Filter News
Area of Research
- (-) Biological Systems (1)
- (-) National Security (13)
- (-) Neutron Science (14)
- Advanced Manufacturing (2)
- Biology and Environment (64)
- Biology and Soft Matter (1)
- Clean Energy (30)
- Climate and Environmental Systems (1)
- Computational Biology (1)
- Fusion and Fission (13)
- Fusion Energy (5)
- Isotopes (17)
- Materials (30)
- Materials for Computing (2)
- Nuclear Science and Technology (8)
- Supercomputing (27)
News Topics
- (-) Biomedical (7)
- (-) Cybersecurity (8)
- (-) Environment (6)
- (-) Materials (6)
- (-) Space Exploration (1)
- 3-D Printing/Advanced Manufacturing (4)
- Artificial Intelligence (10)
- Big Data (5)
- Bioenergy (5)
- Biology (4)
- Biotechnology (1)
- Buildings (1)
- Chemical Sciences (1)
- Clean Water (2)
- Climate Change (4)
- Computer Science (16)
- Coronavirus (4)
- Decarbonization (3)
- Energy Storage (2)
- Fossil Energy (1)
- Grid (3)
- High-Performance Computing (4)
- Machine Learning (11)
- Materials Science (8)
- Mathematics (1)
- Microscopy (1)
- Nanotechnology (3)
- National Security (22)
- Neutron Science (33)
- Nuclear Energy (3)
- Physics (1)
- Polymers (1)
- Quantum Computing (1)
- Quantum Science (2)
- Security (5)
- Simulation (1)
- Summit (2)
- Sustainable Energy (1)
- Transportation (1)
Media Contacts
Scientists have long sought to better understand the “local structure” of materials, meaning the arrangement and activities of the neighboring particles around each atom. In crystals, which are used in electronics and many other applications, most of the atoms form highly ordered lattice patterns that repeat. But not all atoms conform to the pattern.
The Autonomous Systems group at ORNL is in high demand as it incorporates remote sensing into projects needing a bird’s-eye perspective.
Natural gas furnaces not only heat your home, they also produce a lot of pollution. Even modern high-efficiency condensing furnaces produce significant amounts of corrosive acidic condensation and unhealthy levels of nitrogen oxides
The word “exotic” may not spark thoughts of uranium, but Tyler Spano’s investigations of exotic phases of uranium are bringing new knowledge to the nuclear nonproliferation industry.
Though Nell Barber wasn’t sure what her future held after graduating with a bachelor’s degree in psychology, she now uses her interest in human behavior to design systems that leverage machine learning algorithms to identify faces in a crowd.
Scientists develop environmental justice lens to identify neighborhoods vulnerable to climate change
A new capability to identify urban neighborhoods, down to the block and building level, that are most vulnerable to climate change could help ensure that mitigation and resilience programs reach the people who need them the most.
How an Alvin M. Weinberg Fellow is increasing security for critical infrastructure components
A team of researchers has developed a novel, machine learning–based technique to explore and identify relationships among medical concepts using electronic health record data across multiple healthcare providers.
An ORNL-led team comprising researchers from multiple DOE national laboratories is using artificial intelligence and computational screening techniques – in combination with experimental validation – to identify and design five promising drug therapy approaches to target the SARS-CoV-2 virus.
Deborah Frincke, one of the nation’s preeminent computer scientists and cybersecurity experts, serves as associate laboratory director of ORNL’s National Security Science Directorate. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy