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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.

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ITER, the international fusion research facility now under construction in St. Paul-lez-Durance, France, has been called a puzzle of a million pieces. US ITER staff at Oak Ridge National Laboratory are using an affordable tool—desktop three-dimensional printing, also known as additive printing—to help them design and configure components more efficiently and affordably.