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Media Contacts
![Attendees of SMC23 pose for their annual group photo in downtown Knoxville, TN.](/sites/default/files/styles/list_page_thumbnail/public/2023-09/2023-P12048.jpg?h=b18108c1&itok=nPUCBfNi)
ORNL hosted its annual Smoky Mountains Computational Sciences and Engineering Conference in person for the first time since the COVID-19 pandemic.
![Plutonium oxide is loaded onto a truck for shipping. Adam Parkison/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2023-09/PXL_20230620_120836896_0.jpg?h=2848f5af&itok=Nh31DLuy)
In June, ORNL hit a milestone not seen in more than three decades: producing a production-quality amount of plutonium-238
![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.
![The DEMAND single crystal diffractometer at the High Flux Isotope Reactor, or HFIR, is the latest neutron instrument at the Department of Energy’s Oak Ridge National Laboratory to be equipped with machine learning-assisted software, called ReTIA. Credit: Jeremy Rumsey/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2023-09/DEMAND%20thumbnail%20image_0.jpg?h=c673cd1c&itok=5YAVwaP6)
Neutron experiments can take days to complete, requiring researchers to work long shifts to monitor progress and make necessary adjustments. But thanks to advances in artificial intelligence and machine learning, experiments can now be done remotely and in half the time.
![Madhavi Martin portrait image](/sites/default/files/styles/list_page_thumbnail/public/2023-08/2023-P09857_0.jpg?h=036a71b7&itok=4QOEKn5k)
Madhavi Martin brings a physicist’s tools and perspective to biological and environmental research at the Department of Energy’s Oak Ridge National Laboratory, supporting advances in bioenergy, soil carbon storage and environmental monitoring, and even helping solve a murder mystery.
![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
![The OpeN-AM experimental platform, installed at the VULCAN instrument, features a robotic arm that prints layers of molten metal to create complex shapes. Credit: Jill Hemman/ORNL, U.S Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2023-08/Picture2.jpg?h=3c75dc16&itok=_NLdJ0Po)
Technologies developed by researchers at ORNL have received six 2023 R&D 100 Awards.
![Diagram of faults affecting a conventional power system.](/sites/default/files/styles/list_page_thumbnail/public/2023-08/23-G04595-line-faults-pcg_0.jpg?h=d48ba2e6&itok=Gc2T0Rmr)
Researchers at the Department of Energy’s Oak Ridge National Laboratory are leading the way in understanding the effects of electrical faults in the modern U.S. power grid.
![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
![Ken Engle portrait](/sites/default/files/styles/list_page_thumbnail/public/2023-08/engle%20profile.jpg?h=72898f5b&itok=ZIKd9Gn1)
It was reading about current nuclear discoveries in textbooks that first made Ken Engle want to work at a national lab. It was seeing the real-world impact of the isotopes produced at ORNL