Highly Sensitive and Stretchable c-MWCNTs/PPy Embedded Multidirectional Strain Sensor Based on Double Elastic Fabric for Human Motion Detection

Shen, Huiying; Ke, Huizhen; Feng, Jingdong; Jiang, Chenyu; Wei, Qufu; Wang, Qingqing

doi:10.3390/nano11092333

Cited by 17 publications

(14 citation statements)

References 46 publications

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Section: Fabrication Methods Of Strain Sensorsmentioning

confidence: 99%

“…[110] One of the keys to preparing CNT strain sensors using 3D printing technology Reproduced with permission. [97] Copyright 2019, MDPI. b) Schematic illustrations of fabrication procedures for PDMS/CNTs/PDMS strain sensor.…”

Section: D Printing Technologymentioning

confidence: 99%

“…Coating techniques mainly include spraying, [54,67,72,[85][86][87][88] sputtering, [89] vacuum filtration, [65,[90][91][92][93][94] and dip coating. [75,80,[95][96][97] Coating technology is a simple method to fabricate textile-type sensors. Strain sensors with high sensitivity and high stretchability can be fabricated by coating conductive materials on fibers, yarns or textiles using coating technology.…”

Section: Coating Technologymentioning

confidence: 99%

“…[92] Soaking elastomers and yarns in conductive solutions so that conductive materials are adsorbed on elastomers or yarns, which can be used to fabricate highperformance sensors. Shen et al [97] fabricated double elastic fabric/carboxylic multi-walled carbon nanotubes/polypyrrole (Def/cMWCNTs/PPy) strain sensors using immersion and adsorption oxidation method, which can achieve 80% tensile strain and good mechanical stability. (Figure 5a) Coating techniques are also commonly used to achieve the fabrication of CNT films by coating a layer of CNTs or CNT composites onto an elastic substrate.…”

Section: Coating Technologymentioning

confidence: 99%

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Carbon Nanotube‐Based Strain Sensors: Structures, Fabrication, and Applications

Wang

Zhu

et al. 2022

Adv Materials Technologies

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flexible devices has received widespread attention. Among them, flexible strain sensors have attracted great interest from the industry and academia due to their promising applications in wearable devices, [1][2][3] electronic skin, [4,5] intelligent robots, [6] healthcare monitoring, [7] and humanmachine interfaces. [8,9] The three primary categories of strain sensors are resistive, [10] capacitive, [11] and piezoelectric. [12] The advantages of capacitive-type strain sensors are high sensitivity, rapid response, and high linearity, but the sensor has poor response performance on various strains due to their structural limitations. The performance of the piezoelectric-type strain sensor mainly focuses on the piezoelectric material, which requires excellent piezoelectricity of the material, but the piezoelectric material is more expensive and the measurable range is narrower. Compared to the above two types of sensors, resistivetype strain sensors have the advantages of a wider strain sensing range, relatively simple reading mechanism and easy fabrication, which have received wide attention in recent years in the fields of wearable devices and electronic skins. Therefore, this paper will focus on the resistive-type strain sensors. The working principle is that the structure of the conductive material changes when the device is stretched, bent, and twisted, causing the resistance of Flexible strain sensors have received widespread attention because of their great potential in many fields. Carbon nanotubes (CNTs) have been used as conductive materials for flexible strain sensors due to their excellent electrical and mechanical properties, and the fabricated flexible strain sensors have excellent sensing performance. This paper systematically summarizes the advances in flexible resistance-type strain sensors based on CNTs. The strain sensing mechanisms are introduced, including crack extension, tunneling effect, and disconnection of overlapping materials. The performance parameters of the sensors, including sensitivity, stretchability, linearity, hysteresis, dynamic durability, and transparency, are discussed comprehensively. The coating methods, 3D printing techniques, chemical vapor deposition, transfer methods, and spinning processes used to fabricate CNT strain sensors are highlighted. The effect of isolated and porous internal conductive structures, folded and microcracked surface structures, films and fabrics macroscopic structures on sensor performance were systematically analyzed. The applications of the sensors in medical health, motion monitoring, gesture recognition, human-computer interaction, and soft robotics are provided in detail. Finally, the future challenges of CNT flexible strain sensors are summarized and the outlook is presented. Although CNT strain sensors have made great progress so far, there are still many problems that need researchers' attention and solutions.

