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Special Issue "Smart Structures and Materials for Sensor Applications"

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensor Materials".

Deadline for manuscript submissions: closed (1 March 2020).

Special Issue Editors

Prof. Dr. Heung Soo Kim
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Guest Editor
Department of Mechanical, Robotics and Energy Engineering, Dongguk University, 30 Pil-dong 1 Gil, Jung-gu, Seoul 04620, Korea
Interests: smart materials and structures; biomimetic actuators and sensors; smart composite structures; computational structural mechanics
Special Issues and Collections in MDPI journals
Prof.Dr. Asif Khan
Website
Guest Editor
Department of Mechanical, Robotics and Energy Engineering, Dongguk University, 30 Pil-dong 1 Gil, Jung-gu, Seoul 04620, Korea
Interests: mechanics of smart composite laminates; applications of smart materials; machine learning for structural health monitoring; modeling and simulation of dynamic behaviour of engineering systems; finite element methods; energy harvesting from ambient resources
Special Issues and Collections in MDPI journals
Prof. Dr. Jung Woo Sohn
Website
Guest Editor
Department of Mechanical Design Engineering, Kumoh National Institute of Technology, 61 Daehak-ro, Gumi, Gyeongbuk 39177, Korea
Interests: smart materials; smart systems; haptic sytems; soft robotics; robot actuators and sensors; vibration control systems

Special Issue Information

Dear Colleagues,

Sensors play a vital role in a variety of industrial applications such as structural health monitoring, process control, and the mitigation of noise and vibration. Some commonly employed smart materials for sensor applications are piezoelectric materials, shape memory alloys, electroactive polymers, and magnetostrictive materials. Either a theoretical framework or experimental approach could be employed to study the use of sensors made of different materials in smart and intelligent systems and structures, such as piezobonded laminated composites, morphing wings, reconfigurable engine nozzle fan chevron, etc. The aim of this Special Issue is to disseminate new, original, and collective knowledge, gathered from esteemed professionals like yourself, on the use of “Smart Structures and Materials for Sensor Applications”.
You are cordially invited to submit your original research articles and review papers that address the application and characterization of smart materials to the current Special Issue. The list of potential research topics includes, but is not limited to:

  • Modeling of smart intelligent structures and systems
  • Prognostics and health management for engineering systems
  • Structural health monitoring
  • Non-destructive evaluation
  • Computational mechanics
  • Composite structures
  • Energy harvesting
  • Vibration control and isolation
  • Flexible and wearable sensors
  • Sensors in robotics
  • Soft robotics
  • Haptic sytems
  • Solid state sensors
  • Nano sensors

Prof. Dr. Heung Soo Kim
Dr. Aisf Khan
Prof. Dr. Jung Woo Sohn
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • sensors
  • piezoelectric materials
  • shape memory alloys
  • electroactive polymer
  • magnetostrictive materials
  • magnetorheological materials
  • electrorheological materials
  • smart/intelligent structures

Published Papers (9 papers)

