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Media Contacts
![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](/sites/default/files/styles/list_page_thumbnail/public/2024-01/jack.jpg?h=0261ddcd&itok=yZ9N5dAh)
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 establishing a digital thread of data, algorithms and workflows to produce a continuously updated model of earth systems.](/sites/default/files/styles/list_page_thumbnail/public/2023-11/MicrosoftTeams-image%20%2823%29_0.png?h=c6980913&itok=cK99Pg3y)
Digital twins are exactly what they sound like: virtual models of physical reality that continuously update to reflect changes in the real world.
![ORNL’s Climate Change Science Institute and Georgia Tech co-hosted a Southeast Decarbonization Workshop in November 2023. Credit: ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2023-11/GaWorkshop_Decarb_Nov2023.jpg?h=71976bb4&itok=2CsciglE)
ORNL's Climate Change Science Institute and the Georgia Institute of Technology hosted a Southeast Decarbonization Workshop in November that drew scientists and representatives from government, industry, non-profits and other organizations to
![ORNL’s organocatalyst deconstructs mixed plastics at different temperatures, which facilitates recovering their individual monomers separately, in reusable form. Credit: Jill Hemman/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2023-10/23-G05683_MixedPlasticRecycling_proof2_0.png?h=27870e4a&itok=jjYga9GD)
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.
![ORNL’s David Sholl is director of the new DOE Energy Earthshot Non-Equilibrium Energy Transfer for Efficient Reactions center to help decarbonize the industrial chemical industry. Credit: Genevieve Martin, ORNL/U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2023-09/2021-P04915.David_.Sholl_.jpg?h=c6980913&itok=qT7ZMJX2)
ORNL has been selected to lead an Energy Earthshot Research Center, or EERC, focused on developing chemical processes that use sustainable methods instead of burning fossil fuels to radically reduce industrial greenhouse gas emissions to stem climate change and limit the crisis of a rapidly warming planet.
![The Department of Energy’s Oak Ridge National Laboratory announced the establishment of its Center for AI Security Research, or CAISER, to address threats already present as governments and industries around the world adopt artificial intelligence and take advantage of the benefits it promises in data processing, operational efficiencies and decision-making. Credit: Rachel Green/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2023-09/CAISER%20image2.png?h=d1cb525d&itok=VcPbKvuS)
The Department of Energy’s Oak Ridge National Laboratory announced the establishment of the Center for AI Security Research, or CAISER, to address threats already present as governments and industries around the world adopt artificial intelligence and take advantage of the benefits it promises in data processing, operational efficiencies and decision-making.
![Connecting wires to the interface of the topological insulator and superconductor enables probing of novel electronic properties. Researchers aim for qubits based on theorized Majorana particles. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2023-09/2023-P04516.jpg?h=c6980913&itok=BoCZtfwR)
Quantum computers process information using quantum bits, or qubits, based on fragile, short-lived quantum mechanical states. To make qubits robust and tailor them for applications, researchers from the Department of Energy’s Oak Ridge National Laboratory sought to create a new material system.
![Chathuddasie Amarasinghe explains her research poster, “Using Microfluidic Mother Machine Devices to Study the Correlated Dynamics of Ribosomes and Chromosomes in Escherichia Coli.” Credit: Carlos Jones/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2023-09/2023-P11614_0.jpg?h=06ac0d8c&itok=kjePlpfo)
Speakers, scientific workshops, speed networking, a student poster showcase and more energized the Annual User Meeting of the Department of Energy’s Center for Nanophase Materials Sciences, or CNMS, Aug. 7-10, near Market Square in downtown Knoxville, Tennessee.
![ZEISS Head of Additive Manufacturing Technology Claus Hermannstaedter, left, and ORNL Interim Associate Laboratory Director for Energy Science and Technology Rick Raines sign a licensing agreement that allows ORNL’s machine-learning algorithm, Simurgh, to be used for rapid evaluations of 3D-printed components with industrial X-ray computed tomography, or CT. Using machine learning in CT scanning is expected to reduce the time and cost of inspections of 3D-printed parts by more than ten times.](/sites/default/files/styles/list_page_thumbnail/public/2023-08/ZEISS%20signing%20handshake_0.jpg?h=c6980913&itok=4J8nVrPc)
A licensing agreement between the Department of Energy’s Oak Ridge National Laboratory and research partner ZEISS will enable industrial X-ray computed tomography, or CT, to perform rapid evaluations of 3D-printed components using ORNL’s machine
![Cody Lloyd stands in front of images of historical nuclear field testing. The green and red dots are the machine learning algorithm recognizing features in the image. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2023-08/2023-P05797_0.jpg?h=4a7d1ed4&itok=S8h_wvJX)
Cody Lloyd became a nuclear engineer because of his interest in the Manhattan Project, the United States’ mission to advance nuclear science to end World War II. As a research associate in nuclear forensics at ORNL, Lloyd now teaches computers to interpret data from imagery of nuclear weapons tests from the 1950s and early 1960s, bringing his childhood fascination into his career