Search Results (4,362)

This study presents a wide-linear-range flexible pressure sensor based on a gradient non-uniform porous structure. Through co-optimization of material composition and structural parameters, the sensor integrates high sensitivity, a broad linear response range, and excellent stability. The sensing layer is fabricated using a PVC/CNT composite slurry, with interdigital silver electrodes screen-printed on a PET substrate. A porous architecture is constructed via solution blending and a template method. Innovatively, orthogonal experiments were employed to optimize the conductive filler concentration and porosity. A mixed sugar template comprising particles of 50–75 μm and 125–150 μm was introduced to form a gradient non-uniform porous structure, effectively expanding the linear response range. Experimental results demonstrate that the sensor exhibits outstanding linearity (R² > 0.99) and high sensitivity (5.57 kPa⁻¹) over a broad pressure range of 0–120 kPa. It also shows a dynamic response speed of 50 ms, cyclic stability exceeding 500 cycles, and signal fluctuation of less than 5%. Scanning electron microscopy (SEM) analysis reveals the synergistic mechanism of the non-uniform pores, confirming the effectiveness of this design in reconciling the trade-off between sensitivity and linear range. This study offers new insights into the performance optimization of flexible pressure sensors and demonstrates significant potential for applications in health monitoring and electronic skin (E-skin). Full article

Poly(vinylidene fluoride) (PVDF) nanofibers have emerged as promising materials for flexible piezoelectric sensors, yet their performance is fundamentally constrained by the limited formation and alignment of the electroactive β-phase. In this study, we report a phase-engineering strategy that integrates ionic functionalization, inorganic nanofiller incorporation, and post-fabrication corona poling to achieve enhanced crystalline ordering and electromechanical coupling in electrospun PVDF nanofibers. Tetrabutylammonium perchlorate increases solution conductivity, enabling uniform, bead-free fiber formation, while barium titanate nanoparticles act as nucleation centers that promote β-phase crystallization at the expense of the non-polar α-phase. Subsequent corona poling further aligns molecular dipoles and strengthens remnant polarization within both the PVDF matrix and embedded nanoparticles. Structural analyses confirm the synergistic evolution of crystalline phases, and piezoelectric measurements demonstrate a substantial increase in peak-to-peak output voltage under dynamic loading conditions. This combined phase-engineering approach provides a simple and scalable route to high-performance PVDF-based piezoelectric sensors and highlights the importance of coupling crystallization control with dipole alignment in designing next-generation wearable electromechanical materials. Full article

There is a significant demand for flexibility in steam turbines, including rapid cold starts and load changes, as well as operation at low partial loads. Both industrial plants and systems for electricity and heat generation are impacted. These new operating modes result in complex, asymmetric temperature fields and additional thermally induced stresses. These lead to casing deformations, which affect blade tip gap and casing flange sealing integrity. The exact progression of heat flux and heat transfer coefficients within the cavities of steam turbines remains unclear. The current methods used in the calculation departments rely on simplified, averaged estimates, despite the presence of complex flow phenomena. These include swirling inflows, temperature gradients, impinging jets, unsteady turbulence, and vortex formation. This paper presents a novel sensor and its thermal measurements taken on a full-scale steam turbine test rig. Numerical calculations were performed concurrently. The results were validated by measurements. Additionally, the distribution of the heat transfer coefficient along the cavity was analysed. The rule of L’Hôpital was applied at specific locations. A method for handling axial variation in the heat transfer coefficient is also proposed. Measurements were taken under real-life conditions with a full-scale test rig at MAN Energy Solutions SE, Oberhausen, with steam parameters of 400 °C and 30 bar. The results at various operating points are presented. Full article

