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In the present paper, a gamma alumina (γ-Al2O3) loaded zinc oxide (ZnO) nano-catalyst (ZnO/γ-Al2O3) has been synthesized and used to accelerate the removal of sulfur compounds from light gas oil by oxidative desulfurization (ODS) process. The synthesized nano-catalysts have been characterized by atomic force microscopy (AFM) and Brunauer-Emmett-Teller (BET). The ODS process has been conducted in a batch reactor at various reaction temperatures and batch times varying between 30 to 90 °C and 20 to 80 min, respectively. DBT removal was highest (93.781%) while using synthesized nano-catalyst (9% ZnO/γ-Al2O3) at 90°C and 80 min reaction time. Based on the obtained experimental data, a new mathematical modeling technique was performed for the ODS operation under mild experimental conditions to evaluate the most appropriate kinetic variables for the newly synthesized nano-catalysts. Simulation results indicate a good match with experimental observations with less than 5% absolute average error for all runs. The optimization procedure of the process condition displays that > 98% DBT could be eliminated within 200 min, at 87 °C, in the existence of synthesized nano-catalyst (9% ZnO/γ-Al2O3).

A novel electrochemical reactor with a rotating anode attached to its end with four baskets as catalysts holders is proposed for deep desulfurization of diesel fuel. In this reactor two experimentally prepared catalysts of (5% manganese oxide (MnO2)/modified activated carbon (MAC) and 5% iron oxide (Fe2O3)/MAC) were used for an efficient desulfurization process. This design is characterized by conducting two functions at the same time, which are to agitate the reaction mixture and to move the catalyst over all areas of the reaction vessel. Several experiments were conducted at different operating conditions such as voltage, reaction time, and agitating speed. Results showed that the proposed basket reactor is excellent and highly effective in removing dibenzothiophene (DBT) in diesel. The removal efficiency of sulfur compounds is significantly improved by enhancing reaction times, stirring speed, and cell voltage up to 3 volts and drops at higher than 3 volts. At all operating conditions, the 5% Fe2O3/MAC catalyst showed higher performance than the 5% MnO2/MAC catalyst. This result can be attributed to the high reactivity of Fe2O3/MAC toward DBT removal and its magnetic activity which could enhance the oxidation reaction. Under the best operating conditions, the removal efficiencies reached 98.8%, and 93.1% for 5% Fe2O3/MAC and 5% MnO2/MAC, respectively. A model for the proposed reactor was also developed using an artificial neural network (ANN) software. The modeling data displayed an excellent agreement between the experimental and predicted data. This interactive model produced an accurately strong basis for the behavior of the new electrochemical desulfurization (ECDS) process. [ABSTRACT FROM AUTHOR]

Producing an eco-friendly fuel with the least amount of sulfur compounds has been an ongoing issue for petroleum refineries. In this study, bentonite (which is a cheap material and is locally available in abundance) is employed to prepare a nano-silica catalyst with a high surface area to be used for the oxidative desulfurization of kerosene. Two composite catalysts of Fe/silica were supported on CAT-1 (0% HY-zeolite and 100% nano-silica) and CAT-2 (20% HY-zeolite and 80% nano-silica). The activity of the catalysts was evaluated in a batch ODS (oxidative desulfurization) process at temperatures of 30, 60, 90, and 120 °C, a pressure of 1 atm, and a reaction time of 30, 60, 90, and 120 min using 120 L/h of air as the oxidant. The results revealed that the highest total sulfur removal efficiency was 50% and 87.88% for 100% nano-silica (CAT-1) and 80% nano-silica (CAT-2), respectively. The experimental data were then used to construct and validate an accurate mathematical model of the process. The operational parameters for eliminating more than 99% of sulfur and producing eco-friendly fuel were then achieved by using the model. The testing methods for these characterizing materials included X-ray diffraction (XRD), thermal gravimetric examination (TGA), X-ray fluorescence (XRF), and surface area (BET). The outcomes indicated that the addition of HY-zeolite increased the activity of the catalyst (CAT-2 > CAT-1). [ABSTRACT FROM AUTHOR]

In this study, the influence of various metals (iron, cast iron, copper, aluminum) and sunlight on the gum formation rate in Iraqi gasoline fuel (IGF) is studied. Gasoline has been doped with 5 g/100 mL of used metals and various concentrations (5, 10, 15, 20, 25, 30, 35, 40 g/100 mL) of iron metal. Washed gum content has been analyzed employing ASTM D 381 after storage period of 30 days. The results explain that gum formation at 5 μg mL −1 concentration of different metals obeys the following order: iron cost > aluminum > copper > iron. The results explain that the maximum gum content is 24.4 g/100 mL employing cast iron and the minimum content via using iron metal (6.4 g/100 mL). The results prove that the rate gum formation is higher affected by sunlight in comparing with iron, and weaker influence from other metals. The experimental data shows that gum content strongly enhances via increasing of iron content. The highest gum content (21.8 g/100 mL) is at the maximum iron content (40 g/100 mL) but the minimum rate (6.4 g/100 mL) is at minimum iron content (5 g/100 mL). [ABSTRACT FROM AUTHOR]

