Obtention of Hard Coating Using Electrochemical Process in Aluminum-Silicon Alloys for Automotive Vehicles

Surface Activation of NiTi Alloy by Using Electrochemical Process for Biomimetic Deposition of Hydroxyapatite Coating (TECHNICAL NOTE)

Electrochemical depositions of calcium phosphate (Ca-P) film on NiTi alloy in concentrated simulated body flood (SBF×5) were carried out by cathodic polarization. The Ca-P layer was successfully deposited on Ni-Ti alloy substrate under 10mA/cm2 current density for 2 hours at room temperature. Then, in order to investigate the bioactivity of the pre-calcified samples, they were immersed in SBF f...

Modeling of Inlet Zone in Hydrostatic Extrusion Process for Aluminum and Aluminum Alloys

The objective of this paper is to investigate the viscous shear heating effect on the formation of minimum film thickness in inlet zone of the hydrostatic extrusion process as function of various operating parameters. Minimum film thicknesses in the inlet zone has been evaluated at various extrusion speeds, material parameters, extrusion pressures, and die semiangle for extrusion of low strengt...

Operational Cost Analysis for the Treatment of Various Textile Effluents by Electrochemical Process Using Stainless Steel and Aluminum Electrodes

The development of treatment processes from laboratory scale to industries involves a lot of troubles due to the automation of process parameters and fluctuated characteristics of wastewater. In the present study, six different real-time textile effluents of samples such as S1 to S6 are characterized and treated by electrocoagulation process using Stainless Steel (SS) and Aluminum (Al) elec...

PREDICTION OF THE ALUMINUM SILICON MODIFICATION LEVEL IN THE AlSiCu ALLOYS USING ARTIFICIAL NEURAL NETWORKS

In this paper, two feed forward neural network models have been presented to predict the Silicon Modification Level (SiML) of W319 aluminum alloys using the Thermal Analysis (T.A) parameters as inputs. The developed neural networks are a Multilayer Perceptron (MLP) network and a Radial Basis Function (RBF) network. The neural network models were found to predict the SiML accurately (R=0.99). Th...

Theoretical understanding of stability of alloys for hard-coating applications and design