William K. Epting

Three-dimensional (3D) microstructure reconstruction is essential for understanding processing-microstructure-property relationships in solid oxide cell (SOC) electrodes. While high-resolution 3D techniques like FIB-SEM and nano-CT offer precise local quantification, they are costly, destructive, and limited to small volumes. To help overcome these limitations, convolutional neural networks (CNNs) were investigated for estimating 3D microstructural characteristics from more accessible imaging data: phase-segmented high-resolution 2D SEM images and low-resolution 3D µ-CT scans. Two models were developed: a 2D3D CNN for 2D SEM and a LRHR CNN for µ-CT. Each was trained on an open-source library of synthetic SOC microstructures, evaluated across homogeneous and heterogeneous electrode distributions, and compared to traditional stereological methods for 2D SEM. Up to a resolution of 1.0 µm, the LRHR model performs better than the 2D3D model, and both are significantly better than stereology in estimating either local microstructural characteristics or local electrochemical properties computed from those characteristics. These accurate and precise deep-learning-enhanced estimates of local microstructural characteristics will enable the characterization of large numbers and large volumes of heterogeneous functional materials and devices, which is crucial to determining processing-microstructure-property relationships and will guide further design and optimization.

Sr-secondary phase formation is a potentially significant degradation mode with direct impact upon solid-oxide cell (SOC) commercial viability. A first-principles based thermodynamic study was performed for La_1-xSr_xMnO_3±δ (LSM) perovskites to assess their stability against formation of different Sr-secondary phases, including SrO, SrCrO₄, SrSO₄, SrCO₃, and Sr(OH)₂, for SOC applications. The Sr-secondary phase formation reaction free energies were determined via a thermodynamic model by combining ab initio lattice dynamics calculations for the solid phases and ab initio thermodynamic data for the gas phases.The current approach expands the previously reported thermodynamic modeling studies by integrating first-principles based point defect equilibria into the thermodynamic analysis. The modeling results obtained using this new approach indicate an increased tendency to form the SrO oxide upon decreasing the oxygen partial pressure. Additionally, the enhancing factors to form the Sr-related secondary phase from the associated SrO activity in LSM are further quantified by considering the equilibrium of SrO reacting with the contaminant gas species as a function of temperature and pressure.

Sr-secondary phase formation is a potentially significant degradation mode threatening solid-oxide cell (SOC) commercial viability. A first-principles thermodynamic study was performed for rhombohedral perovskite (La1-xSrx) MnO3±δ (LSM) to assess its stability against Sr secondary phase formation in SOC applications. In this work, the Sr secondary phase formation reaction free energies were determined by combining ab initio lattice dynamics calculations for the solid phases and an ab initio thermodynamics approach for the gas phases. Furthermore, this approach goes beyond previous thermodynamic modeling studies by integrating first-principles based point-defect equilibria into the analyses. The modeling results indicate an increased tendency to form SrO oxide from LSM upon decreasing the oxygen partial pressure. Additionally, enhancing factors to form the Sr-related secondary phase from the associated SrO activity in LSM are further quantified by considering the equilibrium of SrO reacting with contaminