Skip to main content
From left, ORNL’s Rick Lowden, Chris Bryan and Jim Kiggans were troubled that target discs of a material needed to produce Mo-99 using an accelerator could deform after irradiation and get stuck in their holder.

“Made in the USA.” That can now be said of the radioactive isotope molybdenum-99 (Mo-99), last made in the United States in the late 1980s. Its short-lived decay product, technetium-99m (Tc-99m), is the most widely used radioisotope in medical diagnostic imaging. Tc-99m is best known ...

Shaheen Dewji, radiological scientist in the Center for Radiation Protection Knowledge within the Environmental Sciences Division at ORNL.

Having begun her career at the lab in the nuclear nonproliferation and radiation safeguards area, Shaheen Dewji is leveraging her expertise to help expand the work of the Center for Radiation Protection Knowledge (CRPK)—a unique organization led by Oak Ridge National Laboratory that ...

Germina Ilas (left) and Ian Gauld review spent fuel data entries in the SFCOMPO 2.0 database.
Oak Ridge National Laboratory provided significant contributions and coordination in the development of the Nuclear Energy Agency’s (NEA’s) recently released Spent Fuel Isotopic Composition (SFCOMPO) 2.0—the world’s largest open database for spent
A conceptual illustration of proton-proton fusion in which two protons fuse to form a deuteron. Image courtesy of William Detmold.

Nuclear physicists are using the nation’s most powerful supercomputer, Titan, at the Oak Ridge Leadership Computing Facility to study particle interactions important to energy production in the Sun and stars and to propel the search for new physics discoveries Direct calculatio...

ORNL’s Steven Young (left) and Travis Johnston used Titan to prove the design and training of deep learning networks could be greatly accelerated with a capable computing system.

A team of researchers from the Department of Energy’s Oak Ridge National Laboratory has married artificial intelligence and high-performance computing to achieve a peak speed of 20 petaflops in the generation and training of deep learning networks on the