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Initially, Kevin Gaddis’s adapted HPIC will be used only for the fourth of six separations in  actinium-225 processing, but he hopes it will later be used for other separations — and other isotopes. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

An Oak Ridge National Laboratory researcher has invented a version of an isotope-separating device that can withstand extreme environments, including radiation and chemical solvents.

Researchers built optical tools called zero-mode waveguides, illustrated here, used to observe proteins that are implicated in human heart function. Credit: David S. White/University of Wisconsin-Madison

Researchers working with Oak Ridge National Laboratory developed a new method to observe how proteins, at the single-molecule level, bind with other molecules and more accurately pinpoint certain molecular behavior in complex

ORNL’s green solvent enables environmentally friendly recycling of valuable Li-ion battery materials. Credit: Andy Sproles/ORNL, U.S. Dept. of Energy

Scientists at Oak Ridge National Laboratory have developed a solvent that results in a more environmentally friendly process to recover valuable materials from used lithium-ion batteries, supports a stable domestic supply chain for new batteries

The proposed Battery Identity Global Passport suggests a scannable QR code or other digital tag affixed to Li-ion batteries to identify materials for efficient end-of-life recycling. Credit: Andy Sproles, ORNL/U.S. Dept. of Energy

Scientists at Oak Ridge National Laboratory have devised a method to identify the unique chemical makeup of every lithium-ion battery around the world, information that could accelerate recycling, recover critical materials and resolve a growing waste stream.

Transition metals stitched into graphene with an electron beam form promising quantum building blocks. Credit: Ondrej Dyck, Andrew Lupini and Jacob Swett/ORNL, U.S. Dept. of Energy

Oak Ridge National Laboratory scientists demonstrated that an electron microscope can be used to selectively remove carbon atoms from graphene’s atomically thin lattice and stitch transition-metal dopant atoms in their place.

ORNL has modeled the spike protein that binds the novel coronavirus to a human cell for better understanding of the dynamics of COVID-19. Credit: Stephan Irle/ORNL, U.S. Dept. of Energy

To better understand the spread of SARS-CoV-2, the virus that causes COVID-19, Oak Ridge National Laboratory researchers have harnessed the power of supercomputers to accurately model the spike protein that binds the novel coronavirus to a human cell receptor.

ORNL welder Devin Johnson uses a new orbital welder to seal a hollow target in a glovebox in the lab’s Radiochemical Engineering Development Center. The new welder makes a clean seam on the metal target, eliminating the need for hand-finishing afterward. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

A better way of welding targets for Oak Ridge National Laboratory’s plutonium-238 production has sped up the process and improved consistency and efficiency. This advancement will ultimately benefit the lab’s goal to make enough Pu-238 – the isotope that powers NASA’s deep space missions – to yield 1.5 kilograms of plutonium oxide annually by 2026.

Researchers at ORNL’s Center for Nanophase Materials Sciences and the University of Tennessee Health Science Center partnered to design a COVID-19 screening whistle for convenient home testing. Credit: Michelle Lehman/ORNL, U.S. Dept. of Energy

Collaborators at Oak Ridge National Laboratory and the University of Tennessee Health Science Center are developing a breath-sampling whistle that could make COVID-19 screening easy to do at home.

Shown here is an on-chip carbonized electrode microstructure from a scanning electron microscope. Credit: ORNL, U.S. Dept. of Energy

Scientists at Oak Ridge National Laboratory and the University of Tennessee designed and demonstrated a method to make carbon-based materials that can be used as electrodes compatible with a specific semiconductor circuitry.

Cars and coronavirus

Oak Ridge National Laboratory researchers have developed a machine learning model that could help predict the impact pandemics such as COVID-19 have on fuel demand in the United States.