Abstract
Aims and Objective: In this work, the performance of a sodalite membrane reactor (MR) in the conversion of methanol to olefins (MTO process) was evaluated for ethylene and propylene production with in situ steam removal using 3-dimensional CFD (computational fluid dynamic) technique.
Methods: Numerical simulation was performed using the commercial CFD package COMSOL Multiphysics 5.3. The finite element method was used to solve the governing equations in the 3- dimensional CFD model for the present work. In the sodalite MR model, a commercial SAPO-34 catalyst in the reaction zone was considered. The influence of key operation parameters, including pressure and temperature on methanol conversion, water recovery, and yields of ethylene, propylene, and water was studied to evaluate the performance of sodalite MR.
Results: The local information of component concentration for methanol, ethylene, propylene, and water was obtained by the proposed CFD model. Literature data were applied to validate model results, and a good agreement was attained between the experimental data and predicted results using CFD model. Permeation flux through the sodalite membrane was increased by an increase of reaction temperature, which led to the enhancement of water stream recovered in the permeate side.
Conclusion: The CFD modeling results showed that the sodalite MR in the MTO process had higher performance in methanol conversion compared to the fixed-bed reactor (methanol conversion of 97% and 89% at 733 K for sodalite MR and fixed-bed reactor, respectively).
Keywords: Methanol to olefins, sodalite membrane, membrabe reactor, CFD modeling, DME, MTOS.
[1]
Hu, X.; Yuan, L.; Cheng, S.; Luo, J.; Sun, H.; Li, S. GeAPSO-34 molecular sieves: Synthesis, characterization and methanol-to-olefins performance. Catal. Commun., 2019, 123, 38-43.
[http://dx.doi.org/10.1016/j.catcom.2019.02.007]
[http://dx.doi.org/10.1016/j.catcom.2019.02.007]
[2]
Wang, S.; Chen, Y.; Qin, Z.; Zhao, T-S.; Fan, S.; Dong, M. Origin and evolution of the initial hydrocarbon pool intermediates in the transition period for the conversion of methanol to olefins over H-ZSM-5 zeolite. J. Catal., 2019, 369, 382-395.
[http://dx.doi.org/10.1016/j.jcat.2018.11.018]
[http://dx.doi.org/10.1016/j.jcat.2018.11.018]
[3]
Sun, Q.; Ma, Y.; Wang, N.; Li, X.; Xi, D.; Xu, J. High performance nanosheet-like silicoaluminophosphate molecular sieves: synthesis, 3D EDT structural analysis and MTO catalytic studies. J. Mater. Chem. A Mater. Energy Sustain., 2014, 2(42), 17828-17839.
[http://dx.doi.org/10.1039/C4TA03419H]
[http://dx.doi.org/10.1039/C4TA03419H]
[4]
Álvaro-Muñoz, T.; Sastre, E.; Márquez-Álvarez, C. Microwave-assisted synthesis of plate-like SAPO-34 nanocrystals with increased catalyst lifetime in the methanol-to-olefin reaction. Catal. Sci. Technol., 2014, 4(12), 4330-4339.
[http://dx.doi.org/10.1039/C4CY00775A]
[http://dx.doi.org/10.1039/C4CY00775A]
[5]
Fatourehchi, N.; Sohrabi, M.; Royaee, S.J.; Mirarefin, S.M. Preparation of SAPO-34 catalyst and presentation of a kinetic model for methanol to olefin process (MTO). Chem. Eng. Res. Des., 2011, 89(6), 811-816.
[http://dx.doi.org/10.1016/j.cherd.2010.10.007]
[http://dx.doi.org/10.1016/j.cherd.2010.10.007]
[6]
Alwahabi, S.M.; Froment, G.F. Single event kinetic modeling of the methanol-to-olefins process on SAPO-34. Ind. Eng. Chem. Res., 2004, 43(17), 5098-5111.
[http://dx.doi.org/10.1021/ie040041u]
[http://dx.doi.org/10.1021/ie040041u]
[7]
Kaarsholm, M.; Joensen, F.; Nerlov, J.; Cenni, R.; Chaouki, J.; Patience, G.S. Phosphorous modified ZSM-5: Deactivation and product distribution for MTO. Chem. Eng. Sci., 2007, 62(18-20), 5527-5532.
[http://dx.doi.org/10.1016/j.ces.2006.12.076]
[http://dx.doi.org/10.1016/j.ces.2006.12.076]
[8]
Liang, J.; Li, H.; Zhao, S.; Guo, W.; Wang, R.; Ying, M. Characteristics and performance of SAPO-34 catalyst for methanol-to-olefin conversion. Appl. Catal., 1990, 64, 31-40.
