Iranian Journal of Chemical Engineering (IJChE)

Abstract In this study, the process of capturing CO₂ by using an aqueous MDEA solution under the operating conditions of the concentration range of 10-98 wt% of MDEA, temperature range of 303-323K and atmospheric pressure is investigated. Most researchers have measured the effect of pressure changes on the loading, but in this work, we have investigated the effect of changing the concentration of amine on the loading. We employed the apparatus introduced by Pahlavanzadeh et al. to evaluate the solubility of carbon dioxide in the aqueous solutions of N-methyldiethanolamine (MDEA). The results indicate that the maximum absorption of CO₂ takes place in concentration of between 40-50 wt% of MDEA. Subsequently, the Cubic-Two-State Equation of State (CTS EoS) was improved and used to describe the solubility of CO₂ in aqueous MDEA solutions in a wide range of concentrations and temperatures. This equation, referred to as CTS^DH, includes three terms relating to the different intermolecular interactions happening in electrolyte solutions. The same EoS was used for vapor and liquid phases. Model parameters were adjusted according to the experimental results of this work and other researches. Using the adjustable parameters from this work, the model successfully approximated CO₂ loading under a wide range of functional conditions. The evaluation of model results with experimental data showed the average absolute percent deviation (AAD%) to be 7.05%, indicating a satisfactory alignment between model predictions and Measured results.

Abstract The design of installations in the chemical industry requires knowledge of the thermodynamic properties of liquid mixtures. In the absence of experimental data, accurate predictive methods are needed. In this work, the refractive index and the surface tension are experimentally determined at different temperatures and atmospheric pressure, for the binary and ternary systems of benzyl alcohol, n-hexanol and water, less studied in the literature. Two models were developed for the correlation of excess surface tension with composition, normalized temperature and refractive index. The statistical processing of the experimental data with the multiple linear regression method allowed the development of a model for which, in the validation stage, the correlation coefficient was 0.9086 and the standard deviation was 4.36. With the best performing neural model, a correlation coefficient of 0.9727 and a standard deviation of 2.14 were obtained in the validation stage.

Abstract One of the methods to reduce the particle size is the GAS method. In this method, the solute and antisolvent should be dissolved well in a solvent. But the solute is not dissolved in a solvent. The aim of studying this model is to determine the phase equilibrium and thermodynamic conditions of (CO₂, solvent, 5-Fluorouracil) in the GAS process. The solvents include methanol, ethanol, acetone, 1-propanol, and 1-butanol. The Peng-Robinson equation of state with a linear combination of Vidal and Michelsen mixing rules (PR-LCVM) was used for the thermodynamic modeling. The volume expansion of the binary system (CO₂, solvent) and ternary system (CO₂, solvent,5-Fluorouracil) at the temperature range of 313.15-319.15 K was investigated. The P_min values for the binary system were 66.7, 69.6, 60, 73.7, and 76.8 bar respectively for methanol, ethanol, acetone, 1-propanol, and 1-butanol at 313.15 K,. The P_min for the ternary system was also calculated. The comparison between the P_min values of binary and ternary systems showed that for a constant temperature and a certain solvent, the calculated minimum pressure in the ternary system was greater than the same in the binary system

Abstract In the present investigation, the physicochemical parameters of dyeing woolen yarn with the CI Acid Red 1 dye in terms of the kinetics and thermodynamic of adsorption were studied. Different models (Zero order, First order, Second order, Parabolic, Cegarra–Puente and modified Cegarra–Puente models) were employed to discover a suitable dyeing apparatus. It was found that the modified Cegarra-Puente model best fitted to the investigational data with the maximum correlation (R² ≥ 0.99). The dyeing-rate constant, half dyeing times, rise time and fixation time were then calculated. Thermodynamic parameters, for instance the Gibbs free energy (∆G^#), enthalpy (∆H^#), entropy (∆S^#), and the activation energy (E_a), were considered. The thermodynamic parameters imply that the dying procedure could be improved by increasing the system temperature. Also, dyeing woolen yarns with CI Acid Red 1 decreases randomness and enhances the order of reaction systems by immobilizing dye molecules onto the solid fiber surface

