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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.

ORNL fusion scientist Elijah Martin is working with TAE Technologies to demonstrate the feasibility of field-reversed configuration reactors, a possible alternative to the traditional tokamak-based devices. Credit: ORNL.

ORNL manages the Innovation Network for Fusion Energy Program, or INFUSE, with Princeton Plasma Physics Laboratory, to help the private sector find solutions to technical challenges that need to be resolved to make practical fusion energy a reality.

Ultra Safe Nuclear Corporation has licensed a novel method to 3D print highly resistant components for use in nuclear reactor designs. USNC Executive Vice President Kurt Terrani, formerly of ORNL, said the novel method will allow the company to make parts with desired complex shapes more efficiently. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

A novel method to 3D print components for nuclear reactors, developed by the Department of Energy’s Oak Ridge National Laboratory, has been licensed by Ultra Safe Nuclear Corporation.

This protein drives key processes for sulfide use in many microorganisms that produce methane, including Thermosipho melanesiensis. Researchers used supercomputing and deep learning tools to predict its structure, which has eluded experimental methods such as crystallography.  Credit: Ada Sedova/ORNL, U.S. Dept. of Energy

A team of scientists led by the Department of Energy’s Oak Ridge National Laboratory and the Georgia Institute of Technology is using supercomputing and revolutionary deep learning tools to predict the structures and roles of thousands of proteins with unknown functions.