Filter News
Area of Research
- Advanced Manufacturing (6)
- Biology and Environment (66)
- Biology and Soft Matter (1)
- Clean Energy (65)
- Climate and Environmental Systems (2)
- Computational Biology (1)
- Computational Engineering (2)
- Computer Science (6)
- Electricity and Smart Grid (1)
- Fuel Cycle Science and Technology (1)
- Functional Materials for Energy (1)
- Fusion and Fission (32)
- Fusion Energy (13)
- Isotope Development and Production (1)
- Isotopes (26)
- Materials (54)
- Materials for Computing (4)
- Mathematics (1)
- National Security (28)
- Neutron Science (16)
- Nuclear Science and Technology (40)
- Nuclear Systems Modeling, Simulation and Validation (2)
- Sensors and Controls (1)
- Supercomputing (87)
News Topics
- (-) Advanced Reactors (33)
- (-) Artificial Intelligence (82)
- (-) Clean Water (29)
- (-) Climate Change (92)
- (-) Composites (25)
- (-) Exascale Computing (34)
- (-) Frontier (39)
- (-) Isotopes (46)
- (-) Nuclear Energy (102)
- (-) Security (23)
- 3-D Printing/Advanced Manufacturing (116)
- Big Data (49)
- Bioenergy (88)
- Biology (93)
- Biomedical (56)
- Biotechnology (21)
- Buildings (54)
- Chemical Sciences (58)
- Computer Science (181)
- Coronavirus (46)
- Critical Materials (23)
- Cybersecurity (35)
- Decarbonization (73)
- Education (3)
- Element Discovery (1)
- Emergency (2)
- Energy Storage (106)
- Environment (191)
- Fossil Energy (5)
- Fusion (52)
- Grid (59)
- High-Performance Computing (80)
- Hydropower (11)
- Irradiation (3)
- ITER (7)
- Machine Learning (43)
- Materials (140)
- Materials Science (132)
- Mathematics (6)
- Mercury (12)
- Microelectronics (2)
- Microscopy (50)
- Molten Salt (8)
- Nanotechnology (60)
- National Security (54)
- Net Zero (11)
- Neutron Science (127)
- Partnerships (38)
- Physics (58)
- Polymers (31)
- Quantum Computing (28)
- Quantum Science (65)
- Renewable Energy (2)
- Simulation (42)
- Software (1)
- Space Exploration (24)
- Statistics (2)
- Summit (57)
- Sustainable Energy (118)
- Transformational Challenge Reactor (7)
- Transportation (93)
Media Contacts
To capitalize on AI and researcher strengths, scientists developed a human-AI collaboration recommender system for improved experimentation performance.
ORNL scientists and researchers attended the annual American Geophysical Union meeting and came away inspired for the year ahead in geospatial, earth and climate science.
Three staff members in ORNL’s Fusion and Fission Energy and Science Directorate have moved into newly established roles facilitating communication and program management with sponsors of the directorate’s Nuclear Energy and Fuel Cycle Division.
A key industrial isotope, iridium-192, has not been produced in the U.S. in almost 20 years. DOE's Isotope Program and QSA Global Inc. announced a joint product development agreement to initiate U.S. production of iridium-192.
In a win for chemistry, inventors at ORNL have designed a closed-loop path for synthesizing an exceptionally tough carbon-fiber-reinforced polymer, or CFRP, and later recovering all of its starting materials.
ORNL climate modeling expertise contributed to a project that assessed global emissions of ammonia from croplands now and in a warmer future, while also identifying solutions tuned to local growing conditions.
Ilenne Del Valle is merging her expertise in synthetic biology and environmental science to develop new technologies to help scientists better understand and engineer ecosystems for climate resilience.
Scientists at the Department of Energy’s Oak Ridge National Laboratory are using a new modeling framework in conjunction with data collected from marshes in the Mississippi Delta to improve predictions of climate-warming methane and nitrous oxide
Gina Tourassi, associate laboratory director for computing and computational sciences at the US Department of Energy’s (DOE’s) Oak Ridge National Laboratory, has been named a fellow of the Institute of Electrical and Electronics Engineers, the world’s largest organization for technical professionals.
Researchers at the Department of Energy’s Oak Ridge and Lawrence Berkeley National Laboratories are evolving graph neural networks to scale on the nation’s most powerful computational resources, a necessary step in tackling today’s data-centric