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Ilias Belharouak, Grace Burke and Phil Snyder represent ORNL’s strengths in battery technology, materials science and fusion energy research.

Three researchers at ORNL have been named ORNL Corporate Fellows in recognition of significant career accomplishments and continued leadership in their scientific fields.

When an electron beam drills holes in heated graphene, single-atom vacancies, shown in purple, diffuse until they join with other vacancies to form stationary structures and chains, shown in blue. Credit: Ondrej Dyck/ORNL, U.S. Dept. of Energy

Oak Ridge National Laboratory researchers serendipitously discovered when they automated the beam of an electron microscope to precisely drill holes in the atomically thin lattice of graphene, the drilled holes closed up.

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Global carbon emissions from inland waters such as lakes, rivers, streams and ponds are being undercounted by about 13% and will likely continue to rise given climate events and land use changes, ORNL scientists found.

Researchers at Oak Ridge National Laboratory probed the chemistry of radium to gain key insights on advancing cancer treatments using radiation therapy. Credit: Adam Malin/ORNL, U.S. Dept. of Energy

Researchers at ORNL explored radium’s chemistry to advance cancer treatments using ionizing radiation.

ORNL’s RapidCure improves lithium-ion electrode production by producing electrodes faster, reducing the energy necessary for manufacturing and eliminating the need for a solvent recycling unit. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Researchers at the Department of Energy’s Oak Ridge National Laboratory and their technologies have received seven 2022 R&D 100 Awards, plus special recognition for a battery-related green technology product.

Oak Ridge National Laboratory researchers developed an invertible neural network, a type of artificial intelligence that mimics the human brain, to improve accuracy in climate-change models and predictions. Credit: Getty Images

Oak Ridge National Laboratory researchers developed an invertible neural network, a type of artificial intelligence that mimics the human brain, to improve accuracy in climate-change models and predictions.

With seismic and acoustic data recorded by remote sensors near ORNL’s High Flux Isotope Reactor, researchers could predict whether the reactor was on or off with 98% accuracy. Credit: Nathan Armistead/ORNL, U.S. Dept. of Energy

An Oak Ridge National Laboratory team developed a novel technique using sensors to monitor seismic and acoustic activity and machine learning to differentiate operational activities at facilities from “noise” in the recorded data.

The ORNL-developed AquaBOT measures a range of water quality indicators, providing data for studies focused on clean water and sustainable energy. Credit: Natalie Griffiths/ORNL, U.S. Dept. of Energy

Measuring water quality throughout river networks with precision, speed and at lower cost than traditional methods is now possible with AquaBOT, an aquatic drone developed by Oak Ridge National Laboratory.

Genetic analysis revealed connections between inflammatory activity and development of atomic dermatitis, according to researchers from the UPenn School of Medicine, the Perelman School of Medicine, and Oak Ridge National Laboratory. Credit: Kang Ko/UPenn

University of Pennsylvania researchers called on computational systems biology expertise at Oak Ridge National Laboratory to analyze large datasets of single-cell RNA sequencing from skin samples afflicted with atopic dermatitis.

ORNL researchers worked with partners at the Colorado School of Mines and Baylor University to develop a new process optimization and control method for a closed-circuit reverse osmosis desalination system. The work is intended to support fully automated, decentralized water treatment plants. Credit: Andrew Sproles/ORNL, U.S. Dept. of Energy

Oak Ridge National Laboratory scientists worked with the Colorado School of Mines and Baylor University to develop and test control methods for autonomous water treatment plants that use less energy and generate less waste.