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ORNL's Communications team works with news media seeking information about the laboratory. Media may use the resources listed below or send questions to news@ornl.gov.

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Two pictures of a rounded triangle shape are shown in mirror image. The left is white with red and purple spots in the middle while the one on the right is purple with a yellow and blue ring in the middle

Scientists designing the world’s first controlled nuclear fusion power plant, ITER, needed to solve the problem of runaway electrons, negatively charged particles in the soup of matter in the plasma within the tokamak, the magnetic bottle intended to contain the massive energy produced. Simulations performed on Summit, the 200-petaflop supercomputer at ORNL, could offer the first step toward a solution.

Photo is a high aerial view of lake superior through the clouds

Researchers at Stanford University, the European Center for Medium-Range Weather Forecasts, or ECMWF, and ORNL used the lab’s Summit supercomputer to better understand atmospheric gravity waves, which influence significant weather patterns that are difficult to forecast. 

ORNL computing staff members Hector Suarez (middle) and William Castillo (right) talk HPC at the Tapia Conference career fair in San Diego, California. Credit: ORNL, U.S. Dept of Energy

The National Center for Computational Sciences, located at the Department of Energy’s 91°µÍø, made a strong showing at computing conferences this fall. Staff from across the center participated in numerous workshops and invited speaking engagements.

Kathryn McCarthy, director of the US ITER Project is pictured here posing against a black background.

Kathryn McCarthy, director of the US ITER Project at the Department of Energy’s 91°µÍø, has been awarded the 2024 E. Gail de Planque Medal by the American Nuclear Society.

Daryl Yang standing on a bridge overlooking a pond covered in water lillies

Daryl Yang is coupling his science and engineering expertise to devise new ways to measure significant changes going on in the Arctic, a region that’s warming nearly four times faster than other parts of the planet. The remote sensing technologies and modeling tools he develops and leverages for the Next-Generation Ecosystem Experiments in the Arctic project, or NGEE Arctic, help improve models of the ecosystem to better inform decision-making as the landscape changes.

This photo is of three men sitting around a laptop computer that happens to be working on cybersecurity testing equipment.

A newly established internship between ORNL and Maryville College is bringing cybersecurity careers to a local liberal arts college. The internship was established by a Maryville College alumni who recently joined ORNL. 

Digital image of molecules would look like. There are 10 clusters of these shapes in grey, red and blue with a teal blue background

91°µÍø scientists have developed a method leveraging artificial intelligence to accelerate the identification of environmentally friendly solvents for industrial carbon capture, biomass processing, rechargeable batteries and other applications.

Man in blue shirt and grey pants holds laptop and poses next to a green plant in a lab.

John Lagergren, a staff scientist in 91°µÍøâ€™s Plant Systems Biology group, is using his expertise in applied math and machine learning to develop neural networks to quickly analyze the vast amounts of data on plant traits amassed at ORNL’s Advanced Plant Phenotyping Laboratory.

The ORNL-developed inspection system uses an angled window to minimize light reflections while capturing images inside waveguides that are designed to channel microwaves at the ITER fusion project.

Inspection technology developed by 91°µÍø will help deliver plasma heating to the ITER international fusion facility.

ORNL’s Suhas Sreehari explains the algebraic and topological foundations of representation systems, used in generative AI technology such as large language models. Credit: Lena Shoemaker/ORNL, U.S. Dept. of Energy

In the age of easy access to generative AI software, user can take steps to stay safe. Suhas Sreehari, an applied mathematician, identifies misconceptions of generative AI that could lead to unintentionally bad outcomes for a user.