Search Results (284)

In this paper, we report a novel application of atomic force microscopy (AFM) for measurement of wear of prosthetic materials. In contrast to previously employed methods, we introduce AFM-based wear induction. In this way, we utilize AFM as both measurement technique and the mean for surface wear. We describe the methodology along with the metrological advantages of the approach regarding the supreme resolution of volume measurement (down to 1 μm³). We investigate wear between prosthetic gold alloy (Degulor M) and FGP polymeric material from Bredent in nanoscale. For that purpose, we modify active piezoresistive cantilever, replacing the original tip with Degulor M microsphere. We elaborate on the process of modification and present how the mass volume and topology of the tip is controlled throughout the process. Wear process was performed in reciprocal motion over the length of 5 μm in 35,000 repetitions to mimic the actual conditions occurring in human mouth cavity. We present how this method, by focusing on a small area of investigated materials, leads to shortening the overall time of wear measurements from tong term observations down to several minutes. AFM-measured data present consistent relation between wear energy and wear volume. Exemplary results seem to confirm durability of the FGP-Degulor M mechanical contact and occurring strengthening of the mechanical contact with roughening of the polymeric surface. Full article

With the rapid development of wearable devices and intelligent human–machine interaction technologies, the demand for high-precision pressure sensors has soared. Piezoresistive pressure sensors excel due to their simple structure, low cost, and high sensitivity, among which flexible piezoresistive pressure sensors based on porous polymers have become a research focus, thanks to their unique 3D porous structure and excellent performance. This review summarizes recent advances: it introduces key performance metrics and the piezoresistive sensing mechanism; outlines porous structure preparation methods (phase separation, 3D printing, electrospinning) with their principles, advantages, and limitations; examines conductive fillers (carbon-based, polymer, metal, MXene) with their properties and applications; and highlights flexible substrates (silicone, polyurethane, polyimide, natural polymers) in ensuring mechanical compliance and device integration. Studies show material innovation, structural optimization, and process improvement can significantly enhance sensor accuracy, stability, and durability, helping break traditional performance bottlenecks. Future prospects are broad in tactile sensing, biomedical monitoring, and human–machine interaction, providing references for related research and industrial development. Full article

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

Rapid developments in intelligent interfaces across service, healthcare, and industry have led to unprecedented demands for advanced tactile perception systems. Traditional tactile sensors often struggle with adaptability on curved surfaces and lack sufficient feedback for delicate interactions. Flexible and wearable tactile sensors are emerging as a revolutionary solution, driven by innovations in flexible electronics and micro-engineered materials. This paper reviews recent advancements in flexible tactile sensors, focusing on their mechanisms, multifunctional performance and applications in health monitoring, human–machine interactions, and robotics. The first section outlines the primary transduction mechanisms of piezoresistive (resistance changes), capacitive (capacitance changes), piezoelectric (piezoelectric effect), and triboelectric (contact electrification) sensors while examining material selection strategies for performance optimization. Next, we explore the structural design of multifunctional flexible tactile sensors and highlight potential applications in motion detection and wearable systems. Finally, a detailed discussion covers specific applications of these sensors in health monitoring, human–machine interactions, and robotics. This review examines their promising prospects across various fields, including medical care, virtual reality, precision agriculture, and ocean monitoring. Full article

Sensor arrays are arrangements of sensors that follow a certain pattern, usually in a row–column distribution. This study presents a systematic review on sensor arrays. For this purpose, several systematic searches of recent studies covering a period of 10 years were performed. As a result of these searches, 361 papers have been analyzed in detail. The most relevant aspects for sensor array design have been studied. In relation to sensing technologies, different categories were identified: resistive/piezoresistive, capacitive, inductive, diode-based, transistor-based, triboelectric, fiber optic, Hall effect-based, piezoelectric, and bioimpedance-based. Other aspects of sensor array design have also been analyzed: applications, validation experiments, software used for sensor array data analysis, sensor array characteristics, and performance metrics. For each aspect, the studies were classified into different subcategories. As a result of this analysis, different emerging technologies and future research challenges in sensor arrays were identified. Full article

The development of multifunctional conductive hydrogels with rapid self-healing capabilities and powerful sensing functions is crucial for advancing wearable electronics. This study designed and prepared a polyvinyl alcohol (PVA)–borax hydrogel incorporating carbon nanotubes (CNTs) and biomass carbon nanospheres (CNPs) as dual-carbon fillers. This hydrogel exhibits excellent conductivity, mechanical flexibility, and self-recovery properties. Serving as a highly sensitive piezoresistive sensor, it efficiently converts mechanical stimuli into reliable electrical signals. Sensing tests demonstrate that the CNT/CNP/PVA–borax hydrogel sensor possesses an extremely fast response time (88 ms) and rapid recovery time (88 ms), enabling the detection of subtle and rapid human motions. Furthermore, the hydrogel sensor also exhibits outstanding cyclic stability, maintaining stable signal output throughout continuous loading–unloading cycles exceeding 3200 repetitions. The hydrogel sensor’s characteristics, including rapid self-healing, fast-sensing response/recovery, and high fatigue resistance, make the CNT/CNP/PVA–borax conductive hydrogel an ideal choice for multifunctional wearable sensors. It successfully monitored various human motions. This study provides a promising strategy for high-performance self-healing sensing devices, suitable for next-generation wearable health monitoring and human–machine interaction systems. 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

