Filter News
Area of Research
News Topics
- (-) Biomedical (2)
- (-) Computer Science (7)
- (-) Environment (4)
- (-) Neutron Science (3)
- 3-D Printing/Advanced Manufacturing (2)
- Artificial Intelligence (4)
- Big Data (2)
- Bioenergy (3)
- Biology (5)
- Biotechnology (1)
- Buildings (1)
- Climate Change (6)
- Coronavirus (3)
- Cybersecurity (2)
- Decarbonization (1)
- Exascale Computing (1)
- Frontier (3)
- Grid (2)
- High-Performance Computing (5)
- Machine Learning (4)
- Materials (5)
- Materials Science (4)
- Microscopy (1)
- Nanotechnology (2)
- National Security (8)
- Quantum Computing (5)
- Quantum Science (3)
- Security (2)
- Simulation (3)
- Summit (4)
- Sustainable Energy (1)
Media Contacts
Scientists at ORNL have developed 3D-printed collimator techniques that can be used to custom design collimators that better filter out noise during different types of neutron scattering experiments
Jack Orebaugh, a forensic anthropology major at the University of Tennessee, Knoxville, has a big heart for families with missing loved ones. When someone disappears in an area of dense vegetation, search and recovery efforts can be difficult, especially when a missing person’s last location is unknown. Recognizing the agony of not knowing what happened to a family or friend, Orebaugh decided to use his internship at the Department of Energy’s Oak Ridge National Laboratory to find better ways to search for lost and deceased people using cameras and drones.
ORNL researchers are deploying their broad expertise in climate data and modeling to create science-based mitigation strategies for cities stressed by climate change as part of two U.S. Department of Energy Urban Integrated Field Laboratory projects.
Cameras see the world differently than humans. Resolution, equipment, lighting, distance and atmospheric conditions can impact how a person interprets objects on a photo.
When the COVID-19 pandemic stunned the world in 2020, researchers at ORNL wondered how they could extend their support and help
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.
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.
Tackling the climate crisis and achieving an equitable clean energy future are among the biggest challenges of our time.
A study by researchers at the ORNL takes a fresh look at what could become the first step toward a new generation of solar batteries.