Background: Acrylic resin polymer s used in prosthodontic treatment as a denture base material for several decades. Separation and debonding of artificial teeth from denture bases present a laboratory and clinical problem affect patient and dentist. The aim of this study is to evaluate the effect of oxygen plasma and argon plasma treatment of acrylic teeth and thermocycling on bonding strength to hot cured acrylic resin denture base material. Materials and Methods: Sixty denture teeth (right maxillary central incisor) are selected. The denture teeth are waxed onto the beveled surface of rectangular wax block according to Japanese standard for artificial teeth. The control group consisted of 20 denture teeth specimen without any treatment.

Background: To evaluate the ISO depth of cure of bulkfill composites and depth of cure which determined by Vickers microhardness test. Materials and Methods: Bulkfill resin composite specimens (n=150) were prepared of three bulkfill composite materials (TetricEvo Ceram, Quixfil and SDR) and light cured by Flash max p3 for 3, 10, 20 seconds and by wood pecker for 10, 20 seconds respectively, a mold was filled with one of the three bulkfill composites and light cured. The specimens removed from the mold and scraped by plastic spatula and the remaining length (absolute length) was measured which represent the ISO depth of cure. After that the specimens were returned into the mold and a microhardness indentation device applied on the specimen

PMMA/TiO2 homogeneous thin films were deposited by using plasma jet system under normal atmospheric pressure and room temperature. PMMA/TiO2 nanocomposite thin film synthesized by plasma polymerization. Titanium oxide was mixed with Methyl Methacrylate Monomer (MMA) with specific weight ratios (1, 3 and 5 grams of TiO2 per 100 ml of MMA). Optical properties of PMMA/TiO2 nanocomposite thin films were characterized by UV-Visible absorption spectra using a double beam UV-Vis-NIR Spectrophotometer. The thin films surface morphological analysis is carried out by employing SEM. The structure analysis are achieved by X-ray diffraction. UV-Visible absorption spectra shows that the increasing the concentration of titanium oxide added to the polym

Quantum dots (QDs) of zinc sulfide (ZnS) was prepared by chemical reaction with different potential of hydrogen (pH) and used to fabricate organic quantum dot hybrid junction device. The optical properties of QDs were characterized by ultraviolet-visible (UV-Vis.) and photoluminescence (PL) spectrometer. The results show that the prepared QDs were nanocrystalline with defects formation. The energy gap (E_g)calculated from PL were 3.64, 3.53 and 3.35 eV for pH=8, 10 and 12 respectively. This decreasing of energy gaps is results of the effect the pH solution increases, which in turn leads to the shifted of the PL spectrum toward red shifted, which makes the energy bands at surface states are shallow ban

This paper presents a numerical simulation for the combined effect of surface roughness and non-Newtonian behavior of the lubricant on the performance of misaligned journal bearing. The modified Reynolds equation to include the effect of non-Newtonian lubricant and bearing surface roughness has been formulated. The model accounts for the lubricant viscosity dependence on temperature and shear rate. In order to make a complete thermo-hydrodynamic analysis (THD) of rough surface misaligned journal bearing lubricated with non-Newtonian lubricant, the modified Reynolds equation coupled with the energy, heat conduction equations, the equation related the viscosity and temperature with appropriate boundary conditions have been solved simultane

Electrochemical machining is one of the widely used non-conventional machining processes to machine complex and difficult shapes for electrically conducting materials, such as super alloys, Ti-alloys, alloy steel, tool steel and stainless steel.  Use of optimal ECM process conditions can significantly reduce the ECM operating, tooling, and maintenance cost and can produce components with higher accuracy. This paper studies the effect of process parameters on surface roughness (Ra) and material removal rate (MRR), and the optimization of process conditions in ECM. Experiments were conducted based on Taguchi’s L9 orthogonal array (OA) with three process parameters viz. current, electrolyte concentration, and inter-electrode gap. Sig

Feed Forward Back Propagation artificial neural network (ANN) model utilizing the MATLAB Neural Network Toolbox is designed for the prediction of surface roughness of Duplex Stainless Steel during orthogonal turning with uncoated carbide insert tool. Turning experiments were performed at various process conditions (feed rate, cutting speed, and cutting depth). Utilizing the Taguchi experimental design method, an optimum ANN architecture with the Levenberg-Marquardt training algorithm was obtained. Parametric research was performed with the optimized ANN architecture to report the impact of every turning parameter on the roughness of the surface. The results suggested that machining at a cutting speed of 355 rpm with a feed rate of 0.07 m

The aim of this research is to investigation the optimization of the machining parameters (spindle speed, feed rate, depth of cut, diameter of cutter and number of flutes of cutter) of surface roughness for free-form surface of composite material (Aluminum 6061 reinforced boron carbide) by using HSS uncoated flat end mill cutters which are rare use of the free-form surface. Side milling (profile) is the method used in this study by CNC vertical milling machine. The purpose of using ANFIS to obtain the better prediction of surface roughness values and decreased of the error prediction value and get optimum machining parameters by using Taguchi method for the best surface roughness at spindle speed 4500 r.p.m, 920mm/rev feed rate, 0.6mm de