Table of Content

25 November 2020, Volume 8 Issue 4

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ARTICLES

High catalytic activity for formaldehyde oxidation of an interconnected network structure composed of δ-MnO₂ nanosheets and γ-MnOOH nanowires

Ying Tao, Rong Li, Ai-Bin Huang, Yi-Ning Ma, Shi-Dong Ji, Ping Jin, Hong-Jie Luo

2020, 8(4):  429-439.  doi:10.1007/s40436-020-00321-2

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Among the transition metal oxide catalysts, manganese oxides have great potential for formaldehyde (HCHO) oxidation at ambient temperature because of their high activity, nontoxicity, low cost, and polybasic morphologies. In this work, a MnO₂-based catalyst (M-MnO₂) with an interconnected network structure was successfully synthesized by a one-step hydrothermal method. The M-MnO₂ catalyst was composed of the main catalytic agent, δ-MnO₂ nanosheets, dispersed in a nonactive framework material of γ-MnOOH nanowires. The catalytic activity of M-MnO₂ for HCHO oxidation at room temperature was much higher than that of the pure δ-MnO₂ nanosheets. This is attributed to the special interconnected network structure. The special interconnected network structure has high dispersion and specific surface area, which can provide more surface active oxygen species and higher surface hydroxyl groups to realize rapid decomposition of HCHO.

The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-020-00321-2

Nanometric polishing of lutetium oxide by plasma-assisted etching

Peng Lyu, Min Lai, Feng-Zhou Fang

2020, 8(4):  440-446.  doi:10.1007/s40436-020-00324-z

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Plasma-assisted etching, in which the irradiation of hydrogen plasma and inorganic acid etching are integrated, is proposed as a novel polishing method for sesquioxide crystals. By means of this approach, low damage and even damage-free surfaces with a high material removal rate can be achieved in lutetium oxide surface finishing. Analysis of transmission electron microscopy and X-ray photoelectron spectroscopy reveal that plasma hydrogenation converts the sesquioxide into hydroxide, which leads a high efficient way to polish the surfaces. The influences of process conditions on the etching boundary and surface roughness are also qualitatively investigated using scanning electron microscope and white light interferometry. The newly developed process is verified by a systematic experiment.

The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-020-00324-z

Elastic-plastic-brittle transitions of potassium dihydrogen phosphate crystals: characterization by nanoindentation

Yong Zhang, Ning Hou, Liang-Chi Zhang, Qi Wang

2020, 8(4):  447-456.  doi:10.1007/s40436-020-00320-3

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Potassium dihydrogen phosphate (KDP) crystals are widely used in laser ignition facilities as optical switching and frequency conversion components. These crystals are soft, brittle, and sensitive to external conditions (e.g., humidity, temperature, and applied stress). Hence, conventional characterization methods, such as transmission electron microscopy, cannot be used to study the mechanisms of material deformation. Nevertheless, understanding the mechanism of plastic-brittle transition in KDP crystals is important to prevent the fracture damage during the machining process. This study explores the plastic deformation and brittle fracture mechanisms of KDP crystals through nanoindentation experiments and theoretical calculations. The results show that dislocation nucleation and propagation are the main mechanisms of plastic deformation in KDP crystals, and dislocation pileup leads to brittle fracture during nanoindentation. Nanoindentation experiments using various indenters indicate that the external stress fields influence the plastic deformation of KDP crystals, and plastic deformation and brittle fracture are related to the material’s anisotropy. However, the effect of loading rate on the KDP crystal deformation is practically negligible. The results of this research provide important information on reducing machining-induced damage and further improving the optical performance of KDP crystal components.

