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Media Contacts
![Bob Bolton has spent much of his career studying environmental change in Alaska. He recently moved to East Tennessee to join the ORNL-led NGEE Arctic project as deputy for operations. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2023-09/2023-P10693.jpg?h=8f9cfe54&itok=VZ2Bo1Ia)
Bob Bolton may have moved to a southerly latitude at ORNL, but he is still stewarding scientific exploration in the Arctic, along with a project that helps amplify the voices of Alaskans who reside in a landscape on the front lines of climate change.
![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
![Researchers used the open-source Community Earth System Model to simulate the effects that extreme climatic conditions have on processes like land carbon storage. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2023-09/wildfire_0.jpg?h=175bab9e&itok=sbjoOQiV)
Researchers from Oak Ridge National Laboratory and Northeastern University modeled how extreme conditions in a changing climate affect the land’s ability to absorb atmospheric carbon — a key process for mitigating human-caused emissions. They found that 88% of Earth’s regions could become carbon emitters by the end of the 21st century.
![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.
![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.
![Oak Ridge National Laboratory entrance sign](/themes/custom/ornl/images/default-thumbnail.jpg)
The Department of Energy’s Office of Science has selected three ORNL research teams to receive funding through DOE’s new Biopreparedness Research Virtual Environment initiative.
![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.
![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