An investigation on effect of backbone geometric anisotropy on the performance of infiltrated SOFC electrodes

Document Type : Research Paper

Authors

1 Mechanical Engineering Department, Babol Noshirvani University of Technology, Babol, Iran

2 School of Mechanical Engineering, College of Engineering, University of Tehran,Tehran, Iran

3 School of Metallurgy and Materials Engineering, College of Engineering, University of Tehran, Iran

Abstract

Design of optimal microstructures for infiltrated solid oxide fuel cell (SOFC) electrodes is a complicated process because of the multitude of the electrochemical and physical phenomena taking place in the electrodes in different temperatures, current densities and reactant flow rates. In this study, a stochastic geometric modeling method is used to create a range of digitally realized infiltrated SOFC electrode microstructures to extract their geometry-related electrochemical and physical properties. Triple Phase Boundary (TPB), active surface density of particles along with the gas transport factor is evaluated in those realized models to adapt for various infiltration strategies. Recently, additive manufacturing or freeze type casting methods enable researchers to investigate the performance of directional electrodes to get the maximum electrochemical reaction sites, gas diffusivity and ionic conductivity simultaneously. A series of directional backbones with different amount of virtually deposited electrocatalyst particles are characterized in the first step. The database of microstructural parameters (inputs) and effective geometric properties (outputs) is used to train a range neural network. A microstructure property hull is created using the best neural network model to discover the range of effective properties, their relative behaviour and optimum microstructure.  The characteristics of models is shown that there is not any contradiction between the high level of TPB and contact surface density of particles, but the highest amount of gas diffusivity can be found in the microstructures with lower level of reaction sites. Also increasing the contact surface density has a negative effect on gas transport but the high level of TPB density is feasible in the full range of microstructures. In the other hand, TPB density and gas diffusion into the models are inversely related, although there are a limited number of microstructures with high level of reaction sites and acceptable gas diffusivity. Finally, using a simple optimization process, the microstructures with the highest level of reaction sites and gas transport factor are identified which have the backbone porosity of about 50%, and  extremely higher gain growth rate normal to the electrolyte. Additive manufacturing and 3D printing methods will enhance researchers in the future to create the real directional electrodes on the base of these proposed models.

