Filter News
Area of Research
- (-) Supercomputing (61)
- Biology and Environment (99)
- Biology and Soft Matter (1)
- Clean Energy (60)
- Climate and Environmental Systems (5)
- Computational Biology (1)
- Computational Engineering (2)
- Computer Science (2)
- Electricity and Smart Grid (1)
- Functional Materials for Energy (1)
- Fusion and Fission (2)
- Fusion Energy (1)
- Isotopes (1)
- Materials (18)
- Materials for Computing (2)
- Mathematics (1)
- National Security (6)
- Neutron Science (14)
- Nuclear Science and Technology (1)
News Topics
- (-) Environment (21)
- (-) Summit (43)
- 3-D Printing/Advanced Manufacturing (5)
- Advanced Reactors (1)
- Artificial Intelligence (36)
- Big Data (20)
- Bioenergy (9)
- Biology (11)
- Biomedical (17)
- Biotechnology (2)
- Buildings (4)
- Chemical Sciences (5)
- Climate Change (17)
- Computer Science (95)
- Coronavirus (14)
- Critical Materials (3)
- Cybersecurity (8)
- Decarbonization (5)
- Energy Storage (8)
- Exascale Computing (24)
- Frontier (29)
- Fusion (1)
- Grid (5)
- High-Performance Computing (40)
- Isotopes (2)
- Machine Learning (14)
- Materials (15)
- Materials Science (16)
- Mathematics (1)
- Microscopy (7)
- Molten Salt (1)
- Nanotechnology (11)
- National Security (8)
- Net Zero (1)
- Neutron Science (13)
- Nuclear Energy (4)
- Partnerships (1)
- Physics (8)
- Polymers (2)
- Quantum Computing (19)
- Quantum Science (24)
- Security (5)
- Simulation (15)
- Software (1)
- Space Exploration (3)
- Sustainable Energy (10)
- Transportation (6)
Media Contacts
A new version of the Energy Exascale Earth System Model, or E3SM, is two times faster than an earlier version released in 2018.
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 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
RamSat’s mission is to take pictures of the forests around Gatlinburg, which were destroyed by wildfire in 2016. The mission is wholly designed and carried out by students, teachers and mentors, with support from numerous organizations, including Oak Ridge National Laboratory.
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.
Twenty-seven ORNL researchers Zoomed into 11 middle schools across Tennessee during the annual Engineers Week in February. East Tennessee schools throughout Oak Ridge and Roane, Sevier, Blount and Loudon counties participated, with three West Tennessee schools joining in.
The U.S. Air Force and Oak Ridge National Laboratory launched a new high-performance weather forecasting computer system that will provide a platform for some of the most advanced weather modeling in the world.