Topology-informed machine learning for efficient prediction of solid oxide fuel cell electrode polarization

Composite electrodes comprising a rare-earth nickelate phase and a doped rare-earth ceria phase with a high level of rare-earth doping have been studied as oxygen electrodes. While rare-earth nickelates have shown great promise as oxygen electrodes in both solid oxide fuel cells (SOFC) and solid oxide electrolysis cells (SOECs), they become unstable in contact with rare-earth doped ceria. In this work we describe a strategy to eliminate this instability and enable the use of these electrodes as stable high performance oxygen electrodes in both SOFC and SOEC applications. The performance of such composite electrodes is explored using a symmetrical cell approach, and through the electrical conductivity relaxation (ECR) method and compare it to state-of-the-art oxygen electrodes comprising strontium doped lanthanum manganite (LSM) – yttria stabilized zirconia (YSZ) composite electrodes. The symmetrical cell tests which reveal the stabilized nickelate-ceria electrodes to be superior, are also well-correlated with the results of testing complete cells in both SOFC and SOEC modes. Based on these results we make the case for deploying these stabilized nickelate-ceria composite electrodes as oxygen electrodes in reversible SOFC-SOEC systems.

Investigation of the active thickness of solid oxide fuel cell electrodes using a 3D microstructure model

Recent progress in micro-scale three-dimensional (3D) characterization techniques such as focused ion beam – scanning electron microscopy (FIB-SEM) and X-ray nanotomography has brought unprecedented opportunities in linking material microstructure to performance and properties. The link between solid oxide fuel cell (SOFC) electrode microstructure and performance is sometimes established by effective medium theory, where effective performance parameters are calculated from a representative volume element (RVE), an adequate volume that statistically represents global microstructure. However, different from performance, degradation and failure have not been addressed by mean parameters from effective medium theory. With the advent of modern 3D characterization techniques, there are new approaches in linking microstructure and degradation. This work aims to emphasize distributions (and outliers), rather than the mean, in better establishing the link between microstructure and degradation, failure, and performance. Using an open source finite element framework (MOOSE, Idaho National Laboratory) on a high performance computing platform (Joule, National Energy Technology Laboratory), a numerical transport and reaction model is applied to microstructural meshes to compute local distributions of electrochemical parameters. The microstructural meshes are obtained from the plasma sourced FIB-SEM characterization of a commercial SOFC electrode. The RVE size with respect to the computed distributions is determined based on examining the distributions from a series of microstructural meshes with various sizes. To validate the distributions, the averaged numbers from the distributions are compared with the effective medium theories in the literature. Finally, features such as the tails of the distributions and the local gradients of the electrochemical parameters are highlighted and discussed.

Quantitative estimation of triple phase boundaries in solid oxide fuel cell electrodes via artificial neural network

Synthetical designing of solid oxide fuel cell electrodes: Effect of particle size and volume fraction

This study aims to improve the understanding of sloshing phenomena in partially filled movable storage systems, particularly in rectangular tanks where experimental data remain limited. A multi-approach methodology was employed by combining analytical and numerical solutions validated with experimental work and supported with various machine learning (ML) prediction approaches. The results were validated by conducting experimental investigations at three different liquid heights (150, 100, and 50) mm. The accuracy of the ML model in predicting the fundamental frequency was compared with three different error metrics and cross-validation, where the extreme gradient boost revealed more robust performance compared with support vector regression and artificial neural networks. The parametric investigations are presented, showing the impact of slope on the first fundamental frequency values for various nonstandard shapes of the liquid fillings, sloped from one side, from both sides, symmetrically, and asymmetrically beveled. The outputs revealed that such a combination of physics-based models with ML prediction provides further insight into sloshing phenomena and frequency responses at various circumstances.

