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Media Contacts
![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.
![ORNL Vehicle Power Electronics Research group R&D Associate Subho Mukherjee has been elevated to the senior member grade IEEE. Credit: ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2023-08/2019-P01533.jpg?h=4d0d7e9c&itok=FIWOFo8C)
Subho Mukherjee, an R&D associate in the Vehicle Power Electronics Research group at the Department of Energy’s Oak Ridge National Laboratory, has been elevated to the grade of senior member of the Institute of Electrical and Electronics Engineers.
![A new nanoscience study led by an ORNL quantum researcher takes a big-picture look at how scientists study materials at the smallest scales. Credit: Getty Images](/sites/default/files/styles/list_page_thumbnail/public/2023-08/QuantumTunnel_0.png?h=ae114f5c&itok=B4Rxkkvs)
A new nanoscience study led by a researcher at ORNL takes a big-picture look at how scientists study materials at the smallest scales.
![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
![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.
![Group of attendees at the Quantum Computing User Forum](/sites/default/files/styles/list_page_thumbnail/public/2023-08/Quantum%20Computing%20User%20Forum%20Group%20Photo%202023.jpg?h=8f9cfe54&itok=AWxcT-bE)
Hosted by the Quantum Computing Institute and the Oak Ridge Leadership Computing Facility, the fourth annual event brought together over 100 attendees to discuss the latest developments in quantum computing and to learn about results from projects supported by the OLCF’s Quantum Computing User Program.
![Yarom Polsky studio portrait](/sites/default/files/styles/list_page_thumbnail/public/2023-07/Yarom%20Polsky_0.jpg?h=0e6c7b49&itok=9H4BJ5Wm)
Yarom Polsky, director of the Manufacturing Science Division, or MSD, at the Department of Energy’s Oak Ridge National Laboratory, has been elected a Fellow of the American Society of Mechanical Engineers, or ASME.
![Clouds of gray smoke in the lower left are funneled northward from wildfires in Western Canada, reaching the edge of the sea ice covering the Arctic Ocean. A second path of thick smoke is visible at the top center of the image, emanating from wildfires in the boreal areas of Russia’s Far East, in this image captured on July 13, 2023. Credit: NASA MODIS](/sites/default/files/styles/list_page_thumbnail/public/2023-07/NASA%20Arctic%20Circle%20wildfire%20smoke_image07182023_1km_1.jpg?h=dbdc3f84&itok=oHQVs6Bn)
Wildfires have shaped the environment for millennia, but they are increasing in frequency, range and intensity in response to a hotter climate. The phenomenon is being incorporated into high-resolution simulations of the Earth’s climate by scientists at the Department of Energy’s Oak Ridge National Laboratory, with a mission to better understand and predict environmental change.
![ORNL researchers used geotagged photos to map crude oil train routes in the U.S. The mapping gives transportation planners insight into understanding potential impacts along the routes. Credit: ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2023-07/trainMap%5B69%5D.png?h=804c67fb&itok=LM393FRy)
Oak Ridge National Laboratory researchers used images from a photo-sharing website to identify crude oil train routes across the nation to provide data that could help transportation planners better understand regional impacts.
![This map illustrates the natural climate variability that affects the cold-season climate of the Central Southwest Asian region. Credit: Moetasim Ashfaq/ORNL](/sites/default/files/styles/list_page_thumbnail/public/2023-07/moet_pr_v2.png?h=0bda418b&itok=V62vm4cC)
As extreme weather devastates communities worldwide, scientists are using modeling and simulation to understand how climate change impacts the frequency and intensity of these events. Although long-term climate projections and models are important, they are less helpful for short-term prediction of extreme weather that may rapidly displace thousands of people or require emergency aid.