Tunable Large-Scale Compressive Strain Sensor Based on Carbon Nanotube/Polydimethylsiloxane Foam Composites by Additive Manufacturing
Date
2021-12
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Wiley
Abstract
The compressive strain sensor is an extensively used flexible electronic device because of its capability to convert mechanical deformation to an electrical signal. However, the difficulty in tuning the performance of the strain sensor limits its further applications. Herein, the approach of fabricating a carbon nanotube (CNT)/polydimethylsiloxane (PDMS) compressive strain sensor, which has both tunable mechanical and electrical performances, is presented. CNT plays the role of reinforcement due to its outstanding mechanical strength and electrical conductivity. PDMS is a widely used matrix because of its softness and nontoxicity. The material extrusion 3D printing method is used to fabricate the composites, due to its advantages of design flexibility and compatibility with liquid-based materials. The foam microstructure formed by removing sodium chloride provides a large-scale deformation of at least 50% compressive strain and excellent elasticity. The strain sensor works durably over 10 000 cycles, with a gauge factor (GF) of 17.4. The compressive strain sensor in detecting both large- and small-scale human motions due to the tunability of CNT/PDMS composites is also tested.
Description
This is the peer reviewed version of the following article: Liu, C., Le, L., Zhang, M. and Ding, J. (2022), Tunable Large-Scale Compressive Strain Sensor Based on Carbon Nanotube/Polydimethylsiloxane Foam Composites by Additive Manufacturing. Adv. Eng. Mater. 2101337., which has been published in final form at https://doi.org/10.1002/adem.202101337. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions.
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Liu, C., Le, L., Zhang, M. and Ding, J. (2022), Tunable Large-Scale Compressive Strain Sensor Based on Carbon Nanotube/Polydimethylsiloxane Foam Composites by Additive Manufacturing. Adv. Eng. Mater. 2101337. https://doi.org/10.1002/adem.202101337