Source abstract
Abstract
Stretchable flexible strain sensors based on conductive elastomers are rapidly emerging as a highly promising candidate for popular wearable flexible electronic and soft-mechanical sensing devices. However, due to the intrinsic limitations of low fidelity and high hysteresis, existing flexible strain sensors are unable to exploit their full application potential. Herein, a design strategy for a successive three-dimensional crack conductive network is proposed to cope with the uncoordinated variation of the output resistance signal arising from the conductive elastomer. The electrical characteristics of the sensor are dominated by the successive crack conductive network through a greater resistance variation and a concise sensing mechanism. As a result, the developed elastomer bionic strain sensors exhibit excellent sensing performance in terms of a smaller overshoot response, a lower hysteresis (∼2.9%), and an ultralow detection limit (0.00179%). What's more, the proposed strategy is universal and applicable to many conductive elastomers with different conductive fillers (including 0-D, 1-D, and 2-D conductive fillers). This approach improves the sensing signal accuracy and reliability of conductive elastomer strain sensors and holds promising potential for various applications in the fields of e-skin and soft robotic systems.
Source: openalex_inverted_index · Quality: baseline
Affiliations
Key Laboratory of Bionic Engineering, Ministry of Education, Jilin University, Changchun 130022, China
Department of Mechanical and Materials Engineering, Queen’s University, Kingston K7L3N6, Canada
Weihai Institute for Bionics, Jilin University, Weihai 264200, China
Institute of Structured and Architected Materials, Liaoning Academy of Materials, Shenyang 110167, China
Funding
Foundation for Innovative Research Groups of the National Natural Science Foundation of China · Shandong Provincial Natural Science Foundation · the National Science Fund for Excellent Young Scholars · Jilin University Science and Technology Innovative Research Team · the National Natural Science Foundation of China