Simulation of Synthesis Gas Production by Using a Plasma Reactor

There are multiple methods for producing synthesis gas and one of the most important of these methods is dry reforming in which two preparations of carbon dioxide and methane are converted into synthesis gas. Carbon dioxide as one of the destructive environmental factors and methane as the main component of natural gas exist in copious amounts in the world, especially in Iran, which has the second largest gas resources of the world after Russia. Therefore, the importance of this method is in converting pollutants into an intermediate substance known as synthesis gas which has considerable applications. In this study, first, synthesis gas production by using dry reforming with the use of plasma technology is studied and for this purpose, glow electric discharge plasma at atmospheric pressure with DC power supply was used. Feed flow rate and the distance between the electrodes were studied as the parameters. In addition, voltage effect on optimal conditions was studied as well. Next, by using fluent software, dynamic simulation of computational fluid of this system was performed which gives us velocity and pressure distributions in the system. For optimization of laboratory conditions, it was assumed that our system has two incoming paths instead of one and the results obtained from this assumption showed that this assumption increases the residence time of the material between the two electrodes which in turn increases the percentage of conversion

Simulation of Synthesis Gas Production by Using a Plasma Reactor

There are multiple methods for producing synthesis gas and one of the most important of these methods is dry reforming in which two preparations of carbon dioxide and methane are converted into synthesis gas. Carbon dioxide as one of the destructive environmental factors and methane as the main component of natural gas exist in copious amounts in the world, especially in Iran, which has the second largest gas resources of the world after Russia. Therefore, the importance of this method is in converting pollutants into an intermediate substance known as synthesis gas which has considerable applications. In this study, first, synthesis gas production by using dry reforming with the use of plasma technology is studied and for this purpose, glow electric discharge plasma at atmospheric pressure with DC power supply was used. Feed flow rate and the distance between the electrodes were studied as the parameters. In addition, voltage effect on optimal conditions was studied as well. Next, by using fluent software, dynamic simulation of computational fluid of this system was performed which gives us velocity and pressure distributions in the system. For optimization of laboratory conditions, it was assumed that our system has two incoming paths instead of one and the results obtained from this assumption showed that this assumption increases the residence time of the material between the two electrodes which in turn increases the percentage of conversion

The Effect of Aluminum Source on Performance of Beta-Zeolite as a Support for Hydrocracking Catalyst

In this paper, three different kinds of aluminum sources (sodium aluminate, aluminum sulfate and aluminum isopropylate) were used for preparing of nano beta-zeolite. The as synthesized zeolites were mixed with the as prepared amorphous silica-alumina to produce the supports for hydrocracking catalyst. The prepared supports were used for preparation of NiMo/silica alumina-nano beta-zeolite by impregnation method. The influence of the aluminum source for preparation of beta-zeolite on the performance of the prepared catalysts has been studied. The samples were thoroughly characterized by X-Ray diffraction method (XRD), field emission-scanning electron microscopy (FE-SEM), N2 adsorption-desorption isotherms (BET), temperature programmed desorption (TPD) and temperature programmed reduction (TPR) methods. The catalysts performance was evaluated by vacuum gas oil (VGO) hydrocracking at 390 oC in a fixed bed reactor. The XRD patterns showed that the beta-zeolite samples obtained from the present methods were pure and highly crystalline and the crystal size of the prepared zeolites were in nanometer scale. Crystallite size of nano beta-zeolite synthesized by aluminum isopropylate [Al(iPrO)3] was smaller than those of prepared by the other aluminum sources. The catalyst containing this zeolite with higher surface area (231 m2/g) and more available acid sites (1.66 mmol NH3/g) possessed higher activity and selectivity to gas oil (71.9 %). Copyright © 2018 BCREC Group. All rights reserved Received: 25th April 2018; Revised:22nd July 2018; Accepted: 29th July 2018 How to Cite: Hadi, M., Aghabozorg, H.R., Bozorgzadeh, H.R., Ghasemi, M.R. (2018). The Effect of Aluminum Source on Performance of Beta-Zeolite as a Support for Hydrocracking Catalyst. Bulletin of Chemical Reaction Engineering & Catalysis, 13 (3): 543-552 (doi:10.9767/bcrec.13.3.2570.543-552) Permalink/DOI: https://doi.org/10.9767/bcrec.13.3.2570.543-55

Continuous adsorption process of CO2/N2/H2O from CH4 flow using type A zeolite adsorbents in the presence of ultrasonic waves

In this study, the adsorption capacity of different types of zeolite (3A, 4A, and 5A) for adsorbing CO2 from a mixture of CH4, N2, and water vapor was investigated with and without the use of ultrasonic waves. In this study, functional groups of O–H, Si–O–Al and Si–O–Si bands were identified in Fourier transform infrared (FTIR) spectroscopy of these adsorbents. X-ray diffraction patterns (XRD) for zeolite 3A and 5A showed the structure of chabazite and for zeolite 4A the structure of sodalite. In the Brunauer-Emmett-Teller (BET) test, the specific surface area of zeolites was measured as 16, 11.96 and 437 m2g−1, respectively. Ultrasonic waves increased the adsorption capacity of zeolites to adsorb CO2 at lower temperatures 80.64 to 175.44 mgg−1. Zeolite 5A has a higher affinity for CO2 than CH4 or N2, the selectivity of CO2/ N2 and CO2/ CH4 were 19.55 and 24.17, respectively. Data from adsorption experiments were used to learn an artificial neural network (ANN), and the ANN provided acceptable results for predicting the adsorption process