Filter News
Area of Research
- Advanced Manufacturing (2)
- Biological Systems (1)
- Biology and Environment (27)
- Clean Energy (26)
- Computational Biology (2)
- Computational Engineering (1)
- Electricity and Smart Grid (1)
- Functional Materials for Energy (1)
- Fusion and Fission (8)
- Fusion Energy (8)
- Isotope Development and Production (1)
- Isotopes (9)
- Materials (18)
- Materials for Computing (6)
- National Security (6)
- Neutron Science (19)
- Nuclear Science and Technology (19)
- Nuclear Systems Modeling, Simulation and Validation (1)
- Supercomputing (55)
News Type
News Topics
- (-) Advanced Reactors (33)
- (-) Biomedical (57)
- (-) Coronavirus (45)
- (-) Frontier (41)
- (-) Space Exploration (25)
- 3-D Printing/Advanced Manufacturing (118)
- Artificial Intelligence (90)
- Big Data (52)
- Bioenergy (91)
- Biology (98)
- Biotechnology (21)
- Buildings (52)
- Chemical Sciences (64)
- Clean Water (28)
- Climate Change (96)
- Composites (25)
- Computer Science (184)
- Critical Materials (25)
- Cybersecurity (35)
- Decarbonization (76)
- Education (4)
- Element Discovery (1)
- Emergency (2)
- Energy Storage (103)
- Environment (189)
- Exascale Computing (37)
- Fossil Energy (6)
- Fusion (53)
- Grid (61)
- High-Performance Computing (85)
- Hydropower (11)
- Irradiation (3)
- Isotopes (52)
- ITER (7)
- Machine Learning (47)
- Materials (143)
- Materials Science (132)
- Mathematics (8)
- Mercury (12)
- Microelectronics (3)
- Microscopy (48)
- Molten Salt (8)
- Nanotechnology (56)
- National Security (59)
- Net Zero (14)
- Neutron Science (128)
- Nuclear Energy (104)
- Partnerships (44)
- Physics (56)
- Polymers (30)
- Quantum Computing (34)
- Quantum Science (68)
- Renewable Energy (2)
- Security (23)
- Simulation (48)
- Software (1)
- Statistics (3)
- Summit (57)
- Sustainable Energy (123)
- Transformational Challenge Reactor (7)
- Transportation (92)
Media Contacts
The U.S. Department of Energy announced funding for 12 projects with private industry to enable collaboration with DOE national laboratories on overcoming challenges in fusion energy development.
The type of vehicle that will carry people to the Red Planet is shaping up to be “like a two-story house you’re trying to land on another planet.
In a recent study, researchers at Oak Ridge National Laboratory performed experiments in a prototype fusion reactor materials testing facility to develop a method that uses microwaves to raise the plasma’s temperature closer to the extreme values
Ask Tyler Gerczak to find a negative in working at the Department of Energy’s Oak Ridge National Laboratory, and his only complaint is the summer weather. It is not as forgiving as the summers in Pulaski, Wisconsin, his hometown.
Using additive manufacturing, scientists experimenting with tungsten at Oak Ridge National Laboratory hope to unlock new potential of the high-performance heat-transferring material used to protect components from the plasma inside a fusion reactor. Fusion requires hydrogen isotopes to reach millions of degrees.
Using the Titan supercomputer at Oak Ridge National Laboratory, a team of astrophysicists created a set of galactic wind simulations of the highest resolution ever performed. The simulations will allow researchers to gather and interpret more accurate, detailed data that elucidates how galactic winds affect the formation and evolution of galaxies.
For the first time, Oak Ridge National Laboratory has completed testing of nuclear fuels using MiniFuel, an irradiation vehicle that allows for rapid experimentation.
OAK RIDGE, Tenn., May 7, 2019—The U.S. Department of Energy today announced a contract with Cray Inc. to build the Frontier supercomputer at Oak Ridge National Laboratory, which is anticipated to debut in 2021 as the world’s most powerful computer with a performance of greater than 1.5 exaflops.
In a step toward advancing small modular nuclear reactor designs, scientists at Oak Ridge National Laboratory have run reactor simulations on ORNL supercomputer Summit with greater-than-expected computational efficiency.
Using artificial neural networks designed to emulate the inner workings of the human brain, deep-learning algorithms deftly peruse and analyze large quantities of data. Applying this technique to science problems can help unearth historically elusive solutions.