Prediction of conversion and products yields in steam reforming of methanol over Cu-Zn/ZrO2 catalyst using Artificial Intelligence methods

Eghbal Ahmadi, Mohammad Hosein; Mosayebi, Amir

Prediction of conversion and products yields in steam reforming of methanol over Cu-Zn/ZrO2 catalyst using Artificial Intelligence methods

Document Type : Original Research

Authors

M. H. Eghbal Ahmadi

A. Mosayebi

Department of Chemical Engineering, Tafresh University, Tafresh, 39518 79611, Iran

Abstract

Subject

In this study, the steam reforming of the methanol process was analyzed based on three different inputs including temperature, pressure, and H₂O/CH₃OH ratio with the use of different Artificial Intelligence methods.

Methodology

In the first step, Cu-Zn/ZrO₂ catalysts were synthesized via the co-precipitation method, and then experimental tests of steam reforming of methanol were performed at a temperature range of 180 –500 °C, the pressure of 1-11 bar, and the H₂O/CH₃OH ratio of 0.75-3.75 on the Cu-Zn/ZrO₂ catalyst in a fixed bed reactor. Afterward, three different methods of Mamdani fuzzy type-1, Mamdani fuzzy type-2, and Sugeno fuzzy were applied in order to develop the models. Using these methods, the developed models only required the heuristics derived from the expert’s knowledge and some experimental data, without needing the calculation of complex kinetic as well as thermodynamic parameters related to the corresponding process. In addition, the structures of the developed fuzzy models were optimized to improve the model performance according to the analysis of the initial results. The model developments didn’t require a high number of experimental data, and this feature is especially interesting when dealing with the process conditions in which data gathering is expensive or the accuracy of data is low.

The main results

The overall accuracy as well as the properties of the developed models were compared. The type-2 Mamdani fuzzy model proved to be the best model, using which, the methanol conversion, H₂ yield, and CO yield were predicted with accuracies of 67%, 91%, and 83%, respectively.