[http://dx.doi.org/10.1016/S0166-9834(00)81551-1]
[http://dx.doi.org/10.1016/S0166-9834(00)81551-1]
[9]
Azarhoosh, M.J.; Halladj, R.; Askari, S. Sonochemical synthesis of SAPO-34 catalyst with hierarchical structure using CNTs as mesopore template. Res. Chem. Intermed., 2017, 43(5), 3265-3282.
[http://dx.doi.org/10.1007/s11164-016-2824-0]
[http://dx.doi.org/10.1007/s11164-016-2824-0]
[10]
Askari, S.; Halladj, R.; Azarhoosh, M.J. Modeling and optimization of catalytic performance of SAPO-34 nanocatalysts synthesized sonochemically using a new hybrid of non-dominated sorting genetic algorithm-II based artificial neural networks (NSGA-II-ANNs). RSC Advances, 2015, 5(65), 52788-52800.
[http://dx.doi.org/10.1039/C5RA03764F]
[http://dx.doi.org/10.1039/C5RA03764F]
[11]
Zhao, X.; Li, J.; Tian, P.; Wang, L.; Li, X.; Lin, S. Achieving a superlong lifetime in the zeolite-catalyzed mto reaction under high pressure: synergistic effect of hydrogen and water. ACS Catal., 2019, 9(4), 3017-3025.
[http://dx.doi.org/10.1021/acscatal.8b04402]
[http://dx.doi.org/10.1021/acscatal.8b04402]
[12]
Azarhoosh, M.J.; Halladj, R.; Askari, S.; Aghaeinejad-Meybodi, A. Performance analysis of ultrasound-assisted synthesized nano-hierarchical SAPO-34 catalyst in the methanol-to-lights-olefins process via artificial intelligence methods. Ultrason. Sonochem., 2019, 58104646
[http://dx.doi.org/10.1016/j.ultsonch.2019.104646 PMID: 31450297]
[http://dx.doi.org/10.1016/j.ultsonch.2019.104646 PMID: 31450297]
[13]
Azarhoosh, M.J.; Halladj, R.; Askari, S. A dynamic kinetic model for methanol to light olefins reactions over a nanohierarchical SAPO‐34 catalyst: catalyst synthesis, model presentation, and validation at the bench scale. Int. J. Chem. Kinet., 2018, 50(3), 149-163.
[http://dx.doi.org/10.1002/kin.21146]
[http://dx.doi.org/10.1002/kin.21146]
[14]
Yang, H.; Miao, P.; Sun, Q.; Zhang, Y.; Tian, D. Dual templating fabrication of hollow SAPO-34 molecular sieves for enhanced MTO catalytic activity and selectivity. Cryst. Res. Technol., 2019, 54(2)1800132
[http://dx.doi.org/10.1002/crat.201800132]
[http://dx.doi.org/10.1002/crat.201800132]
[15]
Zhou, J.; Zhang, J.; Zhi, Y.; Zhao, J.; Zhang, T.; Ye, M. Partial regeneration of the spent SAPO-34 catalyst in the methanol-to-olefins process via steam gasification. Ind. Eng. Chem. Res., 2018, 57(51), 17338-17347.
[http://dx.doi.org/10.1021/acs.iecr.8b04181]
[http://dx.doi.org/10.1021/acs.iecr.8b04181]
[16]
Moradiyan, E.; Halladj, R.; Askari, S.; Bijani, P.M. Ultrasonic-assisted hydrothermal synthesis and catalytic behavior of a novel SAPO-34/Clinoptilolite nanocomposite catalyst for high propylene demand in MTO process. J. Phys. Chem. Solids, 2017, 107, 83-92.
[http://dx.doi.org/10.1016/j.jpcs.2017.03.021]
[http://dx.doi.org/10.1016/j.jpcs.2017.03.021]
[17]
Ahmadova, R.; Ibragimov, H.; Kondratenko, E.; Rodemerc, U. Synthesis of SAPO-34 catalysts via sonochemically prepared method and its catalytic performance in methanol conversion to light olefins. Appl. Petrochem. Res., 2018, 8(1), 13-20.
[http://dx.doi.org/10.1007/s13203-018-0193-x]
[http://dx.doi.org/10.1007/s13203-018-0193-x]
[18]
Azarhoosh, M.J.; Halladj, R.; Askari, S. Application of evolutionary algorithms for modelling and optimisation of ultrasound-related parameters on synthesised SAPO-34 catalysts: crystallinity and particle size. Prog. React. Kinet. Mech., 2018, 43(3-4), 236-243.
