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Rong D, Li Z, Qi Q, Liu Z, Zhou Z, Xu X. Simulation Analysis of Thermoacoustic Effect of CNT Film with Metasurface-Enhanced Acoustic Autofocusing. NANOMATERIALS (BASEL, SWITZERLAND) 2024; 14:1481. [PMID: 39330639 PMCID: PMC11435258 DOI: 10.3390/nano14181481] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/13/2024] [Revised: 09/08/2024] [Accepted: 09/09/2024] [Indexed: 09/28/2024]
Abstract
This study introduces a novel thermoacoustic (TA) focusing system enhanced by Airy beam-based acoustic metasurfaces, significantly improving acoustic focusing and efficiency. The system integrates a TA emitter, fabricated from carbon nanotube (CNT) films, with a binary acoustic metasurface capable of generating quasi-Airy beams. Through finite element simulations, the system's heat conduction, acoustic focusing, and self-healing properties were thoroughly analyzed. The results demonstrate that the system achieves superior sub-wavelength focusing, tunable focal length via frequency control, and robust self-healing, even in the presence of obstacles. These findings address current limitations in TA emitters and suggest broader applications in medical ultrasound and advanced technology.
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Affiliation(s)
- Dalun Rong
- School of Aeronautics and Astronautics, Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, China;
- School of Civil Engineering, Hunan University of Technology, Zhuzhou 412007, China
| | - Zhe Li
- State Key Laboratory of Structural Analysis, Optimization and CAE Software for Industrial Equipment, School of Mechanics and Aerospace Engineering, Dalian University of Technology, Dalian 116024, China; (Z.L.); (Q.Q.); (Z.Z.)
| | - Qianshou Qi
- State Key Laboratory of Structural Analysis, Optimization and CAE Software for Industrial Equipment, School of Mechanics and Aerospace Engineering, Dalian University of Technology, Dalian 116024, China; (Z.L.); (Q.Q.); (Z.Z.)
| | - Zhengnan Liu
- School of Traffic and Transport Engineering, Changsha University of Science & Technology, Changsha 410114, China;
- Hunan Communications Research Institute Co., Ltd., Changsha 410015, China
| | - Zhenhuan Zhou
- State Key Laboratory of Structural Analysis, Optimization and CAE Software for Industrial Equipment, School of Mechanics and Aerospace Engineering, Dalian University of Technology, Dalian 116024, China; (Z.L.); (Q.Q.); (Z.Z.)
| | - Xinsheng Xu
- State Key Laboratory of Structural Analysis, Optimization and CAE Software for Industrial Equipment, School of Mechanics and Aerospace Engineering, Dalian University of Technology, Dalian 116024, China; (Z.L.); (Q.Q.); (Z.Z.)
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2
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Hou W, Wei Y, Wang Y, Duan S, Guo Z, Tian H, Yang Y, Ren TL. A Large-Scale and Low-Cost Thermoacoustic Loudspeaker Based on Three-Dimensional Graphene Foam. ACS APPLIED MATERIALS & INTERFACES 2024. [PMID: 38683903 DOI: 10.1021/acsami.3c18511] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/02/2024]
Abstract
Graphene is a promising material for thermoacoustic sources due to its extremely low heat capacity per unit area and high thermal conductivity. However, current graphene thermoacoustic devices have limited device area and relatively high cost, which limit their applications of daily use. Here, we adopt a dip-coating method to fabricate a large-scale and cost-effective graphene sound source. This sound source has the three-dimensional (3D) porous structure that can increase the contact area between graphene and air, thus assisting heat to release into the air. In this method, polyurethane (PU) is used as a support, and graphene nanoplates are attached onto the PU skeleton so that a highly flexible graphene foam (GrF) device is obtained. At a measuring distance of 1 mm, it can emit sound at up to 70 dB under the normalized input power of 1 W. Considering its unique porous structure, we establish a thermoacoustic analysis model to simulate the acoustic performance of GrF. Furthermore, the obtained GrF can be made up to 44 in. (100 cm × 50 cm) in size, and it has good flexibility and processability, which broadens the application fields of GrF loudspeakers. It can be attached to the surfaces of objects with different shapes, making it suitable to be used as a large-area speaker in automobiles, houses, and other application scenarios, such as neck mounted speaker. In addition, it can also be widely used as a fully flexible in-ear earphone.
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Affiliation(s)
- Weiwei Hou
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Yuhong Wei
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Yunfan Wang
- Electrical Computer Engineering, University of Michigan, Ann Arbor, Michigan 48109, United States
| | - Shuwen Duan
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Zhanfeng Guo
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - He Tian
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Yi Yang
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Tian-Ling Ren
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
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3
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Li H, Tan P, Rao Y, Bhattacharya S, Wang Z, Kim S, Gangopadhyay S, Shi H, Jankovic M, Huh H, Li Z, Maharjan P, Wells J, Jeong H, Jia Y, Lu N. E-Tattoos: Toward Functional but Imperceptible Interfacing with Human Skin. Chem Rev 2024; 124:3220-3283. [PMID: 38465831 DOI: 10.1021/acs.chemrev.3c00626] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/12/2024]
Abstract
The human body continuously emits physiological and psychological information from head to toe. Wearable electronics capable of noninvasively and accurately digitizing this information without compromising user comfort or mobility have the potential to revolutionize telemedicine, mobile health, and both human-machine or human-metaverse interactions. However, state-of-the-art wearable electronics face limitations regarding wearability and functionality due to the mechanical incompatibility between conventional rigid, planar electronics and soft, curvy human skin surfaces. E-Tattoos, a unique type of wearable electronics, are defined by their ultrathin and skin-soft characteristics, which enable noninvasive and comfortable lamination on human skin surfaces without causing obstruction or even mechanical perception. This review article offers an exhaustive exploration of e-tattoos, accounting for their materials, structures, manufacturing processes, properties, functionalities, applications, and remaining challenges. We begin by summarizing the properties of human skin and their effects on signal transmission across the e-tattoo-skin interface. Following this is a discussion of the materials, structural designs, manufacturing, and skin attachment processes of e-tattoos. We classify e-tattoo functionalities into electrical, mechanical, optical, thermal, and chemical sensing, as well as wound healing and other treatments. After discussing energy harvesting and storage capabilities, we outline strategies for the system integration of wireless e-tattoos. In the end, we offer personal perspectives on the remaining challenges and future opportunities in the field.
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Affiliation(s)
- Hongbian Li
- Department of Aerospace Engineering and Engineering Mechanics, The University of Texas at Austin, Austin, Texas 78712, United States
| | - Philip Tan
- Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, Texas 78712, United States
| | - Yifan Rao
- Department of Aerospace Engineering and Engineering Mechanics, The University of Texas at Austin, Austin, Texas 78712, United States
| | - Sarnab Bhattacharya
- Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, Texas 78712, United States
| | - Zheliang Wang
- Department of Aerospace Engineering and Engineering Mechanics, The University of Texas at Austin, Austin, Texas 78712, United States
| | - Sangjun Kim
- Department of Mechanical Engineering, The University of Texas at Austin, Austin, Texas 78712, United States
| | - Susmita Gangopadhyay
- Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, Texas 78712, United States
| | - Hongyang Shi
- Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, Texas 78712, United States
| | - Matija Jankovic
- Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, Texas 78712, United States
| | - Heeyong Huh
- Department of Aerospace Engineering and Engineering Mechanics, The University of Texas at Austin, Austin, Texas 78712, United States
| | - Zhengjie Li
- Department of Aerospace Engineering and Engineering Mechanics, The University of Texas at Austin, Austin, Texas 78712, United States
| | - Pukar Maharjan
- Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, Texas 78712, United States
| | - Jonathan Wells
- Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, Texas 78712, United States
| | - Hyoyoung Jeong
- Department of Electrical and Computer Engineering, University of California Davis, Davis, California 95616, United States
| | - Yaoyao Jia
- Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, Texas 78712, United States
| | - Nanshu Lu
- Department of Aerospace Engineering and Engineering Mechanics, The University of Texas at Austin, Austin, Texas 78712, United States
- Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, Texas 78712, United States
- Department of Mechanical Engineering, The University of Texas at Austin, Austin, Texas 78712, United States
- Department of Biomedical Engineering, The University of Texas at Austin, Austin, Texas 78712, United States
- Texas Materials Institute, The University of Texas at Austin, Austin, Texas 78712, United States
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4
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Fu J, Deng Z, Liu C, Liu C, Luo J, Wu J, Peng S, Song L, Li X, Peng M, Liu H, Zhou J, Qiao Y. Intelligent, Flexible Artificial Throats with Sound Emitting, Detecting, and Recognizing Abilities. SENSORS (BASEL, SWITZERLAND) 2024; 24:1493. [PMID: 38475029 DOI: 10.3390/s24051493] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Revised: 02/22/2024] [Accepted: 02/22/2024] [Indexed: 03/14/2024]
Abstract
In recent years, there has been a notable rise in the number of patients afflicted with laryngeal diseases, including cancer, trauma, and other ailments leading to voice loss. Currently, the market is witnessing a pressing demand for medical and healthcare products designed to assist individuals with voice defects, prompting the invention of the artificial throat (AT). This user-friendly device eliminates the need for complex procedures like phonation reconstruction surgery. Therefore, in this review, we will initially give a careful introduction to the intelligent AT, which can act not only as a sound sensor but also as a thin-film sound emitter. Then, the sensing principle to detect sound will be discussed carefully, including capacitive, piezoelectric, electromagnetic, and piezoresistive components employed in the realm of sound sensing. Following this, the development of thermoacoustic theory and different materials made of sound emitters will also be analyzed. After that, various algorithms utilized by the intelligent AT for speech pattern recognition will be reviewed, including some classical algorithms and neural network algorithms. Finally, the outlook, challenge, and conclusion of the intelligent AT will be stated. The intelligent AT presents clear advantages for patients with voice impairments, demonstrating significant social values.
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Affiliation(s)
- Junxin Fu
- School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, No. 66, Gongchang Road, Guangming District, Shenzhen 518107, China
- Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou 510275, China
| | - Zhikang Deng
- School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, No. 66, Gongchang Road, Guangming District, Shenzhen 518107, China
- Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou 510275, China
| | - Chang Liu
- School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, No. 66, Gongchang Road, Guangming District, Shenzhen 518107, China
- Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou 510275, China
| | - Chuting Liu
- School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, No. 66, Gongchang Road, Guangming District, Shenzhen 518107, China
- Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou 510275, China
| | - Jinan Luo
- School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, No. 66, Gongchang Road, Guangming District, Shenzhen 518107, China
- Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou 510275, China
| | - Jingzhi Wu
- School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, No. 66, Gongchang Road, Guangming District, Shenzhen 518107, China
- Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou 510275, China
| | - Shiqi Peng
- School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, No. 66, Gongchang Road, Guangming District, Shenzhen 518107, China
- Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou 510275, China
| | - Lei Song
- School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, No. 66, Gongchang Road, Guangming District, Shenzhen 518107, China
- Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou 510275, China
| | - Xinyi Li
- School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, No. 66, Gongchang Road, Guangming District, Shenzhen 518107, China
- Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou 510275, China
| | - Minli Peng
- School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, No. 66, Gongchang Road, Guangming District, Shenzhen 518107, China
- Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou 510275, China
| | - Houfang Liu
- School of Integrated Circuits and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Jianhua Zhou
- School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, No. 66, Gongchang Road, Guangming District, Shenzhen 518107, China
- Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou 510275, China
| | - Yancong Qiao
- School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, No. 66, Gongchang Road, Guangming District, Shenzhen 518107, China
- Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou 510275, China
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5
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Gao X, Yuan L, Xue C, Zhang X, Meng X, Li X. Bubbles-Induced Porous Structure-Based Flexible Piezoresistive Sensors for Speech Recognition. ACS APPLIED MATERIALS & INTERFACES 2024; 16:9532-9543. [PMID: 38345942 DOI: 10.1021/acsami.3c18233] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/23/2024]
Abstract
Flexible piezoresistive sensors with a porous structure that are used in the field of speech recognition are seldom characterized by both high sensitivity and ease of preparation. In this study, a piezoresistive sensor with a porous structure that is both highly sensitive and can be prepared by using a simple method is proposed for speech recognition. The preparation process utilizes the interaction of bubbles generated by ethanol evaporation and active agents with polydimethylsiloxane to produce a porous flexible substrate. This preparation process requires neither templates nor harsh experimental conditions such as a low temperature and a low pressure. Furthermore, the prepared piezoresistive sensor has excellent properties, such as a high sensitivity (27.6 kPa-1), a satisfactory response time (800 μs), and a good stability (10,000 cycles). When used for speech recognition, more than 1500 vocalizations and silent speech signals obtained from subjects saying numbers from "0" to "9" were collected by the sensor for training a convolutional neural network model. The average accuracy of the recognition reached 94.8%. The simple preparation process and the excellent performance of the prepared flexible piezoresistive sensor endow it with a wide application prospect in the field of speech recognition.
