The acrylic polymer composites in this study are made up of various weight ratios of cement or silica nanoparticles (1, 3, 5, and 10 wt%) using the casting method. The effects of doping ratio/type on mechanical, dielectric, thermal, and hydrophobic properties were investigated. Acrylic polymer composites containing 5 wt% cement or silica nanoparticles had the lowest abrasion wear rates and the highest shore-D hardness and impact strength. The increase in the inclusion of cement or silica nanoparticles enhanced surface roughness, water contact angle (WCA), and thermal insulation. Acrylic/cement composites demonstrated higher mechanical, electrical, and thermal insulation properties than acrylic/silica composites because of their lowe

   The Sadi reservoir is one of the largest and most important unconventional tight oil reservoirs in southern Iraq. However, it suffers from low production rates, necessitating many development strategies that require a correct and reliable characterization of reservoir fluid properties. Whilst these properties are originally obtained from laboratory experiments, measurement errors often occur despite rigorous workflows, which negatively affect the calculation of reservoir fluid properties. This study utilizes the fluid thermodynamics characterization program (PVTp) to generate a reliable model for determining the oil properties of Sadi reservoir. A methodology was developed to simulate fluid thermodynamic tests, including Differ

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

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

Films of pure Poly (methyl methacrylate) (PMMA) doped by potassium iodide (KI) salt with percentages (1%) at different thickness prepared by casting method at room temperature. In order to study the effect of increasing thickness on optical properties, transmission and absorption spectra have been record for five different thicknesses(80,140,210,250,320)µm. The study has been extended to include the changes in the band gap energies, refractive index, extinction coefficient and absorption coefficient with thickness.

Mixing aluminum nitrate nonahydrate with urea produced room temperatures clear colorless ionic liquid with lowest freezing temperature at (1: 1.2) mole ratio respectively. Freezing point phase diagram was determined and density, viscosity and conductivity were measured at room temperature. It showed physical properties similar to other ionic liquids. FT-IR,UV-Vis, 1H NMR and 13C NMR were used to study the interaction between its species where - CO ??? Al- bond was suggested and basic ion [Al(NO3)4]? and acidic ions [Al(NO3)2. xU]+ were proposed. Water molecule believed to interact with both ions. Redox potential was determined to be about 2 Volt from – 0.6 to + 1.4 Volt with thermal stability up to 326 ?.

The cost-effective carbon cross-linked Y zeolite nanocrystals composite (NYC) was prepared using an eco-friendly substrate prepared from bio-waste and organic adhesive at intermediate conditions. The green synthesis method dependent in this study assures using chemically harmless compounds to ensure homogeneous distribution of zeolite over porous carbon. The greenly prepared cross-linked composite was extensively characterized using Fourier transform infrared, nitrogen adsorption/desorption, Field emission scanning electron microscope, Dispersive analysis by X-ray, Thermogravimetric analysis, and X-ray diffraction. NYC had a surface area of 176.44 m2/g, and a pore volume of 0.0573 cm3/g. NYC had a multi-function nature, sustained at a long-