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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.

ORNL’s new salt purification lab offers tools to make and purify the salt and perform corrosion testing, which are essential steps in qualifying molten salt reactor technologies for commercial use. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Oak Ridge National Laboratory has developed a salt purification lab to study the viability of using liquid salt that contains lithium fluoride and beryllium fluoride, known as FLiBe, to cool molten salt reactors, or MSRs. Multiple American companies developing advanced reactor technol...

Graphical representation of a deuteron, the bound state of a proton (red) and a neutron (blue). Credit: Andy Sproles/Oak Ridge National Laboratory, U.S. Dept. of Energy.

Scientists at the Department of Energy’s Oak Ridge National Laboratory are the first to successfully simulate an atomic nucleus using a quantum computer. The results, published in Physical Review Letters, demonstrate the ability of quantum systems to compute nuclear ph...

Oak Ridge National Laboratory researcher Arnab Banerjee has charted several accomplishments in his neutron studies of quantum phenomena.

Raman. Heisenberg. Fermi. Wollan. From Kolkata to Göttingen, Chicago to Oak Ridge. Arnab Banerjee has literally walked in the footsteps of some of the greatest pioneers in physics history—and he’s forging his own trail along the way. Banerjee is a staff scientist working in the Neu...

Kevin Robb, a staff scientist at the Department of Energy’s Oak Ridge National Laboratory, is taking what he learned from developing the Liquid Salt Test Loop—a key tool in deploying molten salt technology applications

Thanks in large part to developing and operating a facility for testing molten salt reactor (MSR) technologies, nuclear experts at the Energy Department’s Oak Ridge National Laboratory (ORNL) are now tackling the next generation of another type of clean energy—concentrating ...

Illustration of satellite in front of glowing orange celestial body

A shield assembly that protects an instrument measuring ion and electron fluxes for a NASA mission to touch the Sun was tested in extreme experimental environments at Oak Ridge National Laboratory—and passed with flying colors. Components aboard Parker Solar Probe, which will endure th...

Julie Smith

It may take a village to raise a child, according to the old proverb, but it takes an entire team of highly trained scientists and engineers to install and operate a state-of-the-art, exceptionally complex ion microprobe. Just ask Julie Smith, a nuclear security scientist at the Depa...

Composites scientist and engineer Vlastimil Kunc with the latest large-scale 3Dprinter at the MDF.

Vlastimil Kunc grew up in a family of scientists where his natural curiosity was encouraged—an experience that continues to drive his research today in polymer composite additive manufacturing at Oak Ridge National Laboratory. “I’ve been interested in the science of composites si...

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