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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.

A traffic-camera view of Shallowford Road, one of the more than 350 intersections in Chattanooga studied by Oak Ridge National Laboratory researchers.

The daily traffic congestion along the streets and interstate lanes of Chattanooga could be headed the way of the horse and buggy with help from ORNL researchers.

An ORNL-led team comprising researchers from multiple DOE national laboratories is using artificial intelligence and computational screening techniques – in combination with experimental validation – to identify and design five promising drug therapy approaches to target the SARS-CoV-2 virus. Credit: Michelle Lehman/ORNL, U.S. Dept. of Energy

An ORNL-led team comprising researchers from multiple DOE national laboratories is using artificial intelligence and computational screening techniques – in combination with experimental validation – to identify and design five promising drug therapy approaches to target the SARS-CoV-2 virus.

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.

Molecular dynamics simulations of the Fs-peptide revealed the presence of at least eight distinct intermediate stages during the process of protein folding. The image depicts a fully folded helix (1), various transitional forms (2–8), and one misfolded state (9). By studying these protein folding pathways, scientists hope to identify underlying factors that affect human health.

Using artificial neural networks designed to emulate the inner workings of the human brain, deep-learning algorithms deftly peruse and analyze large quantities of data. Applying this technique to science problems can help unearth historically elusive solutions.

Laminations such as these are compiled to form the core of modern electric vehicle motors. ORNL has developed a software toolkit to speed the development of new motor designs and to improve the accuracy of their real-world performance.

Oak Ridge National Laboratory scientists have created open source software that scales up analysis of motor designs to run on the fastest computers available, including those accessible to outside users at the Oak Ridge Leadership Computing Facility.