Search Results (201)

In this research, a single composite-type stretchable triboelectric nanogenerator (TENG) is proposed for efficient energy harvesting and handwriting recognition. The composite TENGs were fabricated by blending dielectric barium titanate (BT) and conductive carbon nanotubes (CNTs) in varying amounts into a styrene–butadiene rubber matrix. The energy harvesting efficiency depends on the type and amount of fillers, as well as their dispersion within the matrix. Stearic acid modification of BT enables near-nanoscale filler distribution, resulting in high energy conversion efficiencies. The composite achieved power efficiency, power density, charge efficiency, and charge density values of 1.127 nW/N, 8.258 mW/m³, 0.146 nC/N, and 1.072 mC/m³, respectively, under only 2% cyclic compressive strain at 0.85 Hz. The material performs better at low stress–strain ranges, exhibiting higher charge efficiency. The generated charge in the TENG composite is well correlated with the compressive stress, which provides a minimum activation pressure of 0.144 kPa, making it suitable for low-pressure sensing applications. A flat composite with dimensions of 0.02 × 6 × 5 cm³ can produce a power density of 26.04 W/m³, a charge density of 0.205 mC/m³, and an output voltage of 10 V from a single hand pat. The rubber composite also demonstrates high accuracy in handwriting recognition across different individuals, with clear differences in sensitivity curves. Repeated attempts by the same person show minimal deviation (<5%) in writing time. Additionally, the presence of reinforcing fillers enhances mechanical strength and durability, making the composite suitable for long-term cyclic energy harvesting and wearable sensor applications. Full article

Liquid metals (LMs), with their unique combination of high electrical conductivity and mechanical deformability, have emerged as promising materials for stretchable electronics and biointerfaces. However, the practical application of bulk LMs in wearable sensors has been hindered by processing challenges and low stability. To overcome these limitations, liquid metal particles (LMPs) encapsulated by native oxide shells have gained attention as versatile and stable fillers for stretchable and conductive composites. Recent advances have focused on the development of LM-based hybrid composites that combine LMPs with metal, carbon, or polymeric fillers. These systems offer enhanced electrical and mechanical properties and can form conductive networks without the need for additional sintering processes. They also impart composites with multiple functions such as self-healing, electromagnetic interference shielding, and recyclability. Hence, the present review summarizes the fabrication methods and functional properties of LM-based composites, with a particular focus on their applications in wearable sensing. In addition, recent developments in the use of LM composites for physical motion monitoring (e.g., strain and pressure sensing) and electrophysiological signal recording (e.g., EMG and ECG) are presented, and the key challenges and opportunities for next-generation wearable platforms are discussed. Full article

Structural Health Monitoring (SHM) is an essential technique for continuously assessing structural conditions using integrated sensor systems during operation. SHM technologies have evolved to address the increasing demand for efficient maintenance strategies in advanced engineering fields, such as civil infrastructure, aerospace, and transportation. However, developing a miniaturized, cost-effective, and multi-sensor solution based on Wireless Sensor Networks (WSNs) remains a significant challenge, particularly for SHM applications in weight-sensitive aerospace structures. To address this, the present study introduces a novel WSN-based Multi-Sensor System (MSS) that integrates multiple sensing capabilities onto a 3 × 3 cm flexible Printed Circuit Board (PCB). The proposed system combines a Piezoelectric Transducer (PZT) for impact detection; a strain gauge for mechanical deformation monitoring; an accelerometer for capturing dynamic responses; and an environmental sensor measuring temperature, pressure, and humidity. This high level of functional integration, combined with real-time Data Acquisition (DAQ) and precise time synchronization via Bluetooth Low Energy (LE), distinguishes the proposed MSS from conventional SHM systems, which are typically constrained by bulky hardware, single sensing modalities, or dependence on wired communication. Experimental evaluations on composite panels and aluminum specimens demonstrate reliable high-fidelity recording of PZT signals, strain variations, and acceleration responses, matching the performance of commercial instruments. The proposed system offers a low-power, lightweight, and scalable platform, demonstrating strong potential for on-board SHM in aircraft applications. Full article