In the present paper, a gamma alumina (γ-Al2O3) loaded zinc oxide (ZnO) nano-catalyst (ZnO/γ-Al2O3) has been synthesized and used to accelerate the removal of sulfur compounds from light gas oil by oxidative desulfurization (ODS) process. The synthesized nano-catalysts have been characterized by atomic force microscopy (AFM) and Brunauer-Emmett- Teller (BET). The ODS process has been conducted in a batch reactor at various reaction temperatures and batch times varying between 30 to 90 °C and 20 to 80 min, respectively. DBT removal was highest (93.781%) while using synthesized nano-catalyst (9% ZnO/γ-Al2O3) at 90°C and 80 min reaction time. Based on the obtained experimental data, a new mathematical modeling technique was performed for the ODS operation under mild experimental conditions to evaluate the most appropriate kinetic variables for the newly synthesized nano-catalysts. Simulation results indicate a good match with experimental observations with less than 5% absolute average error for all runs. The optimization procedure of the process condition displays that > 98% DBT could be eliminated within 200 min, at 87 °C, in the existence of synthesized nano-catalyst (9% ZnO/γ- Al2O3). [ABSTRACT FROM AUTHOR]

Removal of phenol and phenolic compounds from wastewater using various techniques has received considerable attention in recent years. In this work, the removal of phenol from a model solution of phenol via catalytic oxidation is investigated with oxidant H2O2. For this purpose, we designed a new nano-catalyst (8% Fe2O3/AC) by loading iron oxide nanoparticles over nano-activated carbon via the impregnation process. We modified the recently developed digital basket baffle batch reactor (DBBBR) and used it for the catalytic oxidation process in order to examine the activity of the prepared nano-catalyst. The highest efficiency of phenol removal was found to be 95.35% under the following parameters: oxidation time of 120 min, oxidation temperature at 85 °C, and stirrer speed of 600 rpm. The minimization of the sum of the squared error between the experimental data and predicted results of phenol removal was considered as a base for the optimization technique to estimate the optimal parameters for the kinetic process. The predicted conversion of phenol excellently agreed with the experimental results (absolute average errors < 5%) for a wide range of process parameters. [ABSTRACT FROM AUTHOR]

Catalysts play a vital role in petroleum and chemical reactions. Intensified concerns for cleaner air with strict environmental regulations on sulfur content in addition to meet economic requirements have generated significant interests for the development of more efficient and innovative oxidative catalysts recently. In this study, a novel homemade nano catalyst (manganese oxide (MnO2) over tin (IV) oxide (SnO2)) was used for the first time as an effective catalyst in removing dibenzothiophene (DBT) from kerosene fuel using hydrogen peroxide (H2O2) as oxidant in catalytic oxidative-extractive desulfurization process (OEDS). The catalyst was prepared by impregnation method with various amount of MnO2 loaded on SnO2. The oxidation step was carried out at different operating parameters such as reaction temperature and reaction time in batch reactor. The extractive desulfurization step was performed by using acetonitrile as solvent under several operating conditions (agitation speed and mixing time). The activity of MnO2/SnO2 catalyst in removing various sulfur compounds from kerosene fuel at the best operating conditions was investigated in this work. The results of the catalyst characterization proved that a high dispersion of MnO2 over the SnO2 was obtained. The experiments showed that the highest DBT and various sulfur compounds removal efficiency from kerosene fuel under the best operating conditions (oxidation: 5% MnO2/SnO2, reaction temperature of 75 °C, and reaction time of 100 min, extraction: acetonitrile, agitation speed of 900 rpm, and mixing time of 30 min) via the catalytic oxidative-extractive desulfurization process was 92.4 and 91.2%, respectively. Also, the MnO2/SnO2 catalyst activity was studied after six consecutive oxidation cycles at the best operating conditions, and the catalyst prove satisfactory stability in terms of sulfur compounds removal. After that, the spent catalyst were regenerated by utilizing different solvents (methanol, ethanol and iso-octane), and the experimental data explained that iso-octane achieved highest regeneration efficiency. [ABSTRACT FROM AUTHOR]

A novel nano-catalyst based on iron oxide (MnO2/Fe2O3) was developed to promote wet oxidation of phenol. MnO2 was doped in Fe2O3 matrix to prepare composite nano-catalyst with different doping percentage (0, 2 and 5%). The catalytic phenol oxidation was conducted under different reaction temperatures and residence times. To evaluate the optimal kinetic parameters aiming to maximize phenol removal under the optimal conditions for the catalytic wet phenol oxidation process, modeling was applied on the batch reactor using the novel synthesis nano-catalyst (MnO2/Fe2O3) and the model developed was fed with the experimental data. gPROMS package was used to model the process of phenol oxidation and to optimize the experimental data. The error predicted between the simulated and experimental data was less than 5%. The optimal operating conditions were 294 min residence time, 70&176;C reaction temperature, and 764 ppm initial concentration of phenol over the prepared 5% MnO2/Fe2O3. Running of wet oxidation of phenol under the optimal operating conditions resulted in 98% removal of phenol from refinery wastewater. [ABSTRACT FROM AUTHOR]