Skip to main content
This illustration demonstrates how atomic configurations with an equiatomic concentration of niobium (Nb), tantalum (Ta) and vanadium (V) can become disordered. The AI model helps researchers identify potential atomic configurations that can be used as shielding for housing fusion applications in a nuclear reactor. Credit: Massimiliano Lupo Pasini/ORNL, U.S. Dept. of Energy

A study led by the Department of Energy’s Oak Ridge National Laboratory details how artificial intelligence researchers created an AI model to help identify new alloys used as shielding for housing fusion applications components in a nuclear reactor. The findings mark a major step towards improving nuclear fusion facilities.

Through a new technical collaboration program, companies will be able to propose research projects that utilize the labs and expertise in ORNL’s Grid Research Integration and Deployment Center. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

A new technical collaboration program at the Department of Energy’s Oak Ridge National Laboratory will help businesses develop and launch electric grid innovations. Sponsored by the Transformer Resilience and Advanced Components program in DOE’s Office of Electricity, the initiative will provide companies with access to national laboratory resources, enabling them to capture market opportunities. 

Moe Khaleel, left, associate laboratory director for national security sciences, and Maurice Singleton, chief executive officer of U2opia Technology, celebrate the partnership between Oak Ridge National Laboratory and U2opia Technology. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

U2opia Technology has licensed Situ and Heartbeat, a package of technologies from the Department of Energy’s Oak Ridge National Laboratory that offer a new method for advanced cybersecurity monitoring in real time. 

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.

Bryan Maldonado

As a mechanical engineer in building envelope materials research at ORNL, Bryan Maldonado sees opportunities to apply his scientific expertise virtually everywhere he goes, from coast to coast. As an expert in understanding how complex systems operate, he’s using machine learning methods to control the process and ultimately optimize performance. 

Infuse logo

ORNL is the lead partner on five research collaborations with private fusion companies in the 2024 cohort of the Innovation Network for FUSion Energy, or INFUSE, program. These collaborative projects are intended to resolve technical hurdles and develop enabling technologies to accelerate fusion energy research in the private sector.

Illustration of oscillating UCI3 bonds

Researchers for the first time documented the specific chemistry dynamics and structure of high-temperature liquid uranium trichloride salt, a potential nuclear fuel source for next-generation reactors. 

ORNL researchers Tom Beck, left, Sarp Oral and Rafael Ferreira da Silva have proposed a strategy for integrating classical supercomputers such as Frontier, the world’s first exascale computer, with the emerging field of quantum computing.

A study by more than a dozen scientists at the Department of Energy’s Oak Ridge National Laboratory examines potential strategies to integrate quantum computing with the world’s most powerful supercomputing systems in the pursuit of science.

A portrait of John Sanseverino.

John joined the MPEX project in 2019 and has served as project manager for several organizations within ORNL.

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 Oak Ridge National Laboratory’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.