Due to the high mobility, flexibility, and low cost, unmanned aerial vehicles (UAVs) can provide an efficient way for provisioning data communication and computing offloading services for massive Internet of Things (IoT) devices, especially in remote areas with limited infrastructure. However, current transmission schemes for unmanned aerial vehicle-assisted Internet of Things (UAV-IoT) predominantly employ polling scheduling, thus not fully exploiting the potential multiuser diversity gains offered by a vast number of IoT nodes. Furthermore, conventional opportunistic scheduling (OS) or opportunistic beamforming techniques are predominantly designed for downlink transmission scenarios. When applied directly to uplink IoT data transmission, these methods can incur excessive uplink training overhead. To address these issues, this paper first proposes a low-overhead multi-UAV uplink OS framework based on channel reciprocity. To avoid explicit massive uplink channel estimation, two scheduling criteria are designed: minimum downlink interference (MDI) and the maximum downlink signal-to-interference-plus-noise ratio (MD-SINR). Second, for a dual-UAV deployment scenario over Rayleigh block fading channels, we derive closed-form expressions for both the average sum rate and the asymptotic sum rate based on the MDI criterion. A degrees-of-freedom (DoF) analysis demonstrates that when the number of sensors, K, scales as ${\rho }^{\alpha }$, the system can achieve a total of $2\alpha$ DoF, where $\alpha \in \left[0,1\right]$ is the user-scaling factor and $\rho$ is the transmitted signal-to-noise ratio (SNR). Third, for a three-UAV deployment scenario, the Gamma distribution is employed to approximate the uplink interference, thereby yielding a tractable expression for the average sum rate. Simulations confirm the accuracy of the performance analysis for both dual- and three-UAV deployments. The normalized error between theoretical and simulation results falls below 1% for K > 30. Furthermore, the impact of fading severity on the system’s sum rate and DoF performance is systematically evaluated via simulations under Nakagami-m fading channels. The results indicate that more severe fading (a smaller m) yields greater multiuser diversity gain. Both the theoretical and simulation results consistently show that within the medium-to-high SNR regime, the dual-UAV deployment outperforms both the single-UAV and three-UAV schemes in both Rayleigh and Nakagami-m channels. This study provides a theoretical foundation for the adaptive deployment and scheduling design of UAV-assisted IoT uplink systems under various fading environments. Full article

Electromagnetic pumps are developed for industrial, medical and scientific applications, moving electrically conductive liquids and molten solder in electronics manufacturing using electromagnetism instead of mechanical parts. This study presents a comprehensive thermal analysis of an electromagnetic diaphragm pump, focusing on the influence of operating current, permanent magnet switching speed, and cooling conditions on pumping performance. The pump utilizes a flexible diaphragm embedded with a permanent neodymium magnet, which interacts with time-varying magnetic fields generated by electromagnets to drive fluid motion. Temperature monitoring is conducted using a waterproof DS18B20 sensor and an uncooled FLIR A325sc infrared camera, allowing accurate mapping of thermal distribution across the pump surface. Experimental results demonstrate that higher current and increased magnet switching speed lead to faster temperature rise, impacting the volume of fluid pumped. Incorporation of an automatic cooling fan effectively reduces coil temperature and stabilizes pump performance. Polynomial regression models describe the relationship between temperature, pumped liquid volume, and magnet switching speed, providing information to optimize pump operation and cooling strategies. The novel relationship between temperature and the volume of the pumped liquid is considered as a fourth-degree polynomial. In particular the model describes a quantitative evaluation of the effect of heating on pumping efficiency. An initial increase in temperature correlates with a higher pumped volume, but excessive heating leads to efficiency saturation or even decline. Indeed, mathematical dependencies are crucial in mechanical pump engineering for analyzing physical phenomena; this is achieved by using a mathematical equation to define how different physical variables are related to each other, enabling engineers to calculate performance and optimize the pump design. Full article