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Section: Fabrication Methods Of Strain Sensorsmentioning

confidence: 99%

Section: D Printing Technologymentioning

confidence: 99%

Section: Coating Technologymentioning

confidence: 99%

Section: Coating Technologymentioning

confidence: 99%

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Carbon Nanotube‐Based Strain Sensors: Structures, Fabrication, and Applications

Wang

Zhu

et al. 2022

Adv Materials Technologies

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“…The strain sensor is composed of a heterogenous surface architecture featured by stretchable poly(dimethylsiloxane) (PDMS) substrate, poly(ethylene terephthalate) (PET) film forming strain insensitive rigid electrode regions, and strain sensing channel region composed of multiwalled carbon nanotube (MWCNT) with carbon black (CB) nanofiller dispersed in PDMS matrix. [7,24,25] The heterogeneous device architecture can minimize the undesirable electrical interruption from electrodes by strain, leading to more reliable strain sensing characteristics. An omnidirectional strain sensor array with triangular-sensor-assembly is demonstrated by arranging three-unit sensors at tilting angles of 45°, to enable direction-dependent sensing characteristics.…”

Section: Introductionmentioning

confidence: 99%

Heterogeneous Structure Omnidirectional Strain Sensor Arrays With Cognitively Learned Neural Networks

et al. 2023

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ministic parameters such as sensitivity, durability, sensing range, and response time were significantly improved by tremendous efforts of researchers. Notably, many attempts have been carried out to realize highly strain-sensitive composites consisting of metallic nanowires, carbon nanotubes, carbon/metal nanoparticles, and elastomers. [6,7] Along with such material consolidating strategy, a variety of mechanistic device structures (resistive, capacitive, piezoresistive, triboelectric, and piezoelectric types) has been demonstrated to achieve high-performance strain sensors. [8][9][10][11][12] However, most of the conventional strain sensors are only capable of detecting uniaxial strain and lack the ability to determine directional variable motions, limiting their applications in realistic surface stimuli environments such as dynamic human skin motion sensing and human-machine interfaces.To address this issue, geometrically engineered [13][14][15] sensor devices composed of multidimensionally stacked channel or cross-shaped detecting electrodes have been introduced. [16,17] These strain sensors are capable of detecting the difference of gauge factor corresponding to different loading directions, successfully exhibiting direction-dependent sensing characteristics. In fact, these newly engineered architectures have been developed to avoid the difficulty to achieve multidirectional strain sensing by employing microscopically isotropic conducting pathways of sensing channel layers, which typically experience identical deformation upon any stimulating direction. Although Mechanically stretchable strain sensors gain tremendous attention for bioinspired skin sensation systems and artificially intelligent tactile sensors. However, high-accuracy detection of both strain intensity and direction with simple device/array structures is still insufficient. To overcome this limitation, an omnidirectional strain perception platform utilizing a stretchable strain sensor array with triangular-sensor-assembly (three sensors tilted by 45°) coupled with machine learning (ML) -based neural network classification algorithm, is proposed. The strain sensor, which is constructed with strain-insensitive electrode regions and strain-sensitive channel region, can minimize the undesirable electrical intrusion from the electrodes by strain, leading to a heterogeneous surface structure for more reliable strain sensing characteristics. The strain sensor exhibits decent sensitivity with gauge factor (GF) of ≈8, a moderate sensing range (≈0-35%), and relatively good reliability (3000 stretching cycles). More importantly, by employing a multiclassmultioutput behavior-learned cognition algorithm, the stretchable sensor array with triangular-sensor-assembly exhibits highly accurate recognition of both direction and intensity of an arbitrary strain by interpretating the correlated signals from the three-unit sensors. The omnidirectional strain perception platform with its neural network algorithm exhibits overall strain intensity and direction accura...

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Prognosis of Cardiovascular Conditions Noninvasively Using Printable Elastomeric Electronic Skin

Selvan T,

Mondal

2025

Adv Healthcare Materials

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Lack of timely prognosis of cardiovascular condition (CVC) is resulting in increased mortality across the globe. Currently, available techniques are confined to medical facilities and need the intervention of specialists. Frequently, this impedes timely treatment, driven by socioeconomic factors. Consequently, the disease transcends toward incurable complications. In such a scenario, point‐of‐care diagnostic tools can help with prognosis at an early stage. Albeit there are such tools available, it is imperative to develop affordably in uncomplicated manufacturing techniques and should have simple readout and analysis modules for monitoring CVC. Accordingly, the solvent‐free manufacturing of stencil printable liquid elastomer‐carbon nanotube electronic skin‐based strain sensor, capable of accurately detecting pulse (at different positions) and other parameters like augmentation index and stiffness index of artery related to the CVC, is reported. The Poincare plot, derived from the recorded data, measures heart rate variability, a key indicator linked to mortality. Thanks to the staggering linearity, gauge factor of 234.26, fast response time of 85 ms (measured from pulse data), and cyclic stability (over 500 cycles), assist in the ease of detection of vital parameters. Furthermore, the sensor patch demonstrates its capability to acquire pulse waves under different real‐time artery conditions using cuff‐based pressure applications.

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Highly Sensitive and Stretchable c-MWCNTs/PPy Embedded Multidirectional Strain Sensor Based on Double Elastic Fabric for Human Motion Detection

Cited by 17 publications

References 46 publications

Carbon Nanotube‐Based Strain Sensors: Structures, Fabrication, and Applications

Carbon Nanotube‐Based Strain Sensors: Structures, Fabrication, and Applications

Heterogeneous Structure Omnidirectional Strain Sensor Arrays With Cognitively Learned Neural Networks

Prognosis of Cardiovascular Conditions Noninvasively Using Printable Elastomeric Electronic Skin

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