A Modeling Study of Operating Conditions and Different Supports on Fe-Co-Ce Nanocatalyst and Optimizing of Light Olefins Selectivity in the Fischer-Tropsch Synthesis

2021;
: pp. 170 - 182
1
Department of Chemistry, Faculty of Science, University of Sistan and Baluchestan
2
Department of Chemistry, Faculty of Science, University of Sistan and Baluchestan
3
Department of Chemical Engineering, Faculty of Engineering, University of Sistan and Baluchestan
4
Catalyst Division, Research Institute of Petroleum Industry (RIPI), Tehran, Iran

This study demonstrates the effect of operating conditions (Red-GHSV, inlet H2/CO, Oprat-GHSV) and the effect of Fe-Co-Ce nanocatalyst support. A statistical model using the response surface methodology (RSM) was applied with the target of achieving higher olefins selectivity in Fischer-Tropsch synthesis, which indicates the interaction effects of factors. The conditions under which three objectives optimization for maximizing olefins and minimizing paraffins and methane were determined. Synthesized nanocatalysts with various supports were characterized by XRD, SEM and TPR techniques

  1. Zhyznevskiy V., Gumenetskiy V., Matskiv O., Shyshchak O.: Chem. Chem. Technol., 2013, 7, 15. https://doi.org/10.23939/chcht07.01.015
  2. Babyak L., Matsyak O., Shevchuk V.: Chem. Chem. Technol., 2011, 5, 95. https://doi.org/10.23939/chcht05.01.095
  3. Babyak L., Matsyak O., Shevchuk V. et al.: Chem. Chem. Technol., 2009, 3, 305.
  4. Pielichowski J., Kowalski G., Zaikov G.: Chem. Chem. Technol., 2011, 5, 303. https://doi.org/10.23939/chcht05.03.303
  5. Feyzi M., Yaghobi N., Eslamimanesh V.: Mater. Res. Bull., 2015, 72, 143. https://doi.org/doi:10.1016/j.materresbull.2015.07.039
  6. Arsalanfar M., Mirzaei A., Bozorgzadeh H., Atashi H.: J. Ind. Eng. Chem, 2012, 18, 2092. https://doi.org/10.1016/j.jiec.2012.06.003
  7. Jacobs G., Das T., Zhang Y. et al.: Appl. Catal. A, 2002, 233, 263. https://doi.org/10.1016/S0926-860X(02)00195-3
  8. Atashi H., Rezaeian F.: Int. J. Hydrogen. Energ., 2017, 42, 15497. https://doi.org/10.1016/j.ijhydene.2017.04.224
  9. Sun Y., Wei J., Ping Zhang J., G. Yang: J. Nat. Gas. Sci. Eng., 2016, 28, 173. https://doi.org/10.1016/j.jngse.2015.11.008
  10. Gunaraj V., Murugan N.: J. Mater. Process. Technol., 1999, 88, 266. https://doi.org/10.1016/S0924-0136(98)00405-1
  11. Tauster S., Fung S., Baker R., Horsley J.: Science, 1981, 211, 1121. https://doi.org/10.1126/science.211.4487.1121
  12. Peddis D., Jonsson P., Laureti S., Varvaro G.: Front. Nanosci., 2014, 6, 129. https://doi.org/10.1016/B978-0-08-098353-0.00004-X
  13. Khan A., Smimiotis P.: J. Mol. Catal. A, 2008, 280, 43. https://doi.org/10.1016/j.molcata.2007.10.022
  14. Davies K., Wells S., Charles S.: J. Magn. Magn. Mater., 1993, 122, 24. https://doi.org/10.1016/0304-8853(93)91031-2
  15. De Rivas B., Gutierrez-Ortiz J., Lopez-Fonseca R., Gonzalez-Velasco J.: Appl. Catal. A, 2006, 314, 54. https://doi.org/10.1016/j.apcata.2006.08.005
  16. Madon R., Iglesia E.: J. Catal., 1993, 139, 576. https://doi.org/10.1006/jcat.1993.1051
  17. Atashi H., Razmjooei S., Khorashadizadeh M. et al.: J. Taiwan Inst. Chem. Eng., 2015, 54, 83. https://doi.org/10.1016/j.jtice.2015.03.017