Skip to main content
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...

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 senior research scientist at Oak Ridge National Laboratory, Olufemi “Femi” Omitaomu is leveraging Big Data for urban resilience. Image credit: Oak Ridge National Laboratory, U.S. Dept. of Energy; photographer Jason Richards.

At the Department of Energy’s Oak Ridge National Laboratory, Olufemi “Femi” Omitaomu is leveraging Big Data for urban resilience, helping growing cities support future infrastructure and resource needs. A senior research scientist for ORNL’s Computational Sciences and Engineeri...

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

ORNL researcher Miaofang Chi refines her microscopy techniques toward understanding how and why materials have certain properties.

Material surfaces and interfaces may appear flat and void of texture to the naked eye, but a view from the nanoscale reveals an intricate tapestry of atomic patterns that control the reactions between the material and its environment. Electron microscopy allows researchers to probe...