Filter News
Area of Research
- (-) Neutron Science (4)
- (-) Supercomputing (6)
- Biological Systems (1)
- Biology and Environment (28)
- Clean Energy (14)
- Fusion and Fission (18)
- Fusion Energy (4)
- Isotopes (2)
- Materials (18)
- Materials for Computing (2)
- National Security (4)
- Nuclear Science and Technology (17)
- Quantum information Science (2)
News Topics
- (-) Bioenergy (5)
- (-) Microscopy (2)
- (-) Nuclear Energy (3)
- 3-D Printing/Advanced Manufacturing (4)
- Artificial Intelligence (22)
- Big Data (14)
- Biology (6)
- Biomedical (10)
- Biotechnology (1)
- Buildings (2)
- Chemical Sciences (1)
- Clean Water (2)
- Climate Change (12)
- Computer Science (47)
- Coronavirus (7)
- Cybersecurity (2)
- Decarbonization (4)
- Energy Storage (3)
- Environment (16)
- Exascale Computing (14)
- Fossil Energy (1)
- Frontier (14)
- Grid (1)
- High-Performance Computing (22)
- Isotopes (1)
- Machine Learning (9)
- Materials (9)
- Materials Science (13)
- Mathematics (1)
- Nanotechnology (6)
- National Security (3)
- Net Zero (1)
- Neutron Science (36)
- Physics (5)
- Polymers (1)
- Quantum Computing (10)
- Quantum Science (10)
- Security (2)
- Simulation (11)
- Software (1)
- Space Exploration (2)
- Summit (22)
- Sustainable Energy (3)
- Transportation (4)
Media Contacts
Scientists at ORNL used their knowledge of complex ecosystem processes, energy systems, human dynamics, computational science and Earth-scale modeling to inform the nation’s latest National Climate Assessment, which draws attention to vulnerabilities and resilience opportunities in every region of the country.
The Exascale Small Modular Reactor effort, or ExaSMR, is a software stack developed over seven years under the Department of Energy’s Exascale Computing Project to produce the highest-resolution simulations of nuclear reactor systems to date. Now, ExaSMR has been nominated for a 2023 Gordon Bell Prize by the Association for Computing Machinery and is one of six finalists for the annual award, which honors outstanding achievements in high-performance computing from a variety of scientific domains.
To optimize biomaterials for reliable, cost-effective paper production, building construction, and biofuel development, researchers often study the structure of plant cells using techniques such as freezing plant samples or placing them in a vacuum.
Tackling the climate crisis and achieving an equitable clean energy future are among the biggest challenges of our time.
At the Department of Energy’s Oak Ridge National Laboratory, scientists use artificial intelligence, or AI, to accelerate the discovery and development of materials for energy and information technologies.
Biological membranes, such as the “walls” of most types of living cells, primarily consist of a double layer of lipids, or “lipid bilayer,” that forms the structure, and a variety of embedded and attached proteins with highly specialized functions, including proteins that rapidly and selectively transport ions and molecules in and out of the cell.
Illustration of the optimized zeolite catalyst, or NbAlS-1, which enables a highly efficient chemical reaction to create butene, a renewable source of energy, without expending high amounts of energy for the conversion. Credit: Jill Hemman, Oak Ridge National Laboratory/U.S. Dept. of Energy
Researchers at the Department of Energy’s Oak Ridge National Laboratory, Pacific Northwest National Laboratory and Washington State University teamed up to investigate the complex dynamics of low-water liquids that challenge nuclear waste processing at federal cleanup sites.
Scientists at the Department of Energy’s Oak Ridge National Laboratory are working to understand both the complex nature of uranium and the various oxide forms it can take during processing steps that might occur throughout the nuclear fuel cycle.