Keywords

Cu-Zn/ZrO2 catalyst

Methanol conversion

artificial intelligence

Fuzzy Logic

Modeling

Subjects

nano-catalyst

[1] Bagherzadeh S.B. and Haghighi M., Plasma-enhanced comparative hydrothermal and coprecipitation preparation of CuO/ZnO/Al2O3 nanocatalyst used in hydrogen production via methanol steam reforming, Energy Conversion and Management, 142, 452–465, 2017.
[2] Peng L., Mai J., Hu P., Lai X. and Lin Z., Optimum design of the slotted-interdigitated channels flow field for proton exchange membrane fuel cells with consideration of the gas diffusion layer intrusion, Renewable Energy, 36, 1413–1420, 2011.
[3] Danerol A.S., Bas C., Flandin L., Claude E. and Alberola N.D., Influence of ageing in fuel cell on membrane/electrodes interfaces. Journal of Power Sources, 196, 3479–3484, 2011.
[4] Herdem M.S., Younessi-Sinaki M., Farhad S. and Hamdullahpur F., An overview of the methanol reforming process: Comparison of fuels, catalysts, reformers, and systems, International Journal of Energy Research, 43, 5076-5105, 2019.
[5] Tosti S., Basile A., Borgognoni F., Capaldo V., Cordiner S., Cave S.D., Gallucci F., Rizzello C., Santucci A. and Traversa E., Low temperature ethanol steam reforming in a Pd-Ag membrane reactor. Part 1: Ru-based catalyst, Journal of Membrane Science, 308, 250–257, 2008.
[6] Liu Q., Jin H., Hong H., Sui J., Ji J. and Dang J., Performance analysis of a mid and low temperature solar receiver/reactor for hydrogen production with methanol steam reforming, International Journal of Energy Research, 35, 52-60, 2010.
[7] Purnama H., Ressler T., Jentoft R.E., Soerijanto H., Schlogl R. and Schomacker R., CO formation/selectivity for steam reforming of methanol with a commercial CuO/ZnO/Al2O3 catalyst, Applied Catalysis: A-General, 259, 200483–200494, 2011.
[8] Wang C., Liu N., Pan L., Wang S., Yuang Z. and Wang S., Measurement of concentration profiles over ZnO–Cr2O3/CeO2–ZrO2 monolithic catalyst in oxidative steam reforming of methanol. Fuel Process Technology, 88, 65-71, 2007.
[9] Thattarathody R. and Sheintuch M., Kinetics and dynamics of methanol steam reforming on CuO/ZnO/alumina catalyst, Applied Catalysis: A-Gen. 540, 47-56, 2017.
[10] Aouad S., Gennequin C., Mrad M., Tidahy H.L., Estephane J., Aboukaïs A. and Abi-Aad E., Steam reforming of methanol over ruthenium impregnated ceria, alumina and ceria–alumina catalysts. International Journal of Energy Research, 40, 1287-1292, 2016.
[11] Lee J.K., Ko J. B. and Kim D.H., Methanol steam reforming over Cu/ZnO/Al2O3 catalyst: kinetics and effectiveness factor, Applied Catalysis: A-General, 278, 25–35, 2004.
[12] Amiri Y. and Moghaddas J., Cogeled copperesilica aerogel as a catalyst in hydrogen production from methanol steam reforming, International Journal of Hydrogen Energy, 40, 1472-1480, 2015.
[13] Ajamein H., Haghighi M. and Alaei S., The role of various fuels on microwave-enhanced combustion synthesis of CuO/ZnO/ Al2O3 nanocatalyst used in hydrogen production via methanol steam reforming, Energy Conversion and Management, 137, 61-73, 2017.
[14] Ribeirinha P., Boaventura M., Lopes J.C., Sousa J.M. and Mendes A., Study of different designs of methanol steam reformers: experiment and modeling. International Journal of Hydrogen Energy, 39, 19970-19981, 2014.
[15] Amphlett J.C., Creber K.A.M., Davis J.M., Mann R.F., Peppley B.A. and Stokes D.M., Hydrogen production by steam reforming of methanol for polymer electrolyte fuel cells, International Journal of Hydrogen Energy, 19, 131-137, 1994.
[16] Lytkina A.A., Zhilyaeva N.A., Ermilova M.M., Orekhova N.V. and Yaroslavtsev A.B., Influence of the support structure and composition of Ni-Cu-based catalysts on hydrogen production by methanol steam reforming, International Journal of Hydrogen Energy, 40, 9677-9684, 2015.
[17] Silva H., Mateos-Pedrero C., Ribeirinha P., Boaventura M. and Mendes A., Low-temperature methanol steam reforming kinetics over a novel Cu-Zr-DyAl catalyst, Reaction, Kinetics and Mechanism, 115, 321-339, 2015.
[18] Witoon T., Chalorngtham J., Dumrongbunditkul P., Chareonpanich M. and Limtrakul J., CO2 hydrogenation to methanol over Cu/ZrO2 catalysts: effects of zirconia phases, Chemical Engineering Journal, 293, 327-336, 2016.
[19] Qi Y., Cheng Z.M. and Zhou Z.M., Steam reforming of methane over Ni catalysts prepared from hydrotalcite-type precursors: catalytic activity and reaction kinetics, Chinese Journal of Chemical Engineering, 23, 76-85, 2015.
[20] Park J.E., Yim S.D., Kim C.S. and Park E.D., Steam reforming of methanol over Cu/ZnO/ZrO2/Al2O3 catalyst, International Journal of Hydrogen Energy,39, 11517-11527, 2014.
[21] Chang C.C., Wang J.W., Chang C.T., Liaw B.J. and Chen Y.Z., Effect of ZrO2 on steam reforming of methanol over CuO/ZnO/ZrO2/Al2O3 catalysts, Chemical Engineering Journal, 192, 350-356, 2012.
