ORNL’s Luiz Leal of the Department of Energy’s Oak Ridge National Laboratory is the recipient of the 2023 Seaborg Medal from the American Nuclear Society.
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.
A new nanoscience study led by a researcher at ORNL takes a big-picture look at how scientists study materials at the smallest scales.
JungHyun Bae is a nuclear scientist studying applications of particles that have some beneficial properties: They are everywhere, they are unlimited, they are safe.
Like most scientists, Chengping Chai is not content with the surface of things: He wants to probe beyond to learn what’s really going on. But in his case, he is literally building a map of the world beneath, using seismic and acoustic data that reveal when and where the earth moves.
For the third year in a row, the Quantum Science Center held its signature workforce development event: a comprehensive summer school for students and early-career scientists designed to facilitate conversations and hands-on activities related to
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.
A study led by Oak Ridge National Laboratory researchers identifies a new potential application in quantum computing that could be part of the next computational revolution.
Researchers at ORNL have developed a machine-learning inspired software package that provides end-to-end image analysis of electron and scanning probe microscopy images.