Animals, plants, and even viruses change shape to adapt to the environment. This is not a shared property of most engineering materials with fixed formats and functions.
Recent research by Professor Wei Chen and Professor Ryan Truby can help fill that gap by developing materials that can reconstruct themselves according to external factors, such as flowers and other creatures, to act as if they had an intellect of an organism.
The team led by Chen and Truby have developed AI-driven design and 3D printing methods that allow them to autonomously create material systems that can change shape when exposed to stimuli such as heat or light. This new material engineering framework not only designs the structure of the material, but also knows the optimal material (stimulus) distribution and the printing process parameters required to achieve the desired shape depending on the environmental cues.
This new approach to engineering shape morphing, stimulus-responsive materials integrates with the optimization of generalized topology and differential differential simulation of hybrid data, two computational methods that allow for efficient design of complex systems. This approach accelerates high-dimensional design exploration and maximizes advanced manufacturing potential. The system also quickly adapts to changing design requirements and quickly produces new designs in just a few minutes.
For the desired shape morphing task, the team method automatically designs materials and structures in 1 minute and completes all instructions for 3D printing. Properly produced designs have biological systems-like structures and shape change behaviors that resemble patterns that appear naturally from the optimization process. This suggests that this method not only improves performance, but also reveals new design principles that reflect nature.
Chen is Professor Wilson Cook of Engineering Design and Professor and Chair of the McCormick School of Engineering's Faculty of Mechanical Engineering. Truby is June and is Professor Donald Brewer Jr. of Materials Science and Mechanical Engineering at McCormick. They presented their findings in a paper published in the journal on September 12th, “Autonomically Co-Design and the Manufacturing of Multi-Tim-Responsive Material Systems.” Advances in science. Liwei Wang is a former postdoctoral scholar at the Integrated Design Automation (Ideal) Institute, and is currently an assistant professor at Carnegie Mellon University and doctoral candidate at Robot Matter Lab, the research's lead author.
“By combining AI, physics and digital manufacturing, we have created powerful tools for developing adaptive materials that can be used in medical devices, robotics, and other technologies that need to meet changing environments and functional needs,” Chen said. “This is a step towards smarter, more versatile materials that can do what traditional systems can't.”
Recent advances allow materials to respond to multiple stimuli, but current design methods are limited to a single response, limiting creativity and performance, relying heavily on trial and error or expert intuition. Design and manufacturing of multireactive materials remains a major challenge.
The team overcomes this by creating a system that automatically designs and manufactures materials to change shape in a programmed manner under multiple triggers. This approach is generalizable and has been extended to other manufacturing methods and responsive materials.
“This breakthrough helps bridge the gap between the stimulus-responsive materials we can design and the ways we actually build and manufacture them for real engineering applications,” says Truby.
