Filter News
Area of Research
- (-) Materials (15)
- (-) National Security (20)
- Biological Systems (1)
- Biology and Environment (78)
- Biology and Soft Matter (1)
- Clean Energy (54)
- Climate and Environmental Systems (1)
- Computer Science (1)
- Fusion and Fission (3)
- Materials for Computing (3)
- Neutron Science (10)
- Quantum information Science (1)
- Supercomputing (40)
News Type
News Topics
- (-) Bioenergy (4)
- (-) Cybersecurity (8)
- (-) Energy Storage (7)
- (-) Environment (9)
- (-) Machine Learning (9)
- (-) Summit (2)
- 3-D Printing/Advanced Manufacturing (5)
- Advanced Reactors (1)
- Artificial Intelligence (10)
- Big Data (5)
- Biology (3)
- Biomedical (3)
- Biotechnology (1)
- Buildings (2)
- Chemical Sciences (8)
- Clean Water (2)
- Climate Change (4)
- Composites (2)
- Computer Science (16)
- Coronavirus (2)
- Decarbonization (3)
- Exascale Computing (1)
- Fusion (3)
- Grid (5)
- High-Performance Computing (4)
- Isotopes (6)
- Materials (21)
- Materials Science (22)
- Mathematics (1)
- Microscopy (8)
- Nanotechnology (10)
- National Security (23)
- Neutron Science (11)
- Nuclear Energy (12)
- Partnerships (3)
- Physics (13)
- Polymers (5)
- Quantum Computing (1)
- Quantum Science (1)
- Security (5)
- Simulation (1)
- Space Exploration (1)
- Sustainable Energy (3)
- Transformational Challenge Reactor (2)
- Transportation (4)
Media Contacts
Tristen Mullins enjoys the hidden side of computers. As a signals processing engineer for ORNL, she tries to uncover information hidden in components used on the nation’s power grid — information that may be susceptible to cyberattacks.
Andrew Ullman, Distinguished Staff Fellow at Oak Ridge National Laboratory, is using chemistry to devise a better battery
The Autonomous Systems group at ORNL is in high demand as it incorporates remote sensing into projects needing a bird’s-eye perspective.
Having lived on three continents spanning the world’s four hemispheres, Philipe Ambrozio Dias understands the difficulties of moving to a new place.
Researchers at ORNL are tackling a global water challenge with a unique material designed to target not one, but two toxic, heavy metal pollutants for simultaneous removal.
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
ORNL researchers used the nation’s fastest supercomputer to map the molecular vibrations of an important but little-studied uranium compound produced during the nuclear fuel cycle for results that could lead to a cleaner, safer world.
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.