Aluminum has become an increasingly important material in both the aerospace and automotive industries, as companies turn to high-strength, light metals to help reduce overall weight and improve fuel efficiency.
HRL Laboratories recently announced that researchers there have created a way to 3D print these high-strength aluminum alloys (including AI7075 and AI6061), which could enable additive manufacturing of critical airplane or car parts. According to HRL, the same method could be used to additively manufacture parts using high-strength steel and nickel-based superalloys that are otherwise difficult to use in AM processes.
“We’re using a 70-year-old nucleation theory to solve a 100-year-old problem with a 21st century machine,” said Hunter Martin, who co-led the team with Brennan Yahata. Both researchers are engineers in the HRL’s Sensors and Materials Laboratory and Ph.D. students at the University of California.
Using the new technique, the alloys could be used to create complex parts that could be welded instead of riveted.
The research was printing in the September 21 issue of Nature.
The heat used to print high-strength aluminum alloys (which are unweldable) often results in parts that crack and flake. HRL’s nanoparticle functionalization solution combines zirconium-based nanoparticles with the unweldable alloy powders. The nanoparticles act as nucleation sites for the alloy microstructure, which prevents hot cracking and helps retain fully alloy strength in the final part.
HRL says this technique can also make these unweldable alloys weldable in their finished form.
The researchers also used data analysis tools from Citrine Informatics to help determine the right type of nanoparticle to use in the process.
“Using informatics was key,” said Yahata. “The way metallurgy used to be done was by farming the periodic table for alloying elements and testing mostly with trial and error. The point of using informatics software was to do a selective approach to the nucleation theory we knew to find the materials with the exact properties we needed. Once we told them what to look for, their big data analysis narrowed the field of available materials from hundreds of thousands to a select few. We went from a haystack to a handful of possible needles.”
Source: HRL Laboratories