State Key Laboratory of Mechanical Transmission

Double shell FeOOH/PPy on a diatomite ternary complex was assembled via two-step hydrothermal and in situ polymerization routes. The polymerization process generates chemical bonding and introduces oxygen vacancies and mesopores, enhancing the conductivity and electrochemical properties of the electrodes and ensuring structural stability.

As one of the most critical components in rotating machinery, bearing fault diagnosis has attracted many researchers' attention. The traditional methods for bearing fault diagnosis normally requires three steps, including data pre-processing, feature extraction and pattern classification, which require much expertise and experience. This paper takes advantage of deep learning algorithms and proposes an improved bearing fault diagnosis method based on a convolutional neural network (CNN) and a long-short-term memory (LSTM) recurrent neural network whose input is the raw sampling signal without any pre-processing or traditional feature extraction. The CNN is frequently used in image classification as it could extract features automatically from high-dimensional data, while LSTM is most applied in speech recognition as it considers time coherence. This paper combined one-dimensional CNN and LSTM into one unified structure by using the CNN's output as input to the LSTM to identify the bearing fault types. First, a part of raw bearing signal data is used as the training dataset in the model, and the simulation ends when the number of iterations reaches a specific value. Second, the rest of the signal data was input in the trained model as the testing dataset to verify the effectiveness of the proposed method. The results show that the average accuracy rate in the testing dataset of this proposed method reaches more than 99 %, which outperforms other algorithms for bearing fault diagnosis.

Bimetallic phosphides have been identified as promising alternative electrode materials owing to their admirable conductivity and electrochemical activity.

Core/shell structured NiCo₂O₄@NiMn LDH hybrids were fabricated as efficient electrocatalysts for rechargeable Zn–air batteries.

The superiority of layer-structured Ag-NW/PANI composite films over the plain-structured in electrical conductivity and electromagnetic interference shielding.

Generation of high power laser ultrasound strongly demands the advanced materials with efficient laser energy absorption, fast thermal diffusion, and large thermoelastic expansion capabilities. In this study, candle soot nanoparticles-polydimethylsiloxane (CSNPs-PDMS) composite was investigated as the functional layer for an optoacoustic transducer with high-energy conversion efficiency. The mean diameter of the collected candle soot carbon nanoparticles is about 45 nm, and the light absorption ratio at 532 nm wavelength is up to 96.24%. The prototyped CSNPs-PDMS nano-composite laser ultrasound transducer was characterized and compared with transducers using Cr-PDMS, carbon black (CB)-PDMS, and carbon nano-fiber (CNFs)-PDMS composites, respectively. Energy conversion coefficient and −6 dB frequency bandwidth of the CSNPs-PDMS composite laser ultrasound transducer were measured to be 4.41 × 10−3 and 21 MHz, respectively. The unprecedented laser ultrasound transduction performance using CSNPs-PDMS nano-composites is promising for a broad range of ultrasound therapy applications.

); the rechargeable battery can show superior reversibility, excellent stability, and voltage gaps of ∼0.8 V (∼60% of round-trip efficiency) in >1200 continuous cycles. Furthermore, the flexible quasi-solid-state zinc-air battery with bendable ability holds practical potential in portable and wearable electronic devices.

A novel peapod-like Ni2P/C nanocomposite is designed and synthesized using NiNH4PO4H2O nanorods as templates. With enriched nanoporosity and large active surface areas, the peapod-like composites offer superb dual functionality as both electrocatalysts for the hydrogen evolution reaction (HER) and anodes for lithium ion batteries (LIBs). Electrochemical tests demonstrate that the Ni2P/C nanocomposite exhibits an overpotential as low as 60 mV and a notably low Tafel slope of 54 mV dec.(-1). When used as an anode material for lithium-ion batteries, the resulting peapod-like Ni2P/C nanocomposite delivers high specific capacitances of 632 mA h g(-1) at 0.1 A g(-1) and 439 mA h g(-1) at 3 A g(-1), and also exhibits a superior cycling performance, with nearly 100% capacity retention even after 200 charge-discharge cycles at a charge-discharge rate of 0.1 A g(-1). The work demonstrates that the peapod-like materials reported herein are promising materials for electrochemical energy-related applications such as HER and LIBs.

The quasi-paralleled and interlaced nanosheet arrays of NiMn layered double hydroxides are successfully grown on KCu₇S₄ microwires with quasi-one-dimensional channel by tuning the concentration of the metal ions.

