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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.

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.

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.

Santa Jansone-Popova, left, and Ilja Popovs quantify rare-earth element concentrations in liquid samples using a spectroscopy instrument. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy

A new technology for rare-earth elements chemical separation has been licensed to Marshallton Research Laboratories, a North Carolina-based manufacturer of organic chemicals for a range of industries.

Automated disassembly line aims to make battery recycling safer, faster

Researchers at ORNL have developed a robotic disassembly system for spent electric vehicle battery packs to safely and efficiently recycle and reuse critical materials while reducing toxic waste.

Oak Ridge National Laboratory’s MENNDL AI software system can design thousands of neural networks in a matter of hours. One example uses a driving simulator to evaluate a network’s ability to perceive objects under various lighting conditions. Credit: ORNL, U.S. Dept. of Energy

The Department of Energy’s Oak Ridge National Laboratory has licensed its award-winning artificial intelligence software system, the Multinode Evolutionary Neural Networks for Deep Learning, to General Motors for use in vehicle technology and design.

Distinguished Inventors

Six scientists at the Department of Energy’s Oak Ridge National Laboratory were named Battelle Distinguished Inventors, in recognition of obtaining 14 or more patents during their careers at the lab.

New virtual tours of ORNL facilities include the Building Technologies Research and Integration Center, shown in dollhouse view. Credit: ORNL, U.S. Dept. of Energy

ORNL has added 10 virtual tours to its campus map, each with multiple views to show floor plans, rotating dollhouse views and 360-degree navigation. As a user travels through a map, pop-out informational windows deliver facts, videos, graphics and links to other related content.

ORNL’s Ramesh Bhave poses in his lab in March 2019. Bhave developed the Membrane Solvent Extraction process, which can be used to recover cobalt and other metals from spent lithium-ion batteries. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Momentum Technologies Inc., a Dallas, Texas-based materials science company that is focused on extracting critical metals from electronic waste, has licensed an Oak Ridge National Laboratory process for recovering cobalt and other metals from spent

Researcher Chase Joslin uses Peregrine software to monitor and analyze a component being 3D printed at the Manufacturing Demonstration Facility at ORNL. Credit: Luke Scime/ORNL, U.S. Dept. of Energy.

Oak Ridge National Laboratory researchers have developed artificial intelligence software for powder bed 3D printers that assesses the quality of parts in real time, without the need for expensive characterization equipment.