Skip to main content
The electromagnetic isotope separator system operates by vaporizing an element such as ruthenium into the gas phase, converting the molecules into an ion beam, and then channeling the beam through magnets to separate out the different isotopes.

A tiny vial of gray powder produced at the Department of Energy’s Oak Ridge National Laboratory is the backbone of a new experiment to study the intense magnetic fields created in nuclear collisions.

Radiochemical technicians David Denton and Karen Murphy use hot cell manipulators at Oak Ridge National Laboratory during the production of actinium-227.

The Department of Energy’s Oak Ridge National Laboratory is now producing actinium-227 (Ac-227) to meet projected demand for a highly effective cancer drug through a 10-year contract between the U.S. DOE Isotope Program and Bayer.

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 ...

From left, Andrew Lupini and Juan Carlos Idrobo use ORNL’s new monochromated, aberration-corrected scanning transmission electron microscope, a Nion HERMES to take the temperatures of materials at the nanoscale. Image credit: Oak Ridge National Laboratory

A scientific team led by the Department of Energy’s Oak Ridge National Laboratory has found a new way to take the local temperature of a material from an area about a billionth of a meter wide, or approximately 100,000 times thinner than a human hair. This discove...

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
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