Fibrous structure is a promising building block for developing high-performance wearable piezoresistive sensors. However, the inherent non-conductivity of the fibrous polymer remains a bottleneck for highly sensitive and fast-responsive piezoresistive sensors. Herein, we reported a polyaniline/reduced graphene oxide @ polydopamine/poly (vinylidene fluoride) (PANI/rGO@PDA/PVDF) nanofiber piezoresistive sensor (PNPS) capable of versatile wearable biomonitoring. The PNPS was fabricated by integrating rGO sheets and PANI particles into a PDA-modified PVDF nanofiber network, where PDA was implemented to boost the interaction between the nanofiber networks and functional materials, PANI particles were deposited on a nanofiber substrate to construct electroactive nanofibers, and rGO sheets were utilized to interconnect nanofibers to strengthen in-plane charge carrier transport. Benefitting from the synergistic effect of multi-dimensional electroactive materials in piezoresistive membranes, the as-fabricated PNPS exhibits a high sensitivity of 13.43 kPa⁻¹ and a fast response time of 9 ms, which are significantly superior to those without an rGO sheet. Additionally, a wide pressure detection range from 0 to 30 kPa and great mechanical reliability over 12,000 cycles were attained. Furthermore, the as-prepared PNPS demonstrated the capability to detect radial arterial pulses, subtle limb motions, and diverse respiratory patterns, highlighting its potential for wearable biomonitoring and healthcare assessment. 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

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

The current effect of passive devices is crucial for device testing. The current effect of a suspended graphene pressure sensor in the range of 0–2 mA is studied in this paper. The results show that the resistance of graphene films and the piezoresistive effect of devices exhibit stable performance within the current threshold range of 400 μA and 300 μA, respectively. Auger electron spectroscopy and Raman spectroscopy tests indicate that the resistance of graphene increases first and then decreases at high current intensity, resulting from the electrostatic adsorption of oxygen atoms in the initial phase of electrification and the Joule-induced desorption in the later phase. This study presents guiding significance for the electrical testing of suspended graphene devices. Full article

On-chip optical accelerometers can be a promising alternative to capacitive, piezo-resistive, and piezo-electric accelerometers in some applications due to their immunity to electromagnetic interference and high sensitivity, which allow for robust operation in electromagnetically noisy environments. This paper focuses on the characterization of an easy-to-fabricate tri-axial fiber-free optical MEMS accelerometer, which employs a simple assembly consisting of a light emitting diode (LED), a quadrant photodetector (QPD), and a suspended proof mass, measuring acceleration through light power modulation. This configuration enables simple readout circuitry without the need for complex digital signal processing (DSP). Performance modeling was conducted to simulate the LED’s irradiance profile and its interaction with the proof mass and QPD. Additionally, experimental tests were performed to measure the device’s mechanical sensitivity and validate the mechanical model. Lateral mechanical sensitivity is obtained with acceptable discrepancy from that obtained from FEA simulations. This work consolidates the performance of the design adapted and demonstrates the accelerometer’s feasibility for practical applications. Full article

Smart cement-based materials have the potential to monitor the health of structures. The performances of composites with various kinds of conductive fillers have been found to be sensitive and stable. However, poor dispersion of conductive fillers limits their application. This study adopted the coupling agent method to attach carbon nanotubes (CNTs) onto the surface of carbon fibers (CFs). The CNT-grafted CFs (CNT-CFs) were adopted as conductive fillers to develop a CNT-CF-incorporated cementitious composite (CNT-CF/CC). The feasibility of this approach was demonstrated through Scanning Electron Microscopy (SEM) analysis and X-ray Photoelectron Spectroscopy (XPS) analysis. The CNT-CF/CC exhibited excellent conductivity because of the introduction of CNTs compared with the CF-incorporated cementitious composite (CF/CC). The CNT-CF/CC reflected huge responses under different temperatures and moisture contents. Even under conditions of high humidity or elevated temperatures, the CNT-CF/CC demonstrated stable performance and exhibited a broad measurement range. The introduction of CNT-CFs also enhanced the mechanical properties of the composite, displaying superior piezoresistivity. The failure load for the CNT-CF/CC reached 25 kN and the maximum FCR was 24.77%. In the cyclic loading, the maximum FCR reached 20.03% when subjected to peak cyclic load at 45% of the failure load. The additional conductive pathways introduced by CNTs enhanced the conductivity and sensitivity of the composite. And the anchoring connection between CNT-CFs and the cement matrix has been identified as a primary factor enhancing the stability in performance. Full article

Soft sensors are designed to be flexible, making them ideal for wearable devices as they can conform to the human body during motion, capturing pertinent information effectively. However, once these wearable sensors are constructed, modifying them is not straightforward without undergoing a re-prototyping process. In this study, we introduced a novel design for a modular soft sensor unit (M2SU) that incorporates a short, wire-shaped sensory structure made of eutectogel, with magnetic blocks at both ends. This design facilitates the easy assembly and reversible integration of the sensor directly onto a wearable device in situ. Leveraging the piezoresistive properties of eutectogel and the dual conductive and magnetic characteristics of neodymium magnets, our sensor unit acts as both a sensing element and a modular component. To explore the practical application of M2SUs in wearable sensing, we equipped a glove with 8 M2SUs. We evaluated its performance across three common gesture recognition tasks: numeric keypad typing (Task 1), symbol drawing (Task 2), and uppercase letter writing (Task 3). Employing a 1D convolutional neural network to analyze the collected data, we achieved task-specific accuracies of 80.43% (Top 3: 97.68%) for Task 1, 88.58% (Top 3: 96.13%) for Task 2, and 79.87% (Top 3: 91.59%) for Task 3. These results confirm that our modular soft sensor design can facilitate high-accuracy gesture recognition on wearable devices through straightforward, in situ assembly. Full article