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Media Contacts
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.
Digital twins are exactly what they sound like: virtual models of physical reality that continuously update to reflect changes in the real world.
In fiscal year 2023 — Oct. 1–Sept. 30, 2023 — Oak Ridge National Laboratory was awarded more than $8 million in technology maturation funding through the Department of Energy’s Technology Commercialization Fund, or TCF.
Little of the mixed consumer plastics thrown away or placed in recycle bins actually ends up being recycled. Nearly 90% is buried in landfills or incinerated at commercial facilities that generate greenhouse gases and airborne toxins. Neither outcome is ideal for the environment.
The Autonomous Systems group at ORNL is in high demand as it incorporates remote sensing into projects needing a bird’s-eye perspective.
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.
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.
It’s a simple premise: To truly improve the health, safety, and security of human beings, you must first understand where those individuals are.
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.