Background: Poly (methylmethacrylate) is not ideal in every aspect and has disadvantages such as insufficient surface hardness, increase water sorption and poor impact resistance and the latter being the primary cause of fracture of denture base resins. The aim of this study was to evaluate the effect of addition of silanized nano- hydroxyapatite (HA) on some properties of heat cured acrylic denture base material. Materials and methods: HA nano particles were first silanized with MPS (tri methacryloxypropyletrimethoxy silane coupling agent) then ultrasonicated with methylmethacrylate (monomer) to disperse agglomerated nano particles and mixed with polymer. 2% by wt of HA nano particles was selected as the best concentration that add

Background: Denture cleansing was an important step that could prevent the spread of infection and improve a patient's health, the durability of the dentures, and the overall quality of life; therefore, it was necessary to choose a suitable cleanser that, in addition to being effective, did not have an unfavorable effect on the qualities of the denture base resin itself when used for an extended period. For this purpose, this study aimed to evaluate the effect of tea tree oil (TTO) on Candida albicans adhesion and the surface roughness property of poly(methyl methacrylate) denture material after immersion in TTO. Methods: A total of 55 heat-cured acrylic resin specimens were used for C. albicans adherence and surface roughness tests. The

Tungsten inert gas arc welding–based shaped metal deposition is a novel additive manufacturing technology which can be used for fabricating solid dense parts by melting a cold wire on a substrate in a layer-by-layer manner via continuous DC arc heat. The shaped metal deposition method would be an alternative way to traditional manufacturing methods, especially for complex featured and large-scale solid parts manufacturing, and it is particularly used for aerospace structural components, manufacturing, and repairing of die/molds and middle-sized dense parts. This article presents the designing, constructing, and controlling of an additive manufacturing system using tungsten inert gas plus wire–based shaped metal deposition metho

Aims: This study was conducted to assess the effect of the addition of yttrium oxide (Y2O3) nanoparticles on the tensile bond strength, tear strength, shore A hardness, and surface roughness of soft-denture lining material. Materials and Methods: Y2O3 NPs with 1.5 and 2 wt.% were added into acrylic-based heat-cured soft-denture liner. A total of 120 specimens were prepared and divided into four groups according to the test to be performed (tensile bond strength, tear strength, surface hardness, and surface roughness). Results: There was a highly significant increase in tensile bond strength between the soft liner and the acrylic denture base, tear strength, and hardness at both concentrations as compared to the control group, whereas ther

A.C electrical conductivity and dielectric properties for poly
(vinyl alcohol) (PVA) /poly (ethylene oxide) (PEO) blends undoped
and doped with multi-walled carbon nanotube (MWCNTs) with
different concentrations (1, and 3 wt %) in the frequency range
(25x103 - 5x106 Hz) were investigated. Samples of (PVA/PEO)
blends undoped and doped with MWCNTs were prepared using
casting technique. The electrical conductivity measurements showed
that σA.C is frequency dependent and obey the relation σA.C =Aωs for
undoped and doped blends with 1% MWCNTs, while it is frequency
independent with increases of MWCNTs content to 3%. The
exponent s showed proceeding increase with the increase of PEO
ratio (≥50%) for undope

The objective of this study is to apply Artificial Neural Network for heat transfer analysis of shell-and-tube heat exchangers widely used in power plants and refineries. Practical data was obtained by using industrial heat exchanger operating in power generation department of Dura refinery. The commonly used Back Propagation (BP) algorithm was used to train and test networks by divided the data to three samples (training, validation and testing data) to give more approach data with actual case. Inputs of the neural network include inlet water temperature, inlet air temperature and mass flow rate of air. Two outputs (exit water temperature to cooling tower and exit air temperature to second stage of air compressor) were taken in ANN.

Polymer electrolytes systems compose of (PEO+KI+I₂) and (PEO+RbI+I₂) with different concentration, and a fixed amount of ethylene carbonate (EC) and propylene carbonate (PC) over temperatures range 293-343 K prepared by solution cast me