Receiver-initiated MAC protocols, such as the IEEE 802.15.4e RIT scheme, are promising for energy-efficient communication in multi-hop wireless sensor networks. However, their practical use requires a better understanding of how multiple contention-avoidance mechanisms interact under realistic network conditions. This study develops an ns-3 implementation of an RIT-compliant receiver-initiated MAC protocol together with a flexible evaluation framework that enables selective activation of representative enhancement strategies, including carrier-sensing options for data and beacon transmissions and randomization of beacon intervals. Four realistic network scenarios were designed to simulate practical deployment settings. Simulation results revealed that the effectiveness of these enhancement strategies varied significantly depending on network load and topology. In particular, beacon interval randomization, although often assumed to improve robustness, was found to degrade performance under low-load conditions, indicating that even widely adopted mechanisms may behave differently depending on operational environments. Conversely, CSMA-based approaches provided consistent improvements in transmission reliability. These observations highlight the importance of considering environmental factors and parameter configurations when enabling enhancement mechanisms. Overall, the proposed platform provides a reproducible and unified environment for fair comparison of receiver-initiated MAC protocols and their optional mechanisms, offering practical insights for selecting appropriate configurations in real sensor network deployments. Full article

A scalable and facile fabrication strategy is presented for developing a flexible, nanostructured, non-enzymatic electrochemical sensor for lactate detection based on copper-modified laser-induced graphene (CuNPs/LIG). A one-step electrodeposition process was employed to uniformly decorate the porous LIG framework with copper nanostructures, offering a cost-effective and reproducible approach for constructing enzyme-free sensing platforms. Scanning electron microscopy and energy-dispersive X-ray spectroscopy confirmed dense Cu nanostructure loading and efficient interfacial integration across the conductive LIG surface. The resulting CuNPs/LIG electrode exhibited excellent electrocatalytic performance, achieving a sensitivity of 8.56 μA µM⁻¹ cm⁻² with a low detection limit of 42.65 μM and a linear response toward lactate concentrations ranging from 100 to 1100 μM in artificial saliva under physiological conditions. The sensor maintained high selectivity in the presence of physiologically relevant interferents. Practical applicability was demonstrated through recovery studies, where recovery rates exceeding 104% showcase the sensor’s analytical reliability in complex biological matrices. Overall, this work establishes a robust, sensitive, and cost-efficient Cu-nanostructured LIG sensing platform, offering strong potential for non-invasive lactate monitoring in real-world biomedical and wearable applications. Full article

Intelligent driving cabins operated by artificial intelligence technology are evolving into the third living space. They aim to integrate perception, analysis, decision making, and intervention. By using multimodal biosignal acquisition technologies (flexible sensors and non-contact sensing), it is possible to monitor the physiological indicators of heart rate and blood pressure in real time. Leveraging the benefits of domain controllers in the vehicle and edge computing helps the AI platform reduce data latency and enhance real-time processing capabilities, as well as integrate the cabin’s internal and external data through machine learning. Its aim is to build tailored health baselines and high-precision risk prediction models (e.g., CNN, LSTM). This system can initiate multi-level interventions such as adjustments to the environment, health recommendations, and ADAS-assisted emergency parking with telemedicine help. Current issues consist of sensor precision, AI model interpretation, security of data privacy, and whom to attribute legal liability to. Future development will mainly focus on cognitive digital twin construction, L4/L5 autonomous driving integration, new biomedical sensor applications, and smart city medical ecosystems. Full article

Self-powered sensors, leveraging their integrated energy harvesting–signal sensing capability, effectively overcome the bottlenecks of traditional sensors, including reliance on external power resources, high maintenance costs, and challenges in large-scale distributed deployment. As a result, they have become a major research focus in fields such as flexible electronics, smart healthcare, and human–machine interaction. This paper reviews the core technical paths of six major types of self-powered sensors developed in recent years, with particular emphasis on the working principles and innovative material applications associated with frictional charge transfer and electrostatic induction, pyroelectric polarization dynamics, hydrovoltaic interfacial streaming potentials, piezoelectric constitutive behavior, battery integration mechanism, and photovoltaic effect. By comparing representative achievements in fields closely related to self-powered sensors, it summarizes breakthroughs in key performance indicators such as sensitivity, detection range, response speed, cyclic stability, self-powering methods, and energy conversion efficiency. The applications discussed herein mainly cover several critical domains, including wearable medical and health monitoring systems, intelligent robotics and human–machine interaction, biomedical and implantable devices, as well as safety and ecological supervision. Finally, the current challenges facing self-powered sensors are outlined and future development directions are proposed, providing a reference for the technological iteration and industrial application of self-powered sensors. Full article

