Chemical Engineering
Mohammadreza Khosravi-Nikou; Ahmad Shariati; Mohammad Mohammadian; Ali Barati; Adel Najafi-Marghmaleki
Abstract
This study presents a robust and rigorous method based on intelligent models, namely radial basis function networks optimized by particle swarm optimization (PSO-RBF), multilayer perceptron neural networks (MLP-NNs), and adaptive neuro-fuzzy inference system optimized by particle swarm optimization methods ...
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This study presents a robust and rigorous method based on intelligent models, namely radial basis function networks optimized by particle swarm optimization (PSO-RBF), multilayer perceptron neural networks (MLP-NNs), and adaptive neuro-fuzzy inference system optimized by particle swarm optimization methods (PSO-ANFIS), for predicting the equilibrium and kinetics of the adsorption of sulfur and nitrogen containing compounds from a liquid hydrocarbon model fuel on mesoporous materials. All the models were evaluated by the statistical and graphical methods. The predictions of the models were also compared with different kinetics and equilibrium models. The results showed that although all the models lead to accurate results, the PSO-ANFIS model represented the most reliable and dependable predictions with the correlation coefficient (R2) of 0.99992 and average absolute relative deviation (AARD) of 0.039%. The developed models are also able to predict the experimental data with better precision and reliability compared to literature models.
Sina Rashidi; Mohammad Reza Khosravi Nikou; Bagher Anvaripour; Touba Hamoule
Abstract
The performance of MSU-S and its forms modified with phosphotungstic acid (HPW) and nickel (Ni) for the desulfurization and denitrogenation of model diesel fuel were studied. According to the results of the characteristic tests (N2 adsorption-desorption, XRD, SEM, and NH3-TPD), heteropoly acid incorporation ...
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The performance of MSU-S and its forms modified with phosphotungstic acid (HPW) and nickel (Ni) for the desulfurization and denitrogenation of model diesel fuel were studied. According to the results of the characteristic tests (N2 adsorption-desorption, XRD, SEM, and NH3-TPD), heteropoly acid incorporation causes higher acidity along with a negligible loss of structural aspects, while Ni impregnation leaves a drastic negative effect on mesoporous structure, crystalline phase, and particle shape along with a positive impact on surface acidity. With both modifications (HPW and Ni), the maximum increase of 33.18% and 6.88% was occurred for the adsorption loading of total sulfur and total nitrogen respectively. The adsorption loading and selectivity of all the adsorbents for total nitrogen were slightly more than those for total sulfur (the selective adsorption of nitrogen over sulfur). The pseudo-second order model can best fit the kinetics data and Freundlich model can best describe the equilibrium isotherm for all the species over Ni/HPW-MSU-S.