Digital light processing of liquid crystal elastomers for self-sensing artificial muscles

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Abstract

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.

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Li, S., Bai, H., Liu, Z., Zhang, X., Huang, C., Wiesner, L. W., … Shepherd, R. F. (2021). Digital light processing of liquid crystal elastomers for self-sensing artificial muscles. Science Advances, 7(30). https://doi.org/10.1126/sciadv.abg3677

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