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Li Y, Bai N, Chang Y, Liu Z, Liu J, Li X, Yang W, Niu H, Wang W, Wang L, Zhu W, Chen D, Pan T, Guo CF, Shen G. Flexible iontronic sensing. Chem Soc Rev 2025; 54:4651-4700. [PMID: 40165624 DOI: 10.1039/d4cs00870g] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/02/2025]
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.
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Affiliation(s)
- Yang Li
- School of Integrated Circuits, Shandong University, Jinan, 250101, China
| | - Ningning Bai
- School of Mechano-Electronic Engineering, Xidian University, Xi'an, 710071, China
| | - Yu Chang
- Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei, Anhui, 230027, China
- Center for Intelligent Medical Equipment and Devices, Institute for Innovative Medical Devices, Suzhou Institute for Advanced Research, University of Science and Technology of China, Suzhou, Jiangsu 215123, 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 Integrated Circuits, Shandong University, Jinan, 250101, China
| | - Xiaoqin Li
- School of Integrated Circuits, Shandong University, Jinan, 250101, 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 Ubiquitous Intelligent Computing, University of Jinan, Jinan, 250022, China
| | - Weidong Wang
- School of Mechano-Electronic Engineering, Xidian University, Xi'an, 710071, 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, 230027, China
| | - Wenhao Zhu
- Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei, Anhui, 230027, China
| | - Di Chen
- School of Integrated Circuits and Electronics, Beijing Institute of Technology, Beijing, 100081, China.
| | - Tingrui Pan
- Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei, Anhui, 230027, China
- Center for Intelligent Medical Equipment and Devices, Institute for Innovative Medical Devices, Suzhou Institute for Advanced Research, University of Science and Technology of China, Suzhou, Jiangsu 215123, China.
| | - Chuan Fei Guo
- Department of Materials Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, P. R. China.
| | - Guozhen Shen
- School of Integrated Circuits and Electronics, Beijing Institute of Technology, Beijing, 100081, China.
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Zhuo F, Ding Z, Yang X, Chu F, Liu Y, Gao Z, Jin H, Dong S, Wang X, Luo J. Advanced Morphological and Material Engineering for High-Performance Interfacial Iontronic Pressure Sensors. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2025; 12:e2413141. [PMID: 39840613 PMCID: PMC11848549 DOI: 10.1002/advs.202413141] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/17/2024] [Revised: 12/12/2024] [Indexed: 01/23/2025]
Abstract
High-performance flexible pressure sensors are crucial for applications such as wearable electronics, interactive systems, and healthcare technologies. Among these, iontronic pressure sensors have garnered particular attention due to their superior sensitivity, enabled by the giant capacitance variation of the electric double layer (EDL) at the ionic-electronic interface under deformation. Key advancements, such as incorporating microstructures into ionic layers and employing diverse materials, have significantly improved sensor properties like sensitivity, accuracy, stability, and response time. This review highlights advancements in flexible EDL pressure sensors, focusing on structural designs and material engineering. These strategies are tailored to optimize key metrics such as sensitivity, detection limit, linearity, stability, response speed, hysteresis, transparency, wearability, selectivity, and multifunctionality. Key fabrication techniques, including micropatterning and externally assisted methods, are reviewed, along with strategies for sensor comparison and guidelines for selecting appropriate sensors. Emerging applications in healthcare, environmental and aerodynamic sensing, human-machine interaction, robotics, and machine learning-assisted intelligent sensing are explored. Finally, this review discusses the challenges and future directions for advancing EDL-based pressure sensors.
