Since its introduction in 1985, 3D printing has revolutionized manufacturing, offering cheaper and customizable designs.
From aerospace to medicine, its applications have grown rapidly.
However, Associate Professor Pablo Valdivia y Alvarado from the Singapore University of Technology and Design (SUTD) believes there’s more potential to unlock.
Traditional 3D printing involves building objects layer by layer, following a pre-designed toolpath.
While effective for many materials, this approach doesn’t work well with slow-curing materials like silicone, epoxies, and urethanes.
These materials are crucial for creating lightweight, nature-inspired structures such as lattices and webs, often used in robotics and energy-absorbing designs.
However, their slow-hardening nature and non-optimized toolpaths make printing such structures challenging and time-consuming.
To solve this, Professor Valdivia y Alvarado and his team developed an innovative method called “architected design,” which improves how these materials are printed.
Published in Advanced Intelligent Systems, their research focuses on optimizing the toolpath to create smoother and more efficient printing.
The team designed a system to break down 3D designs into points and simple shapes, allowing for a combination of segmented and continuous toolpaths.
This approach minimizes unnecessary starts and stops, speeding up the printing process. They also enhanced the properties of silicone materials by adding a modifier called Thivex, creating nine different material combinations ideal for printing.
Using their optimized method, the team 3D-printed bioinspired structures like cilia, webs, leaf-like shapes, and lattices. Testing these designs revealed promising results. For example, 3D-printed cilia improved the strength of suction cups, while lattices demonstrated outstanding energy-absorbing capabilities, reducing impact forces by up to 85%.
Though still in the research phase, this method shows promise for industries like robotics, wearable technology, and advanced materials. “Our approach could lead to customized, high-performance designs tailored for specific needs,” said Professor Valdivia y Alvarado. He envisions these deposition-based techniques complementing traditional 3D printing for advanced applications.
The team is now focusing on scaling the process, reducing costs, and expanding material options for industrial use. Future research will explore multi-material printing, enabling the creation of “engineered metamaterials” with diverse properties. They also plan to use machine learning to help users design materials based on specific performance requirements.
These advancements could unlock new possibilities for 3D printing, making it a key tool for producing innovative designs in robotics, protective gear, and beyond.
Source: KSR.
