Filter News
Area of Research
- (-) Supercomputing (4)
- Advanced Manufacturing (1)
- Biology and Environment (9)
- Clean Energy (7)
- Climate and Environmental Systems (1)
- Computational Engineering (1)
- Fusion and Fission (2)
- Fusion Energy (6)
- Materials (5)
- Materials for Computing (1)
- Mathematics (1)
- Neutron Science (1)
- Nuclear Science and Technology (4)
- Nuclear Systems Modeling, Simulation and Validation (1)
News Topics
- (-) Advanced Reactors (1)
- (-) Chemical Sciences (1)
- (-) Climate Change (2)
- Artificial Intelligence (1)
- Big Data (4)
- Biology (1)
- Biomedical (4)
- Computer Science (16)
- Coronavirus (2)
- Critical Materials (3)
- Energy Storage (1)
- Environment (4)
- Exascale Computing (1)
- Frontier (1)
- Fusion (1)
- High-Performance Computing (3)
- Machine Learning (1)
- Materials (1)
- Materials Science (1)
- Nanotechnology (1)
- Nuclear Energy (1)
- Polymers (2)
- Quantum Computing (4)
- Quantum Science (3)
- Simulation (1)
- Space Exploration (1)
- Summit (6)
- Sustainable Energy (1)
- Transportation (1)
Media Contacts
Researchers from Oak Ridge National Laboratory and Northeastern University modeled how extreme conditions in a changing climate affect the land’s ability to absorb atmospheric carbon — a key process for mitigating human-caused emissions. They found that 88% of Earth’s regions could become carbon emitters by the end of the 21st century.
Critical Materials Institute researchers at Oak Ridge National Laboratory and Arizona State University studied the mineral monazite, an important source of rare-earth elements, to enhance methods of recovering critical materials for energy, defense and manufacturing applications.
A new tool from Oak Ridge National Laboratory can help planners, emergency responders and scientists visualize how flood waters will spread for any scenario and terrain.
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.