Keywords

References

[1] Minh N.Q., Takahashi T., Science and Technology of Ceramic Fuel Cells (1995) Elsevier.
[2] Steele B.C., Heinzel A., Materials for Fuel-Cell Technologies, Nature (2001) 414(6861): 345-52.
[3] Minh N.Q., Ceramic Fuel Cells, Journal of the American Ceramic Society (1993) 76(3): 563-588.
[4] Brown M., Primdahl S., Mogensen M., Structure/Performance Relations for Ni/Yttria‐Stabilized Zirconia Anodes for Solid Oxide Fuel Cells, Journal of the Electrochemical Society, (2000)147(2):475-85.
[5] Smith J., Chen A., Gostovic D., Hickey D., Kundinger D., Duncan K., Evaluation of the Relationship between Cathode Microstructure and Electrochemical Behavior for SOFCs, Solid State Ionics, (2009)180(1):90-8.
[6] Kishimoto  M.,  Lomberg  M.,  Ruiz-Trejo E., Brandon N.P., Enhanced Triple-Phase Boundary Density in Infiltrated Electrodes for Solid Oxide Fuel Cells Demonstrated by High-Resolution Tomography, Journal of Power Sources, (2014)266:291-5.
[7] Ni M., Zhao T.S., Solid Oxide Fuel Cells, Royal Society of Chemistry (2013).
[8] Shearing P., Brett D., Brandon N., Towards Intelligent Engineering of SOFC Electrodes, A Review of Advanced Microstructural Characterisation Techniques, International Materials Reviews (2010)55(6): 347-363.
[9] Jiang S.P., Nanoscale and Nano-Structured Electrodes of Solid Oxide Fuel Cells by Infiltration, Advances and Challenges, International Journal of Hydrogen Energy (2012) 37(1): 449-470.
[10] Vohs J.M., Gorte R.J., High‐Performance SOFC Cathodes Prepared by Infiltration. Advanced Materials (2009) 21(9): 943-956.
[11] Sarikaya A., Petrovsky V., Dogan F., Development of the Anode Pore Structure and its Effects on the Performance of Solid Oxide Fuel Cells, International Journal of Hydrogen Energy (2013) 38(24): 10081-10091.
[12] Othman M.H.D., Droushiotis N., Wu Z., Kelsall G., Li K., High‐Performance, Anode‐Supported, Microtubular SOFC Prepared from Single‐Step‐Fabricated, Dual‐Layer Hollow Fibers. Advanced Materials (2011) 23(21): 2480-2483.
[13] Cable T.L., Setlock J.A., Farmer S.C., Eckel A.J., Regenerative Performance of the NASA Symmetrical Solid Oxide Fuel Cell Design, International Journal of Applied Ceramic Technology (2011) 8(1): 1-12.
[14] Gannon P., Sofie S., Deibert M., Smith R., Gorokhovsky V., Thin Film YSZ Coatings on Functionally Graded Freeze Cast NiO/YSZ SOFC Anode Supports, Journal of Applied Electrochemistry (2009)39(4): 497-502.
[15] Chen Y., Bunch J., Li T., Mao Z., Chen F., Novel Functionally Graded Acicular Electrode for Solid Oxide Cells Fabricated by the Freeze-Tape-Casting Process, Journal of Power Sources (2012)213: 93-99.
[16] Chen Y., Zhang Y., Baker J., Majumdar P., Yang Z., Han M., Hierarchically Oriented Macroporous Anode-Supported Solid Oxide Fuel Cell with thin Ceria Electrolyte Film, ACS Applied  Materials & Interfaces (2014) 6(7): 5130-5136.
[17] Sofie S.W., Fabrication of Functionally Graded and Aligned Porosity in Thin Ceramic Substrates With the Novel Freeze–Tape‐Casting Process. Journal of the American Ceramic Society (2007) 90(7): 2024-2031.
[18] Hen Y., Liu Q., Yang Z., Chen F., Han M., High Performance Low Temperature Solid Oxide Fuel Cells with Novel Electrode Architecture, RSC Advances (2012) 2(32): 12118-12121.
[19] Chen Y., Lin Y., Zhang Y., Wang S., Su D., Yang Z., Low Temperature Solid Oxide Fuel Cells with Hierarchically Porous Cathode Nano-Network, Nano Energy (2014)8: 25-33.
[20] Chen Y., Zhang Y., Lin Y., Yang Z., Su D., Han M., Direct-Methane Solid Oxide Fuel Cells with Hierarchically Porous Ni-Based Anode Deposited with Nanocatalyst layer, Nano Energy (2014) 10: 1-9.
[21] Torabi A., Hanifi A.R., Etsell T.H., Sarkar P., Effects of Porous Support Microstructure on Performance of Infiltrated Electrodes in Solid Oxide Fuel Cells, Journal of the Electrochemical Society (2011)159(2): B201-B210.
[22] Cassidy M., Doherty D.J., Yue X., Irvine J.T., Development of Tailored Porous Microstructures for Infiltrated Catalyst Electrodes by Aqueous Tape Casting Methods. ECS Transactions (2015) 68(1): 2047-2056.
[23] Zhang Y., Sun Q., Xia C., Ni M., Geometric Properties of Nanostructured Solid oxide Fuel Cell Electrodes, Journal of The Electrochemical Society (2013)160(3): F278-F289.
[24]Zhang Y., Ni M., Xia C., Microstructural insights into dual-phase infiltrated solid oxide fuel cell electrodes. Journal of The Electrochemical Society (2013)160(8): F834-F839.
[25] Bertei A., Pharoah J.G., Gawel D.A., Nicolella C., Microstructural Modeling and Effective Properties of Infiltrated SOFC Electrodes, ECS Transactions (2013)57(1): 2527-2536.
