Supercapacitors have attracted enormous attentions for energy storage in both academic and industrial sectors in the past years. In this study, we report all-solid-state flexible asymmetric supercapacitors (ASCs) without any binder, incorporated with the hydrophilic carbon cloth (HCC) with MnO 2 nanocomposite (HCC@MnO 2 ) as the positive electrode, the HCC with polypyrrole (PPy) (HCC@PPy) as the negative electrode, and polyvinyl alcohol (PVA)-LiCl gel as both gel electrolyte and separator. The HCC@MnO 2 and HCC@PPy electrodes are prepared by direct deposition of either MnO 2 nanoparticles or PPy nano-films on the HCC through a simple, facile and controllable electrochemical deposition method, respectively.The HCC@MnO 2 and HCC@PPy electrodes provide rich contact area for gel electrolyte, This article is protected by copyright. All rights reserved. 2facilitating the rapid delivery of electrolyte ions, and also minimize the resistance of ASCs.As a result, all-solid-state flexible binder-free HCC@MnO 2 //HCC@PPy ASCs exhibit a large operating voltage of 1.8 V, high energy density of 28.2 Wh kg -1 at the power density of 420.5 W kg -1 and excellent cycling stability (91.2% capacitance retention after 5000 cycles). Our studies provide a facile, scalable and efficient approach to fabricate all-solid-state ASCs with high electrochemical storage performance for flexible electronics.

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All‐solid‐state flexible asymmetric supercapacitors (ASCs) are developed by utilization of graphene nanoribbon (GNR)/Co0.85Se composites as the positive electrode, GNR/Bi2Se3 composites as the negative electrode, and polymer‐grafted‐graphene oxide membranes as solid‐state electrolytes. Both GNR/Co0.85Se and GNR/Bi2Se3 composite electrodes are developed by a facile one‐step hydrothermal growth method from graphene oxide nanoribbons as the nucleation framework. The GNR/Co0.85Se composite electrode exhibits a specific capacity of 76.4 mAh g−1 at a current density of 1 A g−1 and the GNR/Bi2Se3 composite electrode exhibits a specific capacity of 100.2 mAh g−1 at a current density of 0.5 A g−1. Moreover, the stretchable membrane solid‐state electrolytes exhibit superior ionic conductivity of 108.7 mS cm−1. As a result, the flexible ASCs demonstrate an operating voltage of 1.6 V, an energy density of 30.9 Wh kg−1 at the power density of 559 W kg−1, and excellent cycling stability with 89% capacitance retention after 5000 cycles. All these results demonstrate that this study provides a simple, scalable, and efficient approach to fabricate high performance flexible all‐solid‐state ASCs for energy storage.

Rolling element bearings are critical mechanical parts that are prone to damage, and the detection of their incipient faults plays an important role in ensuring the safe and reliable operation of rotating machinery. The incipient fault characteristics of rolling bearings suffer attenuation from complicated transmission paths and, moreover, are overwhelmed by background noise, hence it is a challenging task to extract them from a complex environment of vibration signals. In contrast to traditional signal processing methods, stochastic resonance (SR) methods can utilize the noise to highlight incipient fault characteristics. However, most overdamped SR methods can hardly suppress multiscale noise, and the monostable, bistable and even tristable SR methods can hardly achieve arbitrary stable-state matching between various mechanical vibration signals and stable-state types. Combined with genetic algorithms (GAs) and the fourth-order Runge-Kutta algorithm to simultaneously obtain the optimal system parameter, damping factor and damping factor of the new SR model, an improved underdamped periodic SR (UPSR) method with arbitrary stable-state matching in underdamped multistable nonlinear systems with a periodic potential for incipient bearing fault diagnosis is proposed. The periodic potential can achieve the matching between various vibration signals and arbitrary stable-state types and, moreover, underdamped SR can suppress the multiscale noise. To improve the performance in bearing fault detection, the signals in the actual engineering environment are preprocessed by prewhitening processing and a Hilbert transform. Therefore, the improved UPSR method is expected to possess a good ability for extracting incipient fault characteristics. Both simulated and experimental comparison with the underdamped bistable SR (UBSR) and fast-Kurtogram methods are adopted to verify the effectiveness of the proposed method. Compared with the above two methods, the proposed method has better fault characteristic frequency extraction performance. The results show that the proposed method could be more suitable and widely used for incipient bearing fault diagnosis in background noise.

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