In this paper, an effective improved co-evolution ant colony optimisation (MSICEAO) algorithm is presented to solve complex optimisation problem. In the MSICEAO, the multi-population co-evolution strategy is used to divide initial population into several sub-populations to interchange and share information. The weighted initial pheromone distribution strategy is used to improve the efficiency and adjust the pheromone factor and distance factor. The elitist retention strategy is used to improve the solution quality. The adaptive dynamic update strategy for pheromone evaporation rate is used to balance the convergence speed and solution quality. The aggregation pheromone diffusion mechanism is used to enhance the cooperative effect and highlight the cooperative idea of swarm intelligence. In order to verify the effectiveness of the MSICEAO, the experiments have been carried out on eight TSPs and one actual gate allocation problem. The MSICEAO is compared with five state-of-the-art algorithms of TS, GA, PSO, ACO and PSACO. The experiment results demonstrate that the MSICEAO is significantly better than the compared methods.

Al-Based LDH materials have been considered as promising active electrode materials for pseudocapacitors due to their structural tunability.

The development of solid electrolytes with superior electrical and electrochemical performances for the room-temperature operation of sodium (Na)-based batteries is at the infant stage and still remains a challenge.

A modified mathematical model for simulating gear crack from root with linear growth path in a pinion is developed, in which an improved potential energy method is used to calculate the time-varying meshing stiffnesses of the meshing gear pair while we also take the deformation of gear-body into consideration. The formulas for the meshing stiffness are deduced when the crack grows as the linear growth path in the pinion. A 16DOF dynamic model of a one-stage spur gear system is used to study the response from the system considering time-varying meshing stiffnesses and different levels of crack growing in the pinion. As vibration signals induced by the tooth crack are buried in normal vibration signals which are induced by the normal gear pair in meshing at the early stage of crack growth, the algorithm combined autoregressive modeling method and demodulation method is proposed to process the signals to investigate the response characteristics as the crack grows, and the comparison of the relationship between indicators and the crack levels from different simulation methods are given.

Diatom silica, a 3-dimensional (3D) natural biomaterial generated from single cell algae with unique nano- and micro-morphologies and patterns is shown to have several exceptional structural, mechanical, optical, photonics, transport, and chemical properties optimized through millions of years of evolution.

The in-plane and out-of-plane thermal transport properties of the graphene–MoS₂ bilayer are investigated with several influencing factors being considered.

Successful conversion of diatomites (SiO₂) into silicon diatoms was achieved <italic>via</italic> the magnesiothermic reduction method followed by deposition of MnO₂ nanosheets to fabricate unique 3D silicon-diatom@MnO₂ electrodes and demonstrate their application for high-performance supercapacitors.

Vibration characteristics of a deep groove ball bearing caused by a localized surface defect are greatly affected by defect sizes, such as the length, width, and depth. However, effects of the defect depth, the time-varying contact stiffness between the ball and defect, and the relationship between the time-varying contact stiffness and defect sizes have not been considered in previous defect models. In this work, a new defect model considering a new force–deflection relationship is presented to replace the Hertzian force–deflection relationship to describe the ball-line contact between the ball and defect edge. Both the time-varying displacement impulse and time-varying contact stiffness are considered. The relationship between the time-varying contact stiffness and defect sizes is obtained. Effects of defect sizes on the vibrations of the deep groove ball bearing, especially the defect depth that cannot be described by previous defect models, are investigated. The simulation results are compared with those from the previous defect models. The results show that the model developed can predict a more realistic impulse caused by a localized surface defect for dynamic simulation of the deep groove ball bearing. An experimental investigation is also presented to validate the proposed model.

In the past few years, intensive attention has been focused on birnessite based electrodes for supercapacitors. Much progress has been achieved in developing birnessite based nanostructures with high electrochemical performance. However, challenges still remain in taking full advantage of birnessite and building smart structures to overcome the gap between the obtained capacitance and its theoretical capacitance. In this review, the basic information on birnessite and its preparation strategies are summarized and the current challenges are put forward. Finally, some new strategies for preparing high electrochemical performance birnessite based nanostructures are highlighted.

With the development of fuel cells, multi-stack fuel cell system (MFCS) for high power application has shown tremendous development potential owing to their obvious advantages including high efficiency, durability, reliability, and pollution-free. Accordingly, the state-of-the-art of MFCS is summarized and analyzed to advance its research. Firstly, the MFCS applications are presented in high-power scenarios, especially in transportation applications. Then, to further investigate the MFCS, MFCS including hydrogen and air subsystem, thermal and water subsystem, multi-stack architecture, and prognostics and health monitoring are reviewed. It is noted that prognostics and health monitoring are investigated rarely in MFCS compared with previous research. In addition, the efficiency and durability of MFCS are not only related to the application field and design principle but also the energy management strategy (EMS). The reason is that the EMS is crucial for lifespan, cost, and efficiency in the multi-stack fuel cell system. Finally, the challenge and development potential of MFCS is proposed to provide insights and guidelines for future research.

Rational design of the crystal structures of electrode materials is considered as an important strategy to construct high-performance supercapacitors.