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Updated: Apr 15, 2026

Author Spotlight: Microfluidic Channel-Based Soft Electrodes and Their Application in Capacitive Pressure Sensing
Published on: March 17, 2023
Flexible, large-area, recyclable, decoupled dual sensing of temperature and pressure enabled by
Jia Zhu1,2,3, Xionghao Liu4, Jiaying Li4
1School of Materials and Energy, University of Electronic Science and Technology of China, Chengdu, PR China. zhujia1990@uestc.edu.cn.
Abstract:
Thin, conformable electronic skin (e-skin), capable of accurately perceiving various stimuli (e.g., temperature and pressure), is an important building block for various cutting-edge applications, including human healthcare, structural health monitoring, human-machine interfaces, and closed-loop device systems. However, crosstalk from multiple input signals severely deteriorates the sensing accuracy of the measured temperature and pressure. Moreover, different constituent materials and fabrication protocols utilized for flexible sensors hinder their integration towards multifunctional e-skin. Here, this work introduces mechanically and electrically hybrid networks (MEHNs) in functional nanocomposites for large-area, multiplexed, and decoupled sensing. The rigid, high-resistive vanadium oxide (VO2) microparticles with metal-insulator transition combined with soft, low-resistive liquid metal particles (LMPs) in MEHNs serve as temperature sensing units and mechanical buffers, respectively, leading to an ultra-high yet pressure-insensitive temperature coefficient of resistance (TCR) of -2.23%. Modifying VO2 microparticles with silver nanoparticles to cancel the high TCR is combined with a porous structure to render the nanocomposite with temperature-insensitive pressure sensing with a sensitivity of 1.212% kPa-1. The same constituent material and fabrication protocol of the MEHN nanocomposites, along with their scalability and recyclability, can afford low-cost, large-scale, and multiplexed e-skin for broad application opportunities, including human and battery health monitoring, soft electrical impedance tomography, and robotic perception.

