A study on mass transfer modelling in SOFC anode: Comparison of diffusion mass transfer models for estimation of diffusion overpotential

• Autorzy: Ramakrishnan P. , Sahoo Abanti

Identyfikatory

DOI

10.24425/cpe.2023.142293

• Języki publikacji: EN

Abstrakty

EN

The mathematical approach to SOFC modelling helps to reduce dependence on the experimental approach. In the current study, six different diffusion mass transfer models were compared to more accurately predict the process behavior of fuel and product diffusion for SOFC anode. The prediction accuracy of the models was extensively studied over a range of parameters. New models were included as compared to previous studies. The Knudsen diffusion phenomenon was considered in all the models. The stoichiometric flux ratio approach was used. All the models were validated against experimental data for a binary (CO-CO2) and a ternary fuel system (H2-15 H2O-Ar). For ternary system, the pressure gradient is important for pore radius below 0.6 μm and current density above 0.5 A/cm2. For binary system, the pressure gradient may be ignored. The analysis indicates that the MBFM is identified to be the best performing and versatile model under critical SOFC operating conditions such as fuel composition and cell temperature. The diffusive slip phenomenon included in MBFM is useful in SOFC operating conditions when fuel contains heavy molecules. The DGMFM is a good approximation of DGM for the binary system.

Słowa kluczowe

EN

Solid Oxide Fuel Cell; Knudsen diffusion; diffusion overpotential; pressure gradient; tortuosity factor

PL

ogniwo paliwowe ze stałym tlenkiem; dyfuzja Knudsena; gradient ciśnienia; współczynnik krętości

• Wydawca: Komitet Inżynierii Chemicznej i Procesowej Polskiej Akademii Nauk
• Czasopismo: Chemical and Process Engineering : New Frontiers
• Rocznik: 2023
• Tom: Vol. 44, nr 1
• Strony: art. no. e4
• Opis fizyczny: Bibliogr. 40 poz.

Twórcy

autor

Ramakrishnan P.

• NIT Rourkela, Department of Chemical Engineering, Rourkela, Sector-1, Sundergarh, Odisha, India, 769008

• https://orcid.org/0000-0001-6810-0866

autor

Sahoo Abanti

• NIT Rourkela, Department of Chemical Engineering, Rourkela, Sector-1, Sundergarh, Odisha, India, 769008