Ex-situ tracking solid oxide cell electrode microstructural evolution in a redox cycle by high resolution ptychographic nanotomography

Polarization resistance of solid oxide fuel cell electrodes consists of resistances due to mass transfer and chemical reaction. Therefore, higher ion conductivity, electron conductivity, and gas diffusivity and larger triple-phase boundary (TPB) density lead to lower polarization resistance. To increase effective conductivities and diffusivity, tortuosity factors in each mass-transfer path should be reduced. In this study, magnetic alignment method is developed to align the mass-transfer paths in the electrode microstructure. Since Ni as an electron-conducting material in anode has high magnetic permeability, the particles are polarized and aligned by a magnetic field. Therefore, the tortuosity factors can be reduced. In addition, this Ni alignment is expected to reduce the tortuosity factors of yttria-stabilized zirconia (YSZ) and pore phases as well. However, there is a risk for a decrease in TPB density. The effect of magnetic field on resultant microstructure and polarization resistance of Ni-YSZ anode are investigated by impedance measurement of anode symmetrical cells and by reconstruction of three-dimensional microstructure. The tortuosity factors of Ni and YSZ decreased and TPB density decreased by the magnetic field. As a result, the polarization resistance of anode was kept nearly unchanged. The effect of reducing Ni volume fraction is also investigated.

Understanding and optimizing electrochemically active zone for oxygen reduction reaction in solidoxide fuel cells (SOFCs) cathodes are indispensable to maximize device’s performance. For mixed ionicand electronic conductors, the range of this zone depends on the oxygen surface exchange and solid-stateoxygen/electron transport properties of materials [1]. This aspect is also critical to realize validcharacterization of the electrode’s electrochemical activities. For instance, when a material’s electronicconductivity is low or the electrical contact points are spaced beyond a critical distance, the electrodepolarization resistance measured by electrochemical impedance spectroscopy will be controlled by the sheetresistance not the oxygen exchange resistance [2]. The situation becomes more complicated as the electricalconductivity of porous layer, which is an advantageous structure with large surface area and facile gas phasetransport, considerably deviates from the material’s intrinsic property. It is expected that porosity,connectivity, and impurity contents can have significant impact on porous electrode’s electronic conduction[3].In this context, we have studied effective in-plane electronic conductivity of lanthanum strontiumcobalt ferrite (LSCF) porous layers. The in-plane conductivity was measured by four-line probeconfiguration [4], modified from the widely used four-point probe technique to be applied for a porouslayer. We have confirmed that the in-plane electrical conductivity of screen-printed LSCF porous layers isone or two orders of magnitude lower than the material’s bulk property in ambient air, depending ontemperatures. This electronic conductivity deviation was taken into account to rationally designcombination of electrode thickness and current collector spacing and, in turn, to guarantee a validassessment of electrode performance. In addition, we found that electrical conductivity of LSCF porouslayers decreases by 20~30 %, within relatively short period of time (250~400 hours) upon repeated thermalcycles (500 ℃ to 700 ℃). Furthermore, we found that in-plane conductivity of thin (<10 µm) electrodes isstrongly dependent on the measurement time and the local atmospheric environment relative to thickerelectrodes. Special attention is required to use a thin electrode to evaluate electrode performance.This work was supported by the US Department of Energy (DOE), Office of Fossil Energy, (Officeof Clean Coal & Carbon Management), “Solid Oxide Fuel Cell Manufacturing in Support of Office ofFossil Energy” program through Argonne National Laboratory under FWP No. 27327.1.[1] S.B. Adler et al. J. Electrochem. Soc. 143 (1996) 3554-3564; S.B. Alder Solid State Ionics 111 (1998)125-134.[2] B.A. Boukamp et al. Solid State Ionics 192 (2011) 404-408; B.A. Boukamp et al. Solid State Ionics 283(2015) 81-90.[3] L. Holzer et al. J. Mater. Sci. 48 (2013) 2934-2952.[4] S.W. Peterson et al. J. Electrochem. Soc. 161 (2014) A2175-A2181.

Reconstruction of solid oxide fuel cell electrode microstructure and analysis of its effective conductivity