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Affiliation(s)
- Fengling Zhuo
- College of Information Science and Electronic EngineeringZhejiang UniversityHangzhou310027China
- International Joint Innovation CenterZhejiang UniversityHaining314400China
| | - Zhi Ding
- College of Information Science and Electronic EngineeringZhejiang UniversityHangzhou310027China
| | - Xi Yang
- College of Information Science and Electronic EngineeringZhejiang UniversityHangzhou310027China
- International Joint Innovation CenterZhejiang UniversityHaining314400China
| | - Fengjian Chu
- College of Information Science and Electronic EngineeringZhejiang UniversityHangzhou310027China
| | - Yulu Liu
- Research Institute of Medical and Biological EngineeringNingbo UniversityNingbo315211China
| | - Zhuoqing Gao
- College of Information Science and Electronic EngineeringZhejiang UniversityHangzhou310027China
- International Joint Innovation CenterZhejiang UniversityHaining314400China
| | - Hao Jin
- College of Information Science and Electronic EngineeringZhejiang UniversityHangzhou310027China
- International Joint Innovation CenterZhejiang UniversityHaining314400China
| | - Shurong Dong
- College of Information Science and Electronic EngineeringZhejiang UniversityHangzhou310027China
- International Joint Innovation CenterZhejiang UniversityHaining314400China
| | - Xiaozhi Wang
- College of Information Science and Electronic EngineeringZhejiang UniversityHangzhou310027China
- International Joint Innovation CenterZhejiang UniversityHaining314400China
| | - Jikui Luo
- College of Information Science and Electronic EngineeringZhejiang UniversityHangzhou310027China
- International Joint Innovation CenterZhejiang UniversityHaining314400China
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Choi W, Choi J, Han Y, Yoo H, Yoon HJ. Polymer Dielectric-Based Emerging Devices: Advancements in Memory, Field-Effect Transistor, and Nanogenerator Technologies. MICROMACHINES 2024; 15:1115. [PMID: 39337775 PMCID: PMC11434493 DOI: 10.3390/mi15091115] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/06/2024] [Revised: 08/28/2024] [Accepted: 08/29/2024] [Indexed: 09/30/2024]
Abstract
Polymer dielectric materials have recently attracted attention for their versatile applications in emerging electronic devices such as memory, field-effect transistors (FETs), and triboelectric nanogenerators (TENGs). This review highlights the advances in polymer dielectric materials and their integration into these devices, emphasizing their unique electrical, mechanical, and thermal properties that enable high performance and flexibility. By exploring their roles in self-sustaining technologies (e.g., artificial intelligence (AI) and Internet of Everything (IoE)), this review emphasizes the importance of polymer dielectric materials in enabling low-power, flexible, and sustainable electronic devices. The discussion covers design strategies to improve the dielectric constant, charge trapping, and overall device stability. Specific challenges, such as optimizing electrical properties, ensuring process scalability, and enhancing environmental stability, are also addressed. In addition, the review explores the synergistic integration of memory devices, FETs, and TENGs, focusing on their potential in flexible and wearable electronics, self-powered systems, and sustainable technologies. This review provides a comprehensive overview of the current state and prospects of polymer dielectric-based devices in advanced electronic applications by examining recent research breakthroughs and identifying future opportunities.
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Affiliation(s)
- Wangmyung Choi
- Department of Semiconductor Engineering, Gachon University, Seongnam 13120, Republic of Korea
| | - Junhwan Choi
- Department of Chemical Engineering, Dankook University, Yongin 16890, Republic of Korea
| | - Yongbin Han
- Department of Semiconductor Engineering, Gachon University, Seongnam 13120, Republic of Korea
- Department of Electronic Engineering, Gachon University, Seongnam 13120, Republic of Korea
| | - Hocheon Yoo
- Department of Semiconductor Engineering, Gachon University, Seongnam 13120, Republic of Korea
- Department of Electronic Engineering, Gachon University, Seongnam 13120, Republic of Korea
| | - Hong-Joon Yoon
- Department of Semiconductor Engineering, Gachon University, Seongnam 13120, Republic of Korea
- Department of Electronic Engineering, Gachon University, Seongnam 13120, Republic of Korea
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Valerio A, Demarchi D, O’Flynn B, Motto Ros P, Tedesco S. Development of a Personalized Multiclass Classification Model to Detect Blood Pressure Variations Associated with Physical or Cognitive Workload. SENSORS (BASEL, SWITZERLAND) 2024; 24:3697. [PMID: 38894487 PMCID: PMC11175227 DOI: 10.3390/s24113697] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/02/2024] [Revised: 05/23/2024] [Accepted: 06/04/2024] [Indexed: 06/21/2024]
Abstract
Comprehending the regulatory mechanisms influencing blood pressure control is pivotal for continuous monitoring of this parameter. Implementing a personalized machine learning model, utilizing data-driven features, presents an opportunity to facilitate tracking blood pressure fluctuations in various conditions. In this work, data-driven photoplethysmograph features extracted from the brachial and digital arteries of 28 healthy subjects were used to feed a random forest classifier in an attempt to develop a system capable of tracking blood pressure. We evaluated the behavior of this latter classifier according to the different sizes of the training set and degrees of personalization used. Aggregated accuracy, precision, recall, and F1-score were equal to 95.1%, 95.2%, 95%, and 95.4% when 30% of a target subject's pulse waveforms were combined with five randomly selected source subjects available in the dataset. Experimental findings illustrated that incorporating a pre-training stage with data from different subjects made it viable to discern morphological distinctions in beat-to-beat pulse waveforms under conditions of cognitive or physical workload.
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Affiliation(s)
- Andrea Valerio
- Department of Electronics and Telecommunications, Politecnico di Torino, 10129 Torino, Italy;
| | - Danilo Demarchi
- Department of Electronics and Telecommunications, Politecnico di Torino, 10129 Torino, Italy;
| | - Brendan O’Flynn
- Tyndall National Institute, University College Cork, Lee Maltings Complex, Dyke Parade, T12R5CP Cork, Ireland; (B.O.); (S.T.)
| | - Paolo Motto Ros
- Department of Electronics and Telecommunications, Politecnico di Torino, 10129 Torino, Italy;
| | - Salvatore Tedesco
- Tyndall National Institute, University College Cork, Lee Maltings Complex, Dyke Parade, T12R5CP Cork, Ireland; (B.O.); (S.T.)
