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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.

Using quantum Monte Carlo methods, the researchers simulated bulk VO2. Yellow and turquoise represent changes in electron density between the excited and ground states of a compound composed of oxygen, in red, and vanadium, in blue, which allowed them to evaluate how an oxygen vacancy, in white, can alter the compound’s properties. Credit: Panchapakesan Ganesh/ORNL, U.S. Dept. of Energy

Neuromorphic devices — which emulate the decision-making processes of the human brain — show great promise for solving pressing scientific problems, but building physical systems to realize this potential presents researchers with a significant

A material’s spins, depicted as red spheres, are probed by scattered neutrons. Applying an entanglement witness, such as the QFI calculation pictured, causes the neutrons to form a kind of quantum gauge. This gauge allows the researchers to distinguish between classical and quantum spin fluctuations. Credit: Nathan Armistead/ORNL, U.S. Dept. of Energy

A team led by the U.S. Department of Energy’s Oak Ridge National Laboratory demonstrated the viability of a “quantum entanglement witness” capable of proving the presence of entanglement between magnetic particles, or spins, in a quantum material.

ORNL researchers developed a novel process for manufacturing extreme heat resistant carbon-carbon composites at a faster rate and produced fins or strakes made of the materials for testing on a U.S. Navy rocket launching with NASA. Credit: ORNL, Sandia/U.S. Dept. of Energy

Oak Ridge National Laboratory researchers have developed a novel process to manufacture extreme heat resistant carbon-carbon composites. The performance of these materials will be tested in a U.S. Navy rocket that NASA will launch this fall.

A 3D printed thermal protection shield, produced by ORNL researchers for NASA, is part of a cargo spacecraft bound for the International Space Station. The shield was printed at the Department of Energy’s Manufacturing Demonstration Facility at ORNL. Credit: ORNL, U.S. Dept. of Energy

A research team at Oak Ridge National Laboratory have 3D printed a thermal protection shield, or TPS, for a capsule that will launch with the Cygnus cargo spacecraft as part of the supply mission to the International Space Station.

ORNL’s Sergei Kalinin and Rama Vasudevan (foreground) use scanning probe microscopy to study bulk ferroelectricity and surface electrochemistry -- and generate a lot of data. Credit: Jason Richards/ORNL, U.S. Dept. of Energy

At the Department of Energy’s Oak Ridge National Laboratory, scientists use artificial intelligence, or AI, to accelerate the discovery and development of materials for energy and information technologies.

ORNL researchers combined additive manufacturing with conventional compression molding to produce high-performance thermoplastic composites, demonstrating the potential for the use of large-scale multimaterial preforms to create molded composites. Credit: ORNL/U.S. Dept. of Energy

Oak Ridge National Laboratory researchers combined additive manufacturing with conventional compression molding to produce high-performance thermoplastic composites reinforced with short carbon fibers.

ORNL researchers used gas metal arc welding additive technology to print the die for a B-pillar or vertical roof support structure for a sport utility vehicle, demonstrating a 20% improvement in the cooling rate. Credit: ORNL/U.S. Dept. of Energy

A team of Oak Ridge National Laboratory researchers demonstrated that an additively manufactured hot stamping die – a tool used to create car body components – cooled faster than those produced by conventional manufacturing methods.

ORNL researchers are developing a method to print low-cost, high-fidelity, customizable sensors for monitoring power grid equipment. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

A method developed at Oak Ridge National Laboratory to print high-fidelity, passive sensors for energy applications can reduce the cost of monitoring critical power grid assets.

Verónica Melesse Vergara speaks with third and fourth graders at East Side Intermediate School in Brownsville. Credit: ORNL, U.S. Dept. of Energy

Twenty-seven ORNL researchers Zoomed into 11 middle schools across Tennessee during the annual Engineers Week in February. East Tennessee schools throughout Oak Ridge and Roane, Sevier, Blount and Loudon counties participated, with three West Tennessee schools joining in.