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ORNL researchers are establishing a digital thread of data, algorithms and workflows to produce a continuously updated model of earth systems.

Digital twins are exactly what they sound like: virtual models of physical reality that continuously update to reflect changes in the real world.

 

Karen White

Karen White, who works in ORNL’s Neutron Science Directorate, has been honored with a Lifetime Achievement Award.

Frontier, the fastest supercomputer in the world, provides expansive and energy-efficient power, which gives scientists the capability to train large AI models in a responsible way.

ORNL is home to the world's fastest exascale supercomputer, Frontier, which was built in part to facilitate energy-efficient and scalable AI-based algorithms and simulations. 

ORNL researchers found that a polyelectrolyte additive can improve the stability and performance of a salt hydrate PCM, enhancing the potential for use in heat pumps. Credit: ORNL, U.S. Dept. of Energy

ORNL researchers demonstrated that an additive made from polymers and electrolytes improves the thermal performance and stability of salt hydrate phase change materials, or PCMs, a finding that could advance their integration into carbon-reducing heat pumps.

The sun sets behind the ORNL Visitor Center in this aerial photo from April 2023. Credit: Kase Clapp/ORNL, U.S. Dept. of Energy

In fiscal year 2023 — Oct. 1–Sept. 30, 2023 — Oak Ridge National Laboratory was awarded more than $8 million in technology maturation funding through the Department of Energy’s Technology Commercialization Fund, or TCF.

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.

As a scientist at Oak Ridge National Laboratory, Tugba Turnaoglu is investigating new thermal energy storage materials and ways to incorporate them into cost-effective and energy-efficient heat pump designs. Credit: Carlos Jones/ORNL, U.S. Dept of Energy

The common sounds in the background of daily life – like a refrigerator’s hum, an air conditioner’s whoosh and a heat pump’s buzz – often go unnoticed. These noises, however, are the heartbeat of a healthy building and integral for comfort and convenience.

Director of ORNL’s AI Initiative Prasanna Balaprakash addresses attendees at the Generative AI for ORNL Science Workshop. Credit: ORNL, U.S. Dept. of Energy

The Department of Energy’s Oak Ridge National Laboratory hosted its Smoky Mountains Computational Science and Engineering Conference for the first time in person since the COVID pandemic broke in 2020. The conference, which celebrated its 20th consecutive year, took place at the Crowne Plaza Hotel in downtown Knoxville, Tenn., in late August.

Buildings technologies researcher Philip Boudreaux uses a camera and a technique known as background-oriented schlieren photography to identify air leak sources in a concrete block wall mock-up. Credit: ORNL, U.S. Dept. of Energy

Researchers at the Department of Energy’s Oak Ridge National Laboratory have created a new detection system that allows home energy auditors to see air leaking from a building in real time with the help of a camera.

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