Session: 12-29-02: Mechanics of Soft Materials

Paper Number: 147402

147402 - The Electromechanics of Porous Nanocomposite and Stretchable Hybrid Response Pressure Sensor 

Electronic skins or e-skins, which can mimic the softness and tactile sensation of human skin, are essential for a variety of technologies such as soft robots, prostheses, bio-mimetics, and biosensors [1,2,3]. As the central component of e-skins, soft pressure sensors have been the subject of extensive research. Among the different types of pressure sensors, capacitive pressure sensors (CPS) and resistive pressure sensors (RPS) have gained great popularity due to their softness, thinness, high sensitivity, facile fabrication, and easy signal readout. Despite decades of research, RPS and CPS still suffer from two major bottlenecks: the drastic decay of sensitivity with increasing pressure and the inaccurate detection of pressure under in-plane stretch [4].  Recently, Ha et al. [5,6] introduced a novel stretchable hybrid response pressure (SHRPS) sensor that addressed both challenges. The key component of SHRPS is a barely conductive porous nanocomposite (PNC), which exhibits piezocapacitivity and piezoresistivity simultaneously. Despite its success, its fundamental electromechanics remains elusive.

In this work, we conducted electromechanical characterization of both PNC and SHRPS under various loading conditions. A rigorous protocol was developed to calibrate potential parasitic capacitance and fringe effects. Both SHRPS and barely conductive PNC were found to be highly sensitive to compression, much less insensitive to in-plane stretch, and almost insensitive to shear. This anisotropic response was explained through the fact that resistance changes by three magnitudes under compression, but changes little under tension and shear. Therefore, SHRPS only exhibits a hybrid response under compression and acts like a normal CPS under tension and shear, which is much less sensitive.  

The electromechanical response of PNC was described by converting impedance to parallel capacitance and parallel impedance, each following an independent mixing law.  The parallel capacitance of PNC was modeled using a parallel mixing law, while a directional Archie’s law was used to describe the parallel resistance of PNC. A new equivalent circuit model was proposed for SHRPS that eliminates the need for additional multiscale modeling. The proposed model can capture the electromechanical response of SHRPS under various loading conditions. We further conducted finite element simulation based on a random structure using the Voronoi diagram to justify the proposed mixing laws and equivalent circuit models. This work can guide the future design of SHRPS and benefit electromechanical studies of both CPS and RPS based on PNC.

 

[1] Wang, M., Luo, Y., Wang, T., Wan, C., Pan, L., Pan, S., He, K., Neo, A., Chen, X., 2021. Advanced Materials 33, 2003014.

[2] Wang, X., Dong, L., Zhang, H., Yu, R., Pan, C., Wang, Z.L., 2015. Advanced Science 2, 1500169

[3] Lee, W.W., Tan, Y.J., Yao, H., Li, S., See, H.H., Hon, M., Ng, K.A., Xiong, B., Ho, J.S., Tee, B.C., 2019. Science Robotics 4, eaax2198

[4] Ha, K.H., Huh, H., Li, Z., Lu, N., 2022. ACS nano 16, 3442–3448.

[5] Ha, K.H., Zhang, W., Jang, H., Kang, S., Wang, L., Tan, P., Hwang, H., Lu, N., 2021. Advanced Materials 33, 2103320

[6] Ha, K.H., Li, Z., Kim, S.K., Huh, H., Wang, Z., Shi, H., Block, C., Bhattacharya, S., Lu, N.,
2024. Stretchable hybrid response pressure sensors. Matter, accepted.

Presenting Author: Zheliang Wang The University of Texas at Austin

Presenting Author Biography: Zheliang Wang is a postdoctoral researcher in the Department of Aerospace Engineering and Engineering Mechanics at the University of Texas at Austin. He earned his Ph.D. in Mechanical Engineering from Johns Hopkins University in 2022. His research focuses on elucidating the material-structure-performance relationships of soft electronics, employing a combined approach of constitutive modeling, finite element simulation, and analytical modeling.

Authors:

Zheliang Wang The University of Texas at Austin
Zhengjie Li The University of Texas at Austin
Sangjun Kim The University of Texas at Austin
Sungmin Sun The University of Texas at Austin
Xianke Feng The University of Texas at Austin
Nanshu Lu The University of Texas at Austin