Flexible iontronic sensing.

Journal: Chemical Society reviews
Published Date: May 19, 2025

Abstract

The emerging flexible iontronic sensing (FITS) technology has introduced a novel modality for tactile perception, mimicking the topological structure of human skin while providing a viable strategy for seamless integration with biological systems. With research progress, FITS has evolved from focusing on performance optimization and structural enhancement to a new phase of integration and intelligence, positioning it as a promising candidate for next-generation wearable devices. Therefore, a review from the perspective of technological development trends is essential to fully understand the current state and future potential of FITS devices. In this review, we examine the latest advancements in FITS. We begin by examining the sensing mechanisms of FITS, summarizing research progress in material selection, structural design, and the fabrication of active and electrode layers, while also analysing the challenges and bottlenecks faced by different segments in this field. Next, integrated systems based on FITS devices are reviewed, highlighting their applications in human-machine interaction, healthcare, and environmental monitoring. Additionally, the integration of artificial intelligence into FITS is explored, focusing on optimizing front-end device design and improving the processing and utilization of back-end data. Finally, building on existing research, future challenges for FITS devices are identified and potential solutions are proposed.

Authors

  • Yang Li
    Occupation of Chinese Center for Disease Control and Prevention, Beijing, China.
  • Ningning Bai
    Department of Mathematics, Xi'an University of Technology, Xi'an 710048, China. Electronic address: ningnbai@163.com.
  • Yu Chang
    Department of Neurology, Tianjin First Central Hospital, Tianjin, China.
  • Zhiguang Liu
    Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei, Anhui, 230027, China.
  • Jianwen Liu
    School of Information Science and Engineering, Shandong Provincial Key Laboratory of Network Based Intelligent Computing University of Jinan Jinan 250022, China.
  • Xiaoqin Li
    Department of Pulmonary and Critical Care Medicine, Fujian Provincial Hospital, Fuzhou, China.
  • Wenhao Yang
    School of Integrated Circuits, Shandong University, Jinan, 250101, China.
  • Hongsen Niu
    School of Information Science and Engineering, Shandong Provincial Key Laboratory of Network Based Intelligent Computing, University of Jinan, Jinan, 250022, China.
  • Weidong Wang
    Zhejiang Huade New Materials Co., Ltd., Zhejiang Province, Hangzhou, China.
  • Liu Wang
    CAS Key Laboratory of Mechanical Behavior and Design of Materials, Department of Modern Mechanics, University of Science and Technology of China, Hefei, Anhui, China. liuwang@mit.edu.
  • Wenhao Zhu
    School of Computer Engineering and Science, Shanghai University, Shanghai, China.
  • Di Chen
    Department of Gastroenterology, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, China. Electronic address: 2389446889@qq.com.
  • Tingrui Pan
  • Chuan Fei Guo
    Department of Materials Science and Engineering, Southern University of Science and Technology, Shenzhen, 518000, China.
  • Guozhen Shen
    School of Integrated Circuits and Electronics, Beijing Institute of Technology, Beijing, 100081, China.

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