This paper presents an analysis of the time-dependent response of a spherical container to internal pressure that increases over time. The wall of the container is relatively thin, in the sense that the wall thickness is negligible in comparison to the container’s radius. The wall is composed of three layers. The two surface layers of the wall are identical, i.e., they are made from the same material and have the same thickness. One of the most important features regarding the response of the wall layers is the non-linear creep. The stresses and strains are determined, and their relationships with the parameters of the layers are studied. Full article

Wearable sensors have rapidly advanced, enabling applications such as human activity monitoring, electronic skin, and biomimetic robotics. To meet the growing demands of these applications, multifunctional sensing has become essential for wearable devices. However, most existing studies predominantly focus on enhancing single-function sensing capabilities. This study introduces a multifunctional sensor that combines high stretchability for strain and pressure detection with ultraviolet (UV) sensing capability. To achieve simultaneous detection of strain, pressure, and UV light, a multi-sensing approach was employed: a capacitive method for strain and pressure detections and a resistive method utilizing a pn-heterojunction diode for UV detection. In the capacitive method, polyaniline (PANI) served as parallel-plate electrodes, while silicon-based elastomer acted as the dielectric layer. This configuration enabled up to 100% elongation and enhanced operational stability through encapsulation. The sensor demonstrated a strong linear relationship between capacitance value changes reasonably based on the area of PANI, and showed a good linearity with an R-squared value of 0.9918. It also detected pressure across a wide range, from low (0.4 kPa) to high (9.4 kPa). Furthermore, for wearable applications, the sensor reliably captured capacitance variations during finger bending at different angles. For UV detection, a pn-heterojunction diode composed of p-type silicon and n-type zinc oxide nanorods exhibited a rapid response time of 6.1 s and an on/off ratio of 13.8 at −10 V. Durability under 100% tensile strain was confirmed through Von Mises stress calculations using finite element modeling. Overall, this multifunctional sensor offers significant potential for a variety of applications, including human motion detection, wearable technology, and robotics. 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

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

Biofilms, structured microbial consortia embedded in self-produced extracellular matrices, pose significant challenges across the medical, industrial, and environmental sectors due to their resistance to antimicrobial therapies and ability to evade the immune system. Their resilience is driven by multifaceted mechanisms, including matrix-mediated drug sequestration, metabolic dormancy, and quorum sensing (QS)-regulated virulence, which collectively sustain persistent infections and contribute to the amplification of antimicrobial resistance (AMR). This review critically examines the potential of plant-derived essential oils (EOs) as innovative agents for biofilm control. EOs exhibit broad-spectrum antibiofilm activity through multi-target mechanisms, including disrupting initial microbial adhesion, degrading extracellular polymeric substances (EPSs), suppressing QS pathways, and compromising membrane integrity. Their ability to act synergistically with conventional antimicrobials at sub-inhibitory concentrations enhances therapeutic efficacy while reducing the selection pressure for resistance. Despite their potential, EO applications face technical challenges, such as compositional variability due to botanical sources, formulation stability issues, and difficulties in standardization for large-scale production. Clinical translation is further complicated by biofilm stage- and strain-dependent efficacy, insufficient in vivo validation of therapeutic outcomes, and potential cytotoxicity at higher doses. These limitations underscore the need for optimized delivery systems, such as nanoencapsulation, to enhance bioavailability and mitigate adverse effects. Future strategies should include combinatorial approaches with antibiotics or EPS-degrading enzymes, advanced formulation technologies, and standardized protocols to bridge laboratory findings to clinical practice. By addressing these challenges, EOs hold transformative potential to mitigate biofilm-associated AMR, offering sustainable, multi-target alternatives for infection management and biofilm prevention in diverse contexts. Full article

