Search Results (168)

Tire deformation monitoring is a critical requirement for improving vehicle safety, performance, and intelligent transportation systems. However, most existing flexible strain sensors either lack directional sensitivity or have not been validated in real-world driving environments, limiting their practical application in smart tires. In this work, we report the fabrication of a flexible piezoresistive strain sensor based on a porous laser-induced graphene (LIG) network embedded in an Ecoflex elastomer matrix, with integrated directional force recognition. The LIG–Ecoflex sensor exhibits a high gauge factor of 9.7, fast response and recovery times, and stable performance over 10,000 cycles. More importantly, the anisotropic structure of the LIG enables accurate multi-directional stress recognition when combined with a convolutional neural network (CNN), achieving an overall classification accuracy exceeding 98%. To further validate real-world applicability, the sensor was mounted inside passenger car tires and tested under different loads and speeds. The results demonstrate reliable monitoring of tire deformation with clear correlations to load and velocity, confirming robustness under dynamic driving conditions. This study provides a new pathway for the integration of direction-aware, high-performance strain sensors into intelligent tire systems, with broader potential for wearable electronics, vehicle health monitoring, and next-generation Internet of Vehicles applications. Full article

Flexible strain sensors, fabricated from high-elongation polymers and conductive filler particles, are proving an essential tool in the study of biomechanics using wearable technology. It has been previously shown that the resistive response of such composites, relative to the amount of conductive filler material, can be reasonably modeled using a standard percolation-type model. Once a certain critical fraction of filler material is reached, a conductive network across the sample is established and resistance rapidly decreases. However, modeling the more subtle resistance changes that occur while deforming the sensors during operation is more nuanced. Conductivity across the network of particles is dominated by tunneling mechanisms at the interfaces between the filler materials. Small changes in strain at these interfaces lead to relatively large, but nevertheless continuous, changes in local resistance. By assigning some arbitrary value of resistance as a dividing line between ‘low’ and ‘high’ resistance, one might model the piezoresistive behavior using a standard percolation model. But such an assumption is likely to lead to low accuracy. Our alternative approach is to divide the range of potential resistance values into several bins (rather than the usual two bins) and apply a relatively novel multi-state percolation theory. The performance of the multi-state percolation model is assessed using a random resistor model that is assumed to provide the ground truth. The model is applied to predict resistance response with both changes in relative amount of conductive filler (i.e., to help design the initial unstrained sensor) and with applied strain (for an operating sensor). We find that a multi-state percolation model captures the behavior of the simulated composite sensor in both cases. The multicomponent percolation theory becomes more accurate with more divisions/bins of the resistance distribution, and we found good agreement with the simulation using between 10 and 20 divisions. Full article

Polyurethane (PU) foam, renowned for its structural versatility, elasticity, compressibility, and adaptability, has garnered significant attention for its use in flexible strain sensors due to its capability to detect mechanical deformation. This review presents a comprehensive analysis of both the studies and recent advancements in PU foam-based strain sensors, particularly those incorporating conductive materials. The review begins by examining the chemical composition and structural characteristics of PU foam, followed by a discussion of various fabrication methods and their effects on sensor performance. It also explores the sensing mechanisms, including piezoresistive, piezoelectric, and capacitive effects. Moreover, key applications in motion detection, health monitoring, and environmental and industrial sensing are examined. Finally, the review addresses technological advancements, current challenges, and prospects. Full article

