Filter News
Area of Research
News Topics
- (-) Artificial Intelligence (7)
- (-) Big Data (4)
- (-) Bioenergy (4)
- (-) Machine Learning (1)
- (-) Microscopy (1)
- 3-D Printing/Advanced Manufacturing (2)
- Advanced Reactors (1)
- Biomedical (5)
- Clean Water (1)
- Composites (1)
- Computer Science (30)
- Critical Materials (1)
- Cybersecurity (2)
- Energy Storage (4)
- Environment (6)
- Exascale Computing (2)
- Frontier (2)
- Grid (1)
- Materials Science (3)
- Nanotechnology (2)
- Neutron Science (21)
- Nuclear Energy (3)
- Physics (5)
- Polymers (1)
- Quantum Science (6)
- Security (1)
- Space Exploration (2)
- Summit (11)
- Sustainable Energy (2)
- Transportation (3)
Media Contacts
For nearly three decades, scientists and engineers across the globe have worked on the Square Kilometre Array (SKA), a project focused on designing and building the world’s largest radio telescope. Although the SKA will collect enormous amounts of precise astronomical data in record time, scientific breakthroughs will only be possible with systems able to efficiently process that data.
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
ORNL computer scientist Catherine Schuman returned to her alma mater, Harriman High School, to lead Hour of Code activities and talk to students about her job as a researcher.
Students often participate in internships and receive formal training in their chosen career fields during college, but some pursue professional development opportunities even earlier.
Researchers at the Department of Energy’s Oak Ridge National Laboratory have received five 2019 R&D 100 Awards, increasing the lab’s total to 221 since the award’s inception in 1963.
Processes like manufacturing aircraft parts, analyzing data from doctors’ notes and identifying national security threats may seem unrelated, but at the U.S. Department of Energy’s Oak Ridge National Laboratory, artificial intelligence is improving all of these tasks.
In collaboration with the Department of Veterans Affairs, a team at Oak Ridge National Laboratory has expanded a VA-developed predictive computing model to identify veterans at risk of suicide and sped it up to run 300 times faster, a gain that could profoundly affect the VA’s ability to reach susceptible veterans quickly.
More than 6,000 veterans died by suicide in 2016, and from 2005 to 2016, the rate of veteran suicides in the United States increased by more than 25 percent.
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