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Affiliation(s)
- Xiaoguang Gao
- Institute of Biomedical Precision Testing and Instrumentation, College of Biomedical Engineering, Taiyuan University of Technology, Taiyuan 030024, China
| | - Lin Yuan
- Institute of Biomedical Precision Testing and Instrumentation, College of Biomedical Engineering, Taiyuan University of Technology, Taiyuan 030024, China
| | - Chengzhen Xue
- Institute of Biomedical Precision Testing and Instrumentation, College of Biomedical Engineering, Taiyuan University of Technology, Taiyuan 030024, China
| | - Xiaoliang Zhang
- Institute of Biomedical Precision Testing and Instrumentation, College of Biomedical Engineering, Taiyuan University of Technology, Taiyuan 030024, China
| | - Xuejuan Meng
- Institute of Biomedical Precision Testing and Instrumentation, College of Biomedical Engineering, Taiyuan University of Technology, Taiyuan 030024, China
| | - Xiaochun Li
- Institute of Biomedical Precision Testing and Instrumentation, College of Biomedical Engineering, Taiyuan University of Technology, Taiyuan 030024, China
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6
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Gong S, Lu Y, Yin J, Levin A, Cheng W. Materials-Driven Soft Wearable Bioelectronics for Connected Healthcare. Chem Rev 2024; 124:455-553. [PMID: 38174868 DOI: 10.1021/acs.chemrev.3c00502] [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: 01/05/2024]
Abstract
In the era of Internet-of-things, many things can stay connected; however, biological systems, including those necessary for human health, remain unable to stay connected to the global Internet due to the lack of soft conformal biosensors. The fundamental challenge lies in the fact that electronics and biology are distinct and incompatible, as they are based on different materials via different functioning principles. In particular, the human body is soft and curvilinear, yet electronics are typically rigid and planar. Recent advances in materials and materials design have generated tremendous opportunities to design soft wearable bioelectronics, which may bridge the gap, enabling the ultimate dream of connected healthcare for anyone, anytime, and anywhere. We begin with a review of the historical development of healthcare, indicating the significant trend of connected healthcare. This is followed by the focal point of discussion about new materials and materials design, particularly low-dimensional nanomaterials. We summarize material types and their attributes for designing soft bioelectronic sensors; we also cover their synthesis and fabrication methods, including top-down, bottom-up, and their combined approaches. Next, we discuss the wearable energy challenges and progress made to date. In addition to front-end wearable devices, we also describe back-end machine learning algorithms, artificial intelligence, telecommunication, and software. Afterward, we describe the integration of soft wearable bioelectronic systems which have been applied in various testbeds in real-world settings, including laboratories that are preclinical and clinical environments. Finally, we narrate the remaining challenges and opportunities in conjunction with our perspectives.
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Affiliation(s)
- Shu Gong
- Department of Chemical & Biological Engineering, Monash University, Clayton, Victoria 3800, Australia
| | - Yan Lu
- Department of Chemical & Biological Engineering, Monash University, Clayton, Victoria 3800, Australia
| | - Jialiang Yin
- Department of Chemical & Biological Engineering, Monash University, Clayton, Victoria 3800, Australia
| | - Arie Levin
- Department of Chemical & Biological Engineering, Monash University, Clayton, Victoria 3800, Australia
| | - Wenlong Cheng
- Department of Chemical & Biological Engineering, Monash University, Clayton, Victoria 3800, Australia
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7
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Hu F, Huang Z, Luo C, Yue K. High-sensitivity and ultralow-hysteresis fluorine-rich ionogel strain sensors for multi-environment contact and contactless sensing. MATERIALS HORIZONS 2023; 10:5907-5919. [PMID: 37870851 DOI: 10.1039/d3mh01138k] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/24/2023]
Abstract
Information transduction via soft strain sensors under harsh conditions such as marine, oily liquid, vacuum, and extreme temperatures without excess encapsulation facilitates modern scientific and military exploration. However, most reported soft strain sensors struggle to meet these requirements, especially in complex environments. Herein, a class of fluorine-rich ionogels with tunable ultimate strain, high conductivity, and multi-environment tolerance are designed. Abundant ion-dipole and dipole-dipole interactions lead to excellent miscibility between the hydrophobic ionic liquid and the fluorinated polyacrylate matrix, as well as adhesion to diverse substrates in amphibious environments. The ionogel-based sensors, even in encapsulation-free form, exhibit stable operation with a negligible hysteresis (as low as 0.119%) and high sensitivity (gauge factor of up to 6.54) under amphibious conditions. Multi-environment sensing instances in contact and even contactless forms are also demonstrated. This study opens the door for the artificial syntheses of multi-environment tolerance ionic skins with robust sensing applications in soft electronics and robotics.
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Affiliation(s)
- Faqi Hu
- South China Advanced Institute for Soft Matter Science and Technology and School of Emergent Soft Matter, South China University of Technology, Guangzhou 510640, China.
| | - Zhenkai Huang
- School of Materials Science and Hydrogen Energy, Foshan University, Foshan 528000, China
| | - Chuan Luo
- South China Advanced Institute for Soft Matter Science and Technology and School of Emergent Soft Matter, South China University of Technology, Guangzhou 510640, China.
| | - Kan Yue
- South China Advanced Institute for Soft Matter Science and Technology and School of Emergent Soft Matter, South China University of Technology, Guangzhou 510640, China.
- Jiangsu Key Laboratory of Advanced Functional Polymers Design and Application, Soochow University, Suzhou 215000, China
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8
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Gong S, Zhang X, Nguyen XA, Shi Q, Lin F, Chauhan S, Ge Z, Cheng W. Hierarchically resistive skins as specific and multimetric on-throat wearable biosensors. NATURE NANOTECHNOLOGY 2023; 18:889-897. [PMID: 37106048 DOI: 10.1038/s41565-023-01383-6] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/05/2021] [Accepted: 03/22/2023] [Indexed: 06/19/2023]
Abstract
Resistive skin biosensors refer to a class of imperceptible wearable devices for health monitoring and human-machine interfacing, in which conductive materials are deposited onto or incorporated into an elastomeric polymeric sheet. A wide range of resistive skins has been developed so far to detect a wide variety of biometric signals including blood pressure, skin strain, body temperature and acoustic vibrations; however, they are typically non-specific, with one resistive signal corresponding to a single type of biometric data (one-mode sensors). Here we show a hierarchically resistive skin sensor made of a laminated cracked platinum film, vertically aligned gold nanowires and a percolated gold nanowire film, all integrated into a single sensor. As a result, hierarchically resistive skin displays a staircase-shaped resistive response to tensile strain, with distinct sensing regimes associated to a specific active material. We show that we can, through one resistive signal, identify up to five physical or physiological activities associated with the human throat speech: heartbeats, breathing, touch and neck movement (that is, a multimodal sensor). We develop a frequency/amplitude-based neural network, Deep Hybrid-Spectro, that can automatically disentangle multiple biometrics from a single resistive signal. This system can classify 11 activities-with different combinations of speech, neck movement and touch-with an accuracy of 92.73 ± 0.82% while simultaneously measuring respiration and heart rates. We validated the classification accuracy of several biometrics with an overall accuracy of >82%, demonstrating the generality of our concept.
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Affiliation(s)
- Shu Gong
- Department of Chemical and Biological Engineering, Monash University, Melbourne, Australia
| | - Xin Zhang
- Department of Electrical and Computer Systems Engineering, Monash University, Melbourne, Australia
- Monash Medical AI, Monash University, Melbourne, Australia
| | - Xuan Anh Nguyen
- Department of Mechanical and Aerospace Engineering, Monash University, Melbourne, Australia
| | - Qianqian Shi
- Department of Chemical and Biological Engineering, Monash University, Melbourne, Australia
| | - Fenge Lin
- Department of Chemical and Biological Engineering, Monash University, Melbourne, Australia
| | - Sunita Chauhan
- Department of Mechanical and Aerospace Engineering, Monash University, Melbourne, Australia
| | - Zongyuan Ge
- Department of Electrical and Computer Systems Engineering, Monash University, Melbourne, Australia.
- Monash Medical AI, Monash University, Melbourne, Australia.
- Monash-Airdoc Research Center, Monash University, Melbourne, Australia.
| | - Wenlong Cheng
- Department of Chemical and Biological Engineering, Monash University, Melbourne, Australia.
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9
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Qiao Y, Luo J, Cui T, Liu H, Tang H, Zeng Y, Liu C, Li Y, Jian J, Wu J, Tian H, Yang Y, Ren TL, Zhou J. Soft Electronics for Health Monitoring Assisted by Machine Learning. NANO-MICRO LETTERS 2023; 15:66. [PMID: 36918452 PMCID: PMC10014415 DOI: 10.1007/s40820-023-01029-1] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Accepted: 01/05/2023] [Indexed: 06/18/2023]
Abstract
Due to the development of the novel materials, the past two decades have witnessed the rapid advances of soft electronics. The soft electronics have huge potential in the physical sign monitoring and health care. One of the important advantages of soft electronics is forming good interface with skin, which can increase the user scale and improve the signal quality. Therefore, it is easy to build the specific dataset, which is important to improve the performance of machine learning algorithm. At the same time, with the assistance of machine learning algorithm, the soft electronics have become more and more intelligent to realize real-time analysis and diagnosis. The soft electronics and machining learning algorithms complement each other very well. It is indubitable that the soft electronics will bring us to a healthier and more intelligent world in the near future. Therefore, in this review, we will give a careful introduction about the new soft material, physiological signal detected by soft devices, and the soft devices assisted by machine learning algorithm. Some soft materials will be discussed such as two-dimensional material, carbon nanotube, nanowire, nanomesh, and hydrogel. Then, soft sensors will be discussed according to the physiological signal types (pulse, respiration, human motion, intraocular pressure, phonation, etc.). After that, the soft electronics assisted by various algorithms will be reviewed, including some classical algorithms and powerful neural network algorithms. Especially, the soft device assisted by neural network will be introduced carefully. Finally, the outlook, challenge, and conclusion of soft system powered by machine learning algorithm will be discussed.
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Affiliation(s)
- Yancong Qiao
- School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, No. 66, Gongchang Road, Guangming District, Shenzhen, 518107, People's Republic of China.
- Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou, 510275, People's Republic of China.
| | - Jinan Luo
- School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, No. 66, Gongchang Road, Guangming District, Shenzhen, 518107, People's Republic of China
- Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou, 510275, People's Republic of China
| | - Tianrui Cui
- School of Integrated Circuits and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100084, People's Republic of China
| | - Haidong Liu
- School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, No. 66, Gongchang Road, Guangming District, Shenzhen, 518107, People's Republic of China
- Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou, 510275, People's Republic of China
| | - Hao Tang
- School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, No. 66, Gongchang Road, Guangming District, Shenzhen, 518107, People's Republic of China
- Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou, 510275, People's Republic of China
| | - Yingfen Zeng
- School of Integrated Circuits and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100084, People's Republic of China
| | - Chang Liu
- School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, No. 66, Gongchang Road, Guangming District, Shenzhen, 518107, People's Republic of China
- Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou, 510275, People's Republic of China
| | - Yuanfang Li
- School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, No. 66, Gongchang Road, Guangming District, Shenzhen, 518107, People's Republic of China
- Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou, 510275, People's Republic of China
| | - Jinming Jian
- School of Integrated Circuits and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100084, People's Republic of China
| | - Jingzhi Wu
- School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, No. 66, Gongchang Road, Guangming District, Shenzhen, 518107, People's Republic of China
- Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou, 510275, People's Republic of China
| | - He Tian
- School of Integrated Circuits and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100084, People's Republic of China
| | - Yi Yang
- School of Integrated Circuits and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100084, People's Republic of China
| | - Tian-Ling Ren
- School of Integrated Circuits and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100084, People's Republic of China.
| | - Jianhua Zhou
- School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, No. 66, Gongchang Road, Guangming District, Shenzhen, 518107, People's Republic of China.
- Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou, 510275, People's Republic of China.
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10
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Lu T, Ji S, Jin W, Yang Q, Luo Q, Ren TL. Biocompatible and Long-Term Monitoring Strategies of Wearable, Ingestible and Implantable Biosensors: Reform the Next Generation Healthcare. SENSORS (BASEL, SWITZERLAND) 2023; 23:2991. [PMID: 36991702 PMCID: PMC10054135 DOI: 10.3390/s23062991] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Revised: 12/31/2022] [Accepted: 01/04/2023] [Indexed: 06/19/2023]
Abstract
Sensors enable the detection of physiological indicators and pathological markers to assist in the diagnosis, treatment, and long-term monitoring of diseases, in addition to playing an essential role in the observation and evaluation of physiological activities. The development of modern medical activities cannot be separated from the precise detection, reliable acquisition, and intelligent analysis of human body information. Therefore, sensors have become the core of new-generation health technologies along with the Internet of Things (IoTs) and artificial intelligence (AI). Previous research on the sensing of human information has conferred many superior properties on sensors, of which biocompatibility is one of the most important. Recently, biocompatible biosensors have developed rapidly to provide the possibility for the long-term and in-situ monitoring of physiological information. In this review, we summarize the ideal features and engineering realization strategies of three different types of biocompatible biosensors, including wearable, ingestible, and implantable sensors from the level of sensor designing and application. Additionally, the detection targets of the biosensors are further divided into vital life parameters (e.g., body temperature, heart rate, blood pressure, and respiratory rate), biochemical indicators, as well as physical and physiological parameters based on the clinical needs. In this review, starting from the emerging concept of next-generation diagnostics and healthcare technologies, we discuss how biocompatible sensors revolutionize the state-of-art healthcare system unprecedentedly, as well as the challenges and opportunities faced in the future development of biocompatible health sensors.
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Affiliation(s)
- Tian Lu
- School of Integrated Circuit and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Shourui Ji
- School of Integrated Circuit and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Weiqiu Jin
- Shanghai Lung Cancer Center, Shanghai Chest Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Qisheng Yang
- School of Integrated Circuit and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Qingquan Luo
- Shanghai Lung Cancer Center, Shanghai Chest Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Tian-Ling Ren
- School of Integrated Circuit and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
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11
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Yang Q, Jin W, Zhang Q, Wei Y, Guo Z, Li X, Yang Y, Luo Q, Tian H, Ren TL. Mixed-modality speech recognition and interaction using a wearable artificial throat. NAT MACH INTELL 2023. [DOI: 10.1038/s42256-023-00616-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/25/2023]
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12
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Wang Y, Cui TR, Gou GY, Li XS, Qiao YC, Li D, Xu JD, Guo YZ, Tian H, Yang Y, Ren TL. An Ultra-Sensitive and Multifunctional Electronic Skin with Synergetic Network of Graphene and CNT. NANOMATERIALS (BASEL, SWITZERLAND) 2022; 13:179. [PMID: 36616089 PMCID: PMC9823652 DOI: 10.3390/nano13010179] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Revised: 12/21/2022] [Accepted: 12/27/2022] [Indexed: 06/17/2023]
Abstract
Electronic skin (e-skin) has attracted tremendous interest due to its diverse potential applications, including in physiological signal detection, health monitoring, and artificial throats. However, the major drawbacks of traditional e-skin are the weak adhesion of substrates, incompatibility between sensitivity and stretchability, and its single function. These shortcomings limit the application of e-skin and increase the complexity of its multifunctional integration. Herein, the synergistic network of crosslinked SWCNTs within and between multilayered graphene layers was directly drip coated onto the PU thin film with self-adhesion to fabricate versatile e-skin. The excellent mechanical properties of prepared e-skin arise from the sufficient conductive paths guaranteed by SWCNTs in small and large deformation under various strains. The prepared e-skin exhibits a low detection limit, as small as 0.5% strain, and compatibility between sensitivity and stretchability with a gauge factor (GF) of 964 at a strain of 0-30%, and 2743 at a strain of 30-60%. In physiological signals detection application, the e-skin demonstrates the detection of subtle motions, such as artery pulse and blinking, as well as large body motions, such as knee joint bending, elbow movement, and neck movement. In artificial throat application, the e-skin integrates sound recognition and sound emitting and shows clear and distinct responses between different throat muscle movements and different words for sound signal acquisition and recognition, in conjunction with superior sound emission performance with a sound spectrum response of 71 dB (f = 12.5 kHz). Overall, the presented comprehensive study of novel materials, structures, properties, and mechanisms offers promising potential in physiological signals detection and artificial throat applications.
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Affiliation(s)
- Yu Wang
- School of Integrated Circuit, Tsinghua University, Beijing 100084, China
- Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Tian-Rui Cui
- School of Integrated Circuit, Tsinghua University, Beijing 100084, China
- Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Guang-Yang Gou
- School of Integrated Circuit, Tsinghua University, Beijing 100084, China
- Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Xiao-Shi Li
- School of Integrated Circuit, Tsinghua University, Beijing 100084, China
- Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Yan-Cong Qiao
- School of Integrated Circuit, Tsinghua University, Beijing 100084, China
- Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Ding Li
- School of Integrated Circuit, Tsinghua University, Beijing 100084, China
- Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Jian-Dong Xu
- School of Integrated Circuit, Tsinghua University, Beijing 100084, China
- Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Yi-Zhe Guo
- School of Integrated Circuit, Tsinghua University, Beijing 100084, China
- Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - He Tian
- School of Integrated Circuit, Tsinghua University, Beijing 100084, China
- Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Yi Yang
- School of Integrated Circuit, Tsinghua University, Beijing 100084, China
- Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Tian-Ling Ren
- School of Integrated Circuit, Tsinghua University, Beijing 100084, China
- Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
- Center for Flexible Electronics Technology, Tsinghua University, Beijing 100084, China
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13
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Li C, Xiong Z, Zhou L, Huang W, He Y, Li L, Shi H, Lu J, Wang J, Li D, Yin S. Interfacing Perforated Eardrums with Graphene-Based Membranes for Broadband Hearing Recovery. Adv Healthc Mater 2022; 11:e2201471. [PMID: 35899802 DOI: 10.1002/adhm.202201471] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2022] [Indexed: 01/28/2023]
Abstract
Eardrum perforation and associated hearing loss is a global health problem. Grafting perforated eardrum with autologous tissues in clinic can restore low-frequency hearing but often leaves poor recovery of high-frequency hearing. In this study, the potential of incorporating a thin multilayered graphene membrane (MGM) into the eardrum for broadband hearing recovery in rats is examined. The MGM shows good biocompatibility and biostability to promote the growth of eardrum cells in a regulated manner with little sign of tissue rejection and inflammatory response. After three weeks of implantation, the MGM is found to be encapsulated by a thin layer of newly grown tissue on both sides without a significant folded overgrowth that is often seen in natural healing. The perforation is well sealed, and broadband hearing recovery (1-32 kHz) is enabled and maintained for at least 2 months. Mechanical simulations show that the high elastic modulus of MGM and thin thickness of the reconstructed eardrum play a critical role in the recovery of high-frequency hearing. This work demonstrates the promise of the use of MGM as a functional graft for perforated eardrum to recover hearing in the broadband frequency region and suggests a new acoustics-related medical application for graphene-related 2D materials.
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Affiliation(s)
- Chunyan Li
- Department of Otorhinolaryngology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, 200233, China
| | - Zhiyuan Xiong
- Department of Chemical Engineering, The University of Melbourne, Melbourne, Victoria, 3010, Australia
| | - Lei Zhou
- Department of Otorhinolaryngology-Head and Neck Surgery, Zhongshan Hospital affiliated to Fudan University, Shanghai, 200032, China
| | | | - Yushi He
- Shanghai Electrochemical Energy Devices Research Center, School of Chemistry and Chemical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Linpeng Li
- Department of Otorhinolaryngology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, 200233, China
| | - Haibo Shi
- Department of Otorhinolaryngology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, 200233, China
| | - Jiayu Lu
- Department of Stomatology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, 200233, China
| | - Jian Wang
- School of Communication Science and Disorders, Dalhousie University, Halifax, B3J 1Y6, Canada
| | - Dan Li
- Department of Chemical Engineering, The University of Melbourne, Melbourne, Victoria, 3010, Australia
| | - Shankai Yin
- Department of Otorhinolaryngology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, 200233, China
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14
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Yang Y, Wei Y, Guo Z, Hou W, Liu Y, Tian H, Ren TL. From Materials to Devices: Graphene toward Practical Applications. SMALL METHODS 2022; 6:e2200671. [PMID: 36008156 DOI: 10.1002/smtd.202200671] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Indexed: 06/15/2023]
Abstract
Graphene, as an emerging 2D material, has been playing an important role in flexible electronics since its discovery in 2004. The representative fabrication methods of graphene include mechanical exfoliation, liquid-phase exfoliation, chemical vapor deposition, redox reaction, etc. Based on its excellent mechanical, electrical, thermo-acoustical, optical, and other properties, graphene has made a great progress in the development of mechanical sensors, microphone, sound source, electrophysiological detection, solar cells, synaptic transistors, light-emitting devices, and so on. In different application fields, large-scale, low-cost, high-quality, and excellent performance are important factors that limit the industrialization development of graphene. Therefore, laser scribing technology, roll-to-roll technology is used to reduce the cost. High-quality graphene can be obtained through chemical vapor deposition processes. The performance can be improved through the design of structure of the devices, and the homogeneity and stability of devices can be achieved by mechanized machining means. In total, graphene devices show promising prospect for the practical fields of sports monitoring, health detection, voice recognition, energy, etc. There is a hot issue for industry to create and maintain the market competitiveness of graphene products through increasing its versatility and killer application fields.
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Affiliation(s)
- Yi Yang
- School of Integrated Circuits & Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100084, China
| | - Yuhong Wei
- School of Integrated Circuits & Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100084, China
| | - Zhanfeng Guo
- School of Integrated Circuits & Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100084, China
| | - Weiwei Hou
- School of Materials Science and Engineering, Tsinghua University, Beijing, 100084, China
| | - Yingjie Liu
- School of Materials Science and Engineering, Tsinghua University, Beijing, 100084, China
| | - He Tian
- School of Integrated Circuits & Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100084, China
| | - Tian-Ling Ren
- School of Integrated Circuits & Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100084, China
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15
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Yang Q, Liu N, Yin J, Tian H, Yang Y, Ren TL. Understanding the Origin of Tensile Response in a Graphene Textile Strain Sensor with Negative Differential Resistance. ACS NANO 2022; 16:14230-14238. [PMID: 36094408 DOI: 10.1021/acsnano.2c04348] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
The flexible strain sensors based on the textile substrate have natural flexibility, high sensitivity, and wide-range tensile response. However, the textile's complex and anisotropic substructure leads to a negative differential resistance (NDR) response, lacking a deeper understanding of the mechanism. Therefore, we examined a graphene textile strain sensor with a conspicuous NDR tensile response, providing a requisite research platform for mechanism investigation. The pioneering measurement of single fiber bundles confirmed the existence of the NDR effect on the subgeometry scale. Based on the in situ characterization of tensile morphology and measurement, we conducted quantitative behavior analyses to reveal the origin of tensile electrical responses in the full range comprehensively. The results showed that the dominant factor in generating the NDR effect is the relative displacement of fibers within the textile bundles. Based on the neural spiking-like tensile response, we further demonstrated the application potential of the textile strain sensor in threshold detection and near-sensor signal processing. The proposed NDR behavior model would provide a reference for the design and application of wearable intelligent textiles.