The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-020-00320-3

Effects of spinning parameters on microstructures of ellipsoidal heads during marginal-restraint mandrel-free spinning

Jia-Yang Chen, Yong-Cheng Lin, Guo-Dong Pang, Xin-He Li

2020, 8(4):  457-472.  doi:10.1007/s40436-020-00322-1

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Marginal-restraint mandrel-free spinning is an advanced technology for manufacturing ellipsoidal heads with large diameter-thickness ratios. The effects of spinning parameters on the forming accuracy of ellipsoidal heads have been studied, and optimized spinning parameters have been obtained. The microstructure evolution of a workpiece is usually very complicated in the spinning process. In this work, the influence of spinning parameters on the microstructures of two-pass spun ellipsoidal heads is studied. It is found that the forming angle and feed rate of the first pass, angle between passes, and feed rate of the second pass significantly affect the microstructures. Meanwhile, the evolution rule of the microstructures near the inner and outer surfaces of the spun parts is almost consistent. A large forming angle, large angle between passes, or large feed rate of the second pass are beneficial to obtain uniform microstructures. A small or large feed rate of the first pass reduces the microstructure uniformity. To improve the microstructure uniformity between the inner and outer surfaces, the optimized spinning parameters are determined.

The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-020-00322-1

Robust identification of weld seam based on region of interest operation

Ying-Zhong Tian, Hong-Fei Liu, Long Li, Wen-Bin Wang, Jie-Cai Feng, Feng-Feng Xi, Guang-Jie Yuan

2020, 8(4):  473-485.  doi:10.1007/s40436-020-00325-y

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For welding path determination, the use of vision sensors is more effective compared with complex offline programming and teaching in small to medium volume production. However, interference factors such as scratches and stains on the surface of the workpiece may affect the extraction of weld information. In the obtained weld image, the weld seams have two distinct features related to the workpiece, which are continuous in a single process and separated from the workpiece’s gray value. In this paper, a novel method is proposed to identify the welding path based on the region of interest (ROI) operation, which is concentrated around the weld seam to reduce the interference of external noise. To complete the identification of the entire welding path, a novel algorithm is used to adaptively generate a dynamic ROI (DROI) and perform iterative operations. The identification accuracy of this algorithm is improved by setting the boundary conditions within the ROI. Moreover, the experimental results confirm that the coefficient factor used for determining the ROI size is a pivotal influencing factor for the robustness of the algorithm and for obtaining an optimal solution. With this algorithm, the welding path identification accuracy is within 2 pixels for three common butt weld types.

The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-020-00325-y

Prediction and control of surface roughness for the milling of Al/SiC metal matrix composites based on neural networks

Guo Zhou, Chao Xu, Yuan Ma, Xiao-Hao Wang, Ping-Fa Feng, Min Zhang

2020, 8(4):  486-507.  doi:10.1007/s40436-020-00326-x

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In recent years, there has been a significant increase in the utilization of Al/SiC particulate composite materials in engineering fields, and the demand for accurate machining of such composite materials has grown accordingly. In this paper, a feed-forward multi-layered artificial neural network (ANN) roughness prediction model, using the Levenberg-Marquardt backpropagation training algorithm, is proposed to investigate the mathematical relationship between cutting parameters and average surface roughness during milling Al/SiC particulate composite materials. Milling experiments were conducted on a computer numerical control (CNC) milling machine with polycrystalline diamond (PCD) tools to acquire data for training the ANN roughness prediction model. Four cutting parameters were considered in these experiments: cutting speed, depth of cut, feed rate, and volume fraction of SiC. These parameters were also used as inputs for the ANN roughness prediction model. The output of the model was the average surface roughness of the machined workpiece. A successfully trained ANN roughness prediction model could predict the corresponding average surface roughness based on given cutting parameters, with a 2.08% mean relative error. Moreover, a roughness control model that could accurately determine the corresponding cutting parameters for a specific desired roughness with a 2.91% mean relative error was developed based on the ANN roughness prediction model. Finally, a more reliable and readable analysis of the influence of each parameter on roughness or the interaction between different parameters was conducted with the help of the ANN prediction model.

