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Media Contacts
Rose Montgomery, a distinguished researcher and leader of the Used Fuel and Nuclear Material Disposition group at ORNL, has been selected to participate in the U.S. WIN Nuclear Executives of Tomorrow, or NEXT, class of 2023 to 2024.
Leigh R. Martin, a senior scientist and leader of the Fuel Cycle Chemical Technology group at ORNL, has been named a Fellow of the American Chemical Society for 2023.
A research team from the Department of Energy’s Oak Ridge and Lawrence Livermore national laboratories won the first Best Open-Source Contribution Award for its paper at the 37th IEEE International Parallel and Distributed Processing Symposium.
The Oppenheimer Science and Energy Leadership Program has selected Oak Ridge National Laboratory’s Jens Dilling and Christian Petrie as fellows for its 2023 cohort.
Three researchers at ORNL have been named ORNL Corporate Fellows in recognition of significant career accomplishments and continued leadership in their scientific fields.
Oak Ridge National Laboratory scientists recently demonstrated a low-temperature, safe route to purifying molten chloride salts that minimizes their ability to corrode metals. This method could make the salts useful for storing energy generated from the sun’s heat.
Steven Arndt, distinguished R&D staff member in the Nuclear Energy and Fuel Cycle Division at ORNL, began a one-year term on June 16 as the 68th President of the American Nuclear Society.
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.
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.
Oak Ridge National Laboratory, University of Tennessee and University of Central Florida researchers released a new high-performance computing code designed to more efficiently examine power systems and identify electrical grid disruptions, such as