Iranian Journal of Chemical Engineering (IJChE)

Abstract Most of the reactions that occur in microreactors take place on the surface, so it is important to keep the reactants close to the reactive wall. One effective technique in this field is the single-phase hydrodynamic focusing. However, this method has a drawback: a high percentage of reactants penetrate into the sheath fluid. To address this issue, the concept of the two-phase hydrodynamic focusing is introduced in this study. The main idea is to use a highly viscous sheath fluid to create a barrier against reactant penetration into the sheath flow. To demonstrate the effectiveness of this method, a 3D numerical simulation was performed with an irreversible second-order reaction. The results show that the two-phase hydrodynamic focusing increases reaction rates, particularly in downstream regions where the Sherwood number can increase by several orders of magnitude with the use of a highly viscous sheath of liquids. Additionally, it was observed that the use of the two-phase hydrodynamic focusing improves the efficiency, which is defined as the ratio of the solute in the sample flow to the total solute in each cross-section..

Abstract Time-consuming and costly experiments to measure the cetane number (CN) of biodiesel make computations even more valuable. In the current study, two artificial intelligence (AI) models have been used to predict the biodiesel CN by using comprehensive datasets (440 datasets). They were the gradient-based artificial neural network (GB-ANN) and the multi-layer-perceptron ANN optimized by the genetic algorithm (GA-ANN) for the first time. The three input variablesof the model for predicting the target variable of the biodiesel CN are the average number of carbon atoms, average number of double bonds, and average molecular weight of the fatty acid methyl esters. The learning function, transfer function, number of hidden layers, and number of neurons in the hidden layers are some of the optimized parameters in the current AI-models. The developed models were compared using statistical criteria such as the coefficient of determination (R²), mean square error (MSE), average absolute relative deviation (AARD), standard deviation (STD) and mean absolute percentage error (MAPE). The resulting outcomes revealed that the highest R² and the lowest MSE were related to the GB-ANN model with two hidden layers, trainbfg learning method and logsig-tansig-purelin transfer function. The R² and MSE for the optimized model are equal to 0.9296 and 0.0005 respectively. Although the GA-ANN achieved acceptable outcomes, its statistical analyses produced weaker outcomes than the AI-model based on GB-ANN.

Abstract A low cost and environmentally friendly process for the synthesis of the disodium salt of hydroquinone (DSH) is presented. This novel synthesis technique employs water as solvent. Compared to the well-established synthesis techniques which utilize methanol, the presented technique is safer and environmentally friendly. First, a DSH sample is synthesized using the customary synthesis technique by employing methanol as solvent. Then, the technique introduced in this study is implemented under three different scenarios differing in the way the drying step is performed. The resulting DSH powders are then compared using FTIR  analyses. It is shown that all the synthesis techniques yield acceptable results, However, drying at higher temperatures yield better results. Furthermore, the crystal structure of the DSH sample is investigated using an XRD analysis and compared to the simulated diffraction pattern of DSH. The results indicate the correct synthesis of DSH. Finally, a DSC-TGA test is performed to further confirm the correct synthesis of DSH.

Abstract In this research, the methods of oxidation, oxidation along with carbon nanotubes and surface absorption of carbon nanotubes were investigated to remove the drug substance of cefixime from aqueous solutions. In these methods, the removal percentage of cefixime was 78%, 96% and 70% respectively. Therefore, the results showed that oxidation with carbon nanotubes had a positive effect on the removal of cefixime. For this reason, oxidation along with carbon nanotubes was used to remove the cefixime. Next, different operating parameters such as the concentration of drug pollutants (20,30,40 and 55ppm), reaction time (5,10,15,20,25 and 30 min), concentration of hydrogen peroxide (1, 3 and 5ml) and amount of carbon nanotubes (0.05, 0.01 and 0.2 g/l) were studied in the removal process of cefixime using the method of  oxidation along with carbon nanotubes. It should be noted that in all experiments, certain amounts of carbon nanotubes and the oxidizing agent of hydrogen peroxide were used. In addition, a mixer, with a given round, was used to mix the materials. The maximum removal efficiency of cefixime from aqueous solutions is about 96% , which is related to the process of the removal of cefixime at the constant concentration of 55 mg/L by 0.1 g/L of carbon nanotubes and 5ml of hydrogen peroxide at the  t = 30 min.

Abstract In this paper, modeling approaches were given for explaining mass transfer during solid-liquid extraction in continuous fixed, expanded, and fluidized-bed extractors. The first approach utilizes a differential mass balance-based model, focusing on the differential mass conservation within an element of fixed and expanded-bed columns. The second approach employs a model by applying a mass balance concept to a control volume of the fluidized-bed column. The differential mass balance method segments the column into well-mixed stages, with the fluid flowing axially in an ideal plug flow regime. The solute diffusion inside the porous particles is modeled using Fick's second law of diffusion. Modeling parameters like the effective diffusivity and equilibrium concentration were estimated using the batch extraction experiments. These models were developed and validated using experimental column data involving the extraction of potassium bicarbonate from polyamide 6 pellets with distilled water as the solvent. The modeling results show a good agreement with experimental data.

Abstract Polymer chains- tethered membranes exhibited a technic to improve membrane surface, and can be commonly used to change the inherent surface physico-chemical properties of materials. So, the grafting of poly(methyl methacrylate) (PMMA) chains onto poly(vinylidene fluoride) (PVDF) substrate was carried out via surface initiated atom transfer radical polymerization (SI-ATRP) at room temperature. Surface coverage and grafting density were controlled by adjusting the  concentration of the initiator. The attenuated total reflection Fourier transform infrared spectroscopy (ATR-FTIR) and thermogravimetric analysis (TGA) results indicated that the PMMA brush was successfully synthesized on the substrates. The study examined the alterations in the physical characteristics of a the PVDF membrane modified with polymer brushes using the scanning electron microscopy. The results showed that PMMA brushes were attached not only to the outer surface of the membrane but also to the surfaces of its pores. Results from the atomic force microscopy and water contact angle measurements confirmed the homogeneous grafting of PMMA chains onto the substrate.