A flexible and highly sensitive piezoresistive strain sensor was fabricated through the application of CO₂ laser ablation on a composite film composed of multi-walled carbon nanotubes, carbon black, and polydimethylsiloxane (MWCNT/CB/PDMS). The results of scanning electron microscopy (SEM) surface analysis shows that the “bush-like” conductive structure on the PDMS-based composite material membrane post-laser ablation is formed. Transmission electron microscopy (TEM) images and X-ray diffraction (XRD) spectra of the ablation products indicated the formation of an amorphous carbon layer on the surface of carbon nanomaterials due to laser ablation. Experimental findings revealed that the sensitivity (GF) value of the sensor based on CNT0.6CB1.0-P3.0 is up to 584.7 at 5% strain, which is approximately 14% higher than the sensitivity 513 of the sensor previously prepared by the author using CO₂ laser ablation of MWCNT/PDMS composite films. The addition of a very small volume fraction of CB particles significantly enhances the piezoresistive sensitivity of the sensor samples. Combined with the qualitative analysis of microscopic morphology characterization, CB and MWCNT synergistically promote the deposition of amorphous carbon. This phenomenon increases the probability of tunnel effect occurrence in the strain response region of the sensor, which indirectly confirms the synergistic enhancement effect of the combined action of CB and MWCNT on the piezoresistive sensitivity of the sensor. Full article

This paper presents a comparative study examining the effects of carbon nanotubes (CNTs) and expanded graphite (EG) on the thermal, mechanical, morphological, electrical, and piezoresistive properties of poly(ethylene-co-methacrylic acid) (EMAA) nanocomposites. To this end, different amounts of carbonaceous fillers (EG and CNTs separately) were added to the EMAA thermoplastic matrix, and the relative electrical percolation thresholds (EPTs) were determined. The effect of filler concentration on thermo-oxidative degradation and the EMAA crystallinity was investigated via thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC), respectively. Dynamic mechanical analysis (DMA) demonstrated that both fillers enhance the Young’s and storage moduli, as well as the glass transition temperature, with a greater improvement for the bidimensional nanofiller, most likely due to the cumulative effect of more extensive EG-matrix interactions. In tensile tests, a very relevant difference was detected in the Gauge Factor (G.F.) and the elongation at break of the two typologies of nanocomposites. The G.F. of EMAA 10% CNT and EMAA 15% EG were found to be 0.5 ± 0.08 and 165 ± 14, respectively, while elongation at break was about 68% for EMAA 10% CNT and 8% for EMAA 15% EG. Emission Scanning Electron Microscopy (FESEM) and Tunneling Atomic Force Microscopy (TUNA) have contributed to explaining the differences between EG- and CNT-based nanocomposites from a morphological point of view, underlying the pivotal role of the filler aspect ratio and its structural features in determining different mechanical and piezoresistive performance. The comprehensive analysis of EMAA-EG and EMAA-CNT nanocomposites provides a guide for selecting the best self-sensing system for the specific application. More specifically, EMAA-CNT nanocomposites with high elongation at break and lower sensitivity to small strains are suitable for movement sensors in the soft robotic field, where high deformation has to be detected. On the other hand, the high sensitivity at a low strain of EMAA-EG systems makes them suitable for integrated sensors in more rigid composite structures, such as aeronautical and automotive components or wind turbines. Full article

Carbon nanotubes (CNTs) have emerged as pivotal nanomaterials in sensing technologies owing to their unique structural, electrical, and mechanical properties. Their high aspect ratio, exceptional surface area, excellent electrical conductivity, and chemical tunability enable superior sensitivity and rapid response in various sensor platforms. This review presents a comprehensive overview of recent advancements in CNT-based sensors, encompassing both single-walled (SWCNTs) and multi-walled carbon nanotubes (MWCNTs). We discuss their functional roles in diverse sensing applications, including gas sensing, chemical detection, biosensing, and pressure/strain monitoring. Particular emphasis is placed on the mechanisms of sensing, such as changes in electrical conductivity, surface adsorption phenomena, molecular recognition, and piezoresistive effects. Furthermore, we explore strategies for enhancing sensitivity and selectivity through surface functionalization, hybrid material integration, and nanostructuring. The manuscript also covers the challenges of reproducibility, selectivity, and scalability that hinder commercial deployment. In addition, emerging directions such as flexible and wearable CNT-based sensors, and their role in real-time environmental, biomedical, and structural health monitoring systems, are critically analyzed. By outlining both current progress and existing limitations, this review underscores the transformative potential of CNTs in the design of next-generation sensing technologies across interdisciplinary domains. Full article

