High-performance flexible strain sensors are playing an increasingly important role in wearable electronics, such as human motion detection and health monitoring, with broad application prospects. This study developed a flexible resistance strain sensor with a porous structure composed of carbon black and multi-walled carbon nanotubes. A simple and low-cost spraying method for the surface of a porous polydimethylsiloxane substrate was used to form a layer of synergized conductive networks built by carbon black and multi-walled carbon nanotubes. By combining the advantages of the synergetic effects of mixed carbon black and carbon nanotubes and their porous polydimethylsiloxane structure, the performance of the sensor was improved. The results show that the sensor has a high sensitivity (GF) (up to 61.82), a wide strain range (0%–130%), a good linearity, and a high stability. Based on the excellent performance of the sensor, the flexible strain designed sensor was installed successfully on different joints of the human body, allowing for the monitoring of human movement and human respiratory changes. These results indicate that the sensor has promising potential for applications in human motion monitoring and physiological activity monitoring.
High-performance flexible pressure sensors have great application prospects in numerous fields, including the robot skin, intelligent prosthetic hands and wearable devices. In the present study, a novel type of flexible piezoresistive sensor is presented. The proposed sensor has remarkable superiorities, including high sensitivity, high repeatability, a simple manufacturing procedure and low initial cost. In this sensor, multi-walled carbon nanotubes were assembled onto a polydimethylsiloxane film with a pyramidal microarray structure through a layer-by-layer self-assembly system. It was found that when the applied external pressure deformed the pyramid microarray structure on the surface of the polydimethylsiloxane film, the resistance of the sensor varied linearly as the pressure changed. Tests that were performed on sensor samples with different self-assembled layers showed that the pressure sensitivity of the sensor could reach −2.65 kPa−1, which ensured the high dynamic response ability and the high stability of the sensor. Moreover, it was proven that the sensor could be applied as a strain sensor under the tensile force to reflect the stretching extent or the bending object. Finally, a flexible pressure sensor was installed on five fingers and the back of the middle finger of a glove. The obtained results from grabbing different weights and different shapes of objects showed that the flexible pressure sensor not only reflected the change in the finger tactility during the grasping process, but also reflected the bending degree of fingers, which had a significant practical prospect.
Alumina nanowires (Al2O3-NWs)/epoxy resin composites have been thoroughly studied due to their excellent insulating and dielectric performance. In particular, understanding the effect of nano-alumina with different morphologies on the dielectric performance of composites is of great significance. In this study, Al2O3-NWs with lengths of approximately 100 nm and diameters of approximately 5 nm were prepared and blended with anepoxy resin to form composites, and the effect of the mass fraction of fillers on the thermal conductivity of the composites was investigated. Specifically, the effect of alumina fillers with ananowire structure on the insulating and dielectric performance and breakdown strength of the epoxy composites were analyzed. The influence principle of the interfacial effect and heat accumulation on the dielectric and insulating properties of the composites were described. The results demonstrated that the thermal conductivity of Al2O3-NWs/epoxy resin composites was higher than that of the bare epoxy resin. The thermal conductivity of Al2O3-NWs/epoxy resin composites increased with increasing mass fraction of fillers. When the mass fraction of fillers was 10%, the thermal conductivity of the composite was 134% higher than that of the epoxy resin matrix. The volume resistivity of the composites first increased and then decreased as the mass fraction of fillers increased, while the dielectric constant of the composites increased with increasing mass fraction of fillers and decreasing frequency. The dielectric loss of the composites decreased and then increased as the mass fraction of fillers increased, and it increased with increasing frequency. Additionally, the alternating current breakdown strength of the composites first increased and then decreased withincreasingmass fraction of fillers.