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Research

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Open AccessArticle
A Deep Learning Framework for Vibration-Based Assessment of Delamination in Smart Composite Laminates
Sensors 2020, 20(8), 2335; https://doi.org/10.3390/s20082335 - 20 Apr 2020
Cited by 1
Abstract
Delamination is one of the detrimental defects in laminated composite materials that often arose due to manufacturing defects or in-service loadings (e.g., low/high velocity impacts). Most of the contemporary research efforts are dedicated to high-frequency guided wave and mode shape-based methods for the [...] Read more.
Delamination is one of the detrimental defects in laminated composite materials that often arose due to manufacturing defects or in-service loadings (e.g., low/high velocity impacts). Most of the contemporary research efforts are dedicated to high-frequency guided wave and mode shape-based methods for the assessment (i.e., detection, quantification, localization) of delamination. This paper presents a deep learning framework for structural vibration-based assessment of delamination in smart composite laminates. A number of small-sized (4.5% of total area) inner and edge delaminations are simulated using an electromechanically coupled model of the piezo-bonded laminated composite. Healthy and delaminated structures are stimulated with random loads and the corresponding transient responses are transformed into spectrograms using optimal values of window size, overlapping rate, window type, and fast Fourier transform (FFT) resolution. A convolutional neural network (CNN) is designed to automatically extract discriminative features from the vibration-based spectrograms and use those to distinguish the intact and delaminated cases of the smart composite laminate. The proposed architecture of the convolutional neural network showed a training accuracy of 99.9%, validation accuracy of 97.1%, and test accuracy of 94.5% on an unseen data set. The testing confusion chart of the pre-trained convolutional neural network revealed interesting results regarding the severity and detectability for the in-plane and through the thickness scenarios of delamination. Full article
(This article belongs to the Special Issue Smart Structures and Materials for Sensor Applications)
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Open AccessArticle
Development of a Flex and Stretchy Conductive Cotton Fabric Via Flat Screen Printing of PEDOT:PSS/PDMS Conductive Polymer Composite
Sensors 2020, 20(6), 1742; https://doi.org/10.3390/s20061742 - 20 Mar 2020
Cited by 2
Abstract
In this work, we have successfully produced a conductive and stretchable knitted cotton fabric by screen printing of poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) and poly(dimethylsiloxane-b-ethylene oxide)(PDMS-b-PEO) conductive polymer composite. It was observed that the mechanical and electrical properties highly depend on the proportion of [...] Read more.
In this work, we have successfully produced a conductive and stretchable knitted cotton fabric by screen printing of poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) and poly(dimethylsiloxane-b-ethylene oxide)(PDMS-b-PEO) conductive polymer composite. It was observed that the mechanical and electrical properties highly depend on the proportion of the polymers, which opens a new window to produce PEDOT:PSS-based conductive fabric with distinctive properties for different application areas. The bending length analysis proved that the flexural rigidity was lower with higher PDMS-b-PEO to PEDOT:PSS ratio while tensile strength was increased. The SEM test showed that the smoothness of the fabric was better when PDMS-b-PEO is added compared to PEDOT:PSS alone. Fabrics with electrical resistance from 24.8 to 90.8 kΩ/sq have been obtained by varying the PDMS-b-PEO to PEDOT:PSS ratio. Moreover, the resistance increased with extension and washing. However, the change in surface resistance drops linearly at higher PDMS-b-PEO to PEDOT:PSS ratio. The conductive fabrics were used to construct textile-based strain, moisture and biopotential sensors depending upon their respective surface resistance. Full article
(This article belongs to the Special Issue Smart Structures and Materials for Sensor Applications)
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Open AccessArticle
Determining the Fracture Process Zone Length and Mode I Stress Intensity Factor in Concrete Structures via Mechanoluminescent Technology
Sensors 2020, 20(5), 1257; https://doi.org/10.3390/s20051257 - 25 Feb 2020
Abstract
The mechanoluminescent (ML) technology that is being developed as a new and substitutive technology for structural health monitoring systems (SHMS) comprises stress/strain sensing micro-/nanoparticles embedded in a suitable binder, digital imaging system, and digital image processing techniques. The potential of ML technology to [...] Read more.
The mechanoluminescent (ML) technology that is being developed as a new and substitutive technology for structural health monitoring systems (SHMS) comprises stress/strain sensing micro-/nanoparticles embedded in a suitable binder, digital imaging system, and digital image processing techniques. The potential of ML technology to reveal the fracture process zone (FPZ) that is commonly found in structural materials like concrete and to calculate the stress intensity factor (SIF) of concrete, which are crucial for SHMS, has never been done before. Therefore, the potential of ML technology to measure the length of the FPZ and to calculate the SIF has been demonstrated in this work by considering a single-edge notched bend (SENB) test of the concrete structures. The image segmentation approach based on the histogram of an ML image as well the skeletonization of an ML image have been introduced in this work to facilitate the measurement of the length of ML pattern, crack, and FPZ. The results show ML technology has the potential to determine fracture toughness, to visualize FPZ and cracks, and to measure their lengths in structural material like concrete, which makes it applicable to structural health monitoring systems (SHMS) to characterize the structural integrity of structures. Full article
(This article belongs to the Special Issue Smart Structures and Materials for Sensor Applications)
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Open AccessArticle
Impact of Fabric Properties on Textile Pressure Sensors Performance
Sensors 2019, 19(21), 4686; https://doi.org/10.3390/s19214686 - 28 Oct 2019
Cited by 1
Abstract
In recent years, wearable technologies have attracted great attention in physical and chemical sensing applications. Wearable pressure sensors with high sensitivity in low pressure range (<10 kPa) allow touch detection for human-computer interaction and the development of artificial hands for handling objects. Conversely, [...] Read more.
In recent years, wearable technologies have attracted great attention in physical and chemical sensing applications. Wearable pressure sensors with high sensitivity in low pressure range (<10 kPa) allow touch detection for human-computer interaction and the development of artificial hands for handling objects. Conversely, pressure sensors that perform in a high pressure range (up to 100 kPa), can be used to monitor the foot pressure distribution, the hand stress during movements of heavy weights or to evaluate the cyclist’s pressure pattern on a bicycle saddle. Recently, we developed a fully textile pressure sensor based on a conductive polymer, with simple fabrication and scalable features. In this paper, we intend to provide an extensive description on how the mechanical properties of several fabrics and different piezoresistive ink formulation may have an impact in the sensor’s response during a dynamic operation mode. These results highlight the complexity of the system due to the presence of various parameters such as the fabric used, the conductive polymer solution, the operation mode and the desired pressure range. Furthermore, this work can lead to a protocol for new improvements and optimizations useful for adapting textile pressure sensors to a large variety of applications. Full article