Monitoring posture and movement accurately and efficiently is essential for both physical therapy and athletic training evaluation and interventions. Motion Tape (MT), a self-adhesive wearable skin-strain sensor made of piezoresistive graphene nanosheets (GNS), has demonstrated promise in capturing low back posture and movements. However, to address some of its limitations, this work explores alternative materials by replacing GNS with multi-walled carbon nanotubes (MWCNT). This study aimed to characterize the electromechanical properties of MWCNT-based MT. Cyclic load tests for different peak tensile strains ranging from 1% to 10% were performed on MWCNT-MT made with an aqueous ink of 2% MWCNT. Additional tests to examine load rate sensitivity and fatigue were also conducted. After characterizing the properties of MWCNT-MT, a human subject study with 10 participants was designed to test its ability to capture different postures and movements. Sets of six sensors were made from each material (GNS and MWCNT) and applied in pairs at three levels along each side of the lumbar spine. To record movement of the lower back, all participants performed forward flexion, left and right bending, and left and right rotation movements. The results showed that MWCNT-MT exceeded GNS-MT with respect to consistency of signal stability even when strain limits were surpassed. In addition, both types of MT could assess lower back movements. Full article

Vibration sensors are important in many engineering fields, including industry, surgery, space, and mechanics, such as for remote and autonomous driving. We propose a novel, cutting-edge vibratory sensor that mimics human tactile receptors, with a configuration different from current sensors such as strain gauges and piezo materials. The basic principle involves the perception of vibration via touch, with a cutaneous mechanoreceptor that is sensitive to vibration. We investigated the characteristics of the proposed vibratory sensor, in which the mechanoreceptor was covered either in hard rubber (such as silicon oil) or soft rubber (such as urethane), for both low- and high-frequency ranges. The fabricated sensor is based on piezoelectricity with a built-in voltage. It senses applied vibration by means of hairs in the sensor and the hardness of the outer cover. We also investigated two proposed parameters: the sensor response time to stimuli to the vibration aiding the equivalent firing rate (e.f.r.) and the gauge factor (GF_,pe) proposed as treated in piezo-resistivity. The evaluation with the parameters was effective in designing a sensor based on piezoelectricity. These parameters were enhanced by the hairs in the sensor and the hardness of the outer cover. Our results were helpful for designing the present novel vibratory sensor. Full article

The intrinsic trade-off among sensitivity, response speed, and measurement range continues to hinder the wider adoption of flexible pressure sensors in areas such as medical diagnostics and gesture recognition. In this work, we propose a grid-structured polycaprolactone/thermoplastic-polyurethane nanofiber pressure sensor decorated with multi-walled carbon nanotubes (PCL/TPU@MWCNTs). By introducing a gradient grid membrane, the strain distribution and reconstruction of the conductive network can be modulated, thereby alleviating the conflict between sensitivity, response speed, and operating range. First, static mechanical simulations were performed to compare the mechanical responses of planar and grid membranes, confirming that the grid architecture offers superior sensitivity. Next, PCL/TPU@MWCNT nanofiber membranes were fabricated via coaxial electrospinning followed by vacuum-filtration and assembled into three-layer planar and grid piezoresistive pressure sensors. Their sensing characteristics were evaluated by simple index-finger motions and slide the mouse wheel identified. Within 0–34 kPa, the sensitivities of the planar and grid sensors reached 1.80 kPa⁻¹ and 2.24 kPa⁻¹, respectively; in the 35–75 kPa range, they were 1.03 kPa⁻¹ and 1.27 kPa⁻¹. The rise/decay times of the output signals were 10.53 ms/11.20 ms for the planar sensor and 9.17 ms/9.65 ms for the grid sensor. Both sensors successfully distinguished active index-finger bending at 0–0.5 Hz. The dynamic range of the grid sensor during the extension motion of the index finger is 105 dB and, during the scrolling mouse motion, is 55 dB, affording higher measurement stability and a broader operating window, fully meeting the requirements for high-precision hand-motion recognition. Full article

