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Surface structure engineering for a bionic fiber-based sensor toward linear, tunable, and multifunctional sensing

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Abstract

Flexible and stretchable strain sensors have broad applications in human physiological activities, object deformation, as well as human–machine interface. However, it is still challenging to fabricate stretchable strain sensors with linear and superior piezoresistive signal response. Herein, we report a facile and scalable microstructure design strategy to generate a unique segmental hierarchical fiber-surface structure that mimics an arthropod's body and a lobster's tail structure for achieving linear strain sensing response. The alternate modulus difference of the micro-nanoscale segmental soft (thermoplastic polyurethane, TPU)-hard (polystyrene, PS) configurations enables the initiation of significant strain concentration effect, which is consistent with the finite element analysis, thus allowing to tune the sensing properties, for e.g., the linear degree varies from 0.48 to 0.99 and the gauge factor ranges from 5.25 to 23 800 for the strain within 30%. The bionic structured fiber sensors demonstrate potential applications for the detection of human skin epidermal disturbance, small curvature changes, sound wave vibration, as well as mechanochromic response if a fluorescent agent is added to the TPU core. Besides, they are also capable of detecting various types of organic vapors due to the strain amplification effect heterogeneous structure design, paving a new way for the design of multifunctional flexible sensors for variable human–machine interface applications.

Graphical abstract: Surface structure engineering for a bionic fiber-based sensor toward linear, tunable, and multifunctional sensing

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Article information


Submitted
30 Apr 2020
Accepted
30 Jun 2020
First published
30 Jun 2020

Mater. Horiz., 2020, Advance Article
Article type
Communication

Surface structure engineering for a bionic fiber-based sensor toward linear, tunable, and multifunctional sensing

J. Jia, J. Pu, J. Liu, X. Zhao, K. Ke, R. Bao, Z. Liu, M. Yang and W. Yang, Mater. Horiz., 2020, Advance Article , DOI: 10.1039/D0MH00716A

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