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ORNL’s Joseph Lukens runs experiments in an optics lab. Credit: Jason Richards/ORNL, U.S. Dept. of Energy

Scientists’ increasing mastery of quantum mechanics is heralding a new age of innovation. Technologies that harness the power of nature’s most minute scale show enormous potential across the scientific spectrum

High voltage power lines carry electricity generated by the Tennessee Valley Authority to ORNL. Credit: Dobie Gillispie/ORNL, U.S. Dept. of Energy

ORNL and the Tennessee Valley Authority, or TVA, are joining forces to advance decarbonization technologies from discovery through deployment through a new memorandum of understanding, or MOU.

An international team of researchers used Summit to model spin, charge and pair-density waves in cuprates, a type of copper alloy, to explore the materials’ superconducting properties. The results revealed new insights into the relationships between these dynamics as superconductivity develops. Credit: Jason Smith/ORNL

A study led by researchers at ORNL used the nation’s fastest supercomputer to close in on the answer to a central question of modern physics that could help conduct development of the next generation of energy technologies.

An artist's rendering of the Ultium Cells battery cell production facility to be built in Spring Hill, Tennessee, which will employ 1,300 people. Recognizing the unique expertise of their organizations, ORNL, TVA, and the Tennessee Department of Economic and Community Development have been working together for several years to bring startups developing battery technologies for EVs and established automotive firms to Tennessee. Credit: Ultium Cells

ORNL, TVA and TNECD were recognized by the Federal Laboratory Consortium for their impactful partnership that resulted in a record $2.3 billion investment by Ultium Cells, a General Motors and LG Energy Solution joint venture, to build a battery cell manufacturing plant in Spring Hill, Tennessee.

Mars Rover 2020

More than 50 current employees and recent retirees from ORNL received Department of Energy Secretary’s Honor Awards from Secretary Jennifer Granholm in January as part of project teams spanning the national laboratory system. The annual awards recognized 21 teams and three individuals for service and contributions to DOE’s mission and to the benefit of the nation.

Miaofang Chi, a scientist in the Center for Nanophase Materials Sciences, received the 2021 Director’s Award for Outstanding Individual Accomplishment in Science and Technology. Credit: ORNL, U.S. Dept. of Energy

A world-leading researcher in solid electrolytes and sophisticated electron microscopy methods received Oak Ridge National Laboratory’s top science honor today for her work in developing new materials for batteries. The announcement was made during a livestreamed Director’s Awards event hosted by ORNL Director Thomas Zacharia.

Oak Ridge National Laboratory entrance sign

A team from ORNL, Stanford University and Purdue University developed and demonstrated a novel, fully functional quantum local area network, or QLAN, to enable real-time adjustments to information shared with geographically isolated systems at ORNL

ORNL researchers are examining ways to increase the amount of carbon sequestered in soils by crops such as switchgrass. Credit: Jason Richards/ORNL, U.S. Dept. of Energy

Nearly a billion acres of land in the United States is dedicated to agriculture, producing more than a trillion dollars of food products to feed the country and the world. Those same agricultural processes, however, also produced an estimated 700 million metric tons of carbon dioxide equivalent in 2018, according to the U.S. Department of Agriculture.

Oak Ridge National Laboratory’s MENNDL AI software system can design thousands of neural networks in a matter of hours. One example uses a driving simulator to evaluate a network’s ability to perceive objects under various lighting conditions. Credit: ORNL, U.S. Dept. of Energy

The Department of Energy’s Oak Ridge National Laboratory has licensed its award-winning artificial intelligence software system, the Multinode Evolutionary Neural Networks for Deep Learning, to General Motors for use in vehicle technology and design.

 The researchers embedded a programmable model into a D-Wave quantum computer chip. Credit: D-Wave

A multi-institutional team became the first to generate accurate results from materials science simulations on a quantum computer that can be verified with neutron scattering experiments and other practical techniques.