Air pollution is monitored worldwide through networks of sensors. They provide information on local air pollution, which also provides a basis for a multitude of research. To reduce health hazards caused by air pollution, the concentrations of pollutants as measured by sensors need to be apportioned to particular sources. Although several methods to achieve this have been developed, only a few works on the contributions of pollution sources to health hazards are available in the literature. In this work, a simple scheme is proposed to compare health hazards from each of the main sources of air pollution in a given country, region, or area. The comparison involves the main air pollutants of PM_2.5, NO₂, and O₃ for chronic exposures and PM_2.5, NO₂, O₃, and SO₂ for acute exposures. The actual health hazard from each substance is determined from concentrations measured by sensors and the concentration–response functions found in the literature. The apportionment of substances to sources is based on emission inventories, thus avoiding costly methods of source apportionment. This method has been applied to the entire country, i.e., Poland, yielding the average proportion of health hazards from particular sources. The example demonstrates the flexibility and ease of application of the scheme. Uncertainties in the results were subjected to discussion. The key advantage of the scheme lies in its ability to provide an indication of the most harmful sources of pollution, thus highlighting efficient interventions. Full article

Characterized by their atomic thickness and exceptional mechanical properties, two-dimensional (2D) materials offer a compelling platform for developing flexible optoelectronic devices that maintain performance stability under mechanical deformation such as bending and stretching. This review systematically summarizes and critically discusses the recent advancements in applying three prominent 2D material categories—graphene, transition metal dichalcogenides (TMDs, e.g., MoS₂ and WS₂), and MXenes—in flexible optoelectronics. We focus on their specific applications in flexible photodetectors, light-emitting devices, optical modulators, solar cells, and gas sensors. A particular emphasis is placed on analyzing the unique physicochemical properties of these materials and elucidating the underlying mechanisms that enable bandgap stability and efficient optoelectronic conversion under mechanical strain. The potential of these devices demonstrated here underscores their broad application prospects in wearable systems and self-powered electronic platforms. Finally, we conclude by discussing the challenges and future prospects in the field of flexible optoelectronic devices based on two-dimensional materials. Full article

An alternative conductive ink based on carbon nanotubes (CNTs) was developed using a platinum-catalyzed silicone elastomer and isopropyl alcohol (IPA). The inclusion of IPA in the conductive CNT ink facilitated the optimization of its mechanical strength, electrical conductivity, and viscosity. Compared to conventional silicone rubber-based conductive polymers that often solidify in a few hours at room temperature or with heating, this liquid composite of CNT particles and IPA exhibited a prolonged duration of up to several months in a hermetic environment, maintaining chemical stability even with the elastomer and its curing agent. The gradual evaporation of IPA initiates a well-known cross-linking process, leading to stretchability and electrical conductivity derived from the silicone elastomer and CNT particles, respectively. The relationship between the mechanical strength and electrical conductivity of the hardened conductive CNT ink was studied, which helped determine the optimized concentration of CNT particles in the conductive CNT ink. Subsequently, a piezoresistive sensor was designed, fabricated, and evaluated. The conductive CNT ink-based piezoresistive sensor showed high sensitivity and good repeatability with respect to a wide range of external forces. The effect of the concentration of CNT particles on the viscosity of the conductive CNT ink was also investigated, providing a better understanding of the entanglement of CNT particles within the silicone elastomer. A coating test using the conductive CNT ink with a paper cutting machine demonstrated its potential for adaptation to various printing techniques, including screen printing. The proposed conductive CNT ink, characterized by a simple chemical composition, facile fabrication process, use of non-toxic elements, high electrical conductivity, and stretchability, combined with an extended duration, has the potential to be applied for multiple purposes, such as various types of flexible and wearable electronics. Full article