Mechanoluminescence (ML) involves light emission induced by mechanical stress, categorized into triboluminescence (TL), piezoluminescence (PL), sonoluminescence (SL), and triboelectrification-induced electroluminescence (TIEL). The most common is TL, in which crystal fracture generates opposing charges that excite surrounding molecules. In PL, applied pressure induces light emission via charge recombination. SL occurs in gas-saturated liquids under sudden pressure changes. TIEL has gained increasing attention as it operates without the need for asymmetric crystal structures or strain fields. However, conventional ML faces practical limitations due to its dependence on complex structures or strain fields. In contrast, contact-electro-luminescence (CEL) has emerged as a promising alternative, enabling luminol luminescence via charge transfer and reactive oxygen species generation through contact electrification (CE) between inert dielectrics and water. CEL provides a simpler and more versatile approach than traditional ML techniques, underscoring the pivotal role of charge-transfer processes. This perspective highlights the potential of CEL in expanding ML applications across sensing, energy conversion, and environmental monitoring. Full article

Addressing the critical technological needs for the real-time monitoring of stress distribution in mining areas, a new method for inverting goaf pressure using distributed optical fiber monitoring data is proposed. By coupling the key stratum fracture mechanics model with the subsidence trajectory function model, a theoretical model is established to accurately describe spatial stress evolution during coal mining. The model quantifies the relationship between goaf pressure changes and key stratum failures through a two-stage analysis of the subsidence process, based on distinct mechanical properties before and after key stratum fracture. Physical model experiments (3 m × 0.2 m × 1.1 m) using Brillouin Optical Time Domain Analysis (BOTDA) technology validated the proposed method, with comprehensive monitoring of key stratum deformations. By coupling the fracture mechanics model of the critical layer and the settlement trajectory function model, the dynamic transformation of the pre-fracture and post-fracture stages is realized, and the stress evolution can be monitored and predicted in real time. The results demonstrate spatial consistency between key stratum fracture locations and goaf peak stress positions. High-precision optical fiber sensing detected an ultimate strain threshold of 4000 με for key stratum failure, with pre-fracture strain measurements consistently below this threshold. The developed stress inversion formula successfully predicted pressure distribution patterns within the goaf, achieving real-time monitoring capabilities. Compared with the BPPS measurements, the deviation in the inverted data is less than 8.88%, the root mean square error (RMSE) is 0.98–1.20 in different propulsion stages, and the coefficient of determination (R²) is between 0.72 and 0.85. These findings provide a crucial theory for predicting peak stress evolution in mining areas, with implications for improving safety monitoring systems and optimizing mining operations. Full article

Staphylococcus aureus is a formidable pathogen notorious for its antibiotic resistance and diverse virulence mechanisms, including toxin production, biofilm formation, and immune evasion. This article explores innovative anti-virulence strategies to disarm S. aureus by targeting critical virulence factors without exerting bactericidal pressure. Key approaches include inhibiting adhesion and biofilm formation, neutralizing toxins, disrupting quorum sensing (e.g., Agr system inhibitors), and blocking iron acquisition pathways. Additionally, interventions targeting two-component regulatory systems are highlighted. While promising, challenges such as strain variability, biofilm resilience, pharmacokinetic limitations, and resistance evolution underscore the need for combination therapies and advanced formulations. Integrating anti-virulence strategies with traditional antibiotics and host-directed therapies offers a sustainable solution to combat multidrug-resistant S. aureus, particularly methicillin-resistant strains (MRSA), and mitigate the global public health crisis. Full article

This paper comprehensively reviews the latest advances in hydrogel-based continuum soft robots. Hydrogels exhibit exceptional flexibility and adaptability compared to traditional robots reliant on rigid structures, making them ideal as biomimetic robotic skins and platforms for constructing highly accurate, real-time responsive sensory interfaces. The article systematically summarizes recent research developments across several key dimensions, including application domains, fabrication methods, actuator technologies, and sensing mechanisms. From an application perspective, developments span healthcare, manufacturing, and agriculture. Regarding fabrication techniques, the paper extensively explores crosslinking methods, additive manufacturing, microfluidics, and other related processes. Additionally, the article categorizes and thoroughly discusses various hydrogel-based actuators responsive to solute/solvent variations, pH, chemical reactions, temperature, light, magnetic fields, electric fields, hydraulic/electro-osmotic stimuli, and humidity. It also details the strategies for designing and implementing diverse sensors, including strain, pressure, humidity, conductive, magnetic, thermal, gas, optical, and multimodal sensors. Finally, the paper offers an in-depth discussion of the prospective applications of hydrogel-based continuum soft robots, particularly emphasizing their potential in medical and industrial fields. Concluding remarks include a forward-looking outlook highlighting future challenges and promising research directions. Full article