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Affiliation(s)
- Qisheng Yang
- School of Integrated Circuits & Beijing National Research on Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Ning Liu
- School of Integrated Circuits & Beijing National Research on Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Jiaju Yin
- School of Integrated Circuits & Beijing National Research on Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
- School of Aerospace Engineering, Tsinghua University, Beijing 100084, China
| | - He Tian
- School of Integrated Circuits & Beijing National Research on Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Yi Yang
- School of Integrated Circuits & Beijing National Research on Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Tian-Ling Ren
- School of Integrated Circuits & Beijing National Research on Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
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16
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Ismail Z, W Idris WF, Abdullah AH. Graphene-based temperature, humidity, and strain sensor: A review on progress, characterization, and potential applications during Covid-19 pandemic. SENSORS INTERNATIONAL 2022; 3:100183. [PMID: 35633818 PMCID: PMC9126002 DOI: 10.1016/j.sintl.2022.100183] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/25/2021] [Revised: 05/19/2022] [Accepted: 05/19/2022] [Indexed: 11/24/2022] Open
Abstract
Graphene's potential as material for wearable, highly sensitive and robust sensor in various fields of technology has been widely investigated until now in order to capitalize on its unique intrinsic physical and chemical properties. In the wake of Covid-19 pandemic, it has been noticed that there are various potentials roles that can be fulfilled by graphene-based temperature, humidity and strain sensor, whose roles has not been widely explored to date. This paper takes the liberty to mainly highlight the progress layout and characterization technique for graphene-based sensor while including a brief discussion on the possible strategy of sensing data analysis that can be employed to minimize and prevent the risk of Covid-19 infection within a living community. While majority of the reported sensor is still in the in-progress status, its highlighted role in this work may provide a brief idea on how the ongoing research in graphene-based sensor may lead to the future implementation of the device for routine healthcare check-up and diagnostic point-care during and post-pandemic era. On the other hand, the sensitivity and response time data against working temperature, humidity and strain range that are provided could serve as a reference for benchmarking purpose, which certainly would help enthusiast in the development of a graphene-based sensor with a better performance for the future.
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17
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Liu MY, Hang CZ, Wu XY, Zhu LY, Wen XH, Wang Y, Zhao XF, Lu HL. Investigation of stretchable strain sensor based on CNT/AgNW applied in smart wearable devices. NANOTECHNOLOGY 2022; 33:255501. [PMID: 35299168 DOI: 10.1088/1361-6528/ac5ee6] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/11/2021] [Accepted: 03/17/2022] [Indexed: 05/23/2023]
Abstract
Stretchable strain sensor, an important paradigm of wearable sensor which can be attached onto clothing or even human skin, is widely used in healthcare, human motion monitoring and human-machine interaction. Pattern-available and facile manufacturing process for strain sensor is pursued all the time. A carbon nanotube (CNT)/silver nanowire (AgNW)-based stretchable strain sensor fabricated by a facile process is reported here. The strain sensor exhibits a considerable Gauge factor of 6.7, long-term durability (>1000 stretching cycles), fast response and recovery (420 ms and 600 ms, respectively), hence the sensor can fulfill the measurement of finger movement. Accordingly, a smart glove comprising a sensor array and a flexible printed circuit board is assembled to detect the bending movement of five fingers simultaneously. Moreover, the glove is wireless and basically fully flexible, it can detect the finger bending of wearer and display the responses distinctly on an APP of a smart phone or a host computer. Our strain senor and smart glove will broaden the materials and applications of wearable sensors.
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Affiliation(s)
- Meng-Yang Liu
- State Key Laboratory of ASIC and System, Shanghai Institute of Intelligent Electronics & Systems, School of Microelectronics, Fudan University, 200433 Shanghai, People's Republic of China
| | - Cheng-Zhou Hang
- State Key Laboratory of ASIC and System, Shanghai Institute of Intelligent Electronics & Systems, School of Microelectronics, Fudan University, 200433 Shanghai, People's Republic of China
| | - Xue-Yan Wu
- State Key Laboratory of ASIC and System, Shanghai Institute of Intelligent Electronics & Systems, School of Microelectronics, Fudan University, 200433 Shanghai, People's Republic of China
| | - Li-Yuan Zhu
- State Key Laboratory of ASIC and System, Shanghai Institute of Intelligent Electronics & Systems, School of Microelectronics, Fudan University, 200433 Shanghai, People's Republic of China
| | - Xiao-Hong Wen
- State Key Laboratory of ASIC and System, Shanghai Institute of Intelligent Electronics & Systems, School of Microelectronics, Fudan University, 200433 Shanghai, People's Republic of China
| | - Yang Wang
- State Key Laboratory of ASIC and System, Shanghai Institute of Intelligent Electronics & Systems, School of Microelectronics, Fudan University, 200433 Shanghai, People's Republic of China
| | - Xue-Feng Zhao
- State Key Laboratory of ASIC and System, Shanghai Institute of Intelligent Electronics & Systems, School of Microelectronics, Fudan University, 200433 Shanghai, People's Republic of China
| | - Hong-Liang Lu
- State Key Laboratory of ASIC and System, Shanghai Institute of Intelligent Electronics & Systems, School of Microelectronics, Fudan University, 200433 Shanghai, People's Republic of China
- Yiwu Research Institute of Fudan University, Chengbei Road, Yiwu City, 322000 Zhejiang, People's Republic of China
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18
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Qiao Y, Tang H, Liu H, Jian J, Ji S, Han F, Liu Z, Liu Y, Li Y, Cui T, Cai J, Gou G, Zhou B, Yang Y, Ren TL, Zhou J. Intelligent and highly sensitive strain sensor based on indium tin oxide micromesh with a high crack density. NANOSCALE 2022; 14:4234-4243. [PMID: 35234767 DOI: 10.1039/d1nr08005a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Cracks play an important role in strain sensors. However, a systematic analysis of how cracks influence the strain sensors has not been proposed. In this work, an intelligent and highly sensitive strain sensor based on indium tin oxide (ITO)/polyurethane (PU) micromesh is realized. The micromesh has good skin compatibility, water vapor permeability, and stability. Due to the color of the ITO/PU micromesh, it can be invisible on the skin. Based on the fragility of ITO, the density and resistance of cracks in the micromesh are greatly improved. Therefore, the ITO/PU micromesh strain sensor (IMSS) has an ultrahigh gauge factor (744.3). In addition, a finite element model based on four resistance layers is proposed to explain the performance of the IMSS and show the importance of high-density cracks. Compared with other strain sensors based on low-density cracks, the IMSS based on high-density cracks has larger sensitivity and better linearity. Physiological signals, such as respiration, pulse, and joint motion, can be monitored using the IMSS self-fixed on the skin. Finally, an invisible and artificial throat has been realized by combining the IMSS with a convolutional neural network algorithm. The artificial throat can translate the throat vibrations of the tester automatically with an accuracy of 86.5%. This work has great potential in health care and language function reconstruction.
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Affiliation(s)
- Yancong Qiao
- School of Biomedical Engineering, Sun Yat-Sen University, Shenzhen, 518107, China.
| | - Hao Tang
- School of Biomedical Engineering, Sun Yat-Sen University, Shenzhen, 518107, China.
| | - Haidong Liu
- School of Biomedical Engineering, Sun Yat-Sen University, Shenzhen, 518107, China.
| | - Jinming Jian
- School of Integrated Circuits (SIC) and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100084, China.
| | - Shourui Ji
- School of Integrated Circuits (SIC) and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100084, China.
| | - Fei Han
- CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences (CAS), Shenzhen 518055, China
| | - Zhiyuan Liu
- CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences (CAS), Shenzhen 518055, China
| | - Ying Liu
- School of Biomedical Engineering, Sun Yat-Sen University, Shenzhen, 518107, China.
| | - Yuanfang Li
- School of Biomedical Engineering, Sun Yat-Sen University, Shenzhen, 518107, China.
| | - Tianrui Cui
- School of Integrated Circuits (SIC) and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100084, China.
| | - Jingxuan Cai
- School of Biomedical Engineering, Sun Yat-Sen University, Shenzhen, 518107, China.
| | - Guangyang Gou
- School of Integrated Circuits (SIC) and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100084, China.
| | - Bingpu Zhou
- Joint Key Laboratory of the Ministry of Education, Institute of Applied Physics and Materials Engineering, University of Macau, Avenida da Universidade, Taipa, Macau 999078, China
| | - Yi Yang
- School of Integrated Circuits (SIC) and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100084, China.
| | - Tian-Ling Ren
- School of Integrated Circuits (SIC) and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100084, China.
| | - Jianhua Zhou
- School of Biomedical Engineering, Sun Yat-Sen University, Shenzhen, 518107, China.
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19
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Falco A, Marín-Sánchez A, Loghin FC, Castillo E, Salinas-Castillo A, Salmerón JF, Rivadeneyra A. Paper and Salt: Biodegradable NaCl-Based Humidity Sensors for Sustainable Electronics. FRONTIERS IN ELECTRONICS 2022. [DOI: 10.3389/felec.2022.838472] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Flexible and thin-film humidity sensors are currently attracting the attention of the scientific community due to their portability and reduced size, which are highly useful traits for use in the Internet o Things (IoT) industry. Furthermore, in order to perform efficient and profitable mass production, it is necessary to develop a cost-effective and reproducible fabrication process and materials. Green fabrication methods and biodegradable materials would also minimize the environmental impact and create a sustainable IoT development. In this paper, flexible humidity sensors based on a common salt (NaCl) sensing layer are reported. Our sensors and the fabrication techniques employed, such as dip and spray coating, provide a biodegradable, low cost, and highly reproducible device. One of the sensors reported presents a typical resistive behaviour from 40% RH up to 85% RH with a sensitivity of −0.21 (Z/%RH). The performance of the sensors obtained with several fabrication techniques is studied and reported at multiple frequencies from 100 Hz to 10 MHz, showcasing its versatility and robustness.
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20
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Yang Z, Lv S, Zhang Y, Wang J, Jiang L, Jia X, Wang C, Yan X, Sun P, Duan Y, Liu F, Lu G. Self-Assembly 3D Porous Crumpled MXene Spheres as Efficient Gas and Pressure Sensing Material for Transient All-MXene Sensors. NANO-MICRO LETTERS 2022; 14:56. [PMID: 35122157 PMCID: PMC8816976 DOI: 10.1007/s40820-022-00796-7] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Accepted: 12/28/2021] [Indexed: 05/04/2023]
Abstract
Environmentally friendly degradable sensors with both hazardous gases and pressure efficient sensing capabilities are highly desired for various promising applications, including environmental pollution monitoring/prevention, wisdom medical, wearable smart devices, and artificial intelligence. However, the transient gas and pressure sensors based on only identical sensing material that concurrently meets the above detection needs have not been reported. Here, we present transient all-MXene NO2 and pressure sensors employing three-dimensional porous crumpled MXene spheres prepared by ultrasonic spray pyrolysis technology as the sensing layer, accompanied with water-soluble polyvinyl alcohol substrates embedded with patterned MXene electrodes. The gas sensor achieves a ppb-level of highly selective NO2 sensing, with a response of up to 12.11% at 5 ppm NO2 and a detection range of 50 ppb-5 ppm, while the pressure sensor has an extremely wide linear pressure detection range of 0.14-22.22 kPa and fast response time of 34 ms. In parallel, all-MXene NO2 and pressure sensors can be rapidly degraded in medical H2O2 within 6 h. This work provides a new avenue toward environmental monitoring, human physiological signal monitoring, and recyclable transient electronics.
