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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
![Steven Hamilton, an R&D scientist in the HPC Methods for Nuclear Applications group at ORNL, leads the ExaSMR project. ExaSMR was developed to run on the Oak Ridge Leadership Computing Facility’s exascale-class supercomputer, Frontier. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2023-09/2023-P00165_1.jpg?h=c6980913&itok=YE6_qVLk)
The Exascale Small Modular Reactor effort, or ExaSMR, is a software stack developed over seven years under the Department of Energy’s Exascale Computing Project to produce the highest-resolution simulations of nuclear reactor systems to date. Now, ExaSMR has been nominated for a 2023 Gordon Bell Prize by the Association for Computing Machinery and is one of six finalists for the annual award, which honors outstanding achievements in high-performance computing from a variety of scientific domains.
![Cadet Elyse Wages, Mike Shaffer and Amanda Sandifer pose with a collected sample of air. Credit: Liz Neunsinger/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2023-09/20230627_140821.png?h=b6fd9b7a&itok=ESPeHBk1)
Cadet Elyse Wages, a rising junior at the United States Air Force Academy, visited ORNL with one goal in mind: collect air.
![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.
![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
![Rose Montgomery](/sites/default/files/styles/list_page_thumbnail/public/2023-08/Rose%20Montgomery%202022.jpg?h=a3aaed75&itok=W7lx1mwq)
Rose Montgomery, a distinguished researcher and leader of the Used Fuel and Nuclear Material Disposition group at ORNL, has been selected to participate in the U.S. WIN Nuclear Executives of Tomorrow, or NEXT, class of 2023 to 2024.
![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
![Jonathan Harter, a technical professional in ORNL’s Engineering Science and Technology Directorate, uses a robot and other automated methods to disassemble electric vehicle batteries for recycling or reuse in the electric grid. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2023-08/2021-P06328_0.jpg?h=036a71b7&itok=elZeutaQ)
After being stabilized in an ambulance as he struggled to breathe, Jonathan Harter hit a low point. It was 2020, he was very sick with COVID-19, and his job as a lab technician at ORNL was ending along with his research funding.