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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.

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For the past six years, some 140 scientists from five institutions have traveled to the Arctic Circle and beyond to gather field data as part of the Department of Energy-sponsored NGEE Arctic project. This article gives insight into how scientists gather the measurements that inform t...

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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...

ORNL researchers Todd Toops, Charles Finney, and Melanie DeBusk (left to right) hold an example of a particulate filter used to collect harmful emissions in vehicles.

Researchers are looking to neutrons for new ways to save fuel during the operation of filters that clean the soot, or carbon and ash-based particulate matter, emitted by vehicles. A team of researchers from the Energy and Transportation Science Division at the Department of En...

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

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Researchers used neutrons to probe a running engine at ORNL’s Spallation Neutron Source

ORNL’s Xiahan Sang unambiguously resolved the atomic structure of MXene, a 2D material promising for energy storage, catalysis and electronic conductivity. Image credit: Oak Ridge National Laboratory, U.S. Dept. of Energy; photographer Carlos Jones

Researchers have long sought electrically conductive materials for economical energy-storage devices. Two-dimensional (2D) ceramics called MXenes are contenders. Unlike most 2D ceramics, MXenes have inherently good conductivity because they are molecular sheets made from the carbides ...