3D Printing Improved: Near Net Shape Parts with No Post-Processing

Researchers from Carnegie Mellon University, the University of California, Irvine, and Edwards Lifesciences have developed a method to 3D print near net shape parts that require no post-processing. This process could further advance additive manufacturing.

The team led by Professor Rahul Panat encountered an unexpected problem while developing a new type of 3D printed Brain-Computer Interface (BCI) device. The custom micropillars used to capture communication signals from neurons bent during the sintering process. These BCI devices, now called “CMU Arrays,” stack millions of metal nanoparticles in 3D space and then sinter them together.

The researchers were able to not only determine why such a distortion occurred but also find a way to control it. This led to the world’s first illustration of sintering as a mechanism of “4D printing,” a relatively new discipline within additive manufacturing where 3D printed objects are transformed into another shape using heat, water, or other environmental stimuli.

The research findings were published in the latest issue of the journal Nature Communications. “It’s very exciting that we could solve a fundamental problem in additive manufacturing that was the primary barrier to achieving near-net-shape parts using AM,” said Panat. “The idea of sintering as a way to achieve 4D printing will open new research directions.”

The paper, titled “Shape distortion in sintering results from nonhomogeneous temperature activating a long-range mass transport,” can be accessed here.