The growing demand for advanced health-monitoring technologies has intensified the need for early diagnosis of incurable diseases and timely detection of life-threatening conditions. Among various detection modalities, electrochemical sensing has emerged as a particularly promising approach due to its simplicity, cost-effectiveness, high sensitivity, rapid response, ease of miniaturization, and compatibility with portable, wearable, and implantable platforms. The performance of electrochemical sensors is strongly governed by the morphology and physicochemical properties of electrode materials. In this context, MXenes, 2D transition-metal carbides, nitrides, and carbonitrides have attracted increasing attention for sensing applications owing to their high electrical conductivity, large surface area, hydrophilicity, and rich surface chemistry. However, their practical implementation is hindered by oxidation and environmental instability, while surface modification strategies, although improving stability, may compromise intrinsic electrochemical activity and biocompatibility. Notably, MXene-based hybrids consistently demonstrate enhanced sensing performance, underscoring their potential for flexible and wearable electrochemical devices. Despite rapid progress in this field, a comprehensive review addressing the significance of MXene hybrids, their structure–property–performance relationships, and their role in electrochemical detection remains limited. Therefore, this review summarizes recent advances in MXene-based hybrid materials for electrochemical sensing and biosensing of biologically relevant analytes, with an emphasis on design strategies, functional enhancements, and their prospects for next-generation health-monitoring technologies. Full article

A compliant parallel multi-directional piezoelectric vibration energy harvester (C-MVEH) is proposed based on a 3-RRR compliant parallel mechanism. The energy harvester structure consists of three identical L-shaped beams, whose bending deformation can be equivalent to the rotations of the three joints. In order to achieve greater bending deformation for composite beams, motion flexibility optimization of the mechanism theory is applied to structure the synthesis of the C-MVEH. Meanwhile, to reduce the natural frequencies corresponding to the working modes, the length of the elastic beam is optimized with the maximum natural frequency among the first three modes. In order to verify the excellent performance of the C-MVEH, an electromechanical model, finite element simulations, and experimental studies are carried out. Analysis of the studies reveals that the C-MVEH has three resonance peaks of output voltage within a bandwidth of 7–13 Hz and can output a total voltage of at least 20 V under a small excitation of 0.2 g. The energy harvester can achieve multiple peak output voltages under small excitations in different directions and a wide frequency range. With its outstanding stability, the proposed C-MVEH demonstrates considerable application value in the supplying of power to microenergy electronic devices, such as smart sensors and microactuators. Full article

With the advancement of Internet of Things (IoT) technology, flexible sensors with dual optoelectronic sensing modes have emerged as a research hotspot for next-generation smart devices, further driving the urgent demand for environmentally friendly functional materials. Here, we innovatively integrated wastepaper recycling technology with a polyethyleneimine (PEI)-assisted pulping strategy to develop a novel cellulose-based sustainable photo-triboelectric hybrid nanogenerator (PT-HNG). Based on the working mechanism of a freestanding triboelectric nanogenerator (TENG), the PT-HNG can directly convert pressure stimuli into electrical energy and triboelectrification-induced electroluminescence (TIEL) signals. It achieves luminescence brightness of 0.06 mW cm⁻² (3.84 cd m⁻²) and simultaneously delivers excellent electrical output performance (172.4 V, 6.36 μA, 43.7 nC) under sliding motion. More importantly, compatible with existing industrial papermaking processes, the PT-HNG is scalable for large-scale production. By combining PT-HNG with deep learning algorithms, a handwritten e-book system based on trajectory recognition was constructed, with a recognition accuracy of up to 95.5%. In addition, real-time intelligent control of PowerPoint presentations via PT-HNG was demonstrated. This study provides a new pathway for converting wastepaper into intelligent products and presents a novel idea for the interdisciplinary integration of the circular economy and advanced electronic technology. Full article