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Electro-Active Tech license signing ceremony

Electro-Active Technologies, Inc., of Knoxville, Tenn., has exclusively licensed two biorefinery technologies invented and patented by the startup’s co-founders while working at the Department of Energy’s Oak Ridge National Laboratory. The technologies work as a system that converts organic waste into renewable hydrogen gas for use as a biofuel.

early prototype of the optical array developed by Oak Ridge National Laboratory.

IDEMIA Identity & Security USA has licensed an advanced optical array developed at Oak Ridge National Laboratory. The portable technology can be used to help identify individuals in challenging outdoor conditions.

Laccaria bicolor is fruiting aboveground and colonizing the Populus deltoides plant root system belowground in a greenhouse setting.

A team of scientists led by Oak Ridge National Laboratory have discovered the specific gene that controls an important symbiotic relationship between plants and soil fungi, and successfully facilitated the symbiosis in a plant that

(From left) ORNL Associate Laboratory Director for Computing and Computational Sciences Jeff Nichols; ORNL Health Data Sciences Institute Director Gina Tourassi; DOE Deputy Under Secretary for Science Thomas Cubbage; ORNL Task Lead for Biostatistics Blair Christian; and ORNL Research Scientist Ioana Danciu were invited to the White House to showcase an ORNL-developed digital tool aimed at better matching cancer patients with clinical trials.

OAK RIDGE, Tenn., March 4, 2019—A team of researchers from the Department of Energy’s Oak Ridge National Laboratory Health Data Sciences Institute have harnessed the power of artificial intelligence to better match cancer patients with clinical trials.

To develop complex materials with superior properties, Vera Bocharova uses diverse methods including broadband dielectric spectroscopy. Credit: Oak Ridge National Laboratory, U.S. Dept. of Energy; photographer Jason Richards

Vera Bocharova at the Department of Energy’s Oak Ridge National Laboratory investigates the structure and dynamics of soft materials—polymer nanocomposites, polymer electrolytes and biological macromolecules—to advance materials and technologies for energy, medicine and other applications.

Default image of ORNL entry sign

If you ask the staff and researchers at the Department of Energy’s Oak Ridge National Laboratory how they were first referred to the lab, you will get an extremely varied list of responses. Some may have come here as student interns, some grew up in the area and knew the lab by ...

Lauren Garrison

The materials inside a fusion reactor must withstand one of the most extreme environments in science, with temperatures in the thousands of degrees Celsius and a constant bombardment of neutron radiation and deuterium and tritium, isotopes of hydrogen, from the volatile plasma at th...

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...

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