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Affiliation(s)
- Zijie Yang
- State Key Laboratory of Integrated Optoelectronics, College of Electronic Science and Engineering, Jilin University, 2699 Qianjin Street, Changchun, 130012, People's Republic of China
| | - Siyuan Lv
- State Key Laboratory of Integrated Optoelectronics, College of Electronic Science and Engineering, Jilin University, 2699 Qianjin Street, Changchun, 130012, People's Republic of China
| | - Yueying Zhang
- State Key Laboratory of Integrated Optoelectronics, College of Electronic Science and Engineering, Jilin University, 2699 Qianjin Street, Changchun, 130012, People's Republic of China
| | - Jing Wang
- School of Electronic and Information Engineering, Changchun University of Science and Technology, Changchun, 130022, People's Republic of China
| | - Li Jiang
- State Key Laboratory of Integrated Optoelectronics, College of Electronic Science and Engineering, Jilin University, 2699 Qianjin Street, Changchun, 130012, People's Republic of China
| | - Xiaoteng Jia
- State Key Laboratory of Integrated Optoelectronics, College of Electronic Science and Engineering, Jilin University, 2699 Qianjin Street, Changchun, 130012, People's Republic of China.
| | - Chenguang Wang
- State Key Laboratory of Integrated Optoelectronics, College of Electronic Science and Engineering, Jilin University, 2699 Qianjin Street, Changchun, 130012, People's Republic of China
| | - Xu Yan
- State Key Laboratory of Integrated Optoelectronics, College of Electronic Science and Engineering, Jilin University, 2699 Qianjin Street, Changchun, 130012, People's Republic of China
| | - Peng Sun
- State Key Laboratory of Integrated Optoelectronics, College of Electronic Science and Engineering, Jilin University, 2699 Qianjin Street, Changchun, 130012, People's Republic of China
| | - Yu Duan
- State Key Laboratory of Integrated Optoelectronics, College of Electronic Science and Engineering, Jilin University, 2699 Qianjin Street, Changchun, 130012, People's Republic of China
| | - Fangmeng Liu
- State Key Laboratory of Integrated Optoelectronics, College of Electronic Science and Engineering, Jilin University, 2699 Qianjin Street, Changchun, 130012, People's Republic of China.
| | - Geyu Lu
- State Key Laboratory of Integrated Optoelectronics, College of Electronic Science and Engineering, Jilin University, 2699 Qianjin Street, Changchun, 130012, People's Republic of China
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21
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Carvalho AF, Kulyk B, Fernandes AJS, Fortunato E, Costa FM. A Review on the Applications of Graphene in Mechanical Transduction. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2022; 34:e2101326. [PMID: 34288155 DOI: 10.1002/adma.202101326] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Revised: 04/26/2021] [Indexed: 05/26/2023]
Abstract
A pressing need to develop low-cost, environmentally friendly, and sensitive sensors has arisen with the advent of the always-connected paradigm of the internet-of-things (IoT). In particular, mechanical sensors have been widely studied in recent years for applications ranging from health monitoring, through mechanical biosignals, to structure integrity analysis. On the other hand, innovative ways to implement mechanical actuation have also been the focus of intense research in an attempt to close the circle of human-machine interaction, and move toward applications in flexible electronics. Due to its potential scalability, disposability, and outstanding properties, graphene has been thoroughly studied in the field of mechanical transduction. The applications of graphene in mechanical transduction are reviewed here. An overview of sensor and actuator applications is provided, covering different transduction mechanisms such as piezoresistivity, capacitive sensing, optically interrogated displacement, piezoelectricity, triboelectricity, electrostatic actuation, chemomechanical and thermomechanical actuation, as well as thermoacoustic emission. A critical review of the main approaches is presented within the scope of a wider discussion on the future of this so-called wonder material in the field of mechanical transduction.
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Affiliation(s)
- Alexandre F Carvalho
- I3N-Aveiro, Department of Physics, University of Aveiro, Aveiro, 3810-193, Portugal
| | - Bohdan Kulyk
- I3N-Aveiro, Department of Physics, University of Aveiro, Aveiro, 3810-193, Portugal
| | | | - Elvira Fortunato
- I3N/CENIMAT, Materials Science Department, Faculty of Sciences and Technology, Universidade NOVA de Lisboa and CEMOP/UNINOVA, Caparica, 2829-516, Portugal
| | - Florinda M Costa
- I3N-Aveiro, Department of Physics, University of Aveiro, Aveiro, 3810-193, Portugal
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22
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Meng J, Wang T, Zhu H, Ji L, Bao W, Zhou P, Chen L, Sun QQ, Zhang DW. Integrated In-Sensor Computing Optoelectronic Device for Environment-Adaptable Artificial Retina Perception Application. NANO LETTERS 2022; 22:81-89. [PMID: 34962129 DOI: 10.1021/acs.nanolett.1c03240] [Citation(s) in RCA: 48] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
With the development and application of artificial intelligence, there is an appeal to the exploitation of various sensors and memories. As the most important perception of human beings, vision occupies more than 80% of all the received information. Inspired by biological eyes, an artificial retina based on 2D Janus MoSSe was fabricated, which could simulate functions of visual perception with electronic/ion and optical comodulation. Furthermore, inspired by human brain, sensing, memory, and neuromorphic computing functions were integrated on one device for multifunctional intelligent electronics, which was beneficial for scalability and high efficiency. Through the formation of faradic electric double layer (EDL) at the metal-oxide/electrolyte interfaces could realize synaptic weight changes. On the basis of the optoelectronic performances, light adaptation of biological eyes, preprocessing, and recognition of handwritten digits were implemented successfully. This work may provide a strategy for the future integrated sensing-memory-processing device for optoelectronic artificial retina perception application.
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Affiliation(s)
- Jialin Meng
- State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, China
| | - Tianyu Wang
- State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, China
| | - Hao Zhu
- State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, China
- National Integrated Circuit Innovation Center, No. 825 Zhangheng Road, Shanghai 201203, China
| | - Li Ji
- State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, China
- National Integrated Circuit Innovation Center, No. 825 Zhangheng Road, Shanghai 201203, China
| | - Wenzhong Bao
- State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, China
| | - Peng Zhou
- State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, China
- National Integrated Circuit Innovation Center, No. 825 Zhangheng Road, Shanghai 201203, China
| | - Lin Chen
- State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, China
- National Integrated Circuit Innovation Center, No. 825 Zhangheng Road, Shanghai 201203, China
| | - Qing-Qing Sun
- State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, China
- National Integrated Circuit Innovation Center, No. 825 Zhangheng Road, Shanghai 201203, China
| | - David Wei Zhang
- State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, China
- National Integrated Circuit Innovation Center, No. 825 Zhangheng Road, Shanghai 201203, China
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23
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Machine Learning Methods for Automatic Silent Speech Recognition Using a Wearable Graphene Strain Gauge Sensor. SENSORS 2021; 22:s22010299. [PMID: 35009845 PMCID: PMC8749657 DOI: 10.3390/s22010299] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Revised: 12/25/2021] [Accepted: 12/28/2021] [Indexed: 12/24/2022]
Abstract
Silent speech recognition is the ability to recognise intended speech without audio information. Useful applications can be found in situations where sound waves are not produced or cannot be heard. Examples include speakers with physical voice impairments or environments in which audio transference is not reliable or secure. Developing a device which can detect non-auditory signals and map them to intended phonation could be used to develop a device to assist in such situations. In this work, we propose a graphene-based strain gauge sensor which can be worn on the throat and detect small muscle movements and vibrations. Machine learning algorithms then decode the non-audio signals and create a prediction on intended speech. The proposed strain gauge sensor is highly wearable, utilising graphene’s unique and beneficial properties including strength, flexibility and high conductivity. A highly flexible and wearable sensor able to pick up small throat movements is fabricated by screen printing graphene onto lycra fabric. A framework for interpreting this information is proposed which explores the use of several machine learning techniques to predict intended words from the signals. A dataset of 15 unique words and four movements, each with 20 repetitions, was developed and used for the training of the machine learning algorithms. The results demonstrate the ability for such sensors to be able to predict spoken words. We produced a word accuracy rate of 55% on the word dataset and 85% on the movements dataset. This work demonstrates a proof-of-concept for the viability of combining a highly wearable graphene strain gauge and machine leaning methods to automate silent speech recognition.
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Beduk T, de Oliveira Filho JI, Ait Lahcen A, Mani V, Salama KN. Inherent Surface Activation of Laser-Scribed Graphene Decorated with Au and Ag Nanoparticles: Simultaneous Electrochemical Behavior toward Uric Acid and Dopamine. LANGMUIR : THE ACS JOURNAL OF SURFACES AND COLLOIDS 2021; 37:13890-13902. [PMID: 34787434 DOI: 10.1021/acs.langmuir.1c02379] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Laser-scribed graphene electrodes (LSGEs) have attracted great attention for the development of electrochemical (bio)sensors due to their excellent electronic properties, large surface area, and high porosity, which enhances the electrons' transfer rate. An increasing active surface area and defect sites are the quickest way to amplify the electrochemical sensing attributes of the electrodes. Here, we have found that the activation procedure coupled to the electrodeposition of metal nanoparticles resulted in a significant amplification of the active area and the analytical performance. This preliminary study is supported by the demonstration of the simultaneous electrochemical sensing of dopamine (DA) and uric acid (UA) by the electrochemically activated LSGEs (LSGE*s). Furthermore, the electrodeposition of two different metal nanoparticles, gold (Au) and silver (Ag), was performed in multiple combinations on working and reference electrodes to investigate the enhancement in the electrochemical response of LSGE*s. Current enhancements of 32, 27, and 35% were observed from LSGE* with WE:Au/RE:LSG/CE:LSGE, WE:Au/RE:Au/CE:LSGE, and WE:Au/RE:Ag/CE:LSGE, compared to the same combinations of LSGEs without any surface activation. A homemade and practical potentiostat, KAUSTat, was used in these electrochemical depositions in this study. Among all of the combinations, the surface area was increased 1.6-, 2.0-, and 1.2-fold for WE:Au/RE:LSG/CE:LSGE, WE:Au/RE:Au/CE:LSGE, and WE:Au/RE:Ag/CE:LSGE prepared from LSGE*s, respectively. To evaluate the analytical performance, DA and UA were detected simultaneously in the presence of ascorbic acid. The LODs of DA and UA are calculated to be ∼0.8 and ∼0.6 μM, respectively. Hence, this study has the potential to open new insights into new surface activation strategies with a combination of one-step nanostructured metal depositions by a custom-made potentiostat. This novel strategy could be an excellent and straightforward method to enhance the electrochemical transducer sensitivity for various electrochemical sensing applications.
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Affiliation(s)
- Tutku Beduk
- Sensors Lab, Advanced Membranes and Porous Materials Center, Computer, Electrocial and Mathematical Science and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia
| | - José Ilton de Oliveira Filho
- Sensors Lab, Advanced Membranes and Porous Materials Center, Computer, Electrocial and Mathematical Science and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia
| | - Abdellatif Ait Lahcen
- Sensors Lab, Advanced Membranes and Porous Materials Center, Computer, Electrocial and Mathematical Science and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia
| | - Veerappan Mani
- Sensors Lab, Advanced Membranes and Porous Materials Center, Computer, Electrocial and Mathematical Science and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia
| | - Khaled N Salama
- Sensors Lab, Advanced Membranes and Porous Materials Center, Computer, Electrocial and Mathematical Science and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia
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25
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Wei Y, Li X, Wang Y, Hirtz T, Guo Z, Qiao Y, Cui T, Tian H, Yang Y, Ren TL. Graphene-Based Multifunctional Textile for Sensing and Actuating. ACS NANO 2021; 15:17738-17747. [PMID: 34723481 DOI: 10.1021/acsnano.1c05701] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/20/2023]
Abstract
Textiles are materials that are extensively used in everyday life; textile-based sensors can, therefore, be regarded as ideal devices for a health monitor. However, previously reported textile sensors have limited prospects due to their single function or incompatibility. Traditional textile sensors generally focus on signal detection, which has not been able to be combined with an actuator to provide real-time health status feedback. Thus, to date, there are no well-established health monitoring systems based on intelligent textiles. Herein, we present a wearable batch-prepared graphene-based textile based on laser-scribing and thermal-transfer technology. Integrated with four functions of strain sensing, pressure sensing, physiological electrical sensing, and sound emitting, the GT is able to detect human body signals and transduce them to sound signals when the user is in an abnormal physical state. Moreover, the GT has high linearity for both strain and pressure sensing; the coefficients of determination exceed 99.3% and 98.2%, respectively. The performance of the device remains stable up to a pressure of 1000 kPa. The response time of the GT possession reaches as low as 85 ms at 4.2 Pa pressure. Therefore, due to their diversified functions and good performance, the research on GT is expected to extend to the fields of health monitoring, sports monitoring, and so forth.