Commentary: Machine learning and cardiac surgery risk prediction

YSZ layers by pulsed-MOCVD on solid oxide fuel cell electrodes

Solid Oxide Fuel Cells (SOFCs) are widely considered to be an ideal power source across a range of industries in the near future due to their high efficiency, high power density, and fuel flexibility. However, for widespread usage of SOFCs to be feasible, certain disadvantages, such as their high operating temperature, electrochemical losses, and high cost of manufacturing, must be solved. In particular, the field of materials research occupies a unique position of being able to quickly and simultaneously solve many of these issues through the development of material compositions and structures that do not currently exist in the industry. Especially relevant to solid oxide fuel cells in particular, is the impact that the electrodes’ geometries and compositions have on the operating performance. The electrodes’ ability to quickly move reactants to the interface of the electrolyte and remove products to the bulk flow comes into play as the fuel cell operates at higher current densities and concentration losses become prominent. Therefore, the microstructures present throughout the electrodes’ depth plays a vital role in improving overall cell performance. However, current fuel cell research has not yet effectively captured and defined the connections of the microstructure parameters and measured their impact on cell behavior. Additionally, homogeneous electrode design and implementation have dominated the research and commercial space thus far. The technique of functional material grading, which has begun to see wide research and commercial usage for such problems as acoustic impedance matching, thermal control, and mechanical design will be leveraged for the enhancement of SOFC electrodes. Functionally graded electrodes have been used in solid oxide fuel cell research in recent years in an effort to improve the cell performance by altering the microstructure including porosity, particle size, and composition of electronic and ionic conductors near the triple phase boundary region. Normally the functional grading process adds additional fabrication steps making it less desirable as an optimization process and easy manufacturing method. However, by using an additive manufacturing process it eliminates the need for multiple discrete graded layers to be deposited to obtain a graded electrode functional layer. This study seeks to explore the correlations of geometry and structure parameters from the meso-scale through to the micro-scale level, together with mass transfer, ionic and electronic transport, and gas-surface electrochemical reactions inside the electrodes to guide future additive manufacturing of SOFCs. Outlined is the development of an effective medium model for simulating the performance of fuel cell microstructures as a function of specific operating ranges in temperature, pressure, and in fuels used. Smooth and continuous linear and nonlinear functional gradation profiles of porosity and material composition are studied within the framework of an effective medium boundary value problem where the electrochemical relations, such as the Butler-Volmer equation, percolating conduction paths, and gas diffusion are solved using the finite difference method. The form of these relations for homogeneous electrodes was analyzed by Costamagna, et. al [1], who also defined outstanding problems with regards to optimizing SOFC electrodes [2]. Globally optimal linear and nonlinear gradation profiles and cell parameters are derived as a function of particle sizes, ratio of conductivities, and desired operating conditions and scored based on their reduction of cell overpotentials.[1] Costamagna, P., P. Costa, and V. Antonucci, Micro-modelling of solid oxide fuel cell electrodes. Electrochimica Acta, 1998. 43(3-4), pp.375-394.[2] Costamagna, P., P. Costa, and E. Arato, Some more considerations on the optimization of cermet solid oxide fuel cell electrodes. Electrochimica Acta, 1998. 43(8), pp.967-972. Figure 1

For solid oxide fuel cell electrode material, calcium doped lanthanum manganite La0.4Ca0.6MnO3 (LCMO) and cerium-incorporated on Ca-site with composition La0.40Ca0.55Ce0.05MnO3 (LCCMO) were synthesized using most feasible and efficient glycine-nitrate method. The formation of crystalline single phase was confirmed by x-ray diffraction (XRD). The Rietveld analysis reveals that both systems crystallize into orthorhombic crystal structure with Pnma space group. Additionally, 8 mole % Y2O3 stabilized ZrO2 (8YSZ) solid electrolyte was also synthesized using high energy ball mill to check the reaction with electrode materials. It was found that the substitution of Ce+4 cations in LCMO perovskite suppressed formation of undesired insulating CaZrO3 phase.

The microstructure of the electrode determines the performance of the solid oxide fuel cell. Transport phenomena, involving charge and mass transfer, and electrochemical reactions occurring in the fuel cell, depend on the morphology of the electrode. Optimization of a microstructure can take multiple approaches. From experimental grid search to a computational optimization of three-dimensional microstructures. In this article, we explore the performance of the design of experiments methodology when applied to the optimization of an electrode’s microstructure. A parametrized one-dimensional model is used in design of experiments and evolutionary algorithm optimizations. We performed an optimization of a homogeneous microstructure with three optimization variables, namely two volume fractions and pore size. The design of experiments approach resulted in effectively the same thermodynamic loss compared to the evolutionary strategy. Results indicate that the design of experiments can be successfully applied to high-performance optimization of solid oxide fuel cell’s microstructures. Moreover, due to only 18 evaluations required for the design of experiments, the methodology can be effectively used in experiment-based optimization.