Enhanced piezoresistive performance of conductive WPU/CNT composite foam through incorporating brittle cellulose nanocrystal

By Shuaidi Zhang, K. Sun, Hu Liu, Xiaoyu Chen, Yanjun Zheng, X. Shi, Dianbo Zhang, Liwei Mi, Chuntai Liu, Changyu Shen. 2020

158 citations recorded by the source corpus.

Abstract Recently, piezoresistive sensors with wide response range and high sensitivity are in great demands with the rapid development of flexible electronic industry. To meet the demands, highly compressible waterborne polyurethane (WPU)/carbon nanotube (CNT) composite foam with enhanced piezoresistive performance was designed through incorporating the brittle cellulose nanocrystal (CNC) during the fabrication process. Here, the homogeneous dispersion of CNT with the assistance of amphiphilic CNC and the good interfacial interaction between CNC and TPU endowed the composite foam with improved compression properties. In addition, the brittle CNC/CNT conductive network is easier to be destructed, generating more significant resistance variation and about as high as 2.5 times the sensitivity of composite foam without CNC. As a piezoresistive sensor, it exhibits good compressibility and stable piezoresistive sensing signal in 80% compression strain range due to the porous structure and good elasticity of WPU. Cyclic piezoresistive sensing tests under different compression strains and rates demonstrate the excellent recoverability and reproducibility of the piezoresistive sensor after the initial stabilization process. More importantly, it also displays a fast response time of about 30 ms and good durability and reproductivity over 1000 compression cycles. Finally, the piezoresistive sensor can be successfully applied to detect various human motions (such as vocal cords/cheeks/fingers/wrists/feet movements) and to fabricate artificial electronic skin. The investigation provides an effective strategy for the fabrication of high-performance piezoresistive sensor.

Subfields: Biomedical Engineering, Polymers and Plastics

View Paper: https://www.semanticscholar.org/paper/bd843dfdcf1037b046abd495b70b16c3817746df