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Abstract To improve the mechanical properties of the rolling body surface of wind power bearings, extend its service life. In this study, a large-scale molecular/atomic parallel processor LAMMPS was introduced, and then the process of magnetron sputtering technology in the preparation of DLC/Ni-DLC thin films on the 42CrMo substrate material was simulated. The effects of deposition parameters such as sputtering temperature, sputtering voltage, deposition air pressure, and Ni doping on the residual stress, film base bonding, and organizational structure of the thin films were investigated. The simulation results show that for different deposition parameters, the atomic tensile and compressive stresses existed simultaneously in DLC/Ni-DLC films, and the residual stresses were between − 0.504–5.003 Gpa and − 2.11–0.065 Gpa, respectively; the doping of Ni effectively improved the distribution of hybrid structure and the mechanical properties of the DLC films, and the ratio of the sp3 hybrid structure in the film organization was about 2.56 times higher than that of the non-doped films, and the membrane base bonding force was increased by 32.78% and the residual stress is reduced and transitioned from tensile stress to compressive stress. In addition, it was observed that the thickness of the mixed layer of DLC/Ni-DLC films with the substrate was not increased after the thickness of the mixed layer was extended to about 2 nm. Nickel doping and reasonable control of deposition parameters help to reduce the residual stress and improve the bonding strength of the film by changing the organizational structure of the film, which provides an important theoretical and scientific basis for the preparation of low-stress, high-performance and long-life DLC films and the wide application of rolling bodies for wind power bearings under complex working conditions.

Based on the principle of light scattering, measuring dust concentration can only be done manually at fixed times and locations, with poor real-time performance. It can only detect dust mass concentration and cannot provide a range of particle size distribution. At present, research on dust particle detection based on image analysis mainly focuses on unilateral research on dust mass concentration or particle size distribution. It cannot achieve simultaneous detection of dust mass concentration and particle size distribution range. In order to solve the above problems, a method for detecting dust particles in excavation working face based on image analysis is proposed. It explores the relationship between image features and dust mass concentration and particle size distribution. By using a dust sample collection and image acquisition device, dust particle images are collected and the dust mass concentration at the time of image acquisition is obtained. An image processing algorithm for dust samples, is developed to extract parameters related to grayscale features, texture features, and geometric features of the image. The correlation analysis between the extracted image features and the measured dust mass concentration is performed, and the image features with high correlation is selected as parameters to establish a regression mathematical model. The method extracts the number of pixels in the dust particle object. Combining with the conversion coefficient, the method calculates the size and distribution range of the dust particle based on the geometric equivalent area diameter. The experimental results show that the average relative error between the measured dust mass concentration and the calculated values of the established image feature multiple nonlinear regression model mathematical model is 12.37%. The maximum relative error between the standard measured particle size and the geometric equivalent area size obtained from the particle size distribution is 8.63%, and the average relative error is 6.37%. This verifies the accuracy of the image feature based dust mass concentration regression mathematical model and the geometric equivalent area diameter distribution mathematical model.

Three-dimensional (3D) structures capable of reversible transformations in their geometrical layouts have important applications across a broad range of areas. Most morphable 3D systems rely on concepts inspired by origami/kirigami or techniques of 3D printing with responsive materials. The development of schemes that can simultaneously apply across a wide range of size scales and with classes of advanced materials found in state-of-the-art microsystem technologies remains challenging. Here, we introduce a set of concepts for morphable 3D mesostructures in diverse materials and fully formed planar devices spanning length scales from micrometres to millimetres. The approaches rely on elastomer platforms deformed in different time sequences to elastically alter the 3D geometries of supported mesostructures via nonlinear mechanical buckling. Over 20 examples have been experimentally and theoretically investigated, including mesostructures that can be reshaped between different geometries as well as those that can morph into three or more distinct states. An adaptive radiofrequency circuit and a concealable electromagnetic device provide examples of functionally reconfigurable microelectronic devices.

Formation of 3D mesostructures in advanced functional materials is of growing interest due to the widespread envisioned applications of devices that exploit 3D architectures. Mechanically guided assembly based on compressive buckling of 2D precursors represents a promising method, with applicability to a diverse set of geometries and materials, including inorganic semiconductors, metals, polymers, and their heterogeneous combinations. This paper introduces ideas that extend the levels of control and the range of 3D layouts that are achievable in this manner. Here, thin, patterned layers with well-defined residual stresses influence the process of 2D to 3D geometric transformation. Systematic studies through combined analytical modeling, numerical simulations, and experimental observations demonstrate the effectiveness of the proposed strategy through ≈20 example cases with a broad range of complex 3D topologies. The results elucidate the ability of these stressed layers to alter the energy landscape associated with the transformation process and, specifically, the energy barriers that separate different stable modes in the final 3D configurations. A demonstration in a mechanically tunable microbalance illustrates the utility of these ideas in a simple structure designed for mass measurement.

Acidification, as an effective measure to remove blockages and restore oil well productivity, has received widespread concern. However, conventional acid systems can only be used to unblock near‐wellbore zones and are difficult to act on far‐wellbore reservoirs. In this article, scanning electron microscope, energy‐dispersive X‐ray spectroscope, and X‐ray diffractometer were used to analyze the blockages in the Bai 823 well area, and it was determined that their main components were CaCO3 and FeCO3, which provided the basis for the construction of the unblocking formula. Then, the acid dissolution experiments on the plugging materials showed that the dissolution rate of 10% HCl can reach more than 85% for the scale sample; the acid dissolution experiments on the rock sample showed that the autogenous mud acid has better dissolution performance and better retardation performance for the rock sample, and the effective action time is longer, so it can be used for deeper unplugging of the reservoir. Finally, the process parameters such as the optimal acid concentration, acid dosage, and discharge volume were optimized by establishing the fracture‐matrix acid flow reaction model. Research results indicate that the autogenous mud acid can act on the blockage in the far‐wellbore area to improve the acidification effect. [ABSTRACT FROM AUTHOR]