Surface engineering of titanium for biomedical applications by anodizing

Abstract: Competitive manufacturing implies fit for purpose and efficient manufacturing practices. Dental implants are biomedical parts that are manufactured from either Grade 4 or 5 Titanium alloy. In certain situations it may be beneficial for patient satisfaction purposes and for product identification marking to change the appearance (colour and reflectance) of the implant. In the present study, a TiO2 based coating is applied on commercially pure titanium (Grade 4) alloy substrates by the anodizing process. The objective of this study was to engineer the aesthetic appearance of the dental implants while monitoring its effect on aspects as regards to biocompatibility and function. Chromaticity (colour and hue) and reflectance are investigated as a function of the anodizing process parameters (electrolyte voltage, current and electrolyte). Grade 4 titanium was anodized in diluted sulphuric acid electrolyte at various voltages. The reflectance of the anodized specimens was measured with a spectrophotometer. Surface roughness, oxide film thickness and chemical composition of the oxide phase were measured. By varying the electrolyte voltage between 5 V to 40 V different colour ranges were produced. It can be concluded that the surface colour of anodized titanium is dependent on the oxide layer thickness and therefore the applied voltage. Conventional surface roughness did not change and was similar to the virgin material. Elevated voltages resulted in a more crystalline oxide layer. The aesthetic appearance of titanium implants may be improved

Parametric optimization MRR and surface roughness in wire electro discharge machining (WEDM) of D2 steel using Taguchi based utility approach

Abstract: This paper reports the effect of process parameters on material removal rate (MRR) and surface roughness (Ra) in wire electro discharge machining of AISI D2 steel. The experiments were performed by different cutting conditions of pulse on time (Ton), pulse off time (Toff), servo voltage (SV) and wire feed (WF) by keeping workpiece thickness constant. Taguchi L27 orthogonal array of experimental design is employed to conduct the experiments. Multi-objective optimization was performed using Taguchi based utility approach to optimize MRR and Ra. Analysis of means and variance on to signal to noise ratio was performed for determining the optimal parameters. It reveals that the combination of Ton3, Toff1, SV1, WF2 parameter levels is beneficial for maximizing the MRR and minimizing the Ra simultaneously. The results indicated that the pulse on time is the most significant parameter affects the MRR and Ra. The melted droplets, solidified debris around the craters, cracks, and blow holes were observed on the machined surface for a higher pulse on time and lower servo voltage. Recast layer thickness increased from an increase in pulse on time duration. The machined surface hardness of D2 steel is increased due to the repetitive quenching effect and formation oxides on the machined surface

Chaining Algorithm and Protocol for Peer-to-Peer Streaming Video on Demand System

ABSTRACT As the various architectures and protocol have been implemented a tru

A Deep Learning Approaches for Modeling and Predicting of HIV Test Results Using EDHS Dataset

At present, HIV/AIDS has steadily been listed in the top position as a major cause of death. However, HIV is largely preventable and can be avoided by making strategies to increase HIV early prediction. So, there is a need for a predictive tool that can help the domain experts with early prediction of the disease and hence can recommend strategies to stop the prognosis of the diseases. Using deep learning models, we investigated whether demographic and health survey dataset might be utilized to predict HIV test status. The contribution of this work is to improve the accuracy of a model for predicting an individual’s HIV test status. We employed deep learning models to predict HIV status using Ethiopian demography and health survey (EDHS) datasets. Furthermore, we discovered that predictive models based on these dataset may be used to forecast individuals’ HIV test status, which might assist domain experts prioritize strategies and policies to safeguard the pandemic. The outcome of the study confirms that a DL model provides the best results with the most promising extracted features. The accuracy of the all DL models can further be enhanced by including the big dataset for predicting the prognosis of the disease

Chitosan-g-poly(acrylic acid)-bentonite composite: a potential immobilizing agent of heavy metals in soil

Aiming to achieve heavy metal adsorption in water and soil environments, a montmorillonite rich bentonite was graft-copolymerized with chitosan, and the obtained composite material was evaluated as a metal immobilizing agent for remediating metal contaminated soil. The graft-copolymerization reaction in the composite was confirmed by scanning electron microscopy, X-ray diffraction and Fourier transform infrared spectroscopy techniques. Batch adsorption studies with varying experimental conditions, such as adsorbent amount, pH and metal concentration, were conducted to assess the metal adsorption capacity of the composite. The adsorption pattern followed the Langmuir isotherm model, and maximum monolayer capacity was 88.5, 72.9, 51.5 and 48.5 mg g−1 for Cu, Zn, Cd and Ni, respectively. Amendment of a contaminated soil with the composite enhanced the metal retention capacity by 3.4, 3.2, 4.9 and 5.6-fold for Cu, Zn, Cd and Ni, respectively, over unamended soil. The desorption percentage of metals from the composite treated soil was significantly lower than the unamended contaminated soil. The findings indicated that immobilization of heavy metals in soils could be achieved by the chitosan–bentonite, which would potentially be an inexpensive and sustainable environmental remediation technology

Effect of ECAE Die Angle on Microstructure Mechanical Properties and Corrosion Behavior of AZ80/91 Magnesium Alloys

Magnesium alloys have poor tensile strength, ductility and corrosion resistance properties associated with other engineering materials like aluminum alloys, steels and superalloys etc. Therefore, many researchers worked on equal channel angular pressing of magnesium alloys to improve the mechanical properties and corrosion resistance. In this work, the effect of channel angles on material properties was investigated during equal channel angular pressing of AZ80/91 magnesium alloy using processing route-R at 598 K processing temperature. Channel angles of 900 and 1100, common corner angle of 300 have been considered for the study. It has been revealed that the channel angle has a significant influence on deformation homogeneity, microhardness, ultimate tensile strength, ductility, and corrosion behavior of AZ80/91 magnesium alloys. Specifically, AZ80/91 Mg alloys processed through 900 channel angle i.e. die A is considered as optimal die parameter to improve above-said material properties. Investigation showing concerning as-received AZ80 and AZ91 Mg alloy indicates 11%, 14% improvement of UTS and 69%, 59% enhancement in ductility after processing through 4P through die A (90°) at 598 K respectively. Also, the corrosion rate reduces to 97% and 99% after processing the sample with 4P-ECAP die A (90°) at the same processing temperature for AZ80 and AZ91 Mg alloys respectively. This is mainly due to grain refinement and distribution of Mg17Al12 secondary phase during ECAP