[http://dx.doi.org/10.3184/146867818X15233705894446]
[http://dx.doi.org/10.3184/146867818X15233705894446]
[19]
Chen, X.; Vicente, A.; Qin, Z.; Ruaux, V.; Gilson, J-P.; Valtchev, V. The preparation of hierarchical SAPO-34 crystals via post-synthesis fluoride etching. Chem. Commun. (Camb.), 2016, 52(17), 3512-3515.
[http://dx.doi.org/10.1039/C5CC09498D PMID: 26839923]
[http://dx.doi.org/10.1039/C5CC09498D PMID: 26839923]
[20]
Sun, Q.; Wang, N.; Bai, R.; Chen, X.; Yu, J. Seeding induced nano-sized hierarchical SAPO-34 zeolites: cost-effective synthesis and superior MTO performance. J. Mater. Chem. A Mater. Energy Sustain., 2016, 4(39), 14978-14982.
[http://dx.doi.org/10.1039/C6TA06613E]
[http://dx.doi.org/10.1039/C6TA06613E]
[21]
Liu, X.; Ren, S.; Zeng, G.; Liu, G.; Wu, P.; Wang, G. Coke suppression in MTO over hierarchical SAPO-34 zeolites. RSC Advances, 2016, 6(34), 28787-28791.
[http://dx.doi.org/10.1039/C6RA02282K]
[http://dx.doi.org/10.1039/C6RA02282K]
[22]
Chen, X.; Xi, D.; Sun, Q.; Wang, N.; Dai, Z.; Fan, D. A top-down approach to hierarchical SAPO-34 zeolites with improved selectivity of olefin. Microporous Mesoporous Mater., 2016, 234, 401-408.
[http://dx.doi.org/10.1016/j.micromeso.2016.07.045]
[http://dx.doi.org/10.1016/j.micromeso.2016.07.045]
[23]
Barbieri, G.; Marigliano, G.; Golemme, G.; Drioli, E. Simulation of CO2 hydrogenation with CH3OH removal in a zeolite membrane reactor. Chem. Eng. J., 2002, 85(1), 53-59.
[http://dx.doi.org/10.1016/S1385-8947(01)00143-7]
[http://dx.doi.org/10.1016/S1385-8947(01)00143-7]
[24]
Rahimpour, M.; Mirvakili, A.; Paymooni, K.; Moghtaderi, B. A comparative study between a fluidized-bed and a fixed-bed water perm-selective membrane reactor with in situ H2O removal for Fischer–Tropsch synthesis of GTL technology. J. Nat. Gas Sci. Eng., 2011, 3(3), 484-495.
[http://dx.doi.org/10.1016/j.jngse.2011.05.003]
[http://dx.doi.org/10.1016/j.jngse.2011.05.003]
[25]
Rieck genannt Best, F; Mundstock, A; Dräger, G; Rusch, P; Bigall, NC; Richter, H Methanol-to-olefins in a membrane reactor with in situ steam removal–the decisive role of coking. ChemCatChem, 2020, 12(1), 273-280.
[http://dx.doi.org/10.1002/cctc.201901222]
[http://dx.doi.org/10.1002/cctc.201901222]
[26]
Aghaeinejad-Meybodi, A.; Ghasemzadeh, K.; Babaluo, A.A.; Morrone, P.; Basile, A. Modeling study of silica membrane performance for hydrogen separation. Asia-Pac. J. Chem. Eng., 2015, 10(5), 781-790.
[http://dx.doi.org/10.1002/apj.1915]
[http://dx.doi.org/10.1002/apj.1915]
[27]
Ghasemzadeh, K.; Zeynali, R.; Ahmadnejad, F.; Babalou, A.; Basile, A. Investigation of palladium membrane reactor performance during ethanol steam reforming using CFD method. Chemical Product and Process Modeling, 2016, 11(1), 51-55.
[http://dx.doi.org/10.1515/cppm-2015-0056]
[http://dx.doi.org/10.1515/cppm-2015-0056]
[28]
Ji, G.; Wang, G.; Hooman, K.; Bhatia, S.; da Costa, J.D. The fluid dynamic effect on the driving force for a cobalt oxide silica membrane module at high temperatures. Chem. Eng. Sci., 2014, 111, 142-152.
[http://dx.doi.org/10.1016/j.ces.2014.02.006]
[http://dx.doi.org/10.1016/j.ces.2014.02.006]
[29]
Chang, J.; Zhang, K.; Chen, H.; Yang, Y.; Zhang, L. CFD modelling of the hydrodynamics and kinetic reactions in a fluidised-bed MTO reactor. Chem. Eng. Res. Des., 2013, 91(12), 2355-2368.
