Publication Date: 2019
Iranian Polymer Journal (10261265)28(3)pp. 203-211
A conductive polymer composite (CPC) was designed as a gas sensor for the detection of lung cancer biomarkers. A poly(ether-imide) with aromatic bulky pendant groups was synthesized and used as a CPC transducer by introducing multi-walled carbon nanotubes for the detection of acetone, toluene, methanol, ethanol and water vapor as lung cancer biomarkers. The following trend in CPC response was observed for different vapors: AR (acetone) > AR (toluene) > AR (ethanol) > AR (methanol) > AR (water). The sensing ability of the conductive polymer composite towards the above biomarkers was evaluated based on Hansen solubility parameters of the analytes. The prepared sensitive layer showed a good sensitivity against a wide range of analytes with various polarities. The good sensitivity of designed sensitive layer was attributed to the non-polar –CH3 groups besides the bulky aromatic pendant groups of the as-synthesized polymer. The aromatic pendant groups have established relatively strong attractions with the carbon nanotube (CNT) surfaces leading to the creation of significant active sites in the CNTs’ junctions. As a result of adsorption of the analyte molecules on those active sites, especially at low concentrations, the bulky aromatic groups were found much to improve the sensitivity of the prepared gas detector by affecting the electron tunneling of 3-D nano-conductive filler architecture. The experimental results illustrated that the synthesized CPC has a promising potential as a lung cancer biomarker detector. © 2019, Iran Polymer and Petrochemical Institute.
Publication Date: 2014
Advances in Polymer Technology (07306679)33(S1)
This paper addresses the preparation of polyaniline (PAni) and polypyrrole (PPy) nanostructures as humidity sensor elements. The semicrystalline microstructure and chemical structure of synthesized PAni and PPy were studied by X-ray diffraction and Fourier transform infrared spectroscopy, respectively. The morphology of these polymers was studied by scanning electron microscopy and transmission electron microscopy, indicating fibrillar and tubular nanostructures for PAni and PPy, respectively. The humidity sensing performances of sensors based on the prepared nanostructural PAni and PPy were investigated, and the sensing mechanisms of both systems have been discussed. The interesting reverse behaviors during humidity exposure of PAni- and PPy-based sensors in different water vapor concentrations have been comprehensively justified. The temperature dependency of the electrical conductivity for PAni and PPy samples was investigated. The UV-vis spectroscopy was used to study the effect of moisture on the electronic transport properties of PAni and PPy nanostructures. © 2014 Wiley Periodicals, Inc.
Homayoonfalfini, M.,
Mehrnia, M.R.,
Shariaty-niassar, M.,
Akbari, A.,
Fauzi ismail, A.,
Matsuura, T. Publication Date: 2014
Desalination (0011-9164)354pp. 125-142
The aim of this study is to investigate the effect of the presence and impregnation of iron oxide nanoparticles with the polysulfone membrane matrix. The nanoparticles were synthesized via co-precipitation method and were added to the membrane structure through blending with the polymeric matrix (Blended Nanocomposite Membranes (BNM)), deposition by photopolymerization (PhotoPolymerized Nanocomposite Membranes (PPNM)) and deposition by interfacial polymerization (Interfacially Polymerized Nanocomposite Membranes (IPNM)). FTIR analysis proved the presence of nanoparticles in all of the three types of membranes. According to AFM images, nanoparticles enhance the membrane roughness. On the account of SEM images obtained from the membrane surface, nanocomposite membranes have a more uniform surface compared to neat polymeric membranes. In addition, the cross-sectional SEM images of the membrane revealed that the blending method provides the opportunity of controlling the membrane morphology by means of nanoparticles. Contact angle analysis confirmed the development of nanocomposite membrane hydrophilicity versus neat polymeric membranes. The filtration experiments including permeation flux, dye rejection, and molecular weight cut off were done to compare all of the nanocomposite membranes. The results indicated that the blending method can improve the membrane structural properties and the deposition method can improve their separation yield. © 2014 Elsevier B.V.
