| Literature DB >> 34074051 |
Zhenyu Xu1, Yongsen Zhou1, Baoping Zhang1, Chao Zhang1, Jianfeng Wang2, Zuankai Wang1,3.
Abstract
Millions of years' evolution has imparted life on earth with excellent environment adaptability. Of particular interest to scientists are some plants capable of macroscopically and reversibly altering their morphological and mechanical properties in response to external stimuli from the surrounding environment. These intriguing natural phenomena and underlying actuation mechanisms have provided important design guidance and principles for man-made soft robotic systems. Constructing bio-inspired soft robotic systems with effective actuation requires the efficient supply of mechanical energy generated from external inputs, such as temperature, light, and electricity. By combining bio-inspired designs with stimuli-responsive materials, various intelligent soft robotic systems that demonstrate promising and exciting results have been developed. As one of the building materials for soft robotics, hydrogels are gaining increasing attention owing to their advantageous properties, such as ultra-tunable modulus, high compliance, varying stimuli-responsiveness, good biocompatibility, and high transparency. In this review article, we summarize the recent progress on plant-inspired soft robotics assembled by stimuli-responsive hydrogels with a particular focus on their actuation mechanisms, fabrication, and application. Meanwhile, some critical challenges and problems associated with current hydrogel-based soft robotics are briefly introduced, and possible solutions are proposed. We expect that this review would provide elementary tutorial guidelines to audiences who are interested in the study on nature-inspired soft robotics, especially hydrogel-based intelligent soft robotic systems.Entities:
Keywords: adaptive; hydrogel; plant-inspired; soft robotics; stimuli-responsive
Year: 2021 PMID: 34074051 DOI: 10.3390/mi12060608
Source DB: PubMed Journal: Micromachines (Basel) ISSN: 2072-666X Impact factor: 2.891