Filter News
Area of Research
News Topics
- (-) Advanced Reactors (1)
- (-) Clean Water (2)
- (-) Computer Science (11)
- (-) Nuclear Energy (5)
- (-) Physics (1)
- (-) Space Exploration (1)
- 3-D Printing/Advanced Manufacturing (5)
- Artificial Intelligence (4)
- Big Data (2)
- Bioenergy (4)
- Biomedical (2)
- Biotechnology (1)
- Energy Storage (3)
- Environment (8)
- Exascale Computing (1)
- Grid (1)
- Machine Learning (1)
- Materials Science (1)
- Mercury (1)
- Nanotechnology (1)
- Neutron Science (4)
- Quantum Science (2)
- Summit (4)
- Sustainable Energy (1)
- Transportation (3)
Media Contacts
Six new nuclear reactor technologies are set to deploy for commercial use between 2030 and 2040. Called Generation IV nuclear reactors, they will operate with improved performance at dramatically higher temperatures than today’s reactors.
Environmental conditions, lifestyle choices, chemical exposure, and foodborne and airborne pathogens are among the external factors that can cause disease. In contrast, internal genetic factors can be responsible for the onset and progression of diseases ranging from degenerative neurological disorders to some cancers.
Scientists have demonstrated a new bio-inspired material for an eco-friendly and cost-effective approach to recovering uranium from seawater.
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.
Ionic conduction involves the movement of ions from one location to another inside a material. The ions travel through point defects, which are irregularities in the otherwise consistent arrangement of atoms known as the crystal lattice. This sometimes sluggish process can limit the performance and efficiency of fuel cells, batteries, and other energy storage technologies.
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.
Using artificial neural networks designed to emulate the inner workings of the human brain, deep-learning algorithms deftly peruse and analyze large quantities of data. Applying this technique to science problems can help unearth historically elusive solutions.