Abstract The Dry Reforming of Methane, which uses methane and carbon dioxide, the two greenhouse gasses, to produce synthesis gas, has received considerable attention recently. In this work, the equilibrium conversion that is the maximum possible conversion has been obtained experimentally and theoretically. The equilibrium concentration for the Dry Reforming of Methane (DRM) has been calculated using Thermodynamic equilibrium and compared with the experimental equilibrium concentration. The reaction coordinate (ε), Gibbs free energy (G), reaction equilibrium constant (K), and reaction stoichiometric coefficients are used for the calculation of the reaction progress and the equilibrium composition in DRM at different temperatures. These parameters have been calculated by two primary methods, direct and Lagrange, and compared with an empirical equilibrium that has been revealed by the activity test on Ni/Al₂O₃ catalyst. The result shows that none of those can’t make an exact determination of empirical equilibrium compositions, but there was a relatively good agreement between the Lagrange method and the empirical equilibrium. No significant difference has been observed between these methods and empirical conditions at high temperature.

Abstract Considering the high number of ionic liquids (ILs) and impracticability of laboratory measurements for all ILs’ properties, applying theoretical methods to predict the properties of this large family can be very helpful. In the present research, ILs’ thermophysical properties are predicted by a combination of statistical associating fluid theory and group contribution concept (SAFT-γ GC EoS). The studied ionic liquids are 1-ethyl-3-methylimidazolium trifluoromethanesulfonate ([emim][CF3SO3]), 1-butyl-3-methylimidazolium trifluoromethanesulfonate ([bmim][CF3SO3]), 1,3-dimethylimidazolium methylsulfate ([mmim][MeSO4]), 1-ethyl-3-methylimidazolium methylsulfate ([emim][MeSO4]), 1-butyl-3-methylimidazolium methylsulfate ([bmim][MeSO4]), 1-ethyl-3-methylimidazolium methanesulfonate ([emim][MeSO3]) and 1-ethyl-3-methylimidazolium ethylsulfate ([emim][EtSO4]). The thermophysical properties including coefficient of thermal expansion, coefficient of thermal pressure, coefficient of isentropic compressibility, coefficient of isothermal compressibility, speed of sound, isochoric and isobaric heat capacities are estimated within broad ranges of pressure and temperature (0.1-60 MPa and 273-413 K). The comparison among the SAFT-γ predictions and some available experimental data show good ability of SAFT-γ EoS to estimate the ILs’ second-order derivative thermophysical properties.

Abstract Two main objectives have been considered in this paper: providing a good model to predict the critical temperature and pressure of binary hydrocarbon mixtures, and comparing the efficiency of the artificial neural network algorithms and the support vector regression as two commonly used soft computing methods. In order to have a fair comparison and to achieve the highest efficiency, a comprehensive search method is used in neural network modeling, and a particle swram optimization algorithm for SVM modeling. To compare the accuracy of the models, various criteria such as ARD, MAE, MSE, RAE and R2 are used. The simulation results show that the ARD for the prediction of the true critical temperature and pressure of the binary hydrocarbon mixtures for the final optimized ANN-based model is equal to 0.0161 and 0.0387, respectively. The corressponding ARD value for the SVM-based model is equal to 0.0086 and 0.0091 for critical temperature and pressure, respectively. Simulation results show that although both models have a very high predictive accuracy, the SVM has higher learning speed and accuracy than ANN.

Abstract In this study, an Eulerian-Eulerian multi-fluid model (MFM) was used to simulate the segregation pattern of a conical fluidized bed containing ternary mixtures of equidensity TiO2‌ particles. Experimental 'freeze–sieving' method was employed to determine the axial mass fraction profiles of the different-sized particles, and validate the simulation results. The profiles of mass fraction for large, medium and small sized particles along the bed height during the simulation time indicated that the particles’ segregation can be predicted by CFD model. Effect of superficial gas velocity on segregation pattern was also investigated. It was shown that for U0=1.2Umf, partial segregation of large particles occurred, while for U0=1.6Umf, small and medium size particles also segregated and full segregation was achieved. By increasing U0 to 2Umf, mixing of different sized particles was increased and particles segregation was reduced. Therefore, it can be concluded that there was a critical velocity below which particles would segregate while above which their mixing increased.

Abstract Solubility data of solid in aqueous and different organic solvents are very important physicochemical properties considered in the design of the industrial processes and the theoretical studies. In this study, experimental solubility data of 666 pharmaceutical compounds in water and 712 pharmaceutical compounds in organic solvents were collected from different sources. Three different artificial neural networks including multilayer perceptron, radial basis function and support vector machine were constructed to predict the solubility of these different pharmaceutical compounds in water and different solvents. Molecular weight, melting point, temperature and the number of each functional group in the pharmaceutical compound and organic solvents were selected as the input variables of these three different neural network models. The neural network predictions were compared with the experimental data and the SVR-PSO model with the Average Absolute Relative Deviation equal to 0.0166 for the solubility in water and 0.0707 for solubility in organic compounds was selected as the most accurate model.

