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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. 

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 demonstrated the use of drones equipped with cameras and other sensors to check power lines at an EPB of Chattanooga training center for electrical line workers.

Researchers at ORNL recently demonstrated an automated drone-inspection technology at EPB of Chattanooga that will allow utilities to more quickly and easily check remote power lines for malfunctions, catching problems before outages occur.

Benjamin Manard

Benjamin Manard, an analytical chemist in the Chemical Sciences Division of the Department of Energy’s Oak Ridge National Laboratory, will receive the 2024 Lester W. Strock Award from the Society of Applied Spectroscopy.

This photo is of a male scientist sitting at a desk working with materials, wearing protective glasses.

Researchers at the Department of Energy’s Oak Ridge National Laboratory and partner institutions have launched a project to develop an innovative suite of tools that will employ machine learning algorithms for more effective cybersecurity analysis of the U.S. power grid. 

ORNL researchers Phani Marthi and Suman Debnath work on developing and scaling up new EMT simulation software to analyze how power electronics in the electric grid will respond to brief interruptions in power flow. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy

Power companies and electric grid developers turn to simulation tools as they attempt to understand how modern equipment will be affected by rapidly unfolding events in a complex grid. 

Power lines to the right, colorful graphs to the left and in the middle is a cord putting out electrical currents.

Researchers at Oak Ridge National Laboratory have opened a new virtual library where visitors can check out waveforms instead of books. So far, more than 350 users worldwide have utilized the library, which provides vital understanding of an increasingly complex grid.

Woman in a tan blazer is standing at a podium presenting to a room full of people.

SCALE users from 85 organizations across 21 countries gathered online and in person at Oak Ridge National Laboratory from June 5 to June 7 for the Eighth Annual SCALE Users Group Workshop. The meeting included 32 presentations and 14 hands-on tutorials on impactful and innovative applications of SCALE. 

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

Oak Ridge National Laboratory 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.