• https://orcid.org/0000-0002-5607-8988

Bibliografia

• 1. Abdalla A.M., Hossain S., Azad A.T., Petra P.M.I., Begum F., Eriksson S.G., Azad A.K., 2018. Nanomaterials for solid oxide fuel cells: A review. Renewable Sustainable Energy Rev., 82, 353–368. DOI: 10.1016/J.RSER.2017.09.046.
• 2. Bao C., Jiang Z., Zhang X., 2016. Modeling mass transfer in solid oxide fuel cell anode: I. Comparison between Fickian, Stefan– Maxwell and dusty-gas models. J. Power Sources, 310, 32–40. DOI: 10.1016/j.jpowsour.2016.01.099.
• 3. Błesznowski M., Sikora M., Kupecki J., Makowski Ł., Orciuch W., 2022. Mathematical approaches to modelling the mass transfer process in solid oxide fuel cell anode. Energy, 239, 121878. DOI: 10.1016/j.energy.2021.121878.
• 4. Bove R., Ubertini S. (Eds.), 2008. Modeling Solid Oxide Fuel Cells: Methods, Procedures and Techniques. Springer Dordrecht. DOI: 10.1007/978-1-4020-6995-6.
• 5. Cayan F.N., Pakalapati S.R., Elizalde-Blancas F., Celik I., 2009. On modeling multi-component diffusion inside the porous anode of solid oxide fuel cells using Fick’s model. J. Power Sources, 192(2), 467–474. DOI: 10.1016/j.jpowsour. 2009.03.026.
• 6. Chou Y.S., Hardy J., Marina O.A., 2022. Leak test for solid oxid fuel cells and solid oxide electrolysis cells. Front. Energy Res., 10, 1459. DOI: 10.3389/fenrg.2022.945788.
• 7. Gholaminezhad I., Paydar M.H., Jafarpur K., Paydar S., 2017. Multi-scale mathematical modeling of methane-fueled SOFCs: Predicting limiting current density using a modified
• 8. Fick’s model. Energy Convers. Manage., 148, 222–237. DOI: 10.1016/j.enconman.2017.05.071.
• 9. Haberman B.A., Young J.B., 2006. Diffusion and chemical reaction in the porous structures of Solid Oxide Fuel Cells. J. Fuel Cell Sci. Technol., 3, 312-321. DOI: 10.1115/1.2211637.
• 10. He W., Lv W., Dickerson J., 2014. Gas transport in Solid Oxide
• 11. Fuel Cells. Springer Cham. DOI: 10.1007/978-3-319-09737-4.
• 12. Jacobson A.J., 2010. Materials for Solid Oxide Fuel Cells. Chem. Mater., 22, 660–674. DOI: 10.1021/cm902640j.
• 13. Kerkhof P.J.A.M., 1996. A modified Maxwell-Stefan model for transport through inert membranes: the binary friction model. Chem. Eng. J. Biochem. Eng. J., 64, 319–343. DOI: 10.1016/S0923-0467(96)03134-X.
• 14. Kong W., Gao X., Liu S., Su S., Chen D., 2014. Optimization of the interconnect ribs for a cathode-supported Solid Oxide Fuel Cell. Energies, 7, 295–313. DOI: 10.3390/en7010295.
• 15. Kong W., Zhu H., Fei Z., Lin Z., 2012. A modified dusty gas model in the form of a Fick’s model for the prediction of multicomponent mass transport in a solid oxide fuel cell anode. J. Power Sources, 206, 171–178. DOI: 10.1016/j.jpowsour.2012.01.107.
• 16. Krishna R., Wesselingh J., 1997. The Maxwell-Stefan approach to mass transfer. Chem. Eng. Sci., 52, 861–911. DOI: 10.1016/S0009-2509(96)00458-7.
• 17. Lehnert W., Meusinger J., Thom F., 2000. Modelling of gas transport phenomena in SOFC anodes. J. Power Sources, 87, 57–63. DOI: 10.1016/S0378-7753(99)00356-0.
• 18. Mason E.A., Malinauskas A.P., 1983. Gas transport in porous media: The dusty-gas model. Elsevier Scientific Pub. Co., Amsterdam, New York.
• 19. Milewski J., Lewandowski J., 2011. Comparative analysis of time constants in Solid Oxide Fuel Cell processes – selection of key processes for modeling power systems. J. Power Technol., 91(1), 1–5.
• 20. Modjtahedi A., Hedayat N., Chuang S.S.C., 2016. Diffusion-limited electrochemical oxidation of H2/CO on Ni-anode catalyst in a CH4/CO2-solid oxide fuel cell. Catal. Today, 278, 227–236. DOI: 10.1016/j.cattod.2015.12.026.
