Reprogrammable Phase‐Transition Composites for Adaptive Dynamic Shape Morphing
Source abstract
Abstract
ABSTRACT Adaptive dynamic deformation has attracted growing attention because of its great significance for robots to adapt to the environment. However, designing a flexible smart material with reprogrammable and local programmable regulation for adaptive dynamic deformation in robotic systems is a substantial challenge. In nature, phase transitions are used to shape biological tissues, modulate growth shape through stiffness changes and provide growth momentum through fluid pressure. Inspired by this, we report a reprogrammable phase‐transition composites that uses the stiffness change induced by reversible solid‐liquid phase transition to program and regulate the material deformation actuated by reversible liquid‐vapor phase transition, thereby achieving adaptive dynamic deformation in a controllable manner. By regulating the order of the two phase transitions, phase‐transition composites can achieve not only reprogrammable deformation and local programmable deformation, but also rapid deformation and shape locking. We have developed a series of functional enhancements and applications using phase‐transition composites, demonstrating the effectiveness of the composite phase‐transition programmed deformation modulation mechanism. This mechanism enables robots to achieve reversible active deformation modulation and reprogrammable deformation modulation, opening a door for robotic systems with adaptive dynamic deformation.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Advanced Materials and Mechanics · Soft Robotics and Applications · Dielectric materials and actuators
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
State Key Laboratory of Fluid Power and Mechatronic Systems School of Mechanical Engineering Zhejiang University Hangzhou China
Funding
National Natural Science Foundation of China · China Postdoctoral Science Foundation
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