[http://dx.doi.org/10.1016/j.cherd.2013.04.023]
[http://dx.doi.org/10.1016/j.cherd.2013.04.023]
[30]
Zhuang, Y-Q.; Chen, X-M.; Luo, Z-H.; Xiao, J. CFD–DEM modeling of gas–solid flow and catalytic MTO reaction in a fluidized bed reactor. Comput. Chem. Eng., 2014, 60, 1-16.
[http://dx.doi.org/10.1016/j.compchemeng.2013.08.007]
[http://dx.doi.org/10.1016/j.compchemeng.2013.08.007]
[31]
Lu, B.; Luo, H.; Li, H.; Wang, W.; Ye, M.; Liu, Z. Speeding up CFD simulation of fluidized bed reactor for MTO by coupling CRE model. Chem. Eng. Sci., 2016, 143, 341-350.
[http://dx.doi.org/10.1016/j.ces.2016.01.010]
[http://dx.doi.org/10.1016/j.ces.2016.01.010]
[32]
Zhuang, Y-Q.; Gao, X.; Zhu, Y-p.; Luo, Z-h. CFD modeling of methanol to olefins process in a fixed-bed reactor. Powder Technol., 2012, 221, 419-430.
[http://dx.doi.org/10.1016/j.powtec.2012.01.041]
[http://dx.doi.org/10.1016/j.powtec.2012.01.041]
[33]
Rostami, R.B.; Lemraski, A.S.; Ghavipour, M.; Behbahani, R.M.; Shahraki, B.H.; Hamule, T. Kinetic modelling of methanol conversion to light olefins process over silicoaluminophosphate (SAPO-34) catalyst. Chem. Eng. Res. Des., 2016, 106, 347-355.
[http://dx.doi.org/10.1016/j.cherd.2015.10.019]
[http://dx.doi.org/10.1016/j.cherd.2015.10.019]
[34]
Spivey, J.J. Dehydration catalysts for the methanol/dimethyl ether reaction. Chem. Eng. Commun., 1991, 110(1), 123-142.
[http://dx.doi.org/10.1080/00986449108939946]
[http://dx.doi.org/10.1080/00986449108939946]
[35]
Mousavi, S.H.; Fatemi, S.; Razavian, M. Kinetic modeling of the methanol to olefins process in the presence of hierarchical SAPO-34 catalyst: parameter estimation, effect of reaction conditions and lifetime prediction. React. Kinet. Mech. Catal., 2017, 122(2), 1245-1264.
[http://dx.doi.org/10.1007/s11144-017-1266-z]
[http://dx.doi.org/10.1007/s11144-017-1266-z]
[36]
Sedighi, M.; Keyvanloo, K. Kinetic study of the methanol to olefin process on a SAPO-34 catalyst. Frontiers of Chemical Science and Engineering, 2014, 8(3), 306-311.
[http://dx.doi.org/10.1007/s11705-014-1440-z]
[http://dx.doi.org/10.1007/s11705-014-1440-z]
[37]
Ghasemzadeh, K.; Ahmadnejad, F.; Aghaeinejad-Meybodi, A.; Basile, A. Hydrogen production by a PdAg membrane reactor during glycerol steam reforming: ANN modeling study. Int. J. Hydrogen Energy, 2018, 43(15), 7722-7730.
[http://dx.doi.org/10.1016/j.ijhydene.2017.09.120]
[http://dx.doi.org/10.1016/j.ijhydene.2017.09.120]
[38]
Ghasemzadeh, K.; Zeynali, R.; Bahadori, F.; Basile, A. CFD analysis of Pd-Ag membrane reactor performance during ethylbenzene dehydrogenation process. Int. J. Hydrogen Energy, 2018, 43(15), 7675-7683.
[http://dx.doi.org/10.1016/j.ijhydene.2017.09.112]]
[http://dx.doi.org/10.1016/j.ijhydene.2017.09.112]]
[39]
Ghasemzadeh, K.; Zeynali, R.; Basile, A. Theoretical study of hydrogen production using inorganic membrane reactors during WGS reaction. Int. J. Hydrogen Energy, 2016, 41(20), 8696-8705.
[http://dx.doi.org/10.1016/j.ijhydene.2015.12.117]
[http://dx.doi.org/10.1016/j.ijhydene.2015.12.117]
Related Journals
Current Computer-Aided Drug Design
Article Metrics
11
1