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ORNL's Communications team works with news media seeking information about the laboratory. Media may use the resources listed below or send questions to news@ornl.gov.

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Paul Kent, shown above posing with Summit in April 2018, received the 2020 ORNL Director’s Award for Outstanding Individual Accomplishment in Science and Technology. Credit: ORNL, U.S. Dept. of Energy

Paul Kent, a computational nanoscience researcher in ORNL’s Computing and Computational Science Directorate, received the ORNL Director’s Award for Outstanding Individual Accomplishment in Science and Technology. The award recognizes Kent’s leadership in quantum simulation development and application on high-performance computing platforms to help solve major scientific problems.

Substituting deuterium for hydrogen makes methylammonium heavier and slows its swaying so it can interact with vibrations that remove heat, keeping charge carriers hot longer. Credit: Jill Hemman/ORNL, U.S. Dept. of Energy

Led by ORNL and the University of Tennessee, Knoxville, a study of a solar-energy material with a bright future revealed a way to slow phonons, the waves that transport heat.

ORNL researchers developed a quantum, or squeezed, light approach for atomic force microscopy that enables measurement of signals otherwise buried by noise. Credit: Raphael Pooser/ORNL, U.S. Dept. of Energy

Researchers at ORNL used quantum optics to advance state-of-the-art microscopy and illuminate a path to detecting material properties with greater sensitivity than is possible with traditional tools.

Sergei Kalinin

Five researchers at the Department of Energy’s Oak Ridge National Laboratory have been named ORNL Corporate Fellows in recognition of significant career accomplishments and continued leadership in their scientific fields.

A nanobrush made by pulsed laser deposition of CeO2 and Y2O3 with dim and bright bands, respectively, is seen in cross-section with scanning transmission electron microscopy. Credit: Oak Ridge National Laboratory, U.S. Dept. of Energy

A team led by the Department of Energy’s Oak Ridge National Laboratory synthesized a tiny structure with high surface area and discovered how its unique architecture drives ions across interfaces to transport energy or information.

Before the demonstration, the team prepared QKD equipment (pictured) at ORNL. Image credit: Genevieve Martin/Oak Ridge National Laboratory, U.S. Dept. of Energy

For the second year in a row, a team from the Department of Energy’s Oak Ridge and Los Alamos national laboratories led a demonstration hosted by EPB, a community-based utility and telecommunications company serving Chattanooga, Tennessee.

The agreement builds upon years of collaboration, including a 2016 effort using modeling tools developed at ORNL to predict the first six months of operations of TVA’s Watts Bar Unit 2 nuclear power plant. Credit: Andrew Godfrey/Oak Ridge National Laboratory, U.S. Dept. of Energy

OAK RIDGE, Tenn., Feb. 19, 2020 — The U.S. Department of Energy’s Oak Ridge National Laboratory and the Tennessee Valley Authority have signed a memorandum of understanding to evaluate a new generation of flexible, cost-effective advanced nuclear reactors.

Using as much as 50 percent lignin by weight, a new composite material created at ORNL is well suited for use in 3D printing.

Scientists at the Department of Energy’s Oak Ridge National Laboratory have created a recipe for a renewable 3D printing feedstock that could spur a profitable new use for an intractable biorefinery byproduct: lignin.

Graphical representation of a deuteron, the bound state of a proton (red) and a neutron (blue). Credit: Andy Sproles/Oak Ridge National Laboratory, U.S. Dept. of Energy.

Scientists at the Department of Energy’s Oak Ridge National Laboratory are the first to successfully simulate an atomic nucleus using a quantum computer. The results, published in Physical Review Letters, demonstrate the ability of quantum systems to compute nuclear ph...

ORNL’s Steven Young (left) and Travis Johnston used Titan to prove the design and training of deep learning networks could be greatly accelerated with a capable computing system.

A team of researchers from the Department of Energy’s Oak Ridge National Laboratory has married artificial intelligence and high-performance computing to achieve a peak speed of 20 petaflops in the generation and training of deep learning networks on the laboratory’...