Skip to main content
The ORNL DAAC gathers, processes, archives and distributes information on key land processes, including the shifting ecological and geomorphological features of the U.S. Atchafalaya and Terrebonne basins gathered by the NASA Delta-X mission shown here. Credit: NASA Delta-X

In 1993 as data managers at ORNL began compiling observations from field experiments for the National Aeronautics and Space Administration, the information fit on compact discs and was mailed to users along with printed manuals.

The Department of Energy’s Oak Ridge National Laboratory announced the establishment of its Center for AI Security Research, or CAISER, to address threats already present as governments and industries around the world adopt artificial intelligence and take advantage of the benefits it promises in data processing, operational efficiencies and decision-making. Credit: Rachel Green/ORNL, U.S. Dept. of Energy

The Department of Energy’s Oak Ridge National Laboratory announced the establishment of the Center for AI Security Research, or CAISER, to address threats already present as governments and industries around the world adopt artificial intelligence and take advantage of the benefits it promises in data processing, operational efficiencies and decision-making.

 A group of ORNL staff standing in a long corridor with flags hanging from the ceiling

For 25 years, scientists at Oak Ridge National Laboratory have used their broad expertise in human health risk assessment, ecology, radiation protection, toxicology and information management to develop widely used tools and data for the U.S. Environmental Protection Agency as part of the agency’s Superfund program.

Benefit breakdown, 3D printed vs. wood molds

Oak Ridge National Laboratory researchers have conducted a comprehensive life cycle, cost and carbon emissions analysis on 3D-printed molds for precast concrete and determined the method is economically beneficial compared to conventional wood molds.

Steve Nolan, left, who manages many ORNL facilities for United Cleanup Oak Ridge, and Carl Dukes worked closely together to accommodate bringing members of the public into the Oak Ridge Reservation to collect distant images from overhead for the BRIAR biometric recognition project. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Carl Dukes’ career as an adept communicator got off to a slow start: He was about 5 years old when he spoke for the first time. “I’ve been making up for lost time ever since,” joked Dukes, a technical professional at the Department of Energy’s Oak Ridge National Laboratory.

Steven Hamilton, an R&D scientist in the HPC Methods for Nuclear Applications group at ORNL, leads the ExaSMR project. ExaSMR was developed to run on the Oak Ridge Leadership Computing Facility’s exascale-class supercomputer, Frontier. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy

The Exascale Small Modular Reactor effort, or ExaSMR, is a software stack developed over seven years under the Department of Energy’s Exascale Computing Project to produce the highest-resolution simulations of nuclear reactor systems to date. Now, ExaSMR has been nominated for a 2023 Gordon Bell Prize by the Association for Computing Machinery and is one of six finalists for the annual award, which honors outstanding achievements in high-performance computing from a variety of scientific domains.  

Tom Karnowski (left) and Jordan Johnson (right). Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Tom Karnowski and Jordan Johnson of ORNL have been named chair and vice chair, respectively, of the East Tennessee section of the Institute of Electrical and Electronics Engineers, or IEEE.

ORNL Vehicle Power Electronics Research group R&D Associate Subho Mukherjee has been elevated to the senior member grade IEEE. Credit: ORNL, U.S. Dept. of Energy

Subho Mukherjee, an R&D associate in the Vehicle Power Electronics Research group at the Department of Energy’s Oak Ridge National Laboratory, has been elevated to the grade of senior member of the Institute of Electrical and Electronics Engineers.

ZEISS Head of Additive Manufacturing Technology Claus Hermannstaedter, left, and ORNL Interim Associate Laboratory Director for Energy Science and Technology Rick Raines sign a licensing agreement that allows ORNL’s machine-learning algorithm, Simurgh, to be used for rapid evaluations of 3D-printed components with industrial X-ray computed tomography, or CT. Using machine learning in CT scanning is expected to reduce the time and cost of inspections of 3D-printed parts by more than ten times.

A licensing agreement between the Department of Energy’s Oak Ridge National Laboratory and research partner ZEISS will enable industrial X-ray computed tomography, or CT, to perform rapid evaluations of 3D-printed components using ORNL’s machine

Mike Huettel

Mike Huettel is a cyber technical professional. He also recently completed the 6-month Cyber Warfare Technician course for the United States Army, where he learned technical and tactical proficiency leadership in operations throughout the cyber domain.