MIT Researchers Develop Method for Realistic 3D Printing Optimization of Materials

Researchers at the Massachusetts Institute of Technology (MIT) have developed a method that takes into account the physical limitations of 3D printers already during the digital design phase. The goal is to reduce the gap between theoretical material properties and actual printed results — a discrepancy that can lead to performance deviations in components, particularly in aerospace and medical engineering.

“If you don’t account for these limitations, printers can either over- or under-deposit material by quite a lot, so your part becomes heavier or lighter than intended. It can also over- or underestimate the material performance significantly,” says Gilbert W. Winslow Associate Professor of Civil and Environmental Engineering Josephine Carstensen. “With our technique, you know what you’re getting in terms of performance because the numerical model and experimental results align very well.”

“3D printing processes generally give us more flexibility because we don’t have to come up with forms or molds for things that would be made through more traditional means like injection molding,” Hajin Kim-Tackowiak explains. “We thought, ‘We know these limitations in the beginning, and the field has gotten better at quantifying these limitations, so we might as well design from the get-go with that in mind.”

The new model integrates real printing parameters — such as nozzle size and the weaker bonding between layers — directly into topology optimization, a computational method for material design. This enables the creation of structures whose actual material density and strength are much closer to theoretical predictions. In testing, samples designed using this method showed significantly more consistent performance at material densities below 70 percent compared to conventionally optimized counterparts.

“One of the challenges of topology optimization has been that you need a lot of expertise to get good results, so that once you take the designs off the computer, the materials behave the way you thought they would,” Carstensen says. “We’re trying to make it easy to get these high-fidelity products.”

“When you design something, you should use as much context as possible,” Kim-Tackowiak says. “It was rewarding to see that putting more context into the design process makes your final materials more accurate. It means there are fewer surprises. Especially when we’re putting so much more computational resources into these designs, it’s nice to see we can correlate what comes out of the computer with what comes out of the production process.”

Beyond improving mechanical accuracy, the approach also allows for more precise control of the printer’s motion paths. The system accounts for where the extruded material is deposited and how the orientation of layers affects structural stability. The researchers see this as an important step toward making 3D printing processes more efficient and reproducible.

“It was cool to see that just by putting in the size of your deposition and the bonding property values, you get designs that would have required the consultation of somebody who’s worked in the space for years,” Kim-Tackowiak says.

In the future, the method will be extended to materials such as ceramics and cement. This could eventually enable the use of materials that were previously impractical due to printing challenges.

“We’d like to see this enable the use of materials that people have disregarded because printing with them has led to issues,” Kim-Tackowiak says. “Now we can leverage those properties or work with those quirks as opposed to just not using all the material options we have at our disposal.”