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Map of ARM Data Center locations

From the Arctic to the Amazon, understanding the atmosphere is key to understanding our climate and other Earth systems. The ARM Data Center collects and manages global observational and experimental data amassed by the Department of Energy Office of Science’s Atmospheric Radiation Measurement user facility. For the past 30 years, it has been making this data accessible to scientists around the world who study and model the Earth’s climate.

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

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.

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.  

Yaoping Wang. Credit: Yaoping Wang

Yaoping Wang, postdoctoral research associate at ORNL, has received an Early Career Award from the Asian Ecology Section, or AES, of the Ecological Society of America.

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.

A rendering of the CFM RISE program’s open fan architecture. (bottom) A GE visualization of turbulent flow in the tip region of an open fan blade using the Frontier supercomputer at ORNL. Credit: CFM, GE Research (CFM is a 50­–50 joint company between GE and Safran Aircraft Engines)

Outside the high-performance computing, or HPC, community, exascale may seem more like fodder for science fiction than a powerful tool for scientific research. Yet, when seen through the lens of real-world applications, exascale computing goes from ethereal concept to tangible reality with exceptional benefits.

Madhavi Martin portrait image

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.

Diagram of faults affecting a conventional power system.

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.

From left, Gladisol Smith Vega prepares to collect field data on the Oak Ridge Reservation with mentor Scott Brooks. Credit: Carlos Jones/ORNL. U.S. Dept. of Energy

Nearly 100 interns were introduced to Oak Ridge National Laboratory’s biological and environmental research over the summer of 2023 as mentors and students were eager to share knowledge and skills to address the nation’s energy and environmental challenges.

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

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