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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.

Attendees of SMC23 pose for their annual group photo in downtown Knoxville, TN.

ORNL hosted its annual Smoky Mountains Computational Sciences and Engineering Conference in person for the first time since the COVID-19 pandemic.

Conceptual art depicts an atomic nucleus and merging neutron stars, respectively, areas of study in ORNL-led projects called NUCLEI and ENAF within the Scientific Discovery through Advanced Computing, or SciDAC, program. Credit: Adam Malin/ORNL, U.S. Dept. of Energy

ORNL is leading two nuclear physics research projects within the Scientific Discovery through Advanced Computing, or SciDAC, program from the Department of Energy Office of Science.

ORNL researchers are demonstrating an automation system for this portable system, currently based in Colorado, for treatment of non-traditional water sources to drinking water standards. Credit: Tzahi Cath/Colorado School of Mines

Researchers at ORNL are developing advanced automation techniques for desalination and water treatment plants, enabling them to save energy while providing affordable drinking water to small, parched communities without high-quality water supplies.

The DEMAND single crystal diffractometer at the High Flux Isotope Reactor, or HFIR, is the latest neutron instrument at the Department of Energy’s Oak Ridge National Laboratory to be equipped with machine learning-assisted software, called ReTIA. Credit: Jeremy Rumsey/ORNL, U.S. Dept. of Energy

Neutron experiments can take days to complete, requiring researchers to work long shifts to monitor progress and make necessary adjustments. But thanks to advances in artificial intelligence and machine learning, experiments can now be done remotely and in half the time.

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.

oxygen isotope 28

Rare isotope oxygen-28 has been determined to be "barely unbound" by experiments led by researchers at the Tokyo Institute of Technology and by computer simulations conducted at ORNL. The findings from this first-ever observation of 28O answer a longstanding question in nuclear physics: can you get bound isotopes in a very neutron-rich region of the nuclear chart, where instability and radioactivity are the norm? 

Madhavi Martin portrait image

Madhavi Martin brings a physicist’s tools and perspective to biological and environmental research at the Department of Energy’s Oak Ridge National Laboratory, supporting advances in bioenergy, soil carbon storage and environmental monitoring, and even helping solve a murder mystery.

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