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Title: Digital light processing of liquid crystal elastomers for self-sensing artificial muscles
Artificial muscles based on stimuli-responsive polymers usually exhibit mechanical compliance, versatility, and high power-to-weight ratio, showing great promise to potentially replace conventional rigid motors for next-generation soft robots, wearable electronics, and biomedical devices. In particular, thermomechanical liquid crystal elastomers (LCEs) constitute artificial muscle-like actuators that can be remotely triggered for large stroke, fast response, and highly repeatable actuations. Here, we introduce a digital light processing (DLP)–based additive manufacturing approach that automatically shear aligns mesogenic oligomers, layer-by-layer, to achieve high orientational order in the photocrosslinked structures; this ordering yields high specific work capacity (63 J kg −1 ) and energy density (0.18 MJ m −3 ). We demonstrate actuators composed of these DLP printed LCEs’ applications in soft robotics, such as reversible grasping, untethered crawling, and weightlifting. Furthermore, we present an LCE self-sensing system that exploits thermally induced optical transition as an intrinsic option toward feedback control.
Authors:
; ; ; ; ; ; ;
Award ID(s):
1825444 1719875
Publication Date:
NSF-PAR ID:
10291111
Journal Name:
Science Advances
Volume:
7
Issue:
30
Page Range or eLocation-ID:
eabg3677
ISSN:
2375-2548
Sponsoring Org:
National Science Foundation
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