[22] Patel S. and Pant K.K., Experimental study and mechanistic kinetic modeling for selective production of hydrogen via catalytic steam reforming of methanol, Chemical Engineering Science, 62, 5425 –5435, 2007.
[23] Silva S. S., Brandao L., Sousa J.M and Mendes A., Catalysts for methanol steam reforming-A review, Applied Catalysis B- Environmental, 99, 43-57, 2010.
[24] Tong W.Y., Cheung K., West A., Yu K.M. and Tsang S.C.E., Direct methanol steam reforming to hydrogen over Cu-Zn-GaOx catalysts without CO post-treatment: mechanistic considerations, Physical Chemistry Chemical Physics journal, 15, 7240-7248, 2013.
[25] Ozkan O. and Akin A.N., Thermodynamic analysis of methanol steam reforming to produce hydrogen for HT-PEMFC: An optimization study, International Journal of Hydrogen Energy, 44, 14117-14126, 2019.
[26] Pashchenko D., Gnutikova M. and Karpilov I., Comparison study of thermochemical waste-heat recuperation by steam reforming of liquid biofuels, International Journal of Hydrogen Energy, 45, 4174-4181, 2020.
[27] Gaber C., Demuth M., Schluckner C. and Hochenauer C., Thermochemical analysis and experimental investigation of a recuperative waste heat recovery system for the tri-reforming
of light oil, Energy Conversion and Management, 195, 302-312, 2019.
[28] Chakravarthy V.K., Daw C.S., Pihl J.A. and Conklin J.C., Study of the theoretical potential of thermochemical exhaust heat recuperation for internal combustion engines, Energy &
Fuels, 24, 1529-1537, 2010.
[29] Jasper A.W., Klippenstein S.J., Harding L.B. and Ruscic B., Kinetics of the reaction of methyl radical with hydroxyl radical and methanol decomposition, Journal of Physica Chemistry: A, 111, 3932-3950.,2007.
[30] Jiang C.J., Trimm D.L., Wainwright M.S. and Cant N.W., Kinetic mechanism for the reaction between methanol and water over a Cu-ZnO-Al2O3 catalyst, Applied Catalysis: A-General, 97, 145–158, 1993.
[31] Peppley B.A., Amphlett J.C., Kearns L.M. and Mann R.F., Methanol steam reforming on
Cu/ZnO/Al2O3 catalysts. Part 2. A comprehensive kinetic model, Applied Catalysis: A-General, 179, 31-49, 1999.
[32] Wan Y., Zhou Z. and Cheng Z., Hydrogen Production from Steam Reforming of Methanol over CuO/ZnO/Al2O3 Catalysts: Catalytic Performance and Kinetic Modeling, Chinese Journal of Chemical Engineering, 24, 1186-1194, 2016.
[33] Zhang F., Shi Y., Yang L. and Du X., kinetic for hydrogen production by methanol steam reforming in fluidized bed reactor, Science Bulletin, 61, 401-405, 2016;.
[34] Eghbal Ahmadi M.H. and Mosayebi A., Fischer–Tropsch synthesis over Co-Ni/Al2O3 catalyst: Comparison between comprehensive kinetic modeling, Artificial Neural Network, and a novel hybrid GA-Fuzzy models, Journal of the Taiwan Institute of Chemical Engineers, 127, 32-45, 2021.
[35] Batebi D, Abedini R, Mosayebi A. Kinetic modeling of combined steam and CO2 reforming of methane over Ni-Pd/Al2O3 catalyst using Langmuir-Hinshelwood and Langmuir–Freundlich isotherms. Ind Eng Chem Res, 60: 851-63, 2021.
[36] Mosayebi A, Abedini R. Effect of synthesis solution pH of Co/γ-Al2O3 catalyst on its catalytic properties for methane conversion to syngas. J Fuel Chem Technol, 46: 311-8, 2018.
[37] Mosayebi A, Eghbal Ahmadi MH. Combined steam and dry reforming of methanol process to syngas formation: Kinetic modeling and thermodynamic equilibrium analysis. Energy, 261:125254, 2022.
[38] Shariati J, Haghtalab A, Mosayebi A. Fischer–Tropsch synthesis using Co and Co-Ru bifunctional nanocatalyst supported on carbon nanotube prepared via chemical reduction method. J Energy Chem, 28: 9-22, 2019.
[39] Zimmermann H. J., Fuzzy set theory. Wiley interdisciplinary reviews, computational statistics, 2, 317-332, 2010.
[40] Mamdani E. H., Applications of fuzzy algorithms for control of simple dynamic plant,
Proceedings of the IEEE, 121, 1585-1588, 1974.
[41] Takagi T. and Sugeno M., Fuzzy identification of systems and its applications to modeling and control, IEEE transactions on systems, man, and cybernetics, 1, 116-132, 1985.
[42] Eghbal Ahmadi M. H., Royaee S. J., Tayyebi S. and Boozarjomehry R. B., A new insight into implementing Mamdani fuzzy inference system for dynamic process modeling: Application on flash separator fuzzy dynamic modeling, Engineering Applications of Artificial Intelligence, 90, 103485, 2020.
[43] Eghbal Ahmadi M. H., Royaee S. J., Tayyebi S. and Boozarjomehry, R. B., Development of Genetically tuned Fuzzy dynamic model for nonlinear dynamical systems: Application on reaction section of Tennessee Eastman process, Scientia Iranica, 25, 3381-3390, 2018.
[44] Karnik N. N., Mendel J. M. and Liang Q., Type-2 fuzzy logic systems, IEEE transactions on Fuzzy Systems, 7, 643-658, 1999.
[45] Cordón O., A historical review of evolutionary learning methods for Mamdani-type fuzzy rule-based systems: Designing interpretable genetic fuzzy systems, International journal of approximate reasoning, 52, 894-913, 2011.