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Inverse design method used to improve porous surface texture of 3D printed objects
A multi-institutional team of mechanical engineers and materials scientists has developed an inverse design method to improve the texture of porous surfaces on 3D printed structures. In their paper published in the journal Science, the group describes developing micrometer-sized triangles and ribbons to create a lattice upon which to build surface structures.
In the natural world, the arrangement of cells allows for the creation of unique porous surface structures—leaves, flowers and human skin all have a remarkable degree of surface variability with unique visible features and specific characteristics, such as repelling water. Recreating such features using technology as simple as a 3D printer has been impossible.
In this new effort, the research team has come a step closer to mimicking nature by developing a new way to represent such structures in a reproducible way.
The researchers sought to replicate the way cells are arranged by creating digital lattices composed of tiny triangles and ribbons. They came to these shapes using an inverse design method (curved beam deformation theory). They then developed an application to generate desired shapes using their digital lattices.
The application was then taught how to create such shapes using a machine-learning algorithm. The finished product was then sent to a 2D printer, which printed out a pattern onto a base that could be folded into 3D shapes. The system allowed for creating a wide variety of structures with highly porous surfaces.
The team demonstrated their system by first creating simple textured objects such as spheres. They then progressed to creating more complicated objects, such as a bell pepper, an ant and an octopus. They also note that the objects that are created can be made using a variety of materials, such as single crystal silicon, metals, chitosan and laser-honed graphene.
The group finished by creating a scaffold shaped like a contact lens that was embedded with sensors. Once printed, they used the structure to study the electrical properties of neurons in the back of the eye.
More information: Xu Cheng et al, Programming 3D curved mesosurfaces using microlattice designs, Science (2023). DOI: 10.1126/science.adf3824
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