A new Turbidimetric method characterized by simplicity, accuracy and speed for determination of iron(III) in drug samples by continuous flow injection analysis. The method was based on the formation of complex for iron(III) with 8-hydroxyquinoline in presence of ammonium acetate as a medium for the formation of deep green precipitate and this precipitate was determined using homemade Linear Array Ayah-5SX1-T-1D continuous flow injection analyser. The optimum parameters were 2.6 mL.min-1 flow rate using H2O as a carrier, 1.9 mL.min-1 (14 mmol.L-1) ammonium acetate, 2.4 mL.min-1 (14 mmol.L-1) 8-hydroxyquinoline, 60 L sample volume and open valve for the purge of the sample segment. Data treatment shows that linear range 0.1-8.0 mmol.L-1 while L.O.D 4.8×10-9 M/sample equivalent to 16.1 pg/sample from the stepwise dilution for minimum concentration of lowest concentration in linear dynamic range of the calibration graph. The correlation coefficient (r) was 0.9911 while percentage linearity (%r2) C.O.D was 98.24%. R.S.D.% for the repeatability (n=6) was <1% for determination of iron(III) with concentration 4 and 8 mmol.L-1. The method was applied successfully for the determination of iron(III) in pharmaceutical preparations. Using paired t-test between the newly developed method and official method; shows that there were no significant differences between either methods. On this basis the new method can be accepted as an alternative analytical method for determination of iron(III) in pharmaceutical samples.
In this paper, the memorization capability of a multilayer interpolative neural network is exploited to estimate a mobile position based on three angles of arrival. The neural network is trained with ideal angles-position patterns distributed uniformly throughout the region. This approach is compared with two other analytical methods, the average-position method which relies on finding the average position of the vertices of the uncertainty triangular region and the optimal position method which relies on finding the nearest ideal angles-position pattern to the measured angles. Simulation results based on estimations of the mobile position of particles moving along a nonlinear path show that the interpolative neural network approach outperf
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The main parameters and methods influencing the removal of Gentian Violet (GV) dye from aqueous media were investigated using a stachy plant in this study. The surface of the stachy plant was determined using FTIR spectra. Adsorption is influenced by the adsorbent's characteristic groups. The research took into account the usual conditions for GV dye adsorption by the stachy plant, such as the impact of contact time. Mass dosage , after 0.3 g the amount of adsorbed dye declines. Study pH and ionic strength, the results obtained showed that at pH 3 the largest adsorption of (GV) was seen, while at pH 9, the lowest adsorption was observed at 298 K, the adsorption kinetics and equilibrium constants were achieved, and the equilibr
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This study relates to synthesis of bentonite-supported iron/copper nanoparticles through the biosynthesis method using eucalyptus plant leaf extract, which were then named E-Fe/Cu@B-NPs. The synthesised E-Fe/Cu@B-NPs were examined by a set of experiments involving a heterogeneous Fenton-like process that removed direct blue 15 (DB15) dye from wastewater. The resultant E-Fe/Cu@B-NPs were characterised by scanning electron microscopy, Brunauer–Emmet–Teller analysis, zeta potential analysis, Fourier transform infrared spectroscopy and atomic force microscopy. The operating parameters in batch experiments were optimised using Box–Behnken design. These parameters were pH, hydrogen peroxide (H2O2
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Manganese sulfate and Punica granatum plant extract were used to create MnO2 nanoparticles, which were then characterized using techniques like Fourier transform infrared spectroscopy, ultraviolet-visible spectroscopy, atomic force microscopy, X-ray diffraction, transmission electron microscopy, scanning electron microscopy, and energy-dispersive X-ray spectroscopy. The crystal's size was calculated to be 30.94nm by employing the Debye Scherrer equation in X-ray diffraction. MnO2 NPs were shown to be effective in adsorbing M(II) = Co, Ni, and Cu ions, proving that all three metal ions may be removed from water in one go. Ni(II) has a higher adsorption rate throughout the board. Co, Ni, and Cu ion removal efficiencies were 32.79%, 75
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An agricultural waste (walnut shell) was undertaken to remove Cu(II) from aqueous solutions in batch and continuous fluidized bed processes. Walnut shell was found to be effective in batch reaching 75.55% at 20 and 200 rpm, when pH of the solution adjusted to 7. The equilibrium was achieved after 6 h of contacting time. The maximum uptake was 11.94mg/g. The isotherm models indicated that the highest determination coefficient belongs to Langmuir model. Cu (II) uptake process in kinetic rate model followed the pseudo-second-order with determination coefficient of 0.9972. More than 95% of the Cu(II) were adsorbed on the walnut shells within 6 h at optimum agitation speed of 800 rpm. The main functional groups responsible for biosorption of
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