Between strict safety codes and the intense heat inside a reactor, building new components for nuclear reactors usually takes a long time. Researchers at Argonne National Laboratory are working on fixing that with 3D printing.

The lab recently submitted a proposal to the American Society of Mechanical Engineers (ASME) that could officially allow the use of Laser Powder Bed Fusion (LPBF) for high-temperature reactor parts. If approved, it means the industry can stop relying solely on traditional, slower manufacturing methods and start printing critical structural components.

3D Printing the Future of Nuclear

3D printing components
Researchers use 3-D printing to investigate how to strengthen the nuclear supply chain; Photo: Argonne National Laboratory

Instead of waiting months for specialized parts, engineers could print what they need with much more flexibility in the design. It’s a major step for applied material science.

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Argonne teamed up with Oak Ridge, Idaho, and Los Alamos National Laboratories to make this happen. They’ve been working under a Department of Energy program called Advanced Materials and Manufacturing Technologies (AMMT). This group analyzes everything from 3D printing to powder metallurgy to see how they can make nuclear energy more efficient.

The goal here is to take all that high-level research happening in labs and turn it into actual standards that regulators can approve. By creating these pathways, the team is making it much easier to get advanced reactor tech out of the lab and into the real world.

Still More to Come

Argonne is now looking at ways to speed up the testing process even more. Usually, qualifying a new material takes years of empirical data and physical testing. Now, the team wants to use machine learning to help predict how materials will behave over time.

This move toward digital qualification fits right into the Department of Energy’s “Genesis Mission.” The idea is to link supercomputers and data across the national lab system to find answers faster. By combining AI with real-time monitoring during the printing process, the team hopes to make the leap from “experimental” to “standard practice” much sooner than anyone expected.