Filter News
Area of Research
- (-) Climate and Environmental Systems (2)
- (-) Supercomputing (76)
- Advanced Manufacturing (1)
- Biological Systems (1)
- Biology and Environment (66)
- Biology and Soft Matter (1)
- Clean Energy (75)
- Computational Biology (2)
- Computational Engineering (2)
- Computer Science (3)
- Electricity and Smart Grid (3)
- Functional Materials for Energy (1)
- Fusion and Fission (9)
- Fusion Energy (8)
- Isotopes (6)
- Materials (50)
- Materials for Computing (4)
- Mathematics (1)
- National Security (16)
- Neutron Science (26)
- Nuclear Science and Technology (15)
- Nuclear Systems Modeling, Simulation and Validation (1)
- Quantum information Science (1)
- Sensors and Controls (1)
News Topics
- (-) Advanced Reactors (1)
- (-) Biomedical (17)
- (-) Climate Change (19)
- (-) Grid (5)
- (-) Physics (7)
- (-) Summit (42)
- 3-D Printing/Advanced Manufacturing (5)
- Artificial Intelligence (36)
- Big Data (19)
- Bioenergy (9)
- Biology (12)
- Biotechnology (2)
- Buildings (4)
- Chemical Sciences (5)
- Computer Science (96)
- Coronavirus (14)
- Critical Materials (3)
- Cybersecurity (8)
- Decarbonization (5)
- Energy Storage (8)
- Environment (26)
- Exascale Computing (22)
- Frontier (28)
- Fusion (1)
- High-Performance Computing (38)
- Isotopes (1)
- Machine Learning (14)
- Materials (15)
- Materials Science (16)
- Mathematics (1)
- Mercury (1)
- Microscopy (7)
- Molten Salt (1)
- Nanotechnology (11)
- National Security (8)
- Net Zero (1)
- Neutron Science (13)
- Nuclear Energy (4)
- Partnerships (1)
- Polymers (2)
- Quantum Computing (19)
- Quantum Science (24)
- Security (5)
- Simulation (14)
- Software (1)
- Space Exploration (3)
- Sustainable Energy (10)
- Transportation (6)
Media Contacts
A team of scientists led by the Department of Energy’s Oak Ridge National Laboratory and the Georgia Institute of Technology is using supercomputing and revolutionary deep learning tools to predict the structures and roles of thousands of proteins with unknown functions.
The world is full of “huge, gnarly problems,” as ORNL research scientist and musician Melissa Allen-Dumas puts it — no matter what line of work you’re in. That was certainly the case when she would wrestle with a tough piece of music.
The U.S. Department of Energy’s Office of Science announced allocations of supercomputer access to 51 high-impact computational science projects for 2022 through its Innovative and Novel Computational Impact on Theory and Experiment, or INCITE, program.
An international problem like climate change needs solutions that cross boundaries, both on maps and among disciplines. Oak Ridge National Laboratory computational scientist Deeksha Rastogi embodies that approach.
Improved data, models and analyses from ORNL scientists and many other researchers in the latest global climate assessment report provide new levels of certainty about what the future holds for the planet
An ORNL-led team comprising researchers from multiple DOE national laboratories is using artificial intelligence and computational screening techniques – in combination with experimental validation – to identify and design five promising drug therapy approaches to target the SARS-CoV-2 virus.
The Department of Energy’s Oak Ridge National Laboratory has licensed its award-winning artificial intelligence software system, the Multinode Evolutionary Neural Networks for Deep Learning, to General Motors for use in vehicle technology and design.
The U.S. Department of Energy’s Innovative and Novel Computational Impact on Theory and Experiment, or INCITE, program is seeking proposals for high-impact, computationally intensive research campaigns in a broad array of science, engineering and computer science domains.
Since the 1930s, scientists have been using particle accelerators to gain insights into the structure of matter and the laws of physics that govern our world.
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.