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Ding Z, Li W, Wang W, Zhao Z, Zhu Y, Hou B, Zhu L, Chen M, Che L. Highly Sensitive Iontronic Pressure Sensor with Side-by-Side Package Based on Alveoli and Arch Structure. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024; 11:e2309407. [PMID: 38491739 PMCID: PMC11199976 DOI: 10.1002/advs.202309407] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Revised: 01/27/2024] [Indexed: 03/18/2024]
Abstract
Flexible pressure sensors play a significant role in wearable devices and electronic skin. Iontronic pressure sensors with high sensitivity, wide measurement range, and high resolution can meet requirements. Based on the significant deformation characteristics of alveoli to improve compressibility, and the ability of the arch to disperse vertical pressure into horizontal thrust to increase contact area, a graded hollow ball arch (GHBA) microstructure is proposed, greatly improving sensitivity. The fabrication of GHBA ingeniously employs a double-sided structure. One side uses mold casting to create convex structures, while the other utilizes the evaporation of moisture during the curing process to form concave structures. At the same time, a novel side-by-side package structure is proposed, ensuring pressure on flexible substrate is maximally transferred to the GHBA microstructure. Within the range of 0.2 Pa-300 kPa, the iontronic pressure sensor achieves a maximum sensitivity of 10 420.8 kPa-1, pressure resolution of 0.1% under the pressure of 100 kPa, and rapid response/recovery time of 40/35 ms. In wearable devices, it is capable of monitoring dumbbell curl exercises and wirelessly correcting sitting positions. In electronic skin, it can non-contactly detect the location of the wind source and achieve object classification prediction when combined with the CNN model.
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Affiliation(s)
- Zhi Ding
- College of Information Science and Electronic EngineeringZhejiang UniversityHangzhou310027China
- Center for MicroelectronicsShaoxing InstituteZhejiang UniversityShaoxing312035China
| | - Weijian Li
- College of Information Science and Electronic EngineeringZhejiang UniversityHangzhou310027China
| | - Weidong Wang
- College of Information Science and Electronic EngineeringZhejiang UniversityHangzhou310027China
| | - Zhengqian Zhao
- College of Information Science and Electronic EngineeringZhejiang UniversityHangzhou310027China
| | - Ye Zhu
- College of Information Science and Electronic EngineeringZhejiang UniversityHangzhou310027China
| | - Baoyin Hou
- College of Information Science and Electronic EngineeringZhejiang UniversityHangzhou310027China
| | - Lijie Zhu
- College of Information Science and Electronic EngineeringZhejiang UniversityHangzhou310027China
| | - Ming Chen
- College of Information Science and Electronic EngineeringZhejiang UniversityHangzhou310027China
| | - Lufeng Che
- College of Information Science and Electronic EngineeringZhejiang UniversityHangzhou310027China
- Center for MicroelectronicsShaoxing InstituteZhejiang UniversityShaoxing312035China
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Seesaard T, Wongchoosuk C. Flexible and Stretchable Pressure Sensors: From Basic Principles to State-of-the-Art Applications. MICROMACHINES 2023; 14:1638. [PMID: 37630177 PMCID: PMC10456594 DOI: 10.3390/mi14081638] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Revised: 08/14/2023] [Accepted: 08/17/2023] [Indexed: 08/27/2023]
Abstract
Flexible and stretchable electronics have emerged as highly promising technologies for the next generation of electronic devices. These advancements offer numerous advantages, such as flexibility, biocompatibility, bio-integrated circuits, and light weight, enabling new possibilities in diverse applications, including e-textiles, smart lenses, healthcare technologies, smart manufacturing, consumer electronics, and smart wearable devices. In recent years, significant attention has been devoted to flexible and stretchable pressure sensors due to their potential integration with medical and healthcare devices for monitoring human activity and biological signals, such as heartbeat, respiratory rate, blood pressure, blood oxygen saturation, and muscle activity. This review comprehensively covers all aspects of recent developments in flexible and stretchable pressure sensors. It encompasses fundamental principles, force/pressure-sensitive materials, fabrication techniques for low-cost and high-performance pressure sensors, investigations of sensing mechanisms (piezoresistivity, capacitance, piezoelectricity), and state-of-the-art applications.
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Affiliation(s)
- Thara Seesaard
- Department of Physics, Faculty of Science and Technology, Kanchanaburi Rajabhat University, Kanchanaburi 71190, Thailand;
| | - Chatchawal Wongchoosuk
- Department of Physics, Faculty of Science, Kasetsart University, Bangkok 10900, Thailand
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