Effect of BAg1 Ni-Electroplating on microstructure and properties of WC-Co-brazed joints

Excellent strength, joining effectiveness and low cost of brazing make it one of the most favoured methods for hard metals attachments. In this study, WC-Co, as a hard metal, was furnace-brazed by BAg1 (Ag–Cu–Zn–Cd) filler alloy and Ni-electroplated BAg1, and the influence of Ni-electroplating in joint properties was thoroughly studied. The brazing process was carried out using a tube furnace, at 670°C/15?min. The characteristics and microstructure of joints were studied by scanning electron microscope, energy-dispersive spectrometer and XRD. It was revealed that Ni coating of BAg1 represents 20% increase in wettability and approximately 15% increase in shear strength (from 107.98 to 124.17?MPa) by the formation of soft and semi-active NiZn phase and by the substitution of some of brittle TiC phase with NiTi phase.     

Wood–high‐density polyethylene composites: Water absorption and mechanical properties

In this research, the effect of water absorption on the mechanical properties of wood/high‐density polyethylene (HDPE) composites were investigated. HDPE (44005ARPC) was used as the polymer matrix, and spruce sawdust was used as the filler at a maximum loading of 50 wt % of the total weight of each compound. All compounds contained 5 wt % magnesium stearate as a lubricant and 0.5 wt % Irgafos 168 as a heat stabilizer. Four factors in two levels were chosen [talc (filler) at levels of 5 and 15 wt %, zinc borate (fungicide) at levels of 0 and 1 wt %, maleic anhydride polyethylene (coupling agent) at levels of 4 and 6 wt %, and method of mixing (one‐step vs. two‐step mixing)], and eight compounds were prepared with an L8 Taguchi orthogonal array which has 8 combinations of levels. The effects of each factor at two levels on the diffusion constant and the tensile and bending strengths (under wet and dry conditions) were investigated by the analysis of variance of means with 90% confidence. The optimum level for each factor is reported. The results show that there was a linear correlation between the diffusion constant and tensile and bending strengths when the samples were immersed in distilled water. A higher diffusion constant resulted in much lower tensile and bending strengths with immersion in distilled water until saturation was reached. Scanning electron microscopy images confirmed good mixing when two‐steps mixing was used. © 2010 Wiley Periodicals, Inc. J Appl Polym Sci, 2011     

Optimization of coating variables for hardness of industrial tools by using artificial neural networks

Thin-film coating plays a prominent role on the manufacture of many industrial devices. Coating can increase material performance due to the deposition process. This paper proposes the estimation of hardness of titanium thin-film layers as protective industrial tools by using multi layer perceptron (MLP) neural network. Based on the experimental data obtained during the process of chemical vapor deposition (CVD) and physical vapor deposition (PVD), the optimization of the coating variables for achieving the maximum hardness of titanium thin-film layers, is performed. Then, the obtained results are experimentally verified. During titanium coating, improvements of up to 16.75% of the layers hardness are accessible.     

A 4D statistical model of wrist bone motion patterns

Direct imaging of ligament damage in the wrist remains a challenge. Still, such damage can be assessed indirectly through the analysis of changes in wrist pose and motion pattern. For this purpose we built a statistical reference model that describes healthy motion patterns. We show that such a model can also be used to detect and quantify pathologies. A model that only describes the global translations and rotations of the carpal bones is insufficiently accurate due to size and shape variations of the bones. We present a local statistical motion model that minimizes the influence of size and shape differences by analyzing the coordinate differences of pairs of points on adjacent bone surfaces. These differences are determined in a set of 14 healthy example wrists imaged in a range of poses by means of 4D-RX imaging. The distribution of the differences as a function of the pose form the local statistical motion model (LSMM). Translations of 2 mm and rotations of 20° with respect to the healthy example wrists are detected as outliers in the point pair distributions. An evaluation involving wrists with a damaged ligament between scaphoid and lunate shows that not only joint space widenings can be detected, but also shifts of congruent bone surfaces. The LSMM is also used to perform a virtual reconstruction of the most likely healthy wrist after a simulated perturbation of bones. The reconstruction precision is shown to be about 1 mm. Therefore, the presented 4D statistical model of wrist bone movement may become a valuable clinical tool for diagnosis and surgical planning.