[26] Synodis M.J., Porter C.L., Vo N.M., Reszka A.J., Gross M.D., Snyder R.C., A Model to Predict Percolation Threshold and Effective Conductivity of Infiltrated Electrodes for Solid Oxide Fuel Cells. Journal of The Electrochemical Society (2013)160(11): F1216-F1224.
[27]Hardjo E.F., Monder D.S., Karan K., An Effective Property Model for Infiltrated Electrodes in Solid Oxide Fuel Cells. Journal of The Electrochemical Society (2014)161(1): F83-F93.
[28]Reszka A.J., Snyder R.C., Gross M.D., Insights    into   the    Design    of    SOFC nfiltrated Electrodes with Optimized Active TPB Density via Mechanistic Modeling. Journal of The Electrochemical Society (2014)161(12): F1176-F1183.
[29] Kishimoto M., Lomberg M., Ruiz-Trejo E., Brandon N.P., Towards the Microstructural Optimization of SOFC Electrodes Using Nano Particle Infiltration. ECS Transactions (2014) 64(2): 93-102.
[30] Jemeı S., Hissel D., Péra M.C., Kauffmann J.M., On-Board Fuel Cell Power Supply Modeling on the Basis of Neural Network Methodology, Journal of Power Sources (2003)124(2): 479-486.
[31]Ou S., Achenie L.E., A hybrid neural network model for PEM fuel cells. Journal of Power Sources (2005)140(2): 319-330.
[32] Hagan M.T., Demuth H.B., Beale M.H., De Jesús O.,  Neural Network Design, PWS Publishing Company Boston(1996) 20.
[33] Marra D., Sorrentino M., Pianese C., Iwanschitz B.,  A Neural Network Estimator of Solid Oxide Fuel Cell Performance for on-Field Diagnostics and Prognostics Applications, Journal of Power Sources (2013)241: 320-329.
[34]Bozorgmehri S., Hamedi M., Modeling and Optimization of Anode‐Supported Solid Oxide Fuel Cells on Cell Parameters via Artificial Neural Network and Genetic Algorithm. Fuel Cells (2012) 12(1): 11-23.
[35] Tafazoli M., Shakeri M., Baniassadi M., Babaei A., Geometric Modeling of Infiltrated Solid Oxide Fuel Cell Electrodes with Directional Backbones, Fuel Cells (2017)17(1):67-74.
[36] Baniassadi M., Ahzi S., Garmestani H., Ruch D., Remond Y., New Approximate Solution for N-Point Correlation Functions for Heterogeneous Materials, Journal of the Mechanics and Physics of Solids (2012)60(1): 104-119.
[37] Baniassadi M., Garmestani H., Li D., Ahzi S., Khaleel M., Sun X., Three-Phase Solid Oxide Fuel Cell Anode Microstructure Realization using Two-Point Correlation Functions, Acta Materialia (2011)59(1): 30-43.
[38] Rüger B., Joos J., Weber A., Carraro T., Ivers-Tiffée E., 3D Electrode Microstructure Reconstruction and Modelling, ECS Transactions (2009)25(2): 1211-1220.
[39] Joos J., Rüger B., Carraro T., Weber A., Ivers-Tiffée E., Electrode Reconstruction by FIB/SEM and Microstructure Modeling, ECS Transactions (2010)28(11): 81-91.
[40]Cai Q., Adjiman C.S., Brandon N.P., Modelling the 3D microstructure and performance of solid oxide fuel cell electrodes: computational parameters. Electrochimica Acta (2011)56(16): 5804-5814.
[41]Jiang Z., C. Xia, Chen F., Nano-Structured     Composite    Cathodes    for intermediate-temperature solid oxide fuel cells via an infiltration/impregnation technique. Electrochimica Acta (2010) 55(11): 3595-3605.
[42]Adler S.B., Lane J., Steele B., Electrode kinetics of porous mixed‐conducting oxygen electrodes. Journal of the Electrochemical Society (1996)143(11): 3554-3564.
[43]Babaei A., Jiang S.P., Li J., Electrocatalytic promotion of palladium nanoparticles on hydrogen oxidation on Ni/GDC anodes of SOFCs via spillover. Journal of the Electrochemical Society (2009)156(9): B1022-B1029.
[44]Janardhanan V.M., Heuveline V., Deutschmann O., Three-phase boundary length in solid-oxide fuel cells: A mathematical model. Journal of Power Sources (2008)178(1): 368-372.
[45] Kishimoto M., Lomberg M., Ruiz-Trejo E., Brandon N.P.,Towards the Design-Led Optimization of Solid Oxide Fuel Cell Electrodes. in ECS Conference on Electrochemical Energy Conversion & Storage with SOFC-XIV (2015).
[46]Cronin  J.S., Three-Dimensional Structure Combined with Electrochemical Performance Analysis for Solid Oxide Fuel Cell Electrodes (2012).
[47] Shikazono N., Kanno D., Matsuzaki K., Teshima H., Sumino S., Kasagi N., Numerical Assessment of SOFC Anode Polarization Based on Three-Dimensional Model Microstructure Reconstructed from FIB-SEM Images, Journal of The Electrochemical Society (2010) 157(5): B665-B672.
[48]He W., Lv W., Dickerson J., Gas transport in solid oxide fuel cells (2014) Springer.
[49] Fullwood D.T., Niezgoda S.R., Adams B.L., Kalidindi S.R., Microstructure Sensitive Design for Performance Optimization. Progress in Materials Science (2010)55(6): 477-562.
[50]Adams B.L., Kalidindi S., Fullwood D.T., Microstructure-Sensitive Design for Performance Optimization,Butterworth-Heinemann (2013).
Energy Equipment and Systems
Volume 5, Issue 3
September 2017
Pages 251-264

Files

Share

How to cite

Statistics