The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-020-00326-x

Modeling of flow and debris ejection in blasting erosion arc machining in end milling mode

Ji-Peng Chen, Lin Gu, Wan-Sheng Zhao, Mario Guagliano

2020, 8(4):  508-518.  doi:10.1007/s40436-020-00328-9

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Blasting erosion arc machining (BEAM) is a typical arc discharge machining technology that was developed around 2012 to improve the machinability of difficult-to-cut materials. End milling BEAM has been successfully developed and preliminarily applied in industry. However, owing to the high complexity of the flow field and the difficulty of observing debris in the discharge gap, studies of the flow and debris in end milling BEAM are limited. In this study, fluid dynamics simulations and particle tracking are used to investigate the flow characteristics and debris ejection processes in end milling BEAM. Firstly, the end milling BEAM mode is introduced. Then the numerical modeling parameters, geometric models, and simulation methods are presented in detail. Next, the flow distribution and debris ejection are described, analyzed, and discussed. The velocity and pressure distributions of the axial feed and radial feed are observed; the rotation speed and milling depth are found to have almost no effect on the flow velocity magnitude. Further, debris is ejected more rapidly in the radial feed than in the axial feed. The particle kinetic energy tends to increase with increasing milling depth, and smaller particles are more easily expelled from the flushing gap. This study attempts to reveal the flow field properties and debris ejection mechanism of end milling BEAM, which will be helpful in gaining a better understanding of BEAM.

The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-020-00328-9

Prediction and analysis of process failures by ANN classification during wire-EDM of Inconel 718

Abhilash P. M., Chakradhar D.

2020, 8(4):  519-536.  doi:10.1007/s40436-020-00327-w

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Wire breakages and spark absence are two typical machining failures that occur during wire electric discharge machining (wire-EDM), if appropriate parameter settings are not maintained. Even after several attempts to optimize the process, machining failures cannot be eliminated completely. An offline classification model is presented herein to predict machining failures. The aim of the current study is to develop a multiclass classification model using an artificial neural network (ANN). The training dataset comprises 81 full factorial experiments with three levels of pulse-on time, pulse-off time, servo voltage, and wire feed rate as input parameters. The classes are labeled as normal machining, spark absence, and wire breakage. The model accuracy is tested by conducting 20 confirmation experiments, and the model is discovered to be 95% accurate in classifying the machining outcomes. The effects of process parameters on the process failures are discussed and analyzed. A microstructural analysis of the machined surface and worn wire surface is conducted. The developed model proved to be an easy and fast solution for verifying and eliminating process failures.

The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-020-00327-w

Parametric relationship between hypoid gear teeth and accurate face-milling cutter

Mahmoud Rababah, Muhammad Wasif, Syed Amir Iqbal

2020, 8(4):  537-555.  doi:10.1007/s40436-019-00286-x

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The cutter systems of hypoid gear cutting machines contain groups of inside and outside blades. In these cutter systems, the side cutting edges of the blades machine the convex and concave gear teeth while rotating about the cutter rotation axis. The side cutting edges lay on the rake face formed through the blade, rake, and relief angles; hence, the normal cross-section of the cutter swept surface forms hyperboloid gear teeth. Using the accurate geometry of the cutter system, a relationship between the pressure and spiral angles of the gear tooth and the parameters of the cutter system is developed for the FORMAT machining of a hypoid gear. A new parameterization of the gear tooth surfaces is introduced to determine these angles for the accurate gear tooth by the accurate cutter system. A numerical example with different cutter systems and blade parameters is presented, demonstrating the effects of rake and relief angles over the pressure and spiral angles on mean point projections and gear tooth surface. Finally, the change in pressure and spiral angles with respect to the rake and relief angles are plotted, and the results are analyzed. Finally, it is concluded that the pressure and spiral angles are changed up to a few seconds of a degree in the operating area of the tooth with the change in the back and side rake angles. The side relief angle exhibited little or no effect over the geometry of the gear tooth.

The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-019-00286-x