Bentonite is widely used in industrial applications. The present study reports the effect of adding different weights of ZnO to the Iraqi bentonite, on surface area, pore volume and real density. These surface properties were evaluated for pure and modified bentonite. The modification was made by adding different ZnO weights such as; ( 0.5%, 1%, 5%, 10% ). The effect of heat exposing for all modified clay samples at 500 ?C have been also evaluated. The results show that the addition of 0.5% ZnO leads to increase the surface area percentage about 36%, increase pore volume percentage about 5.48% and increase the real density percentage about 27.116%. When the samples exposed to 500 ?C, their surface area and pore volumes have been decreased a

Epoxy resin has many chemical features and mechanical properties, but it has a small elongation at break, low impact strength and crack propagation resistance, i.e. it exhibits a brittle behavior. In the current study, the influence of adding kaolin with variable particle size on the mechanical properties (flexural modulus E, toughness Gc, fracture toughness Kc, hardness HB, and Wear rate WR) of epoxy resin was evaluated. Composites of epoxy with varying concentrations (0, 10, 20, 30, 40 weights %) of kaolin were prepared by hand-out method. The composites showed improved (E, Gc, Kc, HB, and WR) properties with the addition of filler. Also, similar results were observed with the decrease in particle size. In addition, in this study, mult

In this research the results of applying Artificial Neural Networks with modified activation function to perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of identification strategy consists of a feed-forward neural network with a modified activation function that operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have been trained online and offline have been used, without requiring any previous knowledge about the system to be identified. The activation function that is used in the hidden layer in FFNN is a modified version of the wavelet function. This approach ha

In this research the results of applying Artificial Neural Networks with modified activation function to
perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance
Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of
identification strategy consists of a feed-forward neural network with a modified activation function that
operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have
been trained online and offline have been used, without requiring any previous knowledge about the
system to be identified. The activation function that is used in the hidden layer in FFNN is a modified
version of the wavelet func

ABSTRACT Porous silicon has been produced in this work by photochemical etching process (PC). The irradiation has been achieved using ordinary light source (150250 W) power and (875 nm) wavelength. The influence of various irradiation times and HF concentration on porosity of PSi material was investigated by depending on gravimetric measurements. The I-V and C-V characteristics for CdS/PSi structure have been investigated in this work too.

In this research thin films from SnO2 semiconductor have been prepared by using chemical pyrolysis spray method from solution SnCl2.2H2O at 0.125M concentration on glass at substrate temperature (723K ).Annealing was preformed for prepared thin film at (823K) temperature. The structural and sensing properties of SnO2 thin films for CO2 gas was studied before and after annealing ,as well as we studied the effect temperature annealing on grain size for prepared thin films .