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Affiliation(s)
- Yuhong Wei
- School of Integrated Circuits and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Xiaoshi Li
- School of Integrated Circuits and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Yunfan Wang
- Department of Electronic Engineering, Tsinghua University, Beijing 100084, China
| | - Thomas Hirtz
- School of Integrated Circuits and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Zhanfeng Guo
- School of Integrated Circuits and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Yancong Qiao
- School of Integrated Circuits and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Tianrui Cui
- School of Integrated Circuits and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - He Tian
- School of Integrated Circuits and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Yi Yang
- School of Integrated Circuits and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Tian-Ling Ren
- School of Integrated Circuits and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
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26
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Meng L, Turner APF, Mak WC. Conducting Polymer-Reinforced Laser-Irradiated Graphene as a Heterostructured 3D Transducer for Flexible Skin Patch Biosensors. ACS APPLIED MATERIALS & INTERFACES 2021; 13:54456-54465. [PMID: 34726900 PMCID: PMC8603349 DOI: 10.1021/acsami.1c13164] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Accepted: 10/21/2021] [Indexed: 05/26/2023]
Abstract
Flexible skin patch biosensors are promising for the noninvasive determination of physiological parameters in perspiration for fitness and health monitoring. However, various prerequisites need to be met for the development of such biosensors, including the creation of a flexible conductive platform, bending/contact stability, fast electrochemical kinetics, and immobilization of biomolecules. Here, we describe a conducting polymer-reinforced laser-irradiated graphene (LIG) network as a heterostructured three-dimensional (3D) transducer for flexible skin patch biosensors. LIG with a hierarchically interconnected graphene structure is geometrically patterned on polyimide via localized laser irradiation as a flexible conductive platform, which is then reinforced by poly(3,4-ethylenedioxythiophene) (PEDOT) as a conductive binder (PEDOT/LIG) with improved structural/contact stability and electrochemical kinetics. The interconnected pores of the reinforced PEDOT/LIG function as a 3D host matrix for high loading of "artificial" (Prussian blue, PB) and natural enzymes (lactate oxidase, LOx), forming a compact and heterostructured 3D transducer (LOx/PB-PEDOT/LIG) for lactate biosensing with excellent sensitivity (11.83 μA mM-1). We demonstrated the fabrication of flexible skin patch biosensors comprising a custom-built integrated three-electrode system achieve amperometric detection of lactate in artificial sweat over a wide physiological linear range of 0-18 mM. The advantage of this facile and versatile transducer is further illustrated by the development of a folded 3D wristband lactate biosensor and a dual channel biosensors for simultaneous monitoring of lactate and glucose. This innovative design concept of a heterostructured transducer for flexible biosensors combined with a versatile fabrication approach could potentially drive the development of new wearable and skin-mountable biosensors for monitoring various physiological parameters in biofluids for noninvasive fitness and health management.
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27
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Rabbani M, Syed AW, Khalid S, Mohammad MA. Fabrication and Characterization of a Thermophone Based on Laser-Scribed Graphene Intercalated with Multiwalled Carbon Nanotubes. NANOMATERIALS 2021; 11:nano11112874. [PMID: 34835639 PMCID: PMC8621151 DOI: 10.3390/nano11112874] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/15/2021] [Revised: 09/09/2021] [Accepted: 09/23/2021] [Indexed: 11/16/2022]
Abstract
The low sound pressure level and high operating voltages of thermophones have limited their applications in the past. However, in recent years, utilizing nanomaterials in thermophones has improved their efficiency and applicability. Nanomaterials, especially carbon nanotubes and graphene, have the advantage of low heat capacity per unit area (HCPUA) and high electrical and thermal conductivity. Therefore, they require a low electrical input power and generate a high sound pressure level (SPL) by efficiently transferring heat to the surrounding fluid. Laser-scribed graphene (LSG) can generate smooth spectra acoustic emissions over a wide range of frequencies by means of thermoacoustic (TA) emission. In this work, a thermophone based on LSG intercalated with multiwalled carbon nanotubes (MWCNTs) is proposed. The effects of varying input power, duty cycle percentage and measuring distance on the sound pressure level (SPL) of thermophones are studied to extract maximum efficiency. The achieved SPL of LSG, normalized to the input power, has increased by approximately 11 dB by intercalating it with MWCNTs, which shows that our proposed material can be a potential candidate for an efficient thermophone.
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Affiliation(s)
- Moin Rabbani
- School of Chemical and Materials Engineering (SCME), National University of Sciences and Technology (NUST), Sector H-12, Islamabad 44000, Pakistan; (M.R.); (A.W.S.)
| | - Aashir Waheed Syed
- School of Chemical and Materials Engineering (SCME), National University of Sciences and Technology (NUST), Sector H-12, Islamabad 44000, Pakistan; (M.R.); (A.W.S.)
| | - Syed Khalid
- Research Centre of Materials Science, Beijing Key Laboratory of Construction Tailorable Advanced Functional Materials and Green Applications, Beijing Institute of Technology, Beijing 100081, China;
| | - Mohammad Ali Mohammad
- School of Chemical and Materials Engineering (SCME), National University of Sciences and Technology (NUST), Sector H-12, Islamabad 44000, Pakistan; (M.R.); (A.W.S.)
- Correspondence:
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28
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Cheng Y, Wang K, Xu H, Li T, Jin Q, Cui D. Recent developments in sensors for wearable device applications. Anal Bioanal Chem 2021; 413:6037-6057. [PMID: 34389877 DOI: 10.1007/s00216-021-03602-2] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2021] [Revised: 07/26/2021] [Accepted: 08/04/2021] [Indexed: 01/23/2023]
Abstract
Wearable devices are a new means of human-computer interaction with different functions, underlying principles, and forms. They have been widely used in the medical and health fields, in applications including physiological signal monitoring; sports; and environmental detection, while subtly affecting people's lives and work. Wearable sensors as functional components of wearable devices have become a research focus. In this review, we systematically summarize recent progress in the development of wearable sensors and related devices. Wearable sensors in medical health applications, according to the principle of measurement, are divided into physical and chemical quantity detection. These sensors can monitor and measure specific parameters, thereby enabling continuously improvements in the quality and feasibility of medical treatment. Through the detection of human movement, such as breathing, heartbeat, or bending, wearable sensors can evaluate body movement and monitor an individual's physical performance and health status. Wearable devices detecting aspects of the environment while maintaining high adaptability to the human body can be used to evaluate environmental quality and obtain more accurate environmental information. The ultimate goal of this review is to provide new insights and directions for the future development and broader application of wearable devices in various fields.Graphical abstract.
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Affiliation(s)
- Yuemeng Cheng
- Department of Instrument Science and Engineering, School of Electronic Information and Electrical Engineering, Shanghai Engineering Research Center for Intelligent diagnosis and treatment instrument, Key Laboratory of Thin Film and Microfabrication Technology (Ministry of Education), Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Kan Wang
- Department of Instrument Science and Engineering, School of Electronic Information and Electrical Engineering, Shanghai Engineering Research Center for Intelligent diagnosis and treatment instrument, Key Laboratory of Thin Film and Microfabrication Technology (Ministry of Education), Shanghai Jiao Tong University, Shanghai, 200240, China.
| | - Hao Xu
- School of Naval Architecture, Ocean & Civil Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Tangan Li
- Department of Instrument Science and Engineering, School of Electronic Information and Electrical Engineering, Shanghai Engineering Research Center for Intelligent diagnosis and treatment instrument, Key Laboratory of Thin Film and Microfabrication Technology (Ministry of Education), Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Qinghui Jin
- State Key Laboratory of Transducer Technology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai, 200050, China.,Faculty of Electrical Engineering and Computer Science, Ningbo University, Ningbo, 315211, China
| | - Daxiang Cui
- Department of Instrument Science and Engineering, School of Electronic Information and Electrical Engineering, Shanghai Engineering Research Center for Intelligent diagnosis and treatment instrument, Key Laboratory of Thin Film and Microfabrication Technology (Ministry of Education), Shanghai Jiao Tong University, Shanghai, 200240, China
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29
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Xu J, Li R, Ji S, Zhao B, Cui T, Tan X, Gou G, Jian J, Xu H, Qiao Y, Yang Y, Zhang S, Ren TL. Multifunctional Graphene Microstructures Inspired by Honeycomb for Ultrahigh Performance Electromagnetic Interference Shielding and Wearable Applications. ACS NANO 2021; 15:8907-8918. [PMID: 33881822 DOI: 10.1021/acsnano.1c01552] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
High-performance electromagnetic interference (EMI) shielding materials with ultralow density, excellent flexibility, and good mechanical properties are highly desirable for aerospace and wearable electronics. Herein, honeycomb porous graphene (HPG) fabricated by laser scribing technology is reported for EMI shielding and wearable applications. Due to the honeycomb structure, the HPG exhibits an EMI shielding effectiveness (SE) up to 45 dB at a thickness of 48.3 μm. The single-piece HPG exhibits an ultrahigh absolute shielding effectiveness (SSE/t) of 240 123 dB cm2/g with an ultralow density of 0.0388 g/cm3, which is significantly superior to the reported materials such as carbon-based, MXene, and metal materials. Furthermore, MXene and AgNWs are employed to cover the honeycomb holes of the HPG to enhance surface reflection; thus, the SSE/t of the HPG/AgNWs composite membrane can reach up to 292 754 dB cm2/g. More importantly, the HPG exhibits excellent mechanical stability and durability in cyclic stretching and bending, which can be used to monitor weak physiological signals such as pulse, respiration, and laryngeal movement of humans. Therefore, the lightweight and flexible HPG exhibits excellent EMI shielding performance and mechanical properties, along with its low cost and ease of mass production, which is promising for practical applications in EMI shielding and wearable electronics.
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Affiliation(s)
- Jiandong Xu
- Institute of Microelectronics, Tsinghua University, Beijing 100084, China
- Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Ruisong Li
- Department of Electrical Engineering and Computer Science and Department of Bioengineering, College of Engineering, University of California, Berkeley, California 94720, United States
| | - Shourui Ji
- Institute of Microelectronics, Tsinghua University, Beijing 100084, China
- Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Bingchen Zhao
- Institute of Microelectronics, Tsinghua University, Beijing 100084, China
- Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Tianrui Cui
- Institute of Microelectronics, Tsinghua University, Beijing 100084, China
- Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Xichao Tan
- Institute of Microelectronics, Tsinghua University, Beijing 100084, China
- Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Guangyang Gou
- Institute of Microelectronics, Tsinghua University, Beijing 100084, China
- Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Jinming Jian
- Institute of Microelectronics, Tsinghua University, Beijing 100084, China
- Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Haokai Xu
- Institute of Microelectronics, Tsinghua University, Beijing 100084, China
- Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Yancong Qiao
- Institute of Microelectronics, Tsinghua University, Beijing 100084, China
- Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Yi Yang
- Institute of Microelectronics, Tsinghua University, Beijing 100084, China
- Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Sheng Zhang
- Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China
| | - Tian-Ling Ren
- Institute of Microelectronics, Tsinghua University, Beijing 100084, China
- Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
- Center for Flexible Electronics Technology, Tsinghua University, Beijing 100084, China
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30
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Han F, Li M, Ye H, Zhang G. Materials, Electrical Performance, Mechanisms, Applications, and Manufacturing Approaches for Flexible Strain Sensors. NANOMATERIALS (BASEL, SWITZERLAND) 2021; 11:1220. [PMID: 34063165 PMCID: PMC8148098 DOI: 10.3390/nano11051220] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/19/2021] [Revised: 04/30/2021] [Accepted: 05/01/2021] [Indexed: 12/13/2022]
Abstract
With the recent great progress made in flexible and wearable electronic materials, the upcoming next generation of skin-mountable and implantable smart devices holds extensive potential applications for the lifestyle modifying, including personalized health monitoring, human-machine interfaces, soft robots, and implantable biomedical devices. As a core member within the wearable electronics family, flexible strain sensors play an essential role in the structure design and functional optimization. To further enhance the stretchability, flexibility, sensitivity, and electricity performances of the flexible strain sensors, enormous efforts have been done covering the materials design, manufacturing approaches and various applications. Thus, this review summarizes the latest advances in flexible strain sensors over recent years from the material, application, and manufacturing strategies. Firstly, the critical parameters measuring the performances of flexible strain sensors and materials development contains different flexible substrates, new nano- and hybrid- materials are introduced. Then, the developed working mechanisms, theoretical analysis, and computational simulation are presented. Next, based on different material design, diverse applications including human motion detection and health monitoring, soft robotics and human-machine interface, implantable devices, and biomedical applications are highlighted. Finally, synthesis consideration of the massive production industry of flexible strain sensors in the future; different fabrication approaches that are fully expected are classified and discussed.