The durability of piezoresistive sensor materials is a core prerequisite for their implementation in structural health monitoring systems. In this work, three piezoresistive materials were subjected to extensive cyclic tensile loadings, and their behaviour was analysed before, after, and during testing. To this end, aluminium specimens were coated with three different industry-grade lacquers, and then piezoresistive materials were applied onto each specimen. Sensors made from carbon black displayed excellent linearity even after tensile loading cycles ($R^2>0.88$). A decline in linearity of all sensors based on carbon allotropes was discovered, whereas the polymer-based sensors improved. Furthermore, their adhesion to the substrate is of great importance. Good adhesion ensures the strains in the underlying structure are correctly transmitted into the sensor materials. Based on contact angle measurements of liquids on sensor materials and on lacquers, their work of adhesion was determined. The findings were verified by tape adhesion tests. Full article

Carbon nanomaterials, particularly carbon nanotubes (CNTs), are widely used as reinforcing fillers in rubber composites for advanced mechanical and electrical applications. However, the influence of rubber functionality and its interactions with CNTs remains underexplored. This study investigates electroactive elastomeric composites fabricated with CNTs in two common diene rubbers: natural rubber (NR) and acrylonitrile-butadiene rubber (NBR), each with distinct functionalities. For NR-based composites containing 2 vol% CNTs, mechanical properties, such as elastic modulus (2.24 MPa), tensile strength (12.48 MPa), and fracture toughness (26.92 MJ/m³), show significant improvements of 125%, 215%, and 164%, respectively, compared to unfilled rubber. Similarly, for NBR-based composites, the elastic modulus (5.46 MPa), tensile strength (13.47 MPa), and fracture toughness (82.89 MJ/m³) increase by 94%, 22%, and 65%, respectively, over the unfilled system. Although NBR-based composites exhibit higher mechanical properties, NR systems show more significant improvements, suggesting stronger chemical bonding between NR chains and CNTs, as evidenced by dynamic mechanical, X-ray diffraction, thermogravimetric, and thermodynamic analyses. The NBR-based composite at 1 vol% CNT content exhibits 261% higher piezoresistive strain sensitivity (GF = 65 at 0% ≤ Δε ≤ 200%) compared to the NR-based composite (GF = 18 at 0% ≤ Δε ≤ 200%). The highest gauge factor of 39,125 (1000% ≤ Δε ≤ 1220) was achieved in NBR-based composites with 1 vol% CNT content. However, 1.5 vol% CNT content in NBR provides better strain sensitivity and linearity than other composites. Additionally, NBR demonstrates superior electromechanical actuation properties, with 1317% higher actuation displacement and 276% higher electromechanical pressure compared to NR at an applied electric field of 12 kV. Due to the stronger chemical bonding between the rubber and CNT, NR-based composites are more suitable for dynamic mechanical applications. In contrast, NBR-based CNT composites are ideal for stretchable electromechanical sensors and actuators, owing to the high dielectric constant and polarizable functional groups in NBR. Full article

MEMS acoustic sensors are a type of physical quantity sensor based on MEMS manufacturing technology for detecting sound waves. They utilize various sensitive structures such as thin films, cantilever beams, or cilia to collect acoustic energy, and use certain transduction principles to read out the generated strain, thereby obtaining the targeted acoustic signal’s information, such as its intensity, direction, and distribution. Due to their advantages in miniaturization, low power consumption, high precision, high consistency, high repeatability, high reliability, and ease of integration, MEMS acoustic sensors are widely applied in many areas, such as consumer electronics, industrial perception, military equipment, and health monitoring. Through different sensing mechanisms, they can be used to detect sound energy density, acoustic pressure distribution, and sound wave direction. This article focuses on piezoelectric, piezoresistive, capacitive, and optical MEMS acoustic sensors, showcasing their development in recent years, as well as innovations in their structure, process, and design methods. Then, this review compares the performance of devices with similar working principles. MEMS acoustic sensors have been increasingly widely applied in various fields, including traditional advantage areas such as microphones, stethoscopes, hydrophones, and ultrasound imaging, and cutting-edge fields such as biomedical wearable and implantable devices. Full article

