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Nuclear physicists at the Department of Energy’s Oak Ridge National Laboratory recently used Frontier, the world’s most powerful supercomputer, to calculate the magnetic properties of calcium-48’s atomic nucleus.
ORNL hosted its annual Smoky Mountains Computational Sciences and Engineering Conference in person for the first time since the COVID-19 pandemic.
The Department of Energy’s Oak Ridge National Laboratory hosted its Smoky Mountains Computational Science and Engineering Conference for the first time in person since the COVID pandemic broke in 2020. The conference, which celebrated its 20th consecutive year, took place at the Crowne Plaza Hotel in downtown Knoxville, Tenn., in late August.
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.
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.
JungHyun Bae is a nuclear scientist studying applications of particles that have some beneficial properties: They are everywhere, they are unlimited, they are safe.
A study led by researchers at ORNL could uncover new ways to produce more powerful, longer-lasting batteries and memory devices.
A trio of new and improved cosmological simulation codes was unveiled in a series of presentations at the annual April Meeting of the American Physical Society in Minneapolis.
To optimize biomaterials for reliable, cost-effective paper production, building construction, and biofuel development, researchers often study the structure of plant cells using techniques such as freezing plant samples or placing them in a vacuum.
A team of researchers has developed a novel, machine learning–based technique to explore and identify relationships among medical concepts using electronic health record data across multiple healthcare providers.