(This article belongs to the Special Issue Smart Structures and Materials for Sensor Applications)
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Open AccessArticle
Comparative Performance of Four Electrodes for Measuring the Electromechanical Response of Self-Damage Detecting Concrete under Tensile Load
Sensors 2019, 19(17), 3645; https://doi.org/10.3390/s19173645 - 21 Aug 2019
Abstract
Self-damage or/and stress-sensing concrete is a promising area of research for measuring the electromechanical response of structural materials using more robust sensors. However, the copper and silver paste sensors widely used in such applications can be expensive and have detrimental effects on the [...] Read more.
Self-damage or/and stress-sensing concrete is a promising area of research for measuring the electromechanical response of structural materials using more robust sensors. However, the copper and silver paste sensors widely used in such applications can be expensive and have detrimental effects on the load carrying capacity and durability of the structural systems upon which they are installed. Accordingly, this study compared the performance of four electrode types—conventional copper tape with silver paste (CS), copper film with type 1 carbon tape (CC1), copper film with type 2 carbon tape (CC2), and copper wire and film with type 2 carbon tape (WC2)—to develop an economical and practical electrode for measuring the electromechanical response of self-damage-detecting concrete. The CC1 electrode exhibited comparable performance to the CS electrode in measuring the electromechanical response of self-damage-detecting concrete, despite requiring a longer polarization time (80 s) than the CS electrode (25 s). The CS electrode exhibited a higher damage-sensing capacity (GF2), whereas the CC1 electrode exhibited a higher strain-sensing capacity (GF1), as well as good damage-sensing capacity. Therefore, the CC1 electrode using copper film with type 1 carbon tape was determined to be the best alternative to the conventional CS electrode. Full article
(This article belongs to the Special Issue Smart Structures and Materials for Sensor Applications)
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Open AccessArticle
Facile Chemical Bath Synthesis of SnS Nanosheets and Their Ethanol Sensing Properties
Sensors 2019, 19(11), 2581; https://doi.org/10.3390/s19112581 - 06 Jun 2019
Cited by 2
Abstract
Tin(II) monosulfide (SnS) nanosheets were synthesized using SnCl4•5H2O and S powders as raw materials in the presence of H2O via a facile chemical bath method. Orthorhombic phase SnS nanosheets with a thickness of ~100 nm and lateral [...] Read more.
Tin(II) monosulfide (SnS) nanosheets were synthesized using SnCl4•5H2O and S powders as raw materials in the presence of H2O via a facile chemical bath method. Orthorhombic phase SnS nanosheets with a thickness of ~100 nm and lateral dimensions of 2~10 μm were obtained by controlling the synthesis parameters. The formation of a SnO2 intermediate is key to the valence reduction of Sn ions (from IV to II) and the formation of SnS. The gas sensors fabricated from SnS nanosheets exhibited an excellent response of 14.86 to 100 ppm ethanol vapor when operating at 160 °C, as well as fast response and recovery times of 23 s and 26 s, respectively. The sensors showed excellent selectivity for the detection of ethanol over acetone, methanol, and ammonia gases, which indicates the SnS nanosheets are promising for high-performance ethanol gas sensing applications. Full article
(This article belongs to the Special Issue Smart Structures and Materials for Sensor Applications)
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Open AccessArticle
Relaxation-Related Piezoelectric and Dielectric Behavior of Bi(Mg,Ti)O3–PbTiO3 Ceramic
Sensors 2019, 19(9), 2115; https://doi.org/10.3390/s19092115 - 07 May 2019
Cited by 2
Abstract
Piezoelectric and dielectric materials have attracted much attention for their functional device applications. Despite its excellent piezoelectric properties, the content of lead in piezoelectric materials should be restricted to prevent future environmental problems. Therefore, reduced lead content in piezoelectric materials with similar piezoelectric [...] Read more.
Piezoelectric and dielectric materials have attracted much attention for their functional device applications. Despite its excellent piezoelectric properties, the content of lead in piezoelectric materials should be restricted to prevent future environmental problems. Therefore, reduced lead content in piezoelectric materials with similar piezoelectric properties is favorable. In our research, piezoelectric materials with decreased lead content will be studied and discussed. Even though the lead content is decreased in Bi(Mg0.5Ti0.5)O3–PbTiO3 ceramics, they show piezoelectric properties similar to that of lead zirconate titanate (PZT)-based materials. We believe this high piezoelectric behavior is related to the relaxation behavior of Bi(Mg0.5Ti0.5)O3–PbTiO3 (BMT–PT) ceramics. In this study, 0.62Bi(Mg0.5Ti0.5)O3–0.38PbTiO3 ceramics were prepared by the conventional sintering process. These piezoelectric ceramics were sintered at varying temperatures of 975–1100 °C. Crystallinity and structural properties were analyzed and discussed. X-ray diffraction pattern analysis demonstrated that the optimal sintering temperature was around 1075 °C. A very high Curie temperature of 447 °C was recorded for 0.62BMT–0.38PT ceramics sintered at 1075 °C. For the first time, we found that the origin of the high Curie temperature, d33, and the dielectric constant is the relaxation behavior of different dipoles in 0.62BMT–0.38PT ceramics. Full article
(This article belongs to the Special Issue Smart Structures and Materials for Sensor Applications)
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Open AccessArticle
Thermal Wave Scattering by an Elliptic Subsurface Hole Buried in a Block, Based on the Non-Fourier Equation
Sensors 2019, 19(8), 1878; https://doi.org/10.3390/s19081878 - 19 Apr 2019
Cited by 1
Abstract
With the application to engineering practice, the study of the scattering of thermal waves using innovative and comprehensive methods is becoming increasingly important. The thermal wave scattering by an elliptic subsurface hole in a block with two boundaries is discussed based on the [...] Read more.
With the application to engineering practice, the study of the scattering of thermal waves using innovative and comprehensive methods is becoming increasingly important. The thermal wave scattering by an elliptic subsurface hole in a block with two boundaries is discussed based on the non-Fourier heat conduction equation, employing the complex function method and the conformal mapping method, and a general solution for the thermal wave scattering is given. The numerical results of temperature distributions around a subsurface hole are presented and the effects of geometrical and physical parameters on the temperature distributions were analyzed. The wave number, the shape and position of the hole, the scale of the block, and the frequency of the heat load were found to have great effects on distributions and variations of temperature. The findings of this study could be helpful in providing better understandings of infrared thermal wave imaging, the physical inverse problem, and the evaluation of internal holes in materials. Full article
(This article belongs to the Special Issue Smart Structures and Materials for Sensor Applications)
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Review