Abstract In the present research, three different architectures were investigated to predict the coefficients of the Daubert and Danner equation for calculation of saturated liquid density. The first architecture with 4 network input parameters including critical temperature, critical pressure, critical volume and molecular weight, the second architecture with 6 network input parameters including the ones in the first architecture with acentric factor and compressibility factor. The third architecture contains 12 network input parameters including 6 input parameters of the second architecture and 6 structural functional groups of different hydrocarbons. The three different architectures were trained and tested with the 160 sets of Daubert and Danner coefficients gathered from the literature. The trained neural networks were also applied to 15 un-known hydrocarbons and the outputs (Daubert and Danner coefficients) were used to predict the saturated liquid densities. The calculated liquid densities were compared with the experimental values. The Results indicated that the coefficients obtained from the second architecture produced more precise values for the liquid densities of the 15 selected hydrocarbons.

Abstract Varnish and sludge formation are considered as one of the most common problems in lubrication and hydraulic systems. In order to simulate the condition of sludge formation, base stock lubricant (Group 1 API) has been selected and exposed to heat in a laboratory setup. Sludge formation process accelerated in the laboratory scale and solid liquid equilibrium data were extracted. Then solid-liquid equilibrium has been modeled using SAFT equation of state through sludge formation. The results for prediction of sludge formation showed that the absolute average deviations between experimental and theoretical results were less than 1.4%. The calculated results for solubility coefficient of the oxidation byproducts from SN100 (solvent neutral Group I) base stock in fresh (un-oxidized) oil were in good agreement with the experimental data, and average deviation between calculated and experimental data was less than 6.5%. The amount obtained for binary interaction parameter K_ij was – 0.0447. It is shown that SAFT equation of state has the capability of solid liquid equilibrium.

Abstract Guanidine hydrochloride has been widely used in the initial recovery steps of active protein from the inclusion bodies in aqueous two-phase system (ATPS). The knowledge of the guanidine hydrochloride effects on the liquid-liquid equilibrium (LLE) phase diagram behavior is still inadequate and no comprehensive theory exists for the prediction of the experimental trends. Therefore the effect the guanidine hydrochloride on the phase behavior of PEG4000+ potassium phosphate+ water system at different guanidine hydrochloride concentrations and pH was investigated in this study. To fill the theoretical gaps, the typical of support vector machines was applied to the k-nearest neighbor method in order to develop a regression model to predict the LLE equilibrium of guanidine hydrochloride in the above mentioned system. Its advantage is its simplicity and good performance, with the disadvantage of an increase the execution time. The results of our method are quite promising: they were clearly better than those obtained by well-established methods such as Support Vector Machines, k-Nearest Neighbour and Random Forest. It is shown that the obtained results are more adequate than those provided by other common machine learning algorithms.

Abstract A Laser Induced Fluorescence technique (LIF) has been used to study the mixing behavior of two emerging streams in a T-Type mixing chamber. A mixing index on the basis of digital image light intensities is calculated. It has been shown that averaging over more than 800 images leads to a stable mixing index calculation. Moreover, the effect of equal and un-equal flow rates on the mixing behavior of the streams has been studied. The results show that the histograms of the light intensity changes from double peak (unmixed) to a single peak (mixed) at high elevations of the chamber. Mixing index has a linear descending behavior moving toward the cell front wall and it was shown that the mixing index can be reduced up to 50% moving from cell center to near wall region. Moreover, there is a transition zone in both equal and un-equal fluid flow rates in mixing index. It was shown that the third component velocity play an important role in mixing behavior in T-Type mixing chamber.

