Updated software improves slicing for large-format 3D printing
Two decades in the making, a new flagship facility for nuclear physics opened on May 2, and scientists from the Department of Energy’s Oak Ridge National Laboratory have a hand in 10 of its first 34 experiments.
How an Alvin M. Weinberg Fellow is increasing security for critical infrastructure components
ORNL researchers used the nation’s fastest supercomputer to map the molecular vibrations of an important but little-studied uranium compound produced during the nuclear fuel cycle for results that could lead to a cleaner, safer world.
A force within the supercomputing community, Jack Dongarra developed software packages that became standard in the industry, allowing high-performance computers to become increasingly more powerful in recent decades.
A study led by researchers at ORNL used the nation’s fastest supercomputer to close in on the answer to a central question of modern physics that could help conduct development of the next generation of energy technologies.
Spanning no less than three disciplines, Marie Kurz’s title — hydrogeochemist — already gives you a sense of the collaborative, interdisciplinary nature of her research at ORNL.
More than 50 current employees and recent retirees from ORNL received Department of Energy Secretary’s Honor Awards from Secretary Jennifer Granholm in January as part of project teams spanning the national laboratory system. The annual awards recognized 21 teams and three individuals for service and contributions to DOE’s mission and to the benefit of the nation.
Three ORNL scientists have been elected fellows of the American Association for the Advancement of Science, or AAAS, the world’s largest general scientific society and publisher of the Science family of journals.
To explore the inner workings of severe acute respiratory syndrome coronavirus 2, or SARS-CoV-2, researchers from ORNL developed a novel technique.
A team of scientists led by the Department of Energy’s Oak Ridge National Laboratory and the Georgia Institute of Technology is using supercomputing and revolutionary deep learning tools to predict the structures and roles of thousands of proteins with unknown functions.