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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.

This image from Sept. 30, 2022, shows how the Federal Emergency Management Agency used ORNL's USA Structures data along with new satellite images to identify structures that were destroyed in Lee County, Florida, during Hurricane Ian. Credit: ORNL, U.S. Dept. of Energy

Over the past seven years, researchers in ORNL’s Geospatial Science and Human Security Division have mapped and characterized all structures within the United States and its territories to aid FEMA in its response to disasters. This dataset provides a consistent, nationwide accounting of the buildings where people reside and work.

U.S. Secretary of Energy Jennifer Granholm visited Oak Ridge National Laboratory today to attend a groundbreaking ceremony for the U.S. Stable Isotope Research and Development Center. The facility is slated to receive $75 million in funding from the Inflation Reduction Act.

U.S. Secretary of Energy Jennifer Granholm visited Oak Ridge National Laboratory today to attend a groundbreaking ceremony for the U.S. Stable Isotope Production and Research Center. The facility is slated to receive $75 million in funding from the Inflation Reduction Act.

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.

Researchers used quantum Monte Carlo calculations to accurately render the structure and electronic properties of germanium selenide, a semiconducting nanomaterial. Credit: Paul Kent/ORNL, U.S. Dept. of Energy

A multi-lab research team led by ORNL's Paul Kent is developing a computer application called QMCPACK to enable precise and reliable predictions of the fundamental properties of materials critical in energy research.

Magnetic quantum material broadens platform for probing next-gen information technologies

Scientists at ORNL used neutron scattering to determine whether a specific material’s atomic structure could host a novel state of matter called a spiral spin liquid.

Frontier has arrived, and ORNL is preparing for science on Day One. Credit: Carlos Jones/ORNL, Dept. of Energy

The Frontier supercomputer at the Department of Energy’s Oak Ridge National Laboratory earned the top ranking today as the world’s fastest on the 59th TOP500 list, with 1.1 exaflops of performance. The system is the first to achieve an unprecedented level of computing performance known as exascale, a threshold of a quintillion calculations per second.

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ORNL scientists will present new technologies available for licensing during the annual Technology Innovation Showcase. The event is 9 a.m. to 3 p.m. Thursday, June 16, at the Manufacturing Demonstration Facility at ORNL’s Hardin Valley campus.

A smart approach to microscopy and imaging developed at Oak Ridge National Laboratory could drive discoveries in materials for future technologies. Credit: Adam Malin/ORNL, U.S. Dept. of Energy

Researchers at ORNL are teaching microscopes to drive discoveries with an intuitive algorithm, developed at the lab’s Center for Nanophase Materials Sciences, that could guide breakthroughs in new materials for energy technologies, sensing and computing.

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.