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The sensors measure parameters like temperature, chemicals and electric grid elements for industrial and electrical applications. Credit: Carlos Jones/Oak Ridge National Laboratory, U.S. Dept. of Energy

Brixon, Inc., has exclusively licensed a multiparameter sensor technology from the Department of Energy’s Oak Ridge National Laboratory. The integrated platform uses various sensors that measure physical and environmental parameters and respond to standard security applications.

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.

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...

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 ...

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...

Default image of ORNL entry sign

James Peery, who led critical national security programs at Sandia National Laboratories and held multiple leadership positions at Los Alamos National Laboratory before arriving at the Department of Energy’s Oak Ridge National Laboratory last year, has been named a...

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...

Oak Ridge National Laboratory researcher Halil Tekinalp combines silanes and polylactic acid to create supertough renewable plastic.

A novel method developed at Oak Ridge National Laboratory creates supertough renewable plastic with improved manufacturability. Working with polylactic acid, a biobased plastic often used in packaging, textiles, biomedical implants and 3D printing, the research team added tiny amo...

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