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Open AccessReview
PEDOT:PSS-Based Conductive Textiles and Their Applications
Sensors 2020, 20(7), 1881; https://doi.org/10.3390/s20071881 - 28 Mar 2020
Cited by 4
Abstract
The conductive polymer complex poly (3,4-ethylene dioxythiophene):polystyrene sulfonate (PEDOT:PSS) is the most explored conductive polymer for conductive textiles applications. Since PEDOT:PSS is readily available in water dispersion form, it is convenient for roll-to-roll processing which is compatible with the current textile processing applications. [...] Read more.
The conductive polymer complex poly (3,4-ethylene dioxythiophene):polystyrene sulfonate (PEDOT:PSS) is the most explored conductive polymer for conductive textiles applications. Since PEDOT:PSS is readily available in water dispersion form, it is convenient for roll-to-roll processing which is compatible with the current textile processing applications. In this work, we have made a comprehensive review on the PEDOT:PSS-based conductive textiles, methods of application onto textiles and their applications. The conductivity of PEDOT:PSS can be enhanced by several orders of magnitude using processing agents. However, neat PEDOT:PSS lacks flexibility and strechability for wearable electronics applications. One way to improve the mechanical flexibility of conductive polymers is making a composite with commodity polymers such as polyurethane which have high flexibility and stretchability. The conductive polymer composites also increase attachment of the conductive polymer to the textile, thereby increasing durability to washing and mechanical actions. Pure PEDOT:PSS conductive fibers have been produced by solution spinning or electrospinning methods. Application of PEDOT:PSS can be carried out by polymerization of the monomer on the fabric, coating/dyeing and printing methods. PEDOT:PSS-based conductive textiles have been used for the development of sensors, actuators, antenna, interconnections, energy harvesting, and storage devices. In this review, the application methods of PEDOT:SS-based conductive polymers in/on to a textile substrate structure and their application thereof are discussed. Full article
(This article belongs to the Special Issue Smart Structures and Materials for Sensor Applications)
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