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Seeing the difference Ac-225 could make to cancer patients made Raina Setzer want to come to ORNL to directly work with the isotope. Credit: Allison Peacock/ORNL, U.S. Dept. of Energy

Raina Setzer knows the work she does matters. That’s because she’s already seen it from the other side. Setzer, a radiochemical processing technician in Oak Ridge National Laboratory’s Isotope Processing and Manufacturing Division, joined the lab in June 2023.

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Waiting for answers surrounding a healthcare condition can be as stressful as the condition itself. Maria Mahbub, a research collaborator at Oak Ridge National Laboratory, is developing technology that could help providers and patients get answers sooner.

3d prnited lunar rover wheel based on a NASA design

Researchers at the Department of Energy’s Oak Ridge National Laboratory, in collaboration with NASA, are taking additive manufacturing to the final frontier by 3D printing the same kind of wheel as the design used by NASA for its robotic lunar rover, demonstrating the technology for specialized parts needed for space exploration.

The ORNL DAAC gathers, processes, archives and distributes information on key land processes, including the shifting ecological and geomorphological features of the U.S. Atchafalaya and Terrebonne basins gathered by the NASA Delta-X mission shown here. Credit: NASA Delta-X

In 1993 as data managers at ORNL began compiling observations from field experiments for the National Aeronautics and Space Administration, the information fit on compact discs and was mailed to users along with printed manuals.

 A group of ORNL staff standing in a long corridor with flags hanging from the ceiling

For 25 years, scientists at Oak Ridge National Laboratory have used their broad expertise in human health risk assessment, ecology, radiation protection, toxicology and information management to develop widely used tools and data for the U.S. Environmental Protection Agency as part of the agency’s Superfund program.

Attendees of SMC23 pose for their annual group photo in downtown Knoxville, TN.

ORNL hosted its annual Smoky Mountains Computational Sciences and Engineering Conference in person for the first time since the COVID-19 pandemic.

Members of the Analytics and AI Methods at Scale group in the National Center for Computational Sciences at ORNL developed the mixed-precision performance benchmarking tool OpenMxP. From left are group leader Feiyi Wang, technical lead Mike Matheson and research scientist Hao Lu. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

As Frontier, the world’s first exascale supercomputer, was being assembled at the Oak Ridge Leadership Computing Facility in 2021, understanding its performance on mixed-precision calculations remained a difficult prospect.

Plutonium oxide is loaded onto a truck for shipping. Adam Parkison/ORNL, U.S. Dept. of Energy

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

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.  

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

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.