Printed electronics on elastomer substrates have found wide applications in wearable devices and soft robotics. For everyday usage, additional requirements exist for the robustness of the printed ...flexible electrodes, such as the ability to resist scratching and damage. Therefore, highly robust electrodes with self‐healing, and good mechanical strength and stretchability are highly required and challenging. In this paper, a cross‐linking polyurea using polydimethylsiloxane as the soft segment and dynamic urea bonds is prepared and serves as a self‐healing elastomer substrate for coating and printing of silver nanowires (AgNWs). Due to the dynamic exchangeable urea bond at 60 °C, the elastomer exhibits dynamic exchange of the cross‐linking network while retaining the macroscopic shape. As a result, the AgNWs are partially embedded in the surface of the elastomer substrate when coated or printed at 60 °C, forming strong interfacial adhesion. As a result, the obtained stretchable electrode exhibits high mechanical strength and stretchability, the ability to resist scratching and sonication, and self‐healing. This strategy can be applied to a variety of different conducting electrode materials including AgNWs, silver particles, and liquid metal, which provides a new way to prepare robust and self‐healing printed electronics.
A concept involving preparing stretchable, robust, and self‐healing electrodes via a direct surface printing on a polyurea elastomer is developed in this work. Taking advantage of the dynamic polyurea's kinetic chain movement at an elevated temperature, variable conductive nano‐fillers can be self‐embedded into the elastomer's surface without shape changing, exhibiting high significance in designing both robust and self‐healing electrodes.
•We propose the novel MCL framework that allows unbiased risk estimation from samples with arbitrary number of complementary labels and arbitrary losses and models (linear and deep models), which ...shows the practicality of the proposed framework.•We further propose the MCUL framework to utilize the easily accessible unlabeled samples and validate the benefits of the incorporation of unlabeled samples experimentally. The rigorous convergence analysis on the statistical error bounds also shows the reliability of proposed frameworks.•The previous complementary-label learning framework and ordinary classification problems are proven to be special cases of the MCUL framework, which shows the comprehensiveness of the MCUL framework as a weakly-supervised leaning framework.•We further integrate the class-prior information into the risk estimator and experimentally show its efficiency.•We propose a adaptive risk correction scheme for alleviating over-fitting and show its consistency under mild assumptions. The experimental results show its validity on improving classification accuracy.
A weakly-supervised learning framework named as complementary-label learning has been proposed recently, where each sample is equipped with a single complementary label that denotes one of the classes the sample does not belong to. However, the existing complementary-label learning methods cannot learn from the easily accessible unlabeled samples and samples with multiple complementary labels, which are more informative. In this paper, to remove these limitations, we propose the novel multi-complementary and unlabeled learning framework that allows unbiased estimation of classification risk from samples with any number of complementary labels and unlabeled samples, for arbitrary loss functions and models. We first give an unbiased estimator of the classification risk from samples with multiple complementary labels, and then further improve the estimator by incorporating unlabeled samples into the risk formulation. The estimation error bounds show that the proposed methods are in the optimal parametric convergence rate. We also propose a risk correction scheme for alleviating over-fitting caused by negative empirical risk. Finally, the experiments on both linear and deep models show the effectiveness of our proposed methods.
Ionic liquids (ILs) are regarded as ideal components in the next generation of strain sensors because their ultralow modulus can commendably circumvent or manage the mechanical mismatch in ...traditional strain sensors. In addition to strain sensors, stretchable conductors with a strain-insensitive conductance are also indispensable in artificial systems for connecting and transporting electrons, similar to the function of blood vessels in the human body. In this work, two types of ILs-based conductive fibers were fabricated by developing hollow fibers with specific microscale channels, which were then filled with ILs. Typically, the ILs-based fiber with straight microchannels exhibited a high strain sensitivity and simultaneously rapid responses to strain, pressure, and temperature. The other ILs-based fiber with helical microchannels exhibited a good strain-isolate conductance under strain. Due to the high transparency of ILs along with the sealing process, the as-prepared ILs-based fibers are both highly transparent and waterproof. More importantly, owing to the low modulus of ILs and the core–shell structure, both conductive fiber prototypes demonstrated a high durability (>10 000 times) and a long-term stability (>4 months). Ultimately, the ILs-based fibrous sensors were successfully woven into gloves, flaunting the ability to detect human breathing patterns, sign language, hand gestures, and arm motions. The ILs-based strain-insensitive fibers were successfully applied in stretchable wires as well.
•Superhydrophobic and self-cleaning properties on insulators are achieved via coating.•Icing time is delayed, and ice adhesion is weakened after the coating.•Fast dissipation of surface charge is ...realized by introducing shallow traps.•Wet flashover voltage is increased by inhibiting electrical distortion.
Composite insulator is an important component of outdoor insulation systems. It works in complex environments and faces a series of problems such as surface contamination, loss of hydrophobicity, and accumulation of surface charges, which may eventually lead to flashover. Aiming to solve these problems in a simple and scalable method, we propose a multifunctional nano-coating based on SiO2/PDMS/EP. By the combination of multiscale structure and low surface energy modification, this coating shows excellent water-repellency performance, a large contact angle greater than 160° and a small rolling angle near 0° are achieved on coated silicone rubber, which enables the surface with excellent self-cleaning performance. Benefiting from the multiscale roughness, the heat transfer is inhibited by the reduced contact area, which further slows down the icing process on coated silicone rubber. The de-icing force on coated silicone rubber is also smaller than that on pristine silicone rubber. This coating also introduces many shallow traps to the surface, which is beneficial to the fast surface charge dissipation in a short time. Besides, the high water-repelling ability can promote the droplet to roll away under the action of electrical field force, which alleviates the electrical distortion caused by the droplets. As a result, the wet flashover voltage of coated silicone rubber is 60% higher than that of pristine silicone rubber. This multifunctional coating is a facile, scalable, and effective approach to improving the comprehensive surface performance of insulators.
This paper evaluates the outage performance of cognitive relay networks with mutual interference between secondary users and primary users under the underlay approach, while adhering to the ...interference constraint on the primary user. A network path selection criterion, suitable for cognitive relay networks, is provided, from which we derive the outage probability expression of cognitive relay networks. It is shown that the outage probability considering the interference to secondary user from primary user is higher than that without considering the interference to secondary user from primary user. In addition, the outage probability is affected by key network parameters. We analyze network path selection method based on outage probability and prove that the interference to secondary user from primary user has a significant effect on the network path selection and can not be ignored in practical wireless communication environments. Simulation investigation is also provided and used to verify the theoretical analysis.
Color has been widely used to encode data in all types of visualizations. Effective color palettes contain discriminable and harmonious colors, which allow information from visualizations to be ...accurately and aesthetically conveyed. However, predefined color palettes not only lack the flexibility of custom color palette generation but also ignore the context in which the visualizations are used. Designing an effective color palette is a time-consuming and challenging process for users, even experts. In this work, we propose the generation of an image-based visualization color palette to exploit the human perception of visually appealing images while considering visualization cognition. By analyzing color palette constraints, including harmony, discrimination, and context, we propose an image-driven color generation method. We design a color clustering method in the saliency-hue plane based on visual importance detection and then select the palette based on the visualization color constraints. In addition, we design two color optimization and assignment strategies for visualizations of different data types. Evaluations through numeric indicators and user experiments demonstrate that the palettes predicted by our method are visually related to the original images and are aesthetically pleasing, supporting diverse visualization contexts and data types in practical applications.
One of the critical issues for the fabrication of desirable sensing materials has focused on the construction of an effective continuous network with a low percolation threshold. Herein, ...graphene-based elastomer composites with a segregated nanostructured graphene network were prepared by a novel and effective ice-templating strategy. The segregated graphene network bestowed on the natural rubber (NR) composites an ultralow electrical percolation threshold (0.4 vol %), 8-fold lower than that of the NR/graphene composites with homogeneous dispersion morphology (3.6 vol %). The resulting composites containing 0.63 vol % graphene exhibited high liquid sensing responsivity (6700), low response time (114 s), and good reproducibility. The unique segregated structure also provides this graphene-based elastomer (containing 0.42 vol % graphene) with exceptionally high stretchability, sensitivity (gauge factor ≈ 139), and good reproducibility (∼400 cycles) of up to 60% strain under cyclic tests. The fascinating performances highlight the potential applications of graphene–elastomer composites with an effective segregated network as multifunctional sensing materials.
A simple and effective approach, i.e. pre-construction method, was developed to fabricate a three-dimensional segregated graphene network (IL-3DGE) in a styrene butadiene rubber (SBR) matrix. Such ...segregated 3D-GE network dramatically enhanced the electrical conductivity, mechanical properties and gas barrier property of SBR composites. With the incorporation of 1.66 vol% IL-3DGE, the electrical conductivity of the composites was significantly enhanced by 10 orders of magnitude, the tensile strength was increased by 516%, and gas permeability was effectively reduced by 75.5%, as compared with those of neat SBR. Specifically, SBR/IL-3DGE with a segregated morphology showed a much low electrical percolation threshold (0.39 vol%), which is approximately 9-fold lower than that of the non-segregated SBR/IL-GE (3.78 vol%). The excellent properties of the composites were attributed to the construction of a 3D segregated conductive structure and strong interfacial interactions. This work provides a new insight into the fabrication of high-performance rubber composites for versatile practical applications.
Abstract Sliding electrical contact involves multiple conductors sliding in contact at different speeds, with current flowing through the contact surfaces. The Lagrangian method is commonly used to ...describe the electromagnetic field in order to overcome the trouble of convective dominance, especially in high‐speed sliding electrical contact problems. However, to maintain correct field continuity, magnetic vector potential and scalar potential taken as variables cannot be continuous simultaneously at the ideal sliding electrical contact interface. This involves a strongly discontinuous condition for variables. Further, commonly used spatial–temporal discretization algorithms are invalid, for example, the classic finite element (CFEM) framework does not allow discontinuous variables, and the backward Euler method in time domain introduces a significant interface error source associated with the velocity of relative motion. To accurately handle strongly discontinuous conditions in numerical calculations, a mixed nodal finite element scheme and a higher‐order accurate temporal discretization scheme are introduced. In this scheme, classical finite element method is performed in each subdomain, and the derivative terms at the boundary are added as new variables. The effectiveness and accuracy of the above methods are verified by comparing them with a standard solution in a two‐dimensional railgun model and analyzing the current density distribution in a three‐dimensional railgun model.
Textile-based electronics (e-textiles) have attracted huge attention in wearable sensors recently. Even though highly sensitive textile-based pressure sensors and highly stretchable textile-based ...strain sensors are widely researched and reported in recent years, it is still full of challenges to develop high stretchable textile-based sensors simultaneously and satisfy strain and pressure sensing, which is necessary for full-range detection of human motions. On the other hand, compared to traditional planar e-textiles, fiber-shaped e-textiles have plenty of advantages due to their fibrous architecture with lightweight, portable, skin compliant, and easily weave properties. In this work, a fiber-shaped textile, knitted with hierarchical polyurethane (PU) fibers, is used to fabricate a multifunctional e-textile by coating of silver nanowires (AgNWs) and styrene–butadiene–styrene. Due to the AgNWs conductive networks, the inherent stretchability of PU fibers, and the hierarchical structure, the as-prepared e-textile exhibits high conductivity, high stretchability, high sensitivity, and multi-detection of strain and pressure. What is more, the fabricated multifunctional e-textiles are also successfully weaved into electronic fabric for 2D force mapping. The simple, scalable strategy endows the multifunctional e-textiles great potentials in full-range detection and health care areas.
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