Abstract In this study a developed model has been used to evaluate the paper drying process and examine the pocket dryer conditions of a multi-cylinder fluting paper machine. The model has been developed based on the mass and energy balance relationships in which the heat of sorption and its variations with paper temperature and humidity changes have been taken into account. The applied model can be used to compute the drying parameters and analyze the pocket drying conditions. Furthermore, the effects of web tension on the heat transfer have been investigated. In the available operating range of the web tension, the overall mean heat transfer coefficient will be within 300-550 W/m2.K. The pocket air temperature was between 50 and 90 oC. The dew point temperature wasn’t close to the pocket air temperature and dew drop never happened during the dryer section. Based on the modeling result and using a novel technique, the maximum level for the exhaust air in the studied machine can be estimated to be 0.2 kg H2O/kg dry air. Result shows that increasing the exhaust humidity to the optimal level will lead to 4% reduction in the required energy and 20% rise in the heat recovery potential. Accordingly the specific heat consumption per evaporated water for the studied drying section can be reduced from 3.96 to 3.81 GJ per ton water.

Abstract By using response surface methodology, Batch shaking biosorption of cobalt (II) experiments were conducted in order to examine the combined effects of operating parameters. The results indicate that magnesium nitrate performed as an effective biosorbent surface modifier, which increases the rate of adsorption capacity. At optimal conditions (initial pH 7.0, temperature 45◦C, biosorbent concentration 0.1 g/100ml, and initial cobalt concentration 300mg/l for Mg-treated biomass) the biosorption capacity of the algae for cobalt was found to be 80.55 mg/g. The Langmuir and Freundlich isotherms were applied to the equilibrium data. The results are best fitted by the Freundlich model. Evaluation of the experimental data in terms of biosorption dynamics showed that the biosorption of cobalt (II) onto algal biomass followed the pseudo-second-order dynamics well. Using the thermodynamic equilibrium coefficients obtained at different temperatures, the thermodynamic parameters (ΔG◦, ΔH◦ and ΔS◦) were also evaluated.

Abstract In this work, the surface tension (σ ) of aqueous solutions of PEGs (poly ethylene glycol) with molecular weights of 200, 300 and 6000 in water, and poly (propylene glycol) (PPG) with a molecular weight of 2000 in ethanol, were measured in the (293.2-338.2) K temperature range and atmospheric pressure. The results of the measurements were modeled by an Artificial Neural Network(ANN) with input of mass fraction of polymer and solution temperature. The predictions of the artificial neural network model fit the experimental data perfectly.

Abstract In this paper, the thermal properties including molar heat capacity, CP, thermal conductivity, λ, and thermal diffusivity, αD, of the pure physical solvents sulfolane (SFL), N,N-dimethylformamide (DMF), dimethylsulfoxide (DMSO), ethylene glycol
(ETG), choloroform (CCL3H), acetonitrile (CH3CN), and pure chemical solvents monoethanolamine (MEA), diethanolamine (DEA), triethanolamine (TEA), methyldiethanolamine (MDEA), 2-amino-2-methyl-1-propanol (AMP) which all are extensively used in natural gas refinery processes were measured at temperatures ranging from (303.15 to 353.15) K and atmospheric pressure. All experimental measurements were carried out by using a PSL Systemtechnik instrument in which
transient hot-wire method was employed to measure transport properties, λ and αD. All obtained data were correlated by using empirical linear temperature function with a very good correlation coefficient, better than R2 = 0.99. Among the solvents tested in this paper, except for TEA, the thermal diffusivity decreased by increasing temperature and also except for TEA and ETG, thermal conductivity decreased with temperature.

Abstract In this work a simplified model based on perturbation theory is presented for prediction of activity coefficient of amino acids and electrolytes in aqueous electrolyte solution. In comparison with previous works, in this model a new hard sphere equation of state has been utilized as a reference term while other interactions such as charge-charge, charge-dipole, dipole-dipole and dipole-induced dipole have been considered as perturbation terms. For simplification, solvent has been considered as dielectric continuum. Finally, aqueous electrolyte solutions containing amino acids have been modeled just using two adjustable parameters. The results have been compared with similar models and it is shown that new hard spheres equation of state shows an improvement in accuracy of the model.

Abstract In direct molecular dynamics simulations (MD) of inhomogeneous systems the density is distributed across the interface and, as a result, the conventional long range corrections cannot be used for these systems. In this work, to correct the results of MD simulations for vapor-liquid equilibrium of methane, we have used the slab based corrections to the direction perpendicular to the interface(z-direction) of the force affecting on each particle. All the particles in each slab are considered to have the same coordinate in the z-direction. The density profiles from preliminary simulations with large cut-off distance values were used for the calculation of long range correction terms. New sets of simulation runs, including long range corrections, were then executed with smaller values of cut-off distance. By employing this approach, more accurate results by the cut-off radiusRc=2.5σ in comparison with those produced with the cut-off distance Rc=5.5σ without applying the long range corrections, are observed for the values of the coexisting densities and the surface tension.

Abstract Dielectric constant measurements were made on binary mixtures of ethyl acetate (EA) and butyl acetate (BA) with the two amyl alcohols (iso-amyl alcohol (IAA) and tert-butyl alcohol (TBA)) for various concentrations at T = 298.2 K and in a frequency of 100 kHz. In order to obtain valuable information about heterogeneous interaction (interactions between the unlike molecules), the Kirkwood correlation factor, the Bruggeman dielectric factor and the excess permittivity were calculated.

Abstract In this work, a new thermodynamic model based on the perturbation theory is presented. A new hard spheres equation of state as a reference term is applied to correlate the activity coefficient of amino acids and peptides in binary aqueous
solutions. The new hard sphere equation of state has been recently proposed by Dehghani and Modarress [11] and has been applied for different theories and showed excellent capability. In this model dipole-dipole and Lennard-Jones interactions are considered. The results have been compared with similar models and it is shown that application of the new hard spheres equation of state has caused an improvement in the results of perturbation model.

Abstract This work deals with estimation of temperature dependent binary interaction parameters (k ij) for binary systems containing CO 2 using the Soave-Redlich-Kwong equation of state with a group contribution method. In this paper six groups, namely CH 3, CH 2, CH, CH 4 (methane), C2H 6 (ethane), and CO 2 (carbon dioxide) are defined and their relevant values of group interaction parameters are optimized. Using this method, it is possible to estimate the k ij of any mixture containing carbon dioxide and hydrocarbons at any temperature along the coexistence curve. The results obtained in
this study are, in most cases, accurate.

Abstract An experimental study of the phase inversion phenomenon was carried out in a rotating disc contactor (9.3 cm diameter). The effect of energy input via agitation and physical properties of the liquids upon inversion holdup and also delay time (time of inversion) was investigated at the constant input flow rate of the dispersed phase under no mass transfer conditions. Water was chosen as the continuous phase, and it was kept stagnant inside the column. The critical dispersed phase holdup was found to be decreased by increasing the energy input via agitation. It was observed that the lower
both the interfacial tension and the density difference of two phases, the greater the resistance of the system to inversion. Moreover, a reduction in delay time was observed by increasing the energy input via agitation.

Abstract The effect of cobalt naphthenate and 2-benzoylbenzoic acid on UV-photooxidative degradation of low density polyethylene have been studied. Sheets of these samples were prepared from polyethylene and different concentrations of cobalt naphthenate and 2-benzoylbenzoic acid then these samples were UV-irradiated. Changes in the carbonyl index, tensile strength, elongation at break, crystallinity and density were measured to monitor the degradation. The measurements were done before and after UV-irradiation at every 30-day interval for 90 days. The results show that the UV-irradiation affects the rate of degradation of LDPE with increasing the concentration of the cobalt naphthenate and 2-benzoylbenzoic acid. The increasing rate of degradation is more obvious for the increased concentration of cobalt naphthenate and also the time of irradiation, but the rate of degradation is decreased by incorporation of 2-benzoylbenzoic acid.

Abstract In this work, the ability of different mixing rules for the prediction of hydrate formation pressure are compared. For this purpose, by using Van der Waals–Plauteeuw model for solid hydrate phase and PR equation of state for calculation of fugasity of components in gas and liquid phases, the pressure of hydrate formation in different mixtures has been calculated by four different mixing rules: Van der Waals, Danesh, GNQ and Wong-Sandler, then by comparison of the calculated results with experimental data, the accuracy of the mixing rules were determined. Studied systems contain binary mixtures CH4, C2H 6, C3H 8, i-C4H 10, CO 2, and H 2S with water in hydrate forming conditions. The interaction parameters in each mixture have been optimized by using two phase equilibrium data W(V L ) and then the optimized parameters have been used for three phase equilibrium W(V L H ) calculations. Comparison of the calculated
pressure of hydrate forming with experimental pressure shows that for most mixtures in the studied temperature and pressure ranges, the GNQ mixing rule with an average percent of error 6% has more accuracy than the three other mixing rules: Van der Waals, Danesh and WS. According to the obtained results for methane equilibrium concentrations in liquid phase, it seems that Danesh mixing rule is more efficient for the prediction the mole concentrations of components. Since Danesh rule considers the polarity of the water molecule, it has greater precision in predicting the equilibrium fractions.