Filter News
Area of Research
- (-) Advanced Manufacturing (1)
- (-) Computer Science (5)
- Biology and Environment (49)
- Biology and Soft Matter (1)
- Clean Energy (24)
- Climate and Environmental Systems (2)
- Computational Engineering (2)
- Fusion and Fission (14)
- Fusion Energy (11)
- Materials (24)
- Materials for Computing (9)
- Mathematics (1)
- National Security (13)
- Neutron Science (10)
- Nuclear Science and Technology (11)
- Quantum information Science (7)
- Supercomputing (40)
News Topics
- (-) Fusion (1)
- (-) Machine Learning (4)
- (-) Quantum Science (1)
- 3-D Printing/Advanced Manufacturing (14)
- Advanced Reactors (1)
- Artificial Intelligence (4)
- Big Data (3)
- Buildings (1)
- Composites (3)
- Computer Science (12)
- Energy Storage (1)
- Environment (1)
- Grid (2)
- High-Performance Computing (1)
- Materials (6)
- Materials Science (5)
- Neutron Science (2)
- Nuclear Energy (1)
- Space Exploration (1)
- Sustainable Energy (5)
Media Contacts
To minimize potential damage from underground oil and gas leaks, Oak Ridge National Laboratory is co-developing a quantum sensing system to detect pipeline leaks more quickly.
ORNL computer scientist Catherine Schuman returned to her alma mater, Harriman High School, to lead Hour of Code activities and talk to students about her job as a researcher.
Oak Ridge National Laboratory is training next-generation cameras called dynamic vision sensors, or DVS, to interpret live information—a capability that has applications in robotics and could improve autonomous vehicle sensing.
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.
Researchers at Oak Ridge National Laboratory are taking inspiration from neural networks to create computers that mimic the human brain—a quickly growing field known as neuromorphic computing.
A study led by Oak Ridge National Laboratory explored the interface between the Department of Veterans Affairs’ healthcare data system and the data itself to detect the likelihood of errors and designed an auto-surveillance tool