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Epoxy–boron nitride composites are promising insulating materials, and it is highly important to understand their insulating performances at different temperatures with different nano-doping amounts. In this study, we investigated the effects of different mass fractions of epoxy–micron hexagonal boron nitride composites on their thermal conductivity, as well as the effects of temperature and mass fraction on their insulating performances. The results demonstrated that the thermal conductivity of epoxy–micron hexagonal boron nitride composites was superior to that of neat epoxy. The thermal conductivity of epoxy–micron hexagonal boron nitride composites increased with the mass fraction of hexagonal boron nitride, and their dielectric constant and dielectric loss increased with temperature. The dielectric constant of epoxy–micron hexagonal boron nitride composites decreased as the mass fraction of hexagonal boron nitride increased, while their dielectric losses decreased and then increased as the mass fraction of hexagonal boron nitride increased. Due to internal heat accumulation, the alternating current breakdown strength of epoxy–micron hexagonal boron nitride composites increased and then decreased as the mass fraction of hexagonal boron nitride increased. Additionally, as the temperature increased, the composites transitioned from the glassy state to the rubbery or viscous state, and the breakdown strength significantly degraded.
Flexible pressure sensors have been widely used in wearable devices, medical and health, smart services and other industries. However, the fabrication of sensor with high sensitivity, large sensing range and good stability is still a vital research topic. Herein, a flexible capacitive pressure sensor based on micro-structured electrode is developed, which uses a micro-structured polydimethylsiloxane (PDMS) film embedded with a layer of multi-walled carbon nanotubes as the micro-structured conductive electrode, and a smooth PDMS film as the dielectric layer. The results indicate that the sensor exhibits a strong linear pressure-capacitance relationship. The sensitivity of the sensor can reach 1.3 kPa−1 in the pressure range of 0–100 Pa by optimizing the size of the electrode microstructure. In addition, the sensor exhibits a good repeatability even after 4000 repeated pressing. In addition, we demonstrate that the pressure sensor can be applied to monitor arterial pulse waves and breathing. The sensor is assembled in the form of arrays, which can effectively detect the shape of the measured object, proving that the sensor can be applied in complicated scenarios such as service robot and wearable equipment.
Fuzzy graph theory is a useful and well-known tool to model and solve many real-life optimization problems. Since real-life problems are often uncertain due to inconsistent and indeterminate information, it is very hard for an expert to model those problems using a fuzzy graph. A neutrosophic graph can deal with the uncertainty associated with the inconsistent and indeterminate information of any real-world problem, where fuzzy graphs may fail to reveal satisfactory results. The concepts of the regularity and degree of a node play a significant role in both the theory and application of graph theory in the neutrosophic environment. In this work, we describe the utility of the regular neutrosophic graph and bipartite neutrosophic graph to model an assignment problem, a road transport network, and a social network. For this purpose, we introduce the definitions of the regular neutrosophic graph, star neutrosophic graph, regular complete neutrosophic graph, complete bipartite neutrosophic graph, and regular strong neutrosophic graph. We define the d m - and t d m -degrees of a node in a regular neutrosophic graph. Depending on the degree of the node, this paper classifies the regularity of a neutrosophic graph into three types, namely d m -regular, t d m -regular, and m-highly irregular neutrosophic graphs. We present some theorems and properties of those regular neutrosophic graphs. The concept of an m-highly irregular neutrosophic graph on cycle and path graphs is also investigated in this paper. The definition of busy and free nodes in a regular neutrosophic graph is presented here. We introduce the idea of the μ -complement and h-morphism of a regular neutrosophic graph. Some properties of complement and isomorphic regular neutrosophic graphs are presented here.
A reasonable design of flexible pressure sensors is one of the necessary conditions for improving the sensing performance and meeting the demands of various application fields, including intelligent robot, human-machine interface and health monitoring. Herein, the template method is adopted to replicate the unique natural surface microstructure of ginkgo leaf based on the concept of bionics, and a microstructured copper/polydimethylsiloxane electrode is fabricated by the magnetron sputtering method. In addition, a porous carbon black/thermoplastic polyurethane film is used as the intermediate layer to reduce the hysteresis of the sensor. The capacitive pressure sensor exhibits a high sensitivity (1.194 kPa −1 , <1 kPa), wide pressure detection range (0-300 kPa), fast response time (80 ms), low hysteresis (maximum to 6.58%), ultra-low detection limit (6.53 Pa), and high stability. Further, we demonstrate the practical applications of the sensor in human joint motion and pulse signal detection, walking state detection, and providing tactile feedback during grasping with hand prosthesis. The experimental results indicate that the proposed capacitive pressure sensor can be potentially applied in the fields of electronic skin, wearable devices, and smart prostheses.
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