics (3)
- Sustainable Energy (130)
- Transformational Challenge Reactor (7)
- Transportation (99)
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.
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.
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.
Erin Webb, lead for the Bioresources Science and Engineering group at Oak Ridge National Laboratory, has been elected a Fellow of the American Society of Agricultural and Biological Engineers — the society’s highest honor.
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.
Vanderbilt University and ORNL announced a partnership to develop training, testing and evaluation methods that will accelerate the Department of Defense’s adoption of AI-based systems in operational environments.