Significantly reducing defects, new technique opens up applications for 3D printing metal parts


UW-Madison mechanical engineering professor Lianyi Chen, left, and doctoral students Luis Escano and Minglei Qu, right, work in Chen’s lab, where they developed a technique to limit defects in 3D printing with metals. UW-Madison photo by Renee Meiller.

Compared to conventional manufacturing methods, additive manufacturing (also known as 3D printing) is much better at producing metal parts with highly complex shapes, which makes 3D printing attractive for applications in aerospace industries and biomedical, among others.

But there is a downside. Metal parts created with additive manufacturing have defects, such as pores and cracks in the material, which significantly compromise the strength and durability of the finished part.

“Using metal 3D printing, we have not been able to consistently produce parts with the same quality and reliability as those made by conventional methods, which means we have great concerns about using 3D printed parts for critical or load-bearing applications where failure is not an option,” says Lianyi Chen, assistant professor of mechanical engineering at the University of Wisconsin-Madison. “This quality issue is the biggest obstacle to the use of metal 3D printing in various applications.”

Now, Chen and his students have discovered a way to enable a leading additive manufacturing technique called laser powder bed fusion to produce metal parts that have far fewer defects. They detailed their findings in a paper recently published in the journal Nature Communications.

“We demonstrate a potential way to address the quality issue by making metal 3D printing technology much more reliable, allowing it to produce consistent, defect-free parts,” Chen said. “Using our unique method, we were able to 3D print a metal part with very few defects and comparable quality to a commercially manufactured part you might buy off the shelf.”

It’s a promising solution to a long-standing problem in metal additive manufacturing, and it opens the door to the widespread adoption of this manufacturing technology by industry.

The researchers’ technique involves using ceramic nanoparticles to control instabilities in the laser powder bed fusion additive manufacturing process that cause defects.

Laser powder bed fusion uses a high-energy laser beam to melt thin layers of metal powder in certain places. The material then cools, forming the finished metal part. However, when the laser interacts with the powdered material, the surface of the powder heats up to boiling temperature and creates hot steam. This vaporization creates pressure that pushes down on the pool of molten material, causing droplets to splatter. These droplets can cause unpredictable defects in the printed part. Droplets can also collide and coalesce to form a larger droplet, creating even more problems in the additive manufacturing process and leading to lower quality printed parts.

By coating the metal powder with ceramic nanoparticles, the researchers were able to control these instabilities. Using both high-speed synchrotron X-ray imaging and theoretical analysis, they found that the nanoparticle coating stabilized the molten puddle, preventing liquid droplets from sputtering and forming larger splashes.

“When we introduced the nanoparticles, we found that they caused the liquid droplets to almost have an armor on the surface, so that when they collided, they didn’t coalesce,” says student Minglei Qu. graduate and lead author of the study. . “For the first time, we were able to get rid of the problematic big splashes.”

In addition to the possibilities it offers for 3D manufacturing, Chen says this breakthrough could lead to improvements in a wide range of applications, including laser polishing, laser coating, welding, molding and inspection. fluid stability, among others.

Other study authors include Qilin Guo, Luis I. Escano, Ali Nabaa, S. Mohammad H. Hojjatzadeh, and Zachary A. Young, all graduate students in Chen’s lab.

This research was supported by grants from the National Science Foundation (2002840) and the UW-Madison Startup Fund.

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