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Received July 19, 2015
Accepted December 11, 2015
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Using response surface methodology to optimize ultrasound-assisted oxidative desulfurization
Research Institute of Petroleum Industry (RIPI), Gas Department, West Boulevard of Azadi Stadium, P. O. Box 14665-1998, Tehran, Iran 1School of Chemical Engineering, Iran University of Science and Technology, P. O. Box 16765-163, Tehran, Iran
inspirationj82@gmail.com
Korean Journal of Chemical Engineering, April 2016, 33(4), 1286-1295(10), 10.1007/s11814-015-0276-7
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Abstract
Latest strict environmental regulations have restricted the sulfur content of diesel fuels; therefore, deep desulfurization of fuels is required. Ultrasound-assisted oxidative desulfurization (UAOD) is an alternative for conventional desulfurization methods which can remove sulfur compounds from fuels under mild process conditions. In this study, UAOD of gasoil using tungstophosphoric acid catalyst and tetraoctylammonium bromide as a phase transfer agent in the presence of hydrogen peroxide as an oxidant was optimized. The optimal design of experiments was generated based on central composite face-centered design of Response surface methodology (RSM) to study effects of four process variables such as oxidant volume, mass of catalyst, mass of phase transfer agent and the ultrasonic wave amplitude on the sulfur conversion of gasoil. In addition, a predictive model of sulfur conversion was obtained based on RSM. The optimal values of process variables were evaluated to be 21.96 mL of oxidant, 1 gr of catalyst and 0.1 gr of phase transfer agent to achieve the maximum sulfur conversion of 95.92%.
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References
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Ghosh S, Rao CR, in: Handbook of Statistics, Elsevier Science Publishing, Amsterdam (1996).
Hasan SDM, Melo DNC, Filho RM, Chem. Eng. Process., DOI:10.1016/j.cep.2004.05.007., 44(3), 335 (2005)
Bradley N, Response Surface Methodology, in: Department of Mathematical Sciences, Indiana University of South Bend, the US (2007).
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Myers RH, Montgomery DC, Anderson-Cook CM, Response Surface Methodology: Process and Product Optimization Using Designed Experiments, Third Ed., John Wiley & Sons, Hoboken, New Jersey (2009).
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Cheynier V, Feinberg M, Chararas C, Ducauze C, Appl. Environ. Microbiol., 45(2), 634 (1983)
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Narimani E, Kadijani JA, Pet. Coal, 55(4), 330 (2013)
Loning JM, Horst C, Hoffmann U, Ultrason. Sonochem., 9(3), 169 (2002)
