Smooth or Bumpy? New 3D-Printed Surfaces Change on Demand
Andrew Wheeler posted on June 30, 2015 |
MIT research yields soft material with alterable surface textures that can be changed by squeezing.

An MIT team has been working on a way to make soft materials using a 3D printer. The interesting part of their method is that after the material is printed, the surface textures can be modified on demand to be perfectly smooth, ridged, or bumpy, or even to have complex patterns that could potentially guide fluids. 

 
Polymer material produced by a 3D printer includes soft, flexible material (clear or lighter tone) with particles of embedded hard material (black) in predetermined arrangements. When the material is compressed, its surface becomes bumpy in a pattern determined by the hard particles.
Polymer material produced by a 3D printer includes soft, flexible material (clear or lighter tone) with particles of embedded hard material (black) in predetermined arrangements. When the material is compressed, its surface becomes bumpy in a pattern determined by the hard particles.

The key here of course is the material. It is made up of two different polymers with different degrees of stiffness. Rigid particles are embedded within a matrix of a more flexible polymer. When squeezing pressure is applied, the material’s surface changes from smooth to a pre-determined pattern based on the spacing and shapes of the implanted harder particles. When the pressure is removed, the material reverts back to its original form. 

Researchers say this new method could lead to a new class of materials with dynamically controllable and reversible surface properties, as reported in a paper published in Advanced Functional Materials, co-authored by MIT graduate student Mark Guttag and Mary Boyce, a former MIT professor of mechanical engineering and now dean of engineering at Columbia University. 

MITBumpy
This animated simulation shows how embedded hard particles within a softer flexible material produce a textured surface when compressed. (Animation by Mark Guttag)

Animated simulation shows how embedded hard particles within a softer, flexible material produce a textured surface when compressed. (Animation by Mark Guttag) 

“Depending on the arrangement of the particles, using the same amount of compression, you can get different surface topographies, including ridges and bumps, along the surface,” according to Guttag, who is pursuing the research as part of his doctoral thesis in mechanical engineering. 

“The system can produce simple, repetitive patterns of bumps or creases, which could be useful for changing the aerodynamic resistance of an object, or its reflectivity. But by arranging the distribution of the hard particles, it can also be used to produce highly complex surface textures — for example, creating microfluidic channels to control the movement of liquids inside a chemical or biological detector,”Guttag says. 

For instance, such a device could have a smooth, tilted surface allowing fluids to flow evenly across its surface, but with the added ability, on demand, to create raised sections and depressions that would separate the flow of liquids. 

Applications  

  • Camouflage  

  • Making surfaces that repel or attract water  

  • Controlling the motion and turbulence of fluids 

  • Limiting the buildup of organisms on surfaces such as ship hulls  

“There are no previous techniques that provide comparable flexibility for creating dynamically and locally tunable and reversible surface changes,” Guttag and Boyce write in their paper. 

Because the system is “all geometry driven,” Guttag says (based on the shapes and spacing of materials with different degrees of flexibility), “it could be scaled to all different sizes, and the same principles should work.” 

The initial development of the system was done using computer simulations, which were then tested and validated by 3D-printed versions of a few of the designs. The surface patterns were produced when the soft printed materials were compressed closely matched those seen in the simulations. 

The project was funded through a cooperative agreement between MIT and the Masdar Institute of Science and Technology in the United Arab Emirates. 

Source: MIT

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