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Illustration of a computer monitor displaying a green-toned digital twin of an industrial facility or reactor complex, with tanks, buildings, and trees, set against a blue-green background of abstract circuit patterns representing data and connectivity.

In collaboration with the University of Tennessee and GE Vernova Hitachi, researchers at ORNL recently published innovative research on a new risk-informed digital twin designed to enhance operational decision-making for the GE Vernova Hitachi BWRX-300 SMR design.

Illustration of a nanoscale data storage process showing a sharp probe tip writing information onto a surface patterned with colorful circular domains, with a microchip in the background and glowing circuit-like pathways suggesting advanced computing and nanotechnology.

ORNL researchers enhanced atomic force microscopy with machine learning to write and erase nanoscale patterns in ferroic materials. This innovation promises multistate memory capabilities and advances electronic data storage.

Two divers in scuba gear work underwater in a pool, examining and adjusting equipment connected by cables on the pool floor.

X-ray imaging is useful for seeing inside objects without causing damage, but until now it was not practical for use underwater. ORNL researchers have developed the first X-ray imaging system that clearly reveals the interior of suspicious objects or infrastructure underwater. 

An optical microscopy image of nuclear grade PCEA graphite captured at ORNL demonstrates the tiny pores, voids, and cracks that are inherent to this form of graphite.

A study led by ORNL answers a decades-old question in nuclear science: Do tiny pores in graphite affect nuclear reactor performance?  The answer is clear: Graphite’s natural porosity does not affect its performance as a moderator of nuclear reactions. The lab's research confirms that the tiny cracks and voids in graphite do not disturb the atomic vibrations that determine its interactions with neutrons. 

A scanning tunneling microscope and machine learning algorithm autonomously search for atomic structures. This image shows a vacancy defect on europium zinc arsenide.

A research team led by Oak Ridge National Laboratory has developed a new method to uncover the atomic origins of unusual material behavior. This approach uses Bayesian deep learning, a form of artificial intelligence that combines probability theory and neural networks to analyze complex datasets with exceptional efficiency. 

ORNL researcher is standing in front of a screen where data and physics model in rainbow colors is on the screen

A new patent granted to ORNL researchers redefines how nuclear systems are validated, offering a faster path to next-generation nuclear energy. By using machine learning to identify high-value experiments, this approach can eliminate redundancies and define clear boundaries for AI and digital twin models.

ORNL researcher is looking at ORNL's mock reactor test bed for autonomous controls is shaping the future of space exploration.

Nuclear energy is a leading option to power space exploration, but its success depends on reactors that can operate autonomously. To help make that vision a reality, ORNL has built a non-nuclear test bed that mimics the conditions of a space nuclear reactor to overcome the high cost and strict regulations required for testing in a reactor environment.

Carbon nanotubes are sitting on a grey plate on a countertop

The U.S. Air Force awarded startup SkyNano, led by Innovation Crossroads alumna Anna Douglas, a $1.25 million contract to advance its CO2-to-carbon nanotube technology as part of a project to develop low-cost, battery-grade graphite.

A plastic replica of the pellets formed by the system on W7-X, next to a dime, for size reference, and the cutter that extracts the pellet from the extrusion, as seen in the video.

A key milestone in the pursuit of fusion energy is achieving a high “triple product,” an important metric of the temperature and density of a burning plasma and how well it is confined. The Wendelstein 7-X stellarator in Germany recently sustained a plasma with a record high triple product for 43 seconds – far surpassing previous performance – in part due to a novel fuel pellet injection system developed by researchers at ORNL.

Close up image of a automotive piston

Scientists at Oak Ridge National Laboratory have advanced the use of DuAlumin-3D, an innovative aluminum alloy, in high-temperature automotive components, significantly expanding the possibilities of additive manufacturing.