Four antimony compounds were used in this inves as additives to retard combustion of unsaturated polyester and epoxy resins, namely: 1. Tetraethyl ammonium tribromoethylantimonates (additive I). 2. Tetraethyl ammonium chlorodibromoethylantimonates (additive II). 3. Tetraethyl ammonium trichloroethylantimonates (additive III). 4. Tetraethyl ammonium bromodichloroethylantimonates (additive IV). The effects of these additives on flammability of unsaturated polyester and epoxy resins have been studied by using sheets of the resins with weight percentages of (0.5,1.0,1.5,2.0,2.5&3.0%) of the additives in dimensions of (150 X150X3)mm .Three standard test methods were used to measure the flame retardation which are: (ASTM:D -2863), (ASTM:D-635

            Liquid – liquid equilibria data were measured at 293.15 K for the pseudo ternary system (sulfolane + alkanol) + octane + toluene. It is observed that the selectivity of pure sulfolane increases with cosolvent methanol but decreases with increasing the chain length of hydrocarbon in 1-alkanol. The nonrandom two liquid (NRTL) model, UNIQUAC model and UNIFAC model were used to correlate the experimental data and to predict the phase composition of the systems studied. The calculation based on NRTL model gave a good representation of the experimental tie-line data for all systems studied. The agreement between the correlated and the experimental results was very good

This paper presents the ability to use cheap adsorbent (corn leaf) for the removal of Malachite Green (MG) dye from its aqueous solution. A batch mode was used to study several factors, dye concentration (50-150) ppm, adsorbent dosage (0.5-2.5) g/L, contact time (1-4) day, pH (2-10), and temperature (30-60)   The results indicated that the removal efficiency increases with the increase of adsorbent dosage and contact time, while inversely proportional to the increase in pH and temperature. An SEM device characterized the adsorbent corn leaves. The adsorption's resulting data were in agreement with Freundlich isotherm according to the regression analysis, and the kinetics data followed pseudo-first-or

In this paper, the ability of using corn leaves as low-cost natural biowaste adsorbent material for the removal of Indigo Carmen (IC) dye was studied. Batch mode system was used to study several parameters such as, contact time (4 days), concentration of dye (10-50) ppm, adsorbent dosage (0.05-0.25) gram, pH (2-12) and temperature (30-60) ^oC. The corn leaf was characterized by Fourier-transform infrared spectroscopy device before and after the adsorption process of the IC dye and scanning electron microscope device was used to find the morphology of the adsorbent material. The experimental data was imputing with several isotherms where it fits with Freundlich (R² = 0.9

This study concerns the removal of a trihydrate antibiotic (Amoxicillin) from synthetically contaminated water by adsorption on modified bentonite. The bentonite was modified using hexadecyl trimethyl ammonium bromide (HTAB), which turned it from a hydrophilic to a hydrophobic material. The effects of different parameters were studied in batch experiments. These parameters were contact time, solution pH, agitation speed, initial concentration (C0) of the contaminant, and adsorbent dosage. Maximum removal of amoxicillin (93 %) was achieved at contact time = 240 min, pH = 10, agitation speed = 200 rpm, initial concentration = 30 ppm, and adsorbent dosage = 3 g bentonite per 1L of pollutant solution. The characterization of the adsorbent, modi

This paper proposes a new structure of the hybrid neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Weight parameters of the hybrid neural structure with its serial-parallel configuration are adapted by using the Back propagation learning algorithm. The ability of the proposed hybrid neural structure for nonlinear system has achieved a fast learning with minimum number

Density functional theory (DFT) calculations were used to evaluate the capability of Glutamine (Gln) and its derivative chemicals as inhibitors for the anti-corrosive behavior of iron. The current work is devoted to scrutinizing reactivity descriptors (both local and global) of Gln, two states of neutral and protonated. Also, the change of Gln upon the incorporation into dipeptides was investigated. Since the number of reaction centers has increased, an enhancement in dipeptides’ inhibitory effect was observed. Thus, the adsorption of small-scale peptides and glutamine amino acids on Fe surfaces (1 1 1) was performed, and characteristics such as adsorption energies and the configuration with the highest stability and lowest energy were ca