Ali Tarjomannejad - Academia.edu (original) (raw)

Papers by Ali Tarjomannejad

Process of converting methanol to propylene is influenced by many parameters. The use of smart te... more Process of converting methanol to propylene is influenced by many parameters. The use of smart techniques can be an effective way to investigate variable parameters and finding optimal conditions. In this work, optimal design of ZSM-5 catalysts with different combinations of templates and operating conditions in methanol to propylene process was performed using response surface methodology and hybrid artificial neural network-genetic algorithm method. Objective functions for optimization were methanol conversion and propylene selectivity. Effects of different variables in the dual-responses system, including molar ratios of tetra propyl ammonium bromide (TPABr), Cetyltrimethylammonium bromide (CTAB), and Pluronic F127, as well as weight hourly space velocity of feed and process temperature on the performance of catalysts, were studied both experimentally and theoretically. Modeling results showed that the designed neural network structure for the process had superior accuracy compar...

Iranian Institute of Research and Development in Chemical Industries (IRDCI)-ACECR, Dec 1, 2015

In this paper, vapor pressure for pure compounds is estimated using the Artificial Neural Network... more In this paper, vapor pressure for pure compounds is estimated using the Artificial Neural Networks and a simple Group Contribution Method (ANN-GCM). For model comprehensiveness, materials were chosen from various families. Most of materials are from 12 families. Vapor pressure data of 100 compounds is used to train, validate and test the ANN-GCM model. Vapor pressure data were taken from literature for wide ranges of temperature (68.55-559.15 K). Based on results, the best structure for feed-forward back propagation neural network is Levenberg-Marquardt back propagation training algorithm, logsig transfer function for hidden layer and linear transfer function for output layer. The multiplayer network model consists of temperature, acentric factor, critical temperature, critical pressure and the structure of molecules as inputs, 10 neurons in the hidden layer and one neuron in the output layer corresponding to vapor pressure. The weights are optimized to minimize error between experimental and calculated data. Results show that optimum neural network architecture is able to predict vapor pressure data with an acceptable level. The trained network predicts the vapor pressure data with average relative deviation percent of 1.18%.

Egyptian Journal of Chemistry, 2020

In this paper, the CuCr2O4 spinel catalyst was synthesized by the Pechini method, and its activit... more In this paper, the CuCr2O4 spinel catalyst was synthesized by the Pechini method, and its activity was evaluated in catalytic oxidation of CO. CuCr2O4 spinel catalyst was characterized by XRD, BET, H2-TPR, and SEM. This catalyst has a good ability in CO oxidation. The effects of three synthesis variables (EG/citrate, citrate/nitrate ratio, and calcination temperature) and reaction temperature as an operational variable on CO conversion were investigated. Based on the results, the optimum neural network architecture succeeded to predict CO conversion data with an acceptable level of accuracy. The model predicted that the relative importance of variables is as follows: calcination temperature > citrate/nitrate ratio > EG/citrate ratio. The optimum neural network architecture was used as a fitness function for the genetic algorithm to find the optimum catalyst. Under the optimum condition (EG/citrate: 3.24, citrate/nitrate ratio: 0.62 and calcination temperature: 620 °C), the predicted optimum value of CO conversion was found to be in a good agreement with the corresponding actual value.

Artificial neural networks are a suitable algorithm for modeling of chemical processes .In this s... more Artificial neural networks are a suitable algorithm for modeling of chemical processes .In this study the effective factors of catalysts and also the reaction temperature were used in NO+CO reduction over LaCo0.5B0.5O3 (B=Cr, Cu, Mn) perovskite-type nanocatalysts to introduce a neural network. The network was made of 3 layers. One input layer, one hidden layer and an output layer and its training function was Levenberg-Marquardt. Also the optimum number of neurons in hidden layer was19. The correlation coefficient R2 for all data was equal to 0.9967, which means the values which were obtained from the discussed ANN were in a good agreement with the experimental data.

In this paper, LaMn0.7B0.3O3 (B= Cu and Co) perovskite were synthesized by sol-gel auto combustio... more In this paper, LaMn0.7B0.3O3 (B= Cu and Co) perovskite were synthesized by sol-gel auto combustion method and characterized by X-ray diffraction and scanning electron microscope. Activity of synthesized catalysts were evaluated in catalytic oxidation of CO. XRD results show that the studied perovskites were synthesized in single phase perovskite structure. The activity of catalysts improved due to partial substitution of Mn by Cu cation. T50% of CO conversion over LaMnO3, LaMn0.7Cu0.3O3 and LaMn0.7Co0.3O3 was 145, 85 and 155 oC, respectively. LaMn0.7Cu0.3O3 was the optimum catalyst in catalytic oxidation of CO.

In this paper, LaBO3 perovskite type catalyst formulations were prepared by sol-gel auto combusti... more In this paper, LaBO3 perovskite type catalyst formulations were prepared by sol-gel auto combustion method using citric acid as the fuel. Activity of catalysts was tested in catalytic oxidation of toluene as a model of volatile organic compounds. LaCoO3 perovskite formulation showed the highest activity among LaBO3 (Fe, Mn and Co) perovskite catalysts. So, LaCoO3 perovskite based catalyst was selected for further investigation and modification in order to improve catalytic activity. LaBO3 perovskite catalysts were modified by substitution of Co by Fe and Mn. The catalytic activity of LaCoO3 improved due to partial substitution of Co by Fe and Mn cations. LaCo0.7Mn0.3O3 showed the highest catalytic activity among the synthesized catalysts. The structures and morphology of synthesized perovskites were investigated by X-ray diffraction (XRD) and scanning electron microscopy (SEM) analysis. The results of X-ray diffraction indicated that the LaBO3 and LaCo0.7B′0.3O3 samples obtained usi...

Dry reforming of methane is one of the main ways to produce syngas. A proper Kinetic model was em... more Dry reforming of methane is one of the main ways to produce syngas. A proper Kinetic model was employed for modeling of dry reforming reaction over Ni/Al2O3 in a fixed-bed catalytic reactor. In the simulation of the reactor, a one dimensional model is applied. After modeling and simulation, more than 100 data were obtained, these data used in Artificial Neural Network then a net was made and finally the optimization of H2/CO ratio by Genetic Algorithm was done. The flow rates which optimized by GA was used in the modeling that causes H2/CO ratio about one.

In this paper, catalytic oxidation of CO over the LaFe1-xCuxO3 (x= 0, 0.2, 0.4, 0.6) perovskite-t... more In this paper, catalytic oxidation of CO over the LaFe1-xCuxO3 (x= 0, 0.2, 0.4, 0.6) perovskite-type oxides was investigated. The catalysts were synthesized by sol-gel method and characterized by XRD, BET, FT-IR, H2-TPR and SEM methods. The catalytic activity of catalysts was tested in catalytic oxidation of CO. XRD patterns confirmed the synthesized perovskites to be single-phase perovskite-type oxides. The synthesized perovskite catalysts show high activity in the range of reaction temperature (50 - 300 oC). The substitution of Cu in B-site of the perovskite catalysts enhanced their catalytic activity for CO oxidation. Among different synthesized perovskite catalysts, LaFe0.6Cu0.4O3 has the highest activity: nearly complete elimination of CO was achieved at 275 oC with this catalyst. Kinetic studies for CO oxidation were performed based on power law and Mars-van Krevelen mechanisms. According to kinetic calculations, the most probable mechanism is the MKV-D (dissociative adsorptio...

Third International Conference on Advances in Bio-Informatics and Environmental Engineering - ICABEE 2015, Dec 11, 2015

In this paper, LaMn 0.6 B 0.4 O 3 (B= Cu and Fe) perovskite type mixed oxides were prepared by so... more In this paper, LaMn 0.6 B 0.4 O 3 (B= Cu and Fe) perovskite type mixed oxides were prepared by sol-gel method and characterized by X-ray diffraction and scanning electron microscope. Activity of synthesized catalysts were evaluated in catalytic reduction of NO with CO. XRD results show that the studied perovskites were synthesized in single phase perovskite structure. The activity of catalysts improved due to partial substitution of Mn by B cation. T50% of NO over LaMnO 3 , LaMn 0.6 Cu 0.4 O 3 and LaMn 0.6 Fe 0.4 O 3 was 451, 358 and 366 ºC, respectively. LaMn 0.6 Cu 0.4 O 3 was the optimum catalyst in simultaneous reduction of NO with CO.

Periodica Polytechnica Chemical Engineering, 2019

In this work LaFeO3, LaFe0.7Mn0.3O3 and LaMn0.7Fe0.3O3 nanocatalysts with perovskite structures h... more In this work LaFeO3, LaFe0.7Mn0.3O3 and LaMn0.7Fe0.3O3 nanocatalysts with perovskite structures have been synthesized by sol-gel method. The selective catalytic reduction of NO with CO (CO-SCR) using synthesized nanocatalysts was investigated in a plug flow reactor. The kinetics of CO-SCR process was studied and three kinetic models were used to describe the behavior of the system, including power low model (PLM), kinetic model 1 (KM1) and kinetic model 2 (KM2). The KM1 was the best model with correlation coefficients of 0.9924, 0.9911 and 0.9902 and the sum of squared errors of 0.0504, 0.0488 and 0.0397, for LaFeO3, LaFe0.7Mn0.3O3 and LaFe0.3Mn0.7O3 catalysts, respectively. By comparing experimental results with the predicted results of the KM1, it was found that the proposed model can predict the performance of catalysts in the CO-SCR process with considerable precision. The structure and morphology of perovskite-type oxides were characterized by means of X-ray diffraction (XRD) a...

Journal of Inorganic and Organometallic Polymers and Materials, 2018

In this paper, LaFeO 3 perovskite catalysts were synthesized by sol-gel combustion, pechini and c... more In this paper, LaFeO 3 perovskite catalysts were synthesized by sol-gel combustion, pechini and co-precipitation methods and studied as catalysts for the catalytic reduction of NO with CO. The perovskite catalysts were characterized by XRD, BET, H 2-TPR, SEM and DLS. The pechini synthesized perovskite showed the highest activity among the other catalysts in the catalytic reduction of NO with CO. The excellent catalytic activity of LaFeO 3-pechini might be associated with its higher specific surface area, better low-temperature reducibility, more structural defects and more surface oxygen species. For pechini method as the best synthesize method, the effects of synthesis variables on activity of catalysts were studied by response surface methodology. RSM model could predict the experimental data for NO conversions at a good accuracy (R 2 = 0.981). The model predicted that the relative importance of variables is as follows: calcination temperature > citrate/ nitrate ratio > EG/citrate ratio. Under the optimum condition (citrate/nitrate ratio: 0.61, EG/citrate: 2.92 and calcination temperature: 600 °C), the predicted value of NO conversion (91.1%) was found to be in a good agreement with the corresponding actual value (89%).

Journal of Environmental Management, 2019

In the present study, two statistical methods including the response surface method (RSM) and art... more In the present study, two statistical methods including the response surface method (RSM) and artificial neural network (ANN), were employed for modeling and optimization of selective catalytic reduction of NOx with NH 3 (NH 3-SCR) over V 2 O 5 /TiO 2 nanocatalysts. The relationship between catalyst preparation variables, such as metal loading, impregnation temperature, and calcination temperature on NO conversion were investigated. The R 2 value of 0.9898 was obtained for quadratic a RSM model, which proves the high agreement of the model with the experimental data. The results of Pareto analysis revealed that three factors including calcination temperature, V loading, and impregnation temperature have a considerable impact on the response. Deduced from the established RSM model, the order of influence on the NO conversion was as follows: calcination followed by V loading and impregnation temperature. The optimum condition of catalyst preparation for maximum NO conversion over V 2 O 5 /TiO 2 nanocatalysts was predicted to be at 0.0051 mol of V loading, an impregnation temperature of 50°C and a calcination temperature of 491°C. Moreover, an ANN model was created by a feedforward back propagation network (with the topology 4, 12 and 1) to model the relation between the selected catalyst preparation variables and NH 3-SCR process temperature. The R 2 values for training, validation as well as test sets, were 0.99, 0.9810 and 0.9733. These high values proved the accuracy of the AAN model in modeling and estimating the NO conversion over V 2 O 5 /TiO 2 nanocatalysts. According to the ANN model, the relative significance of each variable on NO conversion is calcination temperature, process temperature loading, and impregnation temperature from high to low importance, respectively, corroborating the obtained results from RSM.

Industrial & Engineering Chemistry Research, 2017

A series of transition metals LaBO 3 perovskites (B= Mn, Fe, Co, Ni, Cu and Zn) has been synthesi... more A series of transition metals LaBO 3 perovskites (B= Mn, Fe, Co, Ni, Cu and Zn) has been synthesized and tested as catalysts for simultaneous removal of CO and NO in a fixed bed reactor. To improve the catalytic activity of LaFeO , as the most active formulation, it has been modified by using other active metals (Mn, Co and Cu) for partial substitution of Fe in the perovskite formulation (LaFe 0.7 M 0.3 O 3). The results revealed that Mn substitution improves significantly the catalytic activity because increases the Mn (IV) to Mn (III) ratio leading to the generation of a large amount of structural defects and, also, because increases the amount of reducible active sites.

Journal of Environmental Chemical Engineering, 2017

Catalytic performance of CeO2-MOx (0.25) (M= Mn, Fe and Cu) mixed oxide nanocatalysts were invest... more Catalytic performance of CeO2-MOx (0.25) (M= Mn, Fe and Cu) mixed oxide nanocatalysts were investigated in NO+CO reduction. Sol-gel method was used to synthesize nanocrystalline mixed oxides. Catalysts were characterized by XRD, BET, SEM, TEM and H2-TPR analysis. The Ce-Cu mixed oxide catalyst showed superior activity than other catalysts (with 80% NO and 72% CO conversions), due to its better reduction properties. To model and optimize the NO and CO conversions, a neuro-genetic approach was employed. This approach established by combining an artificial neural network with a genetic algorithm. The results showed that the ANN model is accurate with R 2 =0.991, 0.979 and 0.960 for training, validation and testing, respectively. Catalyst design factors (Cu/Ce molar ratio, citric acid/nitrate and calcination temperature) were optimized by GA. The optimum values were 0.49, 0.98 and 500 o C. For Cu/Ce molar ratio, citric acid /nitrate and calcination temperature, correspondingly. NO conversion predicted through ANN-GA system and obtained via experimental at 300 o C were 91% and 90%, respectively.

Journal of the Taiwan Institute of Chemical Engineers, 2017

In this paper, activity of sol-gel synthesized LaB 0.5 B 0.5 O 3 (B = Fe, Mn, B = Fe, Mn, Co, Cu)... more In this paper, activity of sol-gel synthesized LaB 0.5 B 0.5 O 3 (B = Fe, Mn, B = Fe, Mn, Co, Cu) perovskite catalysts was evaluated in catalytic reduction of NO by CO. Perovskite catalysts were characterized by XRD, BET, H 2-TPR and SEM analysis. LaMn 0.5 Cu 0.5 O 3 has the highest activity among LaB 0.5 B 0.5 O 3 perovskite catalysts (88% CO conversion and 93% NO conversion at 350 °C). The superior activity of LaMn 0.5 Cu 0.5 O 3 over other perovskite catalysts was associated to synergistic effect between Mn and Cu, higher reducibility at low temperature and more structural defects. The Langmuir-Hinshelwood mechanisms were used for Kinetic modeling of reduction of NO by CO. According to kinetic calculations, the most probable mechanism for this process was found to be the one based on dissociation of adsorbed NO (herein referred to as mechanism 1), according to which the experimental data was predicted at correlation coefficient of R 2 > 0.99.

Journal of Thermal Analysis and Calorimetry, 2017

In this paper, catalytic reduction of NO by CO over perovskite-type oxides LaCu 0.7 B 0.3 O 3 (B ... more In this paper, catalytic reduction of NO by CO over perovskite-type oxides LaCu 0.7 B 0.3 O 3 (B = Mn, Fe, Co) synthesized by sol-gel method was investigated. LaCu 0.7 Mn 0.3 O 3 showed the highest activity among LaCu 0.7 B 0.3 O 3 perovskite catalysts (88% CO conversion and 93% NO conversion at 350°C). The effect of alkali and alkaline earth metals (Rb, Sr, Cs and Ba) on the structure and catalytic activity of LaCu 0.7 Mn 0.3 O 3 perovskite catalysts was also investigated. The results showed that catalytic activity was improved by partial substitution of La by alkali and alkaline earth metals. The superior activity of La 0.8 Sr 0.2 Cu 0.7 Mn 0.3 O 3 with respect to other catalysts (93% CO conversion and 96% NO conversion at 350°C) was associated with a higher reducibility at low temperature, more oxygen vacancies and synergistic effect between Cu and Mn. The catalysts were characterized by XRD, BET, H 2-TPR, XPS and SEM.

Journal of the Taiwan Institute of Chemical Engineers, 2016

Toluene oxidation activities of sol-gel synthesized La 1 − x Ce x Mn 1 − y Cu y O 3 perovskite-ty... more Toluene oxidation activities of sol-gel synthesized La 1 − x Ce x Mn 1 − y Cu y O 3 perovskite-type catalysts were modeled and optimized using an intelligent approach. To design an intelligent system, an artificial neural network was coupled with a genetic algorithm. Catalyst formulation (mole fractions of Ce and Cu) and calcination temperature were optimized to have enhanced toluene conversion. The results showed that the best neural network architecture could predict toluene oxidation at an acceptable level of accuracy. The model prediction results indicated the maximum toluene conversion to be produced by La 1 −x Ce x Mn 1 −y Cu y O 3 of the following formulation details: Ce mole fraction of 0.30, Cu mole fraction of 0.52, and calcination temperature of 625 °C. The optimized values of toluene conversion obtained via prediction model and experimentations at 240 °C were 92.7% and 92.1%, respectively. The prepared perovskite catalysts were characterized by XRD, BET, H 2-TPR, and SEM.

Korean Journal of Chemical Engineering, 2016

Catalytic oxidation of toluene over perovskite-type oxides of the general formula LaMn 1−x B x O ... more Catalytic oxidation of toluene over perovskite-type oxides of the general formula LaMn 1−x B x O 3 (B=Cu, Fe and x=0, 0.3, 0.7) and La 0.8 A 0.2 Mn 0.3 B 0.7 O 3 (A=Sr, Ce and B=Cu, Fe) was investigated, where the catalysts were synthesized by sol-gel auto combustion method. The catalysts were characterized by XRD, BET, H 2-TPR, XPS, and SEM. Obtained XRD patterns confirmed the perovskites to be single-phase perovskite-type oxides. Specific surface areas of perovskites were obtained between 25-40 m 2 /g. The perovskite catalysts showed high activity for the toluene oxidation. Based on the results, Fe-containing perovskite catalysts exhibited higher activity than Cu-containing perovskite catalysts. The substitution of Sr and Ce in A-site of the perovskite catalysts enhanced their activity for toluene oxidation. Among different synthesized catalysts in this research, La 0.8 Ce 0.2 Mn 0.3 Fe 0.7 O 3 has the highest activity. Nearly complete elimination of toluene was achieved at 200 o C with this catalyst. Based on Langmuir-Hinshelwood mechanisms, kinetic studies were conducted on toluene oxidation, indicating LH-OS-ND (adsorption of reagents on same types of sites and non-dissociative adsorption of oxygen) as the most probable mechanism which could predict the experimental data with correlation coefficient of R 2 =0.9952.

International Journal of Environmental Science and Technology, 2016

In this paper, catalytic oxidation of CO over the perovskite-type oxides La1−xAxMn0.6Cu0.4O3 (A =... more In this paper, catalytic oxidation of CO over the perovskite-type oxides La1−xAxMn0.6Cu0.4O3 (A = Sr and Ce, x = 0, 0.1, 0.2, 0.3 and 0.4) was investigated. The catalysts were synthesized by sol–gel auto-combustion method and were further characterized by XRD, BET, FT-IR, H2-TPR and SEM. XRD patterns revealed that the oxides were single-phase perovskite-type oxides. Traces of Cu2O3, Sr2O3 and Ce2O3 were also detected in perovskites with high contents of Sr and Ce. Specific surface areas of perovskites were also determined to be about 16 and 32 m2/g. Reducibility of the perovskites, also, is strongly affected by substitution of La in A site by Sr and Ce. Perovskite catalysts show a high activity in catalytic oxidation of CO; substitution of Sr and Ce further enhanced CO oxidation activity. Highest activity was achieved by La0.7Ce0.3Mn0.6Cu0.4O3: Nearly complete elimination of CO was achieved at 145 °C with this catalyst. Kinetic studies for CO oxidation were performed based on Langmuir–Hinshelwood mechanisms. According to kinetic calculations, the most probable mechanism is the LH–OS–ND (adsorption of the reagents on same types of sites and non-dissociative adsorption of oxygen) which can predict the experimental data with correlation coefficient of R2 = 0.9933.