Publication Date: 2012
Chemical Engineering Communications (00986445)199(7)pp. 889-911
Coupling energy-intensive endothermic reaction systems with suitable exothermic reactions improves the thermal efficiency of processes and reduces the capital cost of the reactors. In this study, a steady-state heterogeneous model for a novel thermally coupled reactor, containing methanol synthesis reactions and cyclohexane dehydrogenation, was developed. This heat exchanger reactor consists of two fixed beds separated by a wall, where heat is transferred across the surface of the tube from the exothermic into the endothermic side. The co-current mode is investigated, and the simulation results are compared with corresponding data for an industrial methanol fixed bed reactor operated at the same feed conditions. The results show that although methanol productivity in the thermally coupled reactor is not higher than that in the conventional methanol reactor, benzene is also produced as an additional valuable product in a favorable manner, and autothermality is achieved within the reactor. This novel configuration can increase the methanol synthesis temperature at the first part of the reactor for higher process rates and then reduce the temperature at the second part of reactor for increasing thermodynamic equilibrium; those are two key issues in methanol reactor configurations. The influence of inlet temperature, molar flow rate, and shell diameter of the endothermic stream on reactor behavior is investigated. The results suggest that coupling of these reactions in co-current mode could be feasible and beneficial. Experimental proof-of-concept is needed to establish the validity and safe operation of the novel reactor. © Taylor & Francis Group, LLC.
Publication Date: 2010
Chemical Engineering Science (00092509)65(23)pp. 6206-6214
In this research, the conditions at which a thermally coupled reactor - containing the Fischer-Tropsch synthesis reactions and the dehydrogenation of cyclohexane - operates have been optimized using differential evolution (DE) method. The proposed reactor is a heat exchanger reactor consists of two fixed bed of catalysts separated by the tube wall with the ability to transfer the produced heat from the exothermic side to the endothermic side. This system can perform the exothermic Fischer-Tropsch (F-T) reactions and the endothermic reaction of cyclohexane dehydrogenation to benzene simultaneously which can save energy and improve the reactions' thermal efficiency. The objective of the research is to optimize the operating conditions to maximize the gasoline (C5+) production yield in the reactor's outlet as a desired product. The temperature distribution limit along the reactor to prevent the quick deactivation of the catalysts by sintering at both sides has been considered in the optimization process. The optimization results show a desirable progress compared with the conventional single stage reactor. Optimal inlet molar flow rate and inlet temperature of exothermic and endothermic sides and pressure of exothermic side have been calculated within the practicable range of temperature and pressure for both sides. © 2010 Elsevier Ltd.
Publication Date: 2023
Chemical Engineering Journal (1385-8947)451
This study comprehensively compared two hydrothermally synthesized S-scheme heterojunctions, Bi2WO6/g-C3N4 and Bi2WO6/TiO2. The photocatalytic removal of cefixime (CFX) was used to screen the different mass ratios of the components for each heterojunction. Photocatalytic adsorption/degradation and operational effects such as initial pH, the ratio of CFX concentration to the photocatalyst load, light intensity, UV irradiation, and the presence of anions were compared and evaluated. The adsorption isotherms and kinetics of the photocatalytic adsorption and degradation were studied. Furthermore, the band structure was investigated by valence band X-ray photoelectron spectroscopy (VB-XPS), Mott-Schottky plot, and UV–vis DRS. The mechanism of the photocatalytic reaction under visible and UV–vis irradiation was comprehensively investigated by scavenger tests and electron spin resonance (ESR). The photocurrent response, EIS, and linear sweep voltammetry (LSV) results confirmed the photocatalytic enhancement of the heterojunctions. The leaching of metal ions, reusability, and performance of the heterojunctions were investigated for 6 cycles. The photocatalytic degradation pathway of CFX and the toxicity of the by-products were investigated by LC-MS and Toxicity Estimation Software Tool (T.E.S.T). After 135 min of photocatalytic reactions, the TOC removal efficiency of CFX was 94 % and 91 % for Bi2WO6/g-C3N4 and Bi2WO6/TiO2. CFX and the by-products were entirely mineralized after 180 min of the reactions. It was found that the binary heterojunctions and the photocatalytic reactions are green and environmentally friendly. The optimized artificial neural network with 18 neurons simulated the experiments. The trained feed-forward network was able to successfully simulate different operating conditions and different mass ratios of the heterojunctions. © 2022 Elsevier B.V.
Publication Date: 2022
Fluid Phase Equilibria (03783812)561
In this study, the performance of a novel DES, consisting of butane-1,2-diol as the hydrogen bond donor (HBD) and choline chloride as the hydrogen bond acceptor (HBA), was investigated thermodynamically for carbon dioxide absorption. The molar ratio of choline chloride to butane-1,2-diol was 1:4. Carbon dioxide solubilities in this DES were measured experimentally in a high-pressure equilibrium cell. The solubility measurements were carried out in a temperature range of 303.2 to 333.2 K, and pressures up to almost 3.4 MPa. The P-x isotherms showed an almost linear increase of solubility with increasing pressure. Based on the measured experimental data, the values of Henry's constants at very dilute concentrations were calculated, as well as the standard enthalpies, entropies, and Gibbs free energies of dissolution. By analyzing the calculated parameters, it was concluded that the dissolution process is exothermic, and that stronger interactions prevail in the mixture of carbon dioxide and the investigated DES, as compared to the interactions within the neat components. Finally, the Cubic Plus Association (CPA) and Soave-Redlich-Kwong (SRK) equations of state (EoSs) were used to model the experimental solubility data. Absolute average relative deviation percent (AARD%) values of 3.78% and 5.48% for the CPA and SRK EoSs, respectively, indicated good agreement with experimental values for both models. However, the CPA EoS achieved higher accuracy, and with much smaller values of binary interactions parameters, thus indicating the importance of considering association interactions for the accurate modeling of carbon dioxide solubilities in DESs. © 2022
Publication Date: 2025
Journal of Molecular Liquids (18733166)429
Natural gas is a valuable source of energy, however, it also contains hazardous compounds, such as hydrogen sulfide (H2S) acid gas, which needs to be eliminated to make it safe for use. If H2S is released, it can cause serious hazards like environmental issues and human respiratory or even death. Up to now, amine-based solvents have been used for gas sweetening. However, they are not environmentally friendly solvents, so replacing them with green solvents is required. Deep Eutectic Solvents (DESs) are the high-potential candidates of green solvents for this purpose. This study investigated comprehensive thermodynamic modeling of H2S solubilities in a wide range of different nature DESs using two thermodynamic approaches of φ-φ and γ-φ and one chemical absorption approach. The largest and most updated H2S solubility in DESs’ data bank was gathered from open literature including 338 data points for 33 different DESs over a wide range of temperature and pressure. For the investigated approaches, the SRK-SRK, SRK-NRTL, and RETM (1:2) models with the AARD% values of 13.42, 11.64, and 11.21, respectively led to the best results. According to comprehensive investigation and data analysis, general guidelines for using different thermodynamic models for H2S solubility in DESs were proposed. © 2025 Elsevier B.V.
Publication Date: 2013
Chemical Engineering and Processing - Process Intensification (02552701)70pp. 289-291
A one-dimensional model published previously for spouted beds is evaluated. Certain errors exist in the governing equations which are modified and corrected in this Letter to Editor. It is confirmed that this is an efficient model as it needs few number of empirical correlations to solve. © 2013 Elsevier B.V.
Publication Date: 2013
Journal of Analytical and Applied Pyrolysis (01652370)104pp. 707-709
A kinetic model published previously for pyrolysis of tyre in conical spouted beds is evaluated. Certain errors exist in the model constants which are modified and corrected. © 2013 Elsevier B.V. All rights reserved.
Publication Date: 2015
AIChE Journal (00011541)61(9)pp. 3094-3103
A new model, named the crossover-UNIQUAC model, has been proposed based on the crossover procedure for predicting constant-pressure liquid-liquid equilibria (LLE). In this manner, critical fluctuations were incorporated into the classical UNIQUAC equation. Coexistence curves were estimated for systems having a diverse range of asymmetries. These systems included the LLE of five different mixtures, composed of nitrobenzene with one of the members of the alkane homologous family (either pentane, octane, decane, dodecane, or tetradecane), as well as an extra system having a different chemical nature, namely the mixture of n-perfluorohexane and hexane, to further check the validity of the proposed approach. Using these nonideal mixtures, the validity of the new model was investigated within wide ranges, covering near-critical to regions falling far away from the critical point. The graphical trends, as well as the quantitative comparison with experimental data indicated the good agreement of the proposed model results with the experimental data. A maximum AARD% value of 3.97% was obtained in calculating molar compositions by the proposed model for such challenging systems covering noncritical, as well as critical regions. In addition, to show the strength of the proposed crossover approach to describe properties other than LLE, molar heat capacities were investigated for the system of nitrobenzene+dodecane. © 2015 American Institute of Chemical Engineers.
Publication Date: 2013
International Journal of Mineral Processing (03017516)124pp. 58-66
A general model is developed for moving-bed reactors where multiple non-catalytic gas-solid reactions and multiple gas-phase reactions take place. The grain model is adopted and modified as the kinetics model for multiple non-catalytic gas-solid reactions case. The proposed model covers the modified grain model and provides the local degree knowledge of the origin solid reactant along with the intermediate solids within the porous pellets. The heat transfer by convection, conduction and radiation in the gas bulk and the radial temperature distribution of the pellet are considered. The model predictions for solid conversion, gas temperature, and gas concentrations are obtained for an industrial moving-bed reactor for Fe2O3 pellets reduction. This proposed model well simulates the experimental data with an average 1.2% error. © 2013 Elsevier B.V.
Publication Date: 2013
International Journal of Mineral Processing (03017516)124pp. 67-74
The general model developed in the first part of this study is based on the grain model. In order to determine the overlapping range of this kinetic model and the unreacted shrinking core model the attempt is made in this part of the article to identify the simplest and most accurate model. Although under certain circumstances the found results in both the models are almost similar, the developed model based on grain model predicts the experimental data much better than the shrinking core model. The simplicity of the model's results in the outcome is due the predominant diffusional regime. This regime is revealed where the pellet size is big; nevertheless, the results of two models are not similar even in small values of pellet porosity. Two correlations for determining effective diffusivity are tested and it shows a direct effect on the overlapping range of both the models. © 2013 Elsevier B.V.
Publication Date: 2020
Journal of Molecular Liquids (18733166)307
Deep eutectic solvents (DESs) are a recently introduced class of sustainable solvents, being studied by many researchers in various fields. Because of the vast potential applications of DESs, it is necessary to have their physical properties available. Surface tension is an important physical property which has significant effects on permeability and bubbling, and hence in the design of processes. Up to date, there is no general model available in open literature for estimating the surface tension of DESs. In this study, for the first time, a general, simple, easy-to-use, and accurate correlation is proposed for the estimation of the surface tension of DESs at different temperatures. The correlation was developed based on a large data bank, including 553 data points, from 112 DESs having different natures. The model results were investigated by different statistical analyses and it was found that the correlation is not biased and shows normal behavior. The value of calculated overall AARD% of the model is 8.8%. The proposed model was compared to three general surface tension models in the literature and the comparison showed greater reliability and better agreement of the proposed model with respect to other literature models. © 2020 Elsevier B.V.
Publication Date: 2018
Fluid Phase Equilibria (03783812)470pp. 193-202
Deep eutectic solvents (DESs) make up a most-recent category of ‘green’ solvents with a potentially promising future. Insignificant vapor pressure, biodegradability, low cost, task-specific engineering, and high absorption for gases such as CO2 are the most important characteristics of most DESs. To apply DESs in various industries, knowledge of their physical properties is vital. Since the viscosity of a DES is a strong function of temperature, as well as the ratio of the hydrogen bond donating and accepting components, to estimate the viscosity behavior, a model based on sound theory is proposed in this study, i.e., the free volume theory. Since DESs are strongly associating components, this theory is enriched by using associating equations of state, namely CPA and PC-SAFT. In this study, a large density and viscosity databank of 27 DESs of different nature, also with varying molar ratios of the hydrogen bond donor and acceptor, were used to propose the model. In this way, a global model is presented for the first time to estimate the viscosities of DESs. The pseudo-component approach, with a 2B association scheme, was considered for the DESs. Both the CPA and the PC-SAFT EoSs, coupled with the free volume theory, showed reliable results, with average AARD% values in viscosity for all of the investigated DESs equal to 2.7% and 2.7%, respectively. Furthermore, both models reliably showed the trend of nearly logarithmic increase in DES viscosity with decreasing temperature. Also, both models accurately estimated the viscosity behavior of the DESs by not only changing the molecular nature of the hydrogen bond donor with a fixed hydrogen bond acceptor, but also at all of the various molar ratios investigated. © 2017 Elsevier B.V.
Publication Date: 2010
Chinese Journal of Chemical Engineering (10049541)18(4)pp. 642-647
Lubricating mineral base oils are normally extracted from lube-oil cuts with furfural solvent. Aromatic content in the raffinate phase from extraction process is an essential parameter that affects the quality of the lubricating base-oils. For determination of aromatic content by the usual ASTM D3238 method, density, refractive index and molecular weight of the raffinate are required. In this work, a new generalized correlation is developed for determination the aromatic content by using only the measured viscosity of lubricating oil. With a mole fraction of aromatic compounds, the kinematic viscosity may be obtained at any temperature between 60-100 (C along with their molecular weight and refractive index. © 2010 Chemical Industry and Engineering Society of China (CIESC) and Chemical Industry Press (CIP)
Publication Date: 2020
Molecules (14203049)25(7)
Deep eutectic solvents (DESs) are newly introduced green solvents that have attracted much attention regarding fundamentals and applications. Of the problems along the way of replacing a common solvent by a DES, is the lack of information on the thermophysical properties of DESs. This is even more accentuated by considering the dramatically growing number of DESs, being made by the combination of vast numbers of the constituting substances, and at their various molar ratios. The speed of sound is among the properties that can be used to estimate other important thermodynamic properties. In this work, a global and accurate model is proposed and used to estimate the speed of sound in 39 different DESs. This is the first general speed of sound model for DESs. The model does not require any thermodynamic properties other than the critical properties of the DESs, which are themselves calculated by group contribution methods, and in doing so, make the proposed method entirely independent of any experimental data as input. The results indicated that the average absolute relative deviation percentages (AARD%) of this model for 420 experimental data is only 5.4%. Accordingly, based on the achieved results, the proposed model can be used to predict the speeds of sound of DESs. © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Publication Date: 2022
International Journal of Biological Macromolecules (01418130)208pp. 260-274
A Z-scheme Bi2WO6/CNT/TiO2 photocatalyst was synthesized hydrothermally and loaded on chitosan nanofibers with different mass percentages using the electrospinning process. The batch adsorption experiments for chitosan nanofibrous samples containing Bi2WO6/CNT/TiO2 revealed that the adsorption process and its kinetic followed the Langmuir isotherm and pseudo-second-order model, respectively. A planar microreactor with a reusable plate-type configuration was fabricated employing an inexpensive micromachining technique and integrated with chitosan/Bi2WO6/CNT/TiO2 nanofibers. The synergistic effect of the adsorption and photocatalysis was assessed for removing cephalexin under simulated sunlight irradiation in a continuous flow microreactor. The nanofibers containing 15 wt% of Bi2WO6/CNT/TiO2 exhibited the most removal efficiency. The effects of operational variables were investigated in the microreactor and optimized using response surface methodology as light intensity = 17.45 W/m2, retention time = 256 s, pH = 4.8, and initial cephalexin concentration = 29 mg/L. At this condition, cephalexin and TOC removal efficiencies reached 99.2% and 92.4%, respectively. The kinetic of disappearance of cephalexin under optimal conditions followed the Langmuir-Hinshelwood model. The adsorption equilibrium constant deduced from this model was similar to that one calculated from the Langmuir isotherm model. At the optimum condition, cephalexin removal efficiency reduced to 80% after 1500 min of microreactor operation and the nanofibers revealed appropriate stability and reusability. © 2022
Publication Date: 2019
Scientia Iranica (23453605)26(6)pp. 3401-3414
In recent years, biofuels have attracted considerable attention as a renewable and clean source of energy and have been playing the role of suitable alternatives to fossil fuels. One of the most attractive types of biofuels is Acetone-Butanol-Ethanol (ABE), which is produced in a batch fermentation process by the anaerobic bacterium Clostridium acetobutylicum and sugar-based substrate as feedstock. In this paper, the optimization of this process was carried out according to a bi-objective function. A hybrid model of Multi-Objective Differential Evolution (MODE) algorithm and distinguished decision-making methods, namely linear programming technique for multidimensional analysis of preference (LINMAP), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), and Shannon's entropy, were applied to find the final optimal operating point. The initial concentration of substrate and the final operating time of the process were selected as decision variables to maximize the two main objectives in terms of solvent yield and productivity. A Pareto optimal set presents a wide range of optimal operating points, and a proper operating condition can be selected based on the necessities of the applicant. The best optimal point obtained by TOPSIS, according to the lowest value of deviation index, was also compared with the results of the economy-based optimization. (C) 2019 Sharif University of Technology. All rights reserved.
Publication Date: 2023
Neural Computing and Applications (09410643)35(11)pp. 8517-8541
Using a reliable predictive model is important for modeling, controlling, and optimization of the isomerization process. This process has a significant impact on the gasoline quality, which can reduce greenhouse gases by improving the octane number. On the other hand, the accuracy of the predicted results of a data-driven model depends on the quality of input data; this is while the measured variables of industrial units are inevitably contaminated by various errors. Hence, the present work proposes an improved adaptive machine learning model and a new hybrid multiscale filter to predict the gasoline research octane number reliably from error-contaminated data of a light naphtha isomerization reactor. The proposed machine learning model is based on the integration of the feature selection algorithm of the double-level similarity with the support vector regression model (named DLS-SVR model) for adaptive prediction. The new hybrid filter is based on a combination of the wavelet transform and median absolute deviation, named multiscale median absolute deviation (MSMAD). MSMAD filter is proposed with the aim to establish an accurate method to identify and eliminate outliers and gross errors from the measured process variables. A pilot-scale reactor is employed to provide the required experimental validating dataset to evaluate the predictive performance of the proposed filter–model combination. Inputs of the DLS-SVR model are operating conditions (temperature: 115–150 °C, pressure: 28–42 bar, space velocity: 0.38–3 h−1) and feed composition (benzene: 0–3.5 wt%, cyclohexane: 0.8–23.2 wt%, methylcyclopentane: 1–29 wt%, H2/naphtha ratio: 0.03–0.3). The performance of the DLS-SVR model is compared with the response surface methodology, support vector regression, and double-level locally weighted extreme learning machine through the fivefold cross-validation technique. The particle swarm optimization–sequential quadratic programming algorithm is used to optimize the hyper-parameters of these models. The results prove that the generalized DLS-SVR model outperforms the other generalized models. Furthermore, the performance of the MSMAD filter is compared with the multiscale median, finite impulse response–median hybrid, median, and median absolute deviation filters by rectifying the error-contaminated temperature signal. Findings reveal that the DLS-SVR model utilizing the rectified signal by the MSMAD filter has a maximum coefficient of determination, R2 = 0.91, and minimum root mean square error, RMSE = 0.0562, among the other filter's rectified temperature signals. These values for error-free data are R2 = 0.945 and RMSE = 0.0439. © 2022, The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature.
Publication Date: 2021
Chemical Engineering Journal (1385-8947)405
The side reactions play an evident role in the selectivity of propylene in methanol to propylene (MTP) process. Recycling by-products such as C4 and C5 hydrocarbon cuts is an effective way to utilize these hydrocarbons and to improve the propylene selectivity. So, the aim of this study was to present a kinetic model for the MTP process over the H-ZSM-5 (Si/Al = 200) catalyst in the presence of co-reaction of methanol and C4-C5 olefin mixture based on the Langmuir-Hinshelwood theory. This model was established on a comprehensive mechanism including methanol conversion, methylation, cracking, hydrogenation, dehydrogenation, and oligomerization reactions. The Response Surface Methodology based on Central Composite Design was applied to evaluate the impact of C4= (5–16 wt%) and C5= (2–9 wt%) mass fraction, WHSV (1.93–7.73 h−1), and temperature (455–485 °C) on the product distribution. It was found that the co-feeding of C4-C5 olefin mixture with methanol can enhance the propylene selectivity up to 73% by controlling the operating conditions. The excellent agreement between the model prediction and experimental data shows that the proposed kinetic model accurately describes the product distribution, and is applicable to this process. © 2020 Elsevier B.V.
Montazerolghaem, M.,
Rahimi, A.,
Seyedeyn-azad, F. Publication Date: 2014
Chemical Product and Process Modeling (21946159)9(2)pp. 155-164
In this study, Ni-Y and Ce-Y zeolites are prepared using synthesized Na-Y zeolite through solid-state ion-exchange method. The adsorptive desulfurization of a model gasoline containing 194, 116 and 72 ppmw sulfur is evaluated in a batch system under ambient conditions. A dynamic model is established in order to investigate the performance of the adsorption process. The model predictions are compared with the obtained experimental results for thiophene adsorption on Ni-Y and Ce-Y zeolites from model solution containing different concentrations of thiophene, and a good agreement is observed. The model parameters: diffusivity and mass transfer coefficient are estimated by comparing the model predictions and experimental data. © by De Gruyter 2014.
Publication Date: 2013
Drying Technology (15322300)31(3)pp. 295-307
A mathematical model has been developed for unsteady-state operations in spouted bed dryers based on a streamtube concept. This model predicts radial distributions of heat and mass inside the bed using a set of simple plug-flow stream tubes. The model's predicted results for moisture content and air temperature have been compared with the experimental data for drying of green peas in a spouted bed and a good agreement has been observed with a mean relative deviation of 4.4%. When significant radial distributions exist inside the bed, large discrepancies are observed between the streamtube and plug flow models predictions. The discrepancies become wider when lower air temperature and higher air humidity are applied, whereas particle diameter and air flow rate are not effective in a pilot-scale dryer. © 2013 Copyright Taylor and Francis Group, LLC.
Publication Date: 2019
International Journal of Thermal Sciences (12900729)145
Calcium sulfate fouling was determined experimentally in a heat exchanger during liquid–solid fluidized bed with cylindrical particles and forced convective (without particles) heat transfer. Then a model to predict the fouling resistance during the solid–liquid fluidized bed heating system was proposed. According to the proposed model and experimental data, a correlation is presented for the prediction of fouling resistances of calcium sulfate during liquid–solid fluidized bed heating at any time. Finally, the prediction of the presented correlation for performed fouling is compared with measured data. Results show that the absolute average percent relative error between experimental data and those obtained by the proposed model vary between 0.6 and 22.8. © 2019 Elsevier Masson SAS
Publication Date: 2024
Chemical Engineering Research and Design (17443563)212pp. 121-133
Catalytic dehydrogenation of long-chain normal paraffins is the most attractive route for producing of linear alkyl benzene. To make this happen, the radial-flow packed-bed reactors are employed as one of the most efficient currently available technologies. Simplifying assumptions that are sometimes imposed on reactor models to reduce the computational cost may also significantly decrease the accuracy of simulations. Here, it is decided to shed light on this matter by assessing the effect of typical model-simplifying assumptions on simulation results. To this end, one- and two-dimensional semi-homogeneous models are used to simulate an industrial-scale radial-flow packed-bed dehydrogenation reactor under isothermal and adiabatic conditions. Simulations are designed in four 1D isothermal, 1D adiabatic, 2D isothermal, and 2D adiabatic modes to compare different modeling strategies and investigate the effect of flow distribution on the reactor performance. An appropriate LHHW kinetics model is considered for paraffin dehydrogenation and the main associated side reactions over a commercial Pt-Sn-K-Mg/γ-Al2O3 catalyst. The model equations are solved numerically using the finite element method by COMSOL Multiphysics CFD software. The results show a 1–3 % discrepancy between the predictions of one- and two-dimensional models for feed conversion under isothermal and adiabatic conditions. In contrast, the comparison of isothermal and adiabatic results for each one- and two-dimensional models indicate a discrepancy of 33–36 %. Furthermore, the two-dimensional model shows a low non-uniformity in flow distribution under reaction conditions (∼ 0.175), which has a trivial negative effect on paraffin conversion. © 2024 Institution of Chemical Engineers
Tamimzadeh, A.,
Dodelehband, A.,
Gordanshekan, A.,
Arabian, S.,
Farahmand, R.,
Farhadian, M.,
Solaimany nazar a.r., A.R.,
Tangestaninejad, S. Publication Date: 2025
Advanced Powder Technology (15685527)36(8)
Bi2WO6/TiO2/ZIF-8 photocatalytic degradation and antibacterial toxicity of degraded methylene blue were studied in this paper. The optimum mass ratio of ZIF-8 to Bi2WO6/TiO2 was determined via comprehensive investigation through photocatalytic experiments, and morphological, structural, and photoelectrochemical characterizations. Operating conditions like initial pH, photocatalyst dosage, initial pollutant concentration, and light intensity were examined. The results were modeled by artificial neural networks, and optimization of operating conditions was performed by a genetic algorithm (GA). The GA optimized a cost function expressed as the ratio of the catalyst consumed to the pollutant degraded (mg/g). This optimization computed optimum conditions as pH of 8.41, photocatalyst dosage of 0.05 g/L, dye concentration of 50 ppm, and light intensity of ∼ 580 W/m2 for 99.9 % removal efficiency at 360 min. Experimentally, 935 mg/g removal with ¬93.5 % removal efficiency was obtained. To study the toxicity of degraded solution, LC-MS analysis coupled with density functional theory and quantitative-structure activity relationship indicated that by-products became more toxic than the initial contaminant, representing the necessity of complete removal of the organic dye before releasing to the environment. Gram-positive (Staphylococcus aureus) and gram-negative (Klebsiella pneumoniae) bacteria were determined, and the minimum inhibitory concentration was not achieved for the degraded solution. © 2025 The Society of Powder Technology Japan
