Shape-memory and shrink-on-demand aquabots
ORAL
Abstract
Current soft robots are mainly fabricated from soft solid materials. The deformability is limited by the underlying solid bulk rheology. It remains challenging for current soft robots to navigate and reconfigure their shapes for diverse tasks inside very clustered and constrained spaces. Building on an ultra-soft liquid robot, termed aquabots, we have developed an approach to achieve reversible dimensional shrinkage and shape memory functions. Using photo-crosslinking-assisted water-in-water printing, thermal and magnetic multi-responsive membranes of aquabots are produced. Our shape-memory and shrink-on-demand aquabots can in situ adapt theirs size and shapes to navigate through and conduct tasks in very constrained spaces narrower than the size of aquabots. These unprecedented cooperative abilities of aquabots create new opportunities in the applications of medical manipulation, biosensing, endoscopy and microsurgery.
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Presenters
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Shipei Zhu
The University of Hong Kong
Authors
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Shipei Zhu
The University of Hong Kong
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Huanqing Cui
The University of Hong Kong
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Ho Cheung Shum
The University of Hong Kong
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Thomas P Russell
University of Massachusetts Amherst