Piezoresistive sensors composed of nickel nanostrands, nickel-coated carbon fibers, and silicone can be used to measure large physical deflections but exhibit viscoelastic properties and creep, leading to a complex and nonlinear electrical response that is difficult to interpret. This study considers the impact of modifying the geometry and architecture of the sensors on their mechanical and electrical performance. Varying the sensor thickness leads to potentially significant differences in conductive fiber alignment, while adding external layers of pure silicone provides elastic support for the sensors, potentially reducing their extreme viscoelastic nature. The impact of such modifications on both mechanical and electrical behavior was assessed by analyzing strain to failure, the magnitude of hysteresis with cycling, the repeatability of the electro-mechanical response, the strain level at which resistance begins to monotonically decrease, and the drift in electrical response with cycling. The results indicate that thicker single-layer sensors have less electrical drift. Sensors with a multilayered architecture exhibit several improvements in behavior, such as increasing the range of the monotonic region by approximately 52%. These improvements become more significant as the thickness of the pure silicone layers increases. Full article

This study explores a novel approach to obtaining 3D printed strain sensors, focusing on how changing the printing conditions can produce a different piezoresistive response. Acrylonitrile butadiene styrene (ABS) filled with different weight concentrations of carbon nanotubes (CNTs) was printed in the form of dog bones via fused filament fabrication (FFF) using two different raster angles (0–90°). Scanning electron microscopy (SEM) and atomic force microscopy (AFM) in TUNA mode (TUNA-AFM) were used to study the morphological features and the electrical properties of the 3D printed samples. Tensile tests revealed that sensitivity, measured by the gauge factor (G.F.), decreased with increasing filler content for both raster angles. Notably, the 90° orientation consistently showed higher sensitivity than the 0° orientation for the same filler concentration. Creep and fatigue tests identified permanent damage through residual electrical resistance values. Additionally, a cross-shaped sensor was designed to measure two-dimensional deformations simultaneously, which is applicable in the robotic field. This sensor can monitor small and large deformations in perpendicular directions by tracking electrical resistance variations in its arms, significantly expanding its measuring range. Full article

High electrical conductivity, along with high piezoresistive sensitivity and stretchability, are crucial for designing and developing nanocomposite strain sensors for damage sensing and on-line structural health monitoring of smart carbon fiber-reinforced polymer (CFRP) composites. In this study, the influence of the geometric features and loadings of carbon-based nanomaterials, including reduced graphene oxide (rGO) or carbon nanofibers (CNFs), on the tunable strain-sensing capabilities of epoxy-based nanocomposites was investigated. This work revealed distinct strain-sensing behavior and sensitivities (gauge factor, GF) depending on both factors. The highest GF values were attained with 0.13 wt.% of rGO at various strains. The stability and reproducibility of the most promising self-sensing nanocomposites were also evaluated through ten stretching/relaxing cycles, and a distinct behavior was observed. While the deformation of the conductive network formed by rGO proved to be predominantly elastic and reversible, nanocomposite sensors containing 0.714 wt.% of CNFs showed that new conductive pathways were established between neighboring CNFs. Based on the best results, formulations were selected for the manufacturing of pre-impregnated materials and related smart CFRP composites. Digital image correlation was synchronized with electrical resistance variation to study the strain-sensing capabilities of modified CFRP composites (at 90° orientation). Promising results were achieved through the incorporation of CNFs since they are able to form new conductive pathways and penetrate between micrometer-sized fibers. Full article