The rapid development of flexible sensor technology has made flexible sensor arrays a key research area in various applications due to their exceptional flexibility, wearability, and large-area-sensing capabilities. These arrays can precisely monitor physical parameters like pressure and strain in complex environments, making them highly beneficial for sectors such as smart wearables, robotic tactile sensing, health monitoring, and flexible electronics. This paper reviews the fabrication processes, operational principles, and common materials used in flexible sensors, explores the application of different materials, and outlines two conventional preparation methods. It also presents real-world examples of large-area pressure and strain sensor arrays. Fabrication techniques include 3D printing, screen printing, laser etching, magnetron sputtering, and molding, each influencing sensor performance in different ways. Flexible sensors typically operate based on resistive and capacitive mechanisms, with their structural designs (e.g., sandwich and fork-finger) affecting integration, recovery, and processing complexity. The careful selection of materials—especially substrates, electrodes, and sensing materials—is crucial for sensor efficacy. Despite significant progress in design and application, challenges remain, particularly in mass production, wireless integration, real-time data processing, and long-term stability. To improve mass production feasibility, optimizing fabrication processes, reducing material costs, and incorporating automated production lines are essential for scalability and defect reduction. For wireless integration, enhancing energy efficiency through low-power communication protocols and addressing signal interference and stability are critical for seamless operation. Real-time data processing requires innovative solutions such as edge computing and machine learning algorithms, ensuring low-latency, high-accuracy data interpretation while preserving the flexibility of sensor arrays. Finally, ensuring long-term stability and environmental adaptability demands new materials and protective coatings to withstand harsh conditions. Ongoing research and development are crucial to overcoming these challenges, ensuring that flexible sensor arrays meet the needs of diverse applications while remaining cost-effective and reliable. Full article

Soft robots, constructed from deformable materials, offer significant advantages over rigid robots by mimicking biological tissues and providing enhanced adaptability, safety, and functionality across various applications. Central to these robots are electroactive polymer (EAP) actuators, which allow large deformations in response to external stimuli. This review examines various EAP actuators, including dielectric elastomers, liquid crystal elastomers (LCEs), and ionic polymers, focusing on their potential as artificial muscles. EAPs, particularly ionic and electronic varieties, are noted for their high actuation strain, flexibility, lightweight nature, and energy efficiency, making them ideal for applications in mechatronics, robotics, and biomedical engineering. This review also highlights piezoelectric polymers like polyvinylidene fluoride (PVDF), known for their flexibility, biocompatibility, and ease of fabrication, contributing to tactile and pressure sensing in robotic systems. Additionally, conducting polymers, with their fast actuation speeds and high strain capabilities, are explored, alongside magnetic polymer composites (MPCs) with applications in biomedicine and electronics. The integration of machine learning (ML) and the Internet of Things (IoT) is transforming soft robotics, enhancing actuation, control, and design. Finally, the paper discusses future directions in soft robotics, focusing on self-healing composites, bio-inspired designs, sustainability, and the continued integration of IoT and ML for intelligent, adaptive, and responsive robotic systems. Full article

This study established a real-time measurement system to monitor the melt quality in an injection molding process using a pressure sensor installed on the nozzle and a strain gauge installed on the tie bar. Based on the sensing curves from these two external sensors, the characteristic values of nozzle pressure and clamping force were used to optimize parameters. This study defined product weight as a quality indicator and developed a scientific molding parameter setup process. The optimization sequence of parameters is injection speed, V/P switchover point, packing pressure, packing time, and clamping force. Finally, an adaptive process control system was established based on the online quality characteristic values to maintain product quality consistency. Continuous production experiments were conducted at two sites to verify the system’s effectiveness. The results revealed that the optimized process parameters can ensure product weight stability during long-term production. Furthermore, using the adaptive process control system further enhanced product weight stability at both sites, reducing the standard deviation of product weight to 0.0289 g and 0.0148 g, and the coefficient of variation to 0.065% and 0.035%, respectively. Full article