• 21. Neufeld P.D., Janzen A.R., Aziz R.A., 1972. Empirical equations to calculate 16 of the transport collision integrals Ω(l;s)∗ for the Lennard–Jones (12-6) potential. J. Chem. Phys., 57, 1100–1102. DOI: 10.1063/1.1678363.
• 22. Ni M., Leung D.Y.C., Leung M.K.H., 2008. Importance of pressure gradient in solid oxide fuel cell electrodes for modeling study. J. Power Sources, 183, 668–673. DOI: 10.1016/j.jpowsour.2008.05.013.
• 23. O’Hayre R., Cha S.-W., Colella W., Prinz F.B. (2016). Fuel Cell Fundamentals. 3rd edition, Wiley, 206–207.
• 24. Pant L.M., Mitra S.K., Secanell M., 2013. A generalized mathematical model to study gas transport in PEMFC porous media. Int. J. Heat Mass Transfer, 58, 70–79. DOI: 10.1016/j.ijheat masstransfer.2012.11.023.
• 25. Poling B., Prausnitz J., O’Connell J.P., 2000. The properties of gases and liquids. 5th edition. McGraw-Hill.
• 26. Shaikh S.P.S., Muchtar A., Somalu M.R., 2015. A review on the selection of anode materials for solid-oxide fuel cells. Renewable Sustainable Energy Rev., 51, 1–8. DOI: 10.1016/j.rser.2015.05.069.
• 27. Singhal S.C., Kendall K., 2003. High-temperature Solid Oxide Fuel Cells: Fundamentals, design and applications. Elsevier. DOI: 10.1016/B978-1-85617-387-2.X5016-8.
• 28. Suwanwarangkul R., Croiset E., Fowler M.W., Douglas P.L.,
• 29. Entchev E., Douglas M.A., 2003. Performance comparison of Fick’s, dusty-gas and Stefan–Maxwell models to predict the concentration overpotential of a SOFC anode. J. Power
• 30. Sources, 122, 9–18. DOI: 10.1016/S0378-7753(02)00724-3.
• 31. Taylor R., Krishna R., 1993. Multicomponent mass transfer. John Wiley & Sons, Inc.
• 32. Tseronis K., Kookos I.K., Theodoropoulos C., 2008. Modelling mass transport in solid oxide fuel cell anodes: a case for a multidimensional dusty gas-based model. Chem. Eng. Sci., 63, 5626–5638. DOI: 10.1016/j.ces.2008.07.037.
• 33. Vogler M., Bieberle-Hütter A., Gauckler L., Warnatz J., Bessler W.G., 2009. Modelling study of surface reactions, diffusion, and spillover at a Ni/YSZ patterned anode. J. Electrochem. Soc., 156, B663. DOI: 10.1149/1.3095477.
• 34. Vural Y., Ma L., Ingham D.B., Pourkashanian M., 2010. Comparison of the multicomponent mass transfer models for the prediction of the concentration overpotential for solid oxide fuelcell anodes. J. Power Sources, 195, 4893–4904. DOI: 10.1016/j.jpowsour.2010.01.033.
• 35. Wang S., Worek W.M., Minkowycz W.J., 2012. Performance comparison of the mass transfer models with internal reforming for solid oxide fuel cell anodes. Int. J. Heat Mass Transfer, 55, 3933–3945. DOI: 10.1016/j.ijheatmasstransfer.2012.03.024.
• 36. Yakabe H., Hishinuma M., Uratani M., Matsuzaki Y., Yasuda I., 2000. Evaluation and modeling of performance of anodesupported solid oxide fuel cell. J. Power Sources, 86, 423–431. DOI: 10.1016/S0378-7753(99)00444-9.
• 37. Yang F., Gu J., Ye L., Zhang Z., Rao G., Liang Y., Wen K., Zhao J., Goodenough J.B., He W., 2016. Justifying the significance of Knudsen diffusion in solid oxide fuel cells. Energy, 95, 242–246. DOI: 10.1016/j.energy.2015.12.022.
• 38. Zhou W., Jiao Y., Li S.-D., Shao Z., 2016. Anodes for carbonfueled Solid Oxide Fuel Cells. ChemElectroChem, 3, 193–203. DOI: 10.1002/celc.201500420.
• 39. Zhu H., Kee R.J., 2003. A general mathematical model for analyzing the performance of fuel-cell membrane-electrode assemblies. J. Power Sources, 117, 61–74. DOI: 10.1016/S0378-7753(03)00358-6.
• 40. Zhu H., Kee R.J., Janardhanan V.M., Deutschmann O., Goodwin D.G., 2005. Modeling elementary heterogeneous chemistry and electrochemistry in Solid-Oxide Fuel Cells. J. Electrochem. Soc., 152, A2427. DOI: 10.1149/1.2116607.

Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).