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Understanding the magnetic states and their dynamics in patterned ferromagnetic materials is of great importance for ultrahigh-density recording from the viewpoints of both fundamental research and practical applications. However, reliable access to magnetization dynamics in magnetic materials and devices on the technologically highly relevant terahertz range remains challenging. Currently, there is a lack of reports on terahertz magnetic susceptibility. Here, through micromagnetic simulations, we study the dynamics of pyramid-shaped, isolated magnetic nanodots and their arrays made of L10-FePt with high magnetocrystalline anisotropy. Numerical results reveal a significant magnetic response of isolated pyramid nanodots in the terahertz range. Specifically, two resonant modes, namely, a bulk mode and an edge mode, have been identified. For the lateral size above ∼100 nm, the nanodot's bulk mode splits and higher-order modes appear. Furthermore, the calculated spatial Fourier amplitude of resonant modes of nanopyramid arrays exhibits the dependence of lateral size and inter-dot spacing. These findings are expected to open up a promising route to terahertz spintronics utilizing magnetic nanostructures. [ABSTRACT FROM AUTHOR]

In this study, we proposed the preparation of phosphate composite coatings (LSPCs) using a Fe3O4/hexagonal boron nitride (h-BN) hybrid, where the ordered dispersion and orientation of h-BN was achieved through a weak magnetic field. The evolution of the physiochemical structure of Fe3O4/h-BN before and after the modification was investigated by FTIR, XRD, XPS, TEM, SEM, and EDS. In addition, the corrosion protection performance of LSPCs was evaluated by electrochemical tests combining the analysis of the microstructure and phase characterization. Results indicate that the nano-Fe3O4 particles are successfully deposited on the surface of h-BN after modification. In addition, electrochemical results confirm that the corrosion protection performance of the layered phosphate composite coating is higher than that of the randomly dispersed coating. That is because the layered structure promotes the densification of the phosphate composite coating, thus delaying the permeation of corrosive media and makes the coatings more protective. [ABSTRACT FROM AUTHOR]

Introducing a flexible substrate in functional devices often brings about stress-tunable properties. Ferromagnetic nanorings fabricated on flexible substrates hold promise for microwave applications based on a stretchable functional system. Here, through micromagnetic simulations, we report high-frequency dynamic properties of such FeGa nanorings each with a magnetic vortex, concentrating on the dynamic susceptibility and the spatial structure of relevant resonance modes in response to an induced tensile or compressive stress. It is seen that the fundamental resonance frequency varies significantly with the mechanical stress and ring width. Furthermore, spatial profiles of the resonance modes are found to evolve with the stress and ring width, resulting in a repeated fluctuation in dynamic susceptibility. Our findings provide guidance for the design of stress tunable microwave devices. [ABSTRACT FROM AUTHOR]

Knowledge of the dynamic magnetic susceptibility of patterned films is of great importance for exploring future data-storage applications and microwave devices. Since ferromagnetic resonance frequency is a function of the geometric parameters of a certain magnetic system, in this work, we investigate by micromagnetic simulations a set of stripe-patterned FeGa films, which have an identical thickness of 10 nm but a varying width in the range of 30–80 nm and a varying length in the range of 200–1000 nm. Fast-Fourier transform analysis of the simulation results for ferromagnetic resonance calculation identifies two distinct resonance peaks, which are assigned to a “bulk” mode and an “edge” mode. The presence of stress-induced anisotropy significantly affects both the two resonant modes. The occupation area of the spreading magnetization near the stripe ends is controllable by a tensile or compressive stress applied along the strip width. Consequently, the dynamic susceptibility of FeGa can be adjusted by an applied stress. [ABSTRACT FROM AUTHOR]

Manipulation of light‐induced magnetization has become a fundamentally hot topic with a potentially high impact for atom trapping, confocal and magnetic resonance microscopy, and data storage. The control of the magnetization orientation mainly relies on the direct methods composed of amplitude, phase, and polarization modulations of the incident light under the tight focusing condition, leaving the achievement of arbitrary desirable 3D magnetization orientation complicated, inflexible, and inefficient. Here, a facile approach called machine learning inverse design to achieve expected vectorial opto‐magnetization orientation is proposed. This pathway is time‐efficient and accurate to produce the demanded incident beam for arbitrary prescribed 3D magnetization orientation. It is highlighted that the machine learning method is not only applied for magnetization orientations, but also widely used in the control of magnetization structures. [ABSTRACT FROM AUTHOR]

With the development of Industry 4.0, companies are increasingly applying sensors and information technologies to capture data at all stages of production. Simultaneously, technologies such as Big data, Internet of Things(IoT), Internet of Services(IoS), Artificial intelligence(AI), and data mining(DM), are being used to facilitate a more adaptable and smart maintenance policy. The deep learning algorithms has been playing a very important role in predictive maintenance. This paper presents a review of deep leaning application in realizing predictive maintenance policy. [ABSTRACT FROM AUTHOR]

This paper presented a method to carry out fault diagnosis via analyzing the motion signals of a SCARA. To analyze the motion signals of the end joint of a selective compliance assembly robot arm (SCARA) and carry out fault diagnosis. A model parameter-based threshold algorithm is proposed in this study to improve the efficiency of the fault diagnosis on the end joint of a SCARA manipulator. The operation state of the robot is determined by comparing the speed curve of the end joint of the robot with the threshold using the proposed algorithm. Firstly, the threshold range of the system output is estimated using the speed observer constructed via parameter separation. Secondly, the acceleration signals of the end joint of the robot are collected at various operational angular speeds by a single acceleration sensor installed at the end joint of the manipulator. The operation state of the robot is evaluated by analyzing the trend and vibration characteristics of its acceleration. Finally, experiments are conducted at three different speeds: 2.4rad/s, 3.12rad/s and 3.6rad/s. Some robot malfunctions are detected by comparing the actual speed with the threshold. Thus, the proposed method can be used to monitor the variation signal in each robot joint through a single accelerometer mounted on the top of the manipulator. [ABSTRACT FROM AUTHOR]