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Affiliation(s)
- Fei Han
- Institute of Future Lighting, Academy for Engineering and Technology, Fudan University, Shanghai 200433, China; (F.H.); (M.L.)
- Shenzhen Institute of Wide-Bandgap Semiconductors, Shenzhen 518055, China
| | - Min Li
- Institute of Future Lighting, Academy for Engineering and Technology, Fudan University, Shanghai 200433, China; (F.H.); (M.L.)
| | - Huaiyu Ye
- Shenzhen Institute of Wide-Bandgap Semiconductors, Shenzhen 518055, China
| | - Guoqi Zhang
- Institute of Future Lighting, Academy for Engineering and Technology, Fudan University, Shanghai 200433, China; (F.H.); (M.L.)
- Shenzhen Institute of Wide-Bandgap Semiconductors, Shenzhen 518055, China
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Zhang J, Feng J, Jia L, Xu R, Zhao J, Zheng Z, Zhou T. Top-Down Direct Preparation of Orange-Yellow Dye Similar to Psittacofulvins from Commercial Polymer by Laser Writing. ACS APPLIED MATERIALS & INTERFACES 2020; 12:58339-58348. [PMID: 33320523 DOI: 10.1021/acsami.0c15471] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/23/2023]
Abstract
Laser manufacturing is a promising method for the design and preparation of high value-added materials. When the laser acts on the polymer precursors, some wonderful phenomena will always occur and accompanied by the generation of new substances. Herein, we report a top-down approach for the direct preparation of orange-yellow dye that is similar to psittacofulvins from commercial polymer resins by laser writing. Conjugated double bonds and micro-rough structures are formed simultaneously on laser-irradiated polymer substrate surfaces. The typical polyconjugated structures of psittacofulvin dyes were confirmed by micro-Raman and Raman imaging results. Temperature-dependent Fourier transform infrared and X-ray photoelectron spectroscopy further demonstrated the formation mechanism of laser-induced psittacofulvins dyes based on the chemical composition. Further, optical microscopy, laser confocal microscopy, and scanning electron microscopy were carried out to characterize the physical morphologies of laser-irradiated polymer substrates. A unique advantage of preparing psittacofulvins dye using laser writing is its simple steps, and the dye can be converted directly from the appropriate precursor substrate. Interestingly, the laser-irradiated polymer substrate surface undergoes color change. This laser-induced color patterning is attractive due to the characteristics of high precision, flexibility, and maskless; any patterns can be easily designed and produced on the polymer at desired positions.
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Affiliation(s)
- Jihai Zhang
- State Key Laboratory of Polymer Materials Engineering of China, Polymer Research Institute, Sichuan University, Chengdu 610065, China
| | - Jin Feng
- State Key Laboratory of Polymer Materials Engineering of China, Polymer Research Institute, Sichuan University, Chengdu 610065, China
| | - Liyang Jia
- State Key Laboratory of Polymer Materials Engineering of China, Polymer Research Institute, Sichuan University, Chengdu 610065, China
| | - Rui Xu
- State Key Laboratory of Polymer Materials Engineering of China, Polymer Research Institute, Sichuan University, Chengdu 610065, China
| | - Jing Zhao
- College of Chemistry, Sichuan University, Chengdu 610065, China
| | - Zhuo Zheng
- State Key Laboratory of Polymer Materials Engineering of China, Polymer Research Institute, Sichuan University, Chengdu 610065, China
| | - Tao Zhou
- State Key Laboratory of Polymer Materials Engineering of China, Polymer Research Institute, Sichuan University, Chengdu 610065, China
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Qiao Y, Li X, Jian J, Wu Q, Wei Y, Shuai H, Hirtz T, Zhi Y, Deng G, Wang Y, Gou G, Xu J, Cui T, Tian H, Yang Y, Ren TL. Substrate-Free Multilayer Graphene Electronic Skin for Intelligent Diagnosis. ACS APPLIED MATERIALS & INTERFACES 2020; 12:49945-49956. [PMID: 33090758 DOI: 10.1021/acsami.0c12440] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/15/2023]
Abstract
Current wearable sensors are fabricated with substrates, which limits the comfort, flexibility, stretchability, and induces interface mismatch. In addition, the substrate prevents the evaporation of sweat and is harmful to skin health. In this work, we have enabled the substrate-free laser scribed graphene (SFG) electronic skin (e-skin) with multifunctions. Compared with the e-skin with the substrate, the SFG has good gas permeability, low impedance, and flexibility. Only assisted using water, the SFG can be transferred to almost any objects including silicon and human skin and it can even be suspended. Many through-holes like stomas in leaf can be formed in the SFG, which make it breathable. After designing the pattern, the gauge factor (GF) of graphene electronic skin (GES) can be designed as the strain sensor. Physiological signals such as respiration, human motion, and electrocardiogram (ECG) can be detected. Moreover, the suspended SFG detect vibrations with high sensitivity. Due to the substrate-free structure, the impedance between SFG e-skin and the human body decreases greatly. Finally, an ECG detecting system has been designed based on the GES, which can monitor the body condition in real time. To analyze the ECG signals automatically, a convolutional neural network (CNN) was built and trained successfully. This work has high potential in the field of health telemonitoring.
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Affiliation(s)
- Yancong Qiao
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Xiaoshi Li
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Jinming Jian
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Qi Wu
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Yuhong Wei
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Hua Shuai
- Department of Physics, Engineering Physics, The Ohio State University, 191 West Woodruff Avenue, Columbus, Ohio 43210, United States
| | - Thomas Hirtz
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Yao Zhi
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Ge Deng
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Yunfan Wang
- Institute of Electronics, Tsinghua University, Beijing 100084, China
| | - Guangyang Gou
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Jiandong Xu
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Tianrui Cui
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - He Tian
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Yi Yang
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Tian-Ling Ren
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
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Liu X, Zhang Q, Gao G. Solvent-Resistant and Nonswellable Hydrogel Conductor toward Mechanical Perception in Diverse Liquid Media. ACS NANO 2020; 14:13709-13717. [PMID: 32924434 DOI: 10.1021/acsnano.0c05932] [Citation(s) in RCA: 58] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Wet-resistant flexible electronics have gained impressive attention as underwater wearable sensors, all-weather electronic skins, and implantable bioelectrodes. However, fabricating a stable and nonswelling hydrogel-based electronic device used in diverse liquid media is challenging and promising for the progress of wet-resistance electronics. Herein, a solvent-resistant and tough hydrogel conductor is successfully prepared and exhibits fatigue resistance, antifreezing behavior, and nonswelling and wet-adhesion performances in organic and aqueous solutions. Moreover, the hydrogels are utilized as all-weather wearable sensors featuring high sensitivity, reliability, and wide sensing ranges for monitoring and distinguishing various physiological signals and human motions. Furthermore, the hydrogel sensors can even achieve accurate and stable mechanical sensing of pressure, bending, and stretching in diverse solvents consisting of water, chloroform, hexane, and dodecane. It is envisioned that the solvent-resistant and antifreezing hydrogel conductor can present promising feasibility as all-weather electronic skins, intelligent sensors in solvents, and soft robots in various harsh liquid environments.
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Affiliation(s)
- Xin Liu
- Polymeric and Soft Materials Laboratory, School of Chemical Engineering and Advanced Institute of Materials Science, Changchun University of Technology, No. 2055, Yan'an Street, Changchun 130000, China
- Beijing Graphene Institute (BGI), Beijing 100095, China
| | - Qin Zhang
- Polymeric and Soft Materials Laboratory, School of Chemical Engineering and Advanced Institute of Materials Science, Changchun University of Technology, No. 2055, Yan'an Street, Changchun 130000, China
| | - Guanghui Gao
- Polymeric and Soft Materials Laboratory, School of Chemical Engineering and Advanced Institute of Materials Science, Changchun University of Technology, No. 2055, Yan'an Street, Changchun 130000, China
- Beijing Graphene Institute (BGI), Beijing 100095, China
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Gong S, Du S, Kong J, Zhai Q, Lin F, Liu S, Cameron NR, Cheng W. Skin-Like Stretchable Fuel Cell Based on Gold-Nanowire-Impregnated Porous Polymer Scaffolds. SMALL (WEINHEIM AN DER BERGSTRASSE, GERMANY) 2020; 16:e2003269. [PMID: 32864831 DOI: 10.1002/smll.202003269] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/26/2020] [Revised: 07/16/2020] [Indexed: 06/11/2023]
Abstract
Skin-like energy devices can be conformally attached to the human body, which are highly desirable to power soft wearable electronics in the future. Here, a skin-like stretchable fuel cell based on ultrathin gold nanowires (AuNWs) and polymerized high internal phase emulsions (polyHIPEs) scaffolds is demonstrated. The polyHIPEs can offer a high porosity of 80% yet with an overall thickness comparable to human skin. Upon impregnation with electronic inks containing ultrathin (2 nm in diameter) and ultrahigh aspect-ratio (>10 000) gold nanowires, skin-like strain-insensitive stretchable electrodes are successfully fabricated. With such designed strain-insensitive electrodes, a stretchable fuel cell is fabricated by using AuNWs@polyHIPEs, platinum (Pt)-modified AuNWs@polyHIPEs, and ethanol as the anode, cathode, and fuel, respectively. The resulting epidermal fuel cell can be patterned and transferred onto skin as "tattoos" yet can offer a high power density of 280 µW cm-2 and a high durability (>90% performance retention under stretching, compression, and twisting). The results presented here demonstrate that this skin-thin, porous, yet stretchable electrode is essentially multifunctional, simultaneously serving as a current collector, an electrocatalyst, and a fuel host, indicating potential applications to power future soft wearable 2.0 electronics for remote healthcare and soft robotics.
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Affiliation(s)
- Shu Gong
- Department of Chemical Engineering, Monash University, Clayton, Victoria, 3800, Australia
| | - Shengrong Du
- Department of Materials Science and Engineering, Monash University, Clayton, Victoria, 3800, Australia
| | - Jianfei Kong
- Department of Chemical Engineering, Monash University, Clayton, Victoria, 3800, Australia
- School of Pharmacy, Jiangsu Vocational College of Medicine, Yancheng, Jiangsu, 224000, China
| | - Qingfeng Zhai
- Department of Chemical Engineering, Monash University, Clayton, Victoria, 3800, Australia
| | - Fenge Lin
- Department of Chemical Engineering, Monash University, Clayton, Victoria, 3800, Australia
| | - Siyuan Liu
- Department of Chemical Engineering, Monash University, Clayton, Victoria, 3800, Australia
| | - Neil R Cameron
- Department of Materials Science and Engineering, Monash University, Clayton, Victoria, 3800, Australia
- School of Engineering, University of Warwick, Coventry, CV4 7AL, UK
| | - Wenlong Cheng
- Department of Chemical Engineering, Monash University, Clayton, Victoria, 3800, Australia
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Lahcen AA, Rauf S, Beduk T, Durmus C, Aljedaibi A, Timur S, Alshareef HN, Amine A, Wolfbeis OS, Salama KN. Electrochemical sensors and biosensors using laser-derived graphene: A comprehensive review. Biosens Bioelectron 2020; 168:112565. [PMID: 32927277 DOI: 10.1016/j.bios.2020.112565] [Citation(s) in RCA: 77] [Impact Index Per Article: 19.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Revised: 08/22/2020] [Accepted: 08/24/2020] [Indexed: 12/12/2022]
Abstract
Laser-derived graphene (LDG) technology is gaining attention as a promising material for the development of novel electrochemical sensors and biosensors. Compared to established methods for graphene synthesis, LDG provides many advantages such as cost-effectiveness, fast electron mobility, mask-free, green synthesis, good electrical conductivity, porosity, mechanical stability, and large surface area. This review discusses, in a critical way, recent advancements in this field. First, we focused on the fabrication and doping of LDG platforms using different strategies. Next, the techniques for the modification of LDG sensors using nanomaterials, conducting polymers, biological and artificial receptors are presented. We then discussed the advances achieved for various LDG sensing and biosensing schemes and their applications in the fields of environmental monitoring, food safety, and clinical diagnosis. Finally, the drawbacks and limitations of LDG based electrochemical biosensors are addressed, and future trends are also highlighted.
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Affiliation(s)
- Abdellatif Ait Lahcen
- Sensors Lab, Advanced Membranes and Porous Materials Center (AMPMC), Computer, Electrical and Mathematical Science and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900, Saudi Arabia.
| | - Sakandar Rauf
- Sensors Lab, Advanced Membranes and Porous Materials Center (AMPMC), Computer, Electrical and Mathematical Science and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900, Saudi Arabia
| | - Tutku Beduk
- Sensors Lab, Advanced Membranes and Porous Materials Center (AMPMC), Computer, Electrical and Mathematical Science and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900, Saudi Arabia
| | - Ceren Durmus
- Department of Biochemistry, Faculty of Science, Ege University, 35100, Bornova, Izmir, Turkey
| | - Abdulrahman Aljedaibi
- Sensors Lab, Advanced Membranes and Porous Materials Center (AMPMC), Computer, Electrical and Mathematical Science and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900, Saudi Arabia
| | - Suna Timur
- Department of Biochemistry, Faculty of Science, Ege University, 35100, Bornova, Izmir, Turkey
| | - Husam N Alshareef
- Materials Science and Engineering, Physical Science & Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900, Saudi Arabia.
| | - Aziz Amine
- Chemical Analysis and Biosensors Group, Laboratory of Process Engineering and Environment, Faculty of Science and Techniques, Hassan II University of Casablanca, B.P. 146. Mohammedia, Morocco.
| | - Otto S Wolfbeis
- Institute of Analytical Chemistry, Chemo- and Biosensors, University of Regensburg, D-93040, Regensburg, Germany.
| | - Khaled N Salama
- Sensors Lab, Advanced Membranes and Porous Materials Center (AMPMC), Computer, Electrical and Mathematical Science and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900, Saudi Arabia.
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Qiao Y, Gou G, Wu F, Jian J, Li X, Hirtz T, Zhao Y, Zhi Y, Wang F, Tian H, Yang Y, Ren TL. Graphene-Based Thermoacoustic Sound Source. ACS NANO 2020; 14:3779-3804. [PMID: 32186849 DOI: 10.1021/acsnano.9b10020] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Thermoacoustic (TA) effect has been discovered for more than 130 years. However, limited by the material characteristics, the performance of a TA sound source could not be compared with magnetoelectric and piezoelectric loudspeakers. Recently, graphene, a two-dimensional material with the lowest heat capacity per unit area, was discovered to have a good TA performance. Compared with a traditional sound source, graphene TA sound sources (GTASSs) have many advantages, such as small volume, no diaphragm vibration, wide frequency range, high transparency, good flexibility, and high sound pressure level (SPL). Therefore, graphene has a great potential as a next-generation sound source. Photoacoustic (PA) imaging can also be applied to the diagnosis and treatment of diseases using the photothermo-acoustic (PTA) effect. Therefore, in this review, we will introduce the history of TA devices. Then, the theory and simulation model of TA will be analyzed in detail. After that, we will talk about the graphene synthesis method. To improve the performance of GTASSs, many strategies such as lowering the thickness and using porous or suspended structures will be introduced. With a good PTA effect and large specific area, graphene PA imaging and drug delivery is a promising prospect in cancer treatment. Finally, the challenges and prospects of GTASSs will be discussed.
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Affiliation(s)
- Yancong Qiao
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Guangyang Gou
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Fan Wu
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Jinming Jian
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Xiaoshi Li
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Thomas Hirtz
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Yunfei Zhao
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Yao Zhi
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Fangwei Wang
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - He Tian
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Yi Yang
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Tian-Ling Ren
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
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37
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Zhang S, Li S, Xia Z, Cai K. A review of electronic skin: soft electronics and sensors for human health. J Mater Chem B 2020; 8:852-862. [PMID: 31942905 DOI: 10.1039/c9tb02531f] [Citation(s) in RCA: 62] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
This article reviews several categories of electronic skins (e-skins) for monitoring signals involved in human health. It covers advanced candidate materials, compositions, structures, and integrate strategies of e-skin, focusing on stretchable and wearable electronics. In addition, this article further discusses the potential applications and expected development of e-skins. It is possible to provide a new generation of sensors which are able to introduce artificial intelligence to the clinic and daily healthcare.
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Affiliation(s)
- Songyue Zhang
- Key Laboratory of Biorheological Science and Technology, Ministry of Education, College of Bioengineering, Chongqing University, Chongqing, 400044, China
| | - Shunbo Li
- Key Laboratory of Optoelectronic Technology and Systems, Ministry of Education and Key Disciplines Laboratory of Novel Micro-Nano Devices and System Technology, School of Optoelectronics Engineering, Chongqing University, Chongqing 400044, China.
| | - Zengzilu Xia
- Key Laboratory of Biorheological Science and Technology, Ministry of Education, College of Bioengineering, Chongqing University, Chongqing, 400044, China
| | - Kaiyong Cai
- Key Laboratory of Biorheological Science and Technology, Ministry of Education, College of Bioengineering, Chongqing University, Chongqing, 400044, China
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38
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Liu H, Dong W, Li Y, Li F, Geng J, Zhu M, Chen T, Zhang H, Sun L, Lee C. An epidermal sEMG tattoo-like patch as a new human-machine interface for patients with loss of voice. MICROSYSTEMS & NANOENGINEERING 2020; 6:16. [PMID: 34567631 PMCID: PMC8433406 DOI: 10.1038/s41378-019-0127-5] [Citation(s) in RCA: 46] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/10/2019] [Revised: 10/25/2019] [Accepted: 11/18/2019] [Indexed: 05/03/2023]
Abstract
Throat cancer treatment involves surgical removal of the tumor, leaving patients with facial disfigurement as well as temporary or permanent loss of voice. Surface electromyography (sEMG) generated from the jaw contains lots of voice information. However, it is difficult to record because of not only the weakness of the signals but also the steep skin curvature. This paper demonstrates the design of an imperceptible, flexible epidermal sEMG tattoo-like patch with the thickness of less than 10 μm and peeling strength of larger than 1 N cm-1 that exhibits large adhesiveness to complex biological surfaces and is thus capable of sEMG recording for silent speech recognition. When a tester speaks silently, the patch shows excellent performance in recording the sEMG signals from three muscle channels and recognizing those frequently used instructions with high accuracy by using the wavelet decomposition and pattern recognization. The average accuracy of action instructions can reach up to 89.04%, and the average accuracy of emotion instructions is as high as 92.33%. To demonstrate the functionality of tattoo-like patches as a new human-machine interface (HMI) for patients with loss of voice, the intelligent silent speech recognition, voice synthesis, and virtual interaction have been implemented, which are of great importance in helping these patients communicate with people and make life more enjoyable.
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Affiliation(s)
- Huicong Liu
- School of Mechanical and Electric Engineering, Jiangsu Provincial Key Laboratory of Advanced Robotics, Soochow University, 215123 Suzhou, China
| | - Wei Dong
- School of Mechanical and Electric Engineering, Jiangsu Provincial Key Laboratory of Advanced Robotics, Soochow University, 215123 Suzhou, China
| | - Yunfei Li
- School of Mechanical and Electric Engineering, Jiangsu Provincial Key Laboratory of Advanced Robotics, Soochow University, 215123 Suzhou, China
| | - Fanqi Li
- School of Mechanical and Electric Engineering, Jiangsu Provincial Key Laboratory of Advanced Robotics, Soochow University, 215123 Suzhou, China
| | - Jiangjun Geng
- School of Mechanical and Electric Engineering, Jiangsu Provincial Key Laboratory of Advanced Robotics, Soochow University, 215123 Suzhou, China
| | - Minglu Zhu
- Department of Electrical & Computer Engineering, National University of Singapore, 4 Engineering Drive 3, Singapore, 117576 Singapore
- National University of Singapore Suzhou Research Institute (NUSRI), Suzhou Industrial Park, 215123 Suzhou, China
| | - Tao Chen
- School of Mechanical and Electric Engineering, Jiangsu Provincial Key Laboratory of Advanced Robotics, Soochow University, 215123 Suzhou, China
| | - Hongmiao Zhang
- School of Mechanical and Electric Engineering, Jiangsu Provincial Key Laboratory of Advanced Robotics, Soochow University, 215123 Suzhou, China
| | - Lining Sun
- School of Mechanical and Electric Engineering, Jiangsu Provincial Key Laboratory of Advanced Robotics, Soochow University, 215123 Suzhou, China
| | - Chengkuo Lee
- Department of Electrical & Computer Engineering, National University of Singapore, 4 Engineering Drive 3, Singapore, 117576 Singapore
- National University of Singapore Suzhou Research Institute (NUSRI), Suzhou Industrial Park, 215123 Suzhou, China
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39
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Qiao Y, Li X, Hirtz T, Deng G, Wei Y, Li M, Ji S, Wu Q, Jian J, Wu F, Shen Y, Tian H, Yang Y, Ren TL. Graphene-based wearable sensors. NANOSCALE 2019; 11:18923-18945. [PMID: 31532436 DOI: 10.1039/c9nr05532k] [Citation(s) in RCA: 44] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
The human body is a "delicate machine" full of sensors such as the fingers, nose, and mouth. In addition, numerous physiological signals are being created every moment, which can reflect the condition of the body. The quality and the quantity of the physiological signals are important for diagnoses and the execution of therapies. Due to the incompact interface between the sensors and the skin, the signals obtained by commercial rigid sensors do not bond well with the body; this decreases the quality of the signal. To increase the quantity of the data, it is important to detect physiological signals in real time during daily life. In recent years, there has been an obvious trend of applying graphene devices with excellent performance (flexibility, biocompatibility, and electronic characters) in wearable systems. In this review, we will first provide an introduction about the different methods of synthesis of graphene, and then techniques for graphene patterning will be outlined. Moreover, wearable graphene sensors to detect mechanical, electrophysiological, fluid, and gas signals will be introduced. Finally, the challenges and prospects of wearable graphene devices will be discussed. Wearable graphene sensors can improve the quality and quantity of the physiological signals and have great potential for health-care and telemedicine in the future.
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Affiliation(s)
- Yancong Qiao
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China.
| | - Xiaoshi Li
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China.
| | - Thomas Hirtz
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China.
| | - Ge Deng
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China.
| | - Yuhong Wei
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China.
| | - Mingrui Li
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China.
| | - Shourui Ji
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China. and School of Aerospace Engineering, Tsinghua University, Beijing 100084, China
| | - Qi Wu
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China.
| | - Jinming Jian
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China.
| | - Fan Wu
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China.
| | - Yang Shen
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China.
| | - He Tian
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China.
| | - Yi Yang
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China.
| | - Tian-Ling Ren
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China.
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