Soudabeh Bahrami Gharamaleki

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 R2 = 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 °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 °C were 91% and 90%, respectively.

Fuel cells are electrochemical devices utilized for converting chemical energy to electrical energy. Solid Oxide Fuel Cells (SOFCs) have several advantages over other kinds. For instance, high energy efficiency expanded fuel flexibility, low environmental pollutant emission are the properties of SOFCs that make them superior to other fuel cell types. Due to these special characteristics, SOFCs are gained a great deal of attraction. These fuel cells consist of different main operating parts, a cathode, an anode, and electrolyte which each of them demands special materials to operate with the most efficiency. SOFCs mostly operate in high temperatures (800- 1000 ᵒC). Reducing the operating temperature to lower than 600 ᵒC or intermediate temperatures 600-800 ᵒC is one of the methods that can make them more practical devices. Perovskite oxides can be used effectively as all main parts of SOFCs because of their excellent properties like electrical and ionic conductivities, oxygen ion vacancies, great catalytic properties, thermal durability, and chemical stability to decrease the operating temperature. In this review, numerous perovskite-based materials utilized in the anode and the cathode electrodes of SOFCs are investigated in the most recent, advanced, and novel works. The perovskite materials, their properties, and their influence on the fuel cell’s performance, and in some cases the sulfur tolerance of the materials when H2S co-exists in the fuel of the fuel cell are reviewed in this paper Adding different dopants in A-site and B-site of the perovskite oxides is the most effective way to modify the characteristics of the materials. This review can provide great data on the possible perovskite oxides with the capability of enhancing the efficiency of SOFCs by reducing the operating temperature, and their most decisive and significant characteristics, like composition, structure, electrical conductivity, electrochemical and mechanical properties for research groups working on solid oxide fuel cells.

The usage of environment-friendly energy converter devices is getting more and more attention as a result of environmental crises and regulations. SOFCs are among the highly efficient chemical to electrical energy converters. Thus, their effectiveness is a significant issue to improve. To increase the efficiency of SOFCs, their properties should be investigated. However, it is costly and time-consuming to test all the important characteristics of a solid oxide fuel cell by experimental methods. Computational methods can contribute to evaluate the influence of each parameter on the performance of the fuel cell. In this paper, a 3D mathematical model of a SOFC is presented. The model can describe the fuel cell’s temperature, the concentration of material, and current distribution inside the cell. Also, the influence of the flow pattern (co-current and counter-current) on the distribution plots and performance of the solid oxide fuel cell is investigated. The results demonstrate that the distribution of the current, concentration, and temperature is firmly related and wherever the concentration of reactants is higher, the temperature and current increase too. Also, the plots of power density and cell potential versus current were consistent with the results of the literature. Moreover, the comparison between two types of flow patterns shows that there is no significant variation when the type of current changes from counter to co-current. However, the performance of the SOFC is mildly better with a co-current flow pattern.

In this paper, cerium based mixed oxide catalysts were tested in catalytic reduction of NO with CO. Nano crystalline CeO2-MnOx mixed oxide catalysts with Mn/ (Mn + Ce) =0 and 0.25 molar ratio were prepared by sol-gel combustion method. To characterize the physicochemical properties of prepared catalysts the following analysis were evaluated X-Ray Diffraction (XRD), Transmission Electron Microscopy (TEM), and also their activities have been checked for reduction of NOx with CO. The CeO2-MnOx catalysts demonstrated better activity than CeO2 in both low and high temperature. The superior activity of CeO2-MnOx with Mn/ (Mn+Ce) =0.25 molar ratio compare to CeO2 was obtained in 400 oC with 77% NO conversion and 74% CO conversion.

 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