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ORNL intern Jack Orebaugh holds the drone used in his research to help locate human remains. Credit: Lena Shoemaker/ORNL, U.S. Dept. of Energy

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. 

A LiDAR survey of a local stream collected from one of ORNL’s drones. Credit: Andrew Duncan/ORNL, U.S. Dept. of Energy

The Autonomous Systems group at ORNL is in high demand as it incorporates remote sensing into projects needing a bird’s-eye perspective.

Data from different sources are joined on platforms created by ORNL researchers to offer better information for decision makers. Credit: ORNL/Nathan Armistead

When the COVID-19 pandemic stunned the world in 2020, researchers at ORNL wondered how they could extend their support and help

ORNL scientists created a geodemographic cluster for the Atlanta metro area that identifies risk factors related to climate impacts. Credit: ORNL/U.S. Dept. of Energy

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.

The ORNL researchers’ findings may enable better detection of uranium tetrafluoride hydrate, a little-studied byproduct of the nuclear fuel cycle, and better understanding of how environmental conditions influence the chemical behavior of fuel cycle materials. Credit: Kevin Pastoor/Colorado School of Mines

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.

ORNL, VA and Harvard researchers developed a sparse matrix full of anonymized information on what is thought to be the largest cohort of healthcare data used for this type of research in the U.S. The matrix can be probed with different methods, such as KESER, to gain new insights into human health. Credit: Nathan Armistead/ORNL, U.S. Dept. of Energy

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.

The CrossVis application includes a parallel coordinates plot (left), a tiled image view (right) and other interactive data views. Credit: Chad Steed/Oak Ridge National Laboratory, U.S. Dept. of Energy

From materials science and earth system modeling to quantum information science and cybersecurity, experts in many fields run simulations and conduct experiments to collect the abundance of data necessary for scientific progress.

Recent research involving Oak Ridge National Laboratory’s Spallation Neutron Source demonstrates crystal-like heat conduction in a solid-liquid hybrid, AgCrSe2.

Research by an international team led by Duke University and the Department of Energy’s Oak Ridge National Laboratory scientists could speed the way to safer rechargeable batteries for consumer electronics such as laptops and cellphones.

GIS – LandScan goes public

Oak Ridge National Laboratory’s high-resolution population distribution database, LandScan USA, became permanently available to researchers in time to aid the response to the novel coronavirus pandemic.

A new computational approach by ORNL can more quickly scan large-scale satellite images, such as these of Puerto Rico, for more accurate mapping of complex infrastructure like buildings. Credit: Maxar Technologies and Dalton Lunga/Oak Ridge National Laboratory, U.S. Dept. of Energy

A novel approach developed by scientists at ORNL can scan massive datasets of large-scale satellite images to more accurately map infrastructure – such as buildings and roads – in hours versus days.