Filter News
Area of Research
News Topics
- (-) Advanced Reactors (1)
- (-) Artificial Intelligence (4)
- (-) Clean Water (2)
- (-) Grid (1)
- 3-D Printing/Advanced Manufacturing (5)
- Big Data (2)
- Bioenergy (4)
- Biomedical (2)
- Biotechnology (1)
- Computer Science (11)
- Energy Storage (3)
- Environment (8)
- Exascale Computing (1)
- Machine Learning (1)
- Materials Science (1)
- Mercury (1)
- Nanotechnology (1)
- Neutron Science (4)
- Nuclear Energy (5)
- Physics (1)
- Quantum Science (2)
- Space Exploration (1)
- Summit (4)
- Sustainable Energy (1)
- Transportation (3)
Media Contacts
While Tsouris’ water research is diverse in scope, its fundamentals are based on basic science principles that remain largely unchanged, particularly in a mature field like chemical engineering.
Students often participate in internships and receive formal training in their chosen career fields during college, but some pursue professional development opportunities even earlier.
Ask Tyler Gerczak to find a negative in working at the Department of Energy’s Oak Ridge National Laboratory, and his only complaint is the summer weather. It is not as forgiving as the summers in Pulaski, Wisconsin, his hometown.
Artificial intelligence (AI) techniques have the potential to support medical decision-making, from diagnosing diseases to prescribing treatments. But to prioritize patient safety, researchers and practitioners must first ensure such methods are accurate.
Materials scientists, electrical engineers, computer scientists, and other members of the neuromorphic computing community from industry, academia, and government agencies gathered in downtown Knoxville July 23–25 to talk about what comes next in
Isabelle Snyder calls faults as she sees them, whether it’s modeling operations for the nation’s power grid or officiating at the US Open Tennis Championships.
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.
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.