MIT researchers have developed a method for 3D printing materials with tunable mechanical properties, that sense how they are moving and interacting with the environment. The researchers created these sensing structures using just one material and a single run on a 3D printer.
To accomplish this, the researchers began with 3D-printed lattice materials and incorporated networks of air-filled channels into the structure during the printing process. By measuring how the pressure changes within these channels when the structure is squeezed, bent, or stretched, engineers can receive feedback on how the material is moving.
The method opens opportunities for embedding sensors within architected materials, a class of materials whose mechanical properties are programmed through form and composition. Controlling the geometry of features in architected materials alters their mechanical properties, such as stiffness or toughness.
The researchers focused their efforts on lattices, a type of “architected material,” which exhibits customizable mechanical properties based solely on its geometry. For instance, changing the size or shape of cells in the lattice makes the material flexible.
While architected materials can exhibit unique properties, integrating sensors within them is challenging given the materials’ often sparse, complex shapes. Placing sensors on the outside of the material is typically a simpler strategy than embedding sensors within the material. However, when sensors are placed on the outside, the feedback they provide may not provide a complete description of how the material is deforming or moving.
Instead, the researchers used 3D printing to incorporate airfilled channels directly into the struts that form the lattice. When the structure is moved or squeezed, those channels deform and the volume of air inside changes. The researchers can measure the corresponding change in pressure with an off-the-shelf pressure sensor, which gives feedback on how the material is deforming.
Because they are incorporated into the material, these “fluidic sensors” offer advantages over conventional sensor materials. Building off these results, they also incorporated sensors into a new class of materials developed for motorized soft robots known as handed shearing auxetics (HSAs). HSAs can be twisted and stretched simultaneously, which enables them to be used as effective soft robotic actuators. But they are difficult to “sensorize” because of their complex forms.
The team 3D printed an HSA soft robot capable of several movements, including bending, twisting, and elongating. They ran the robot through a series of movements for more than 18 hours and used the sensor data to train a neural network that could accurately predict the robot’s motion.
This technique could someday be used to create flexible soft robots with embedded sensors that enable the robots to understand their posture and movements. It might also be used to produce wearable smart devices that provide feedback on how a person is moving or interacting with their environment.
In the future, the researchers look forward to finding new applications for this technique, such as creating novel human-machine interfaces or soft devices that have sensing capabilities within the internal structure.