Drawing inspiration from the extraordinary adaptability seen in biological entities such as the octopus, a significant advancement in the field of soft robotics has been made. Under the guidance of Professor Jiyun Kim from the Department of Materials Science and Engineering at UNIST, a research team has successfully developed an encodable multifunctional material that can dynamically tune its shape and mechanical properties in real-time.
This groundbreaking metamaterial surpasses the limitations of existing materials, opening up new possibilities for applications in robotics and other fields requiring adaptability.
Current soft machines lack the level of adaptability demonstrated by their biological counterparts, primarily due to limited real-time tunability and restricted reprogrammable space of properties and functionalities. In order to bridge this gap, the research team introduced a novel approach utilizing graphical stiffness patterns. By independently switching the digital binary stiffness states (soft or rigid) of individual constituent units within a simple auxetic structure featuring elliptical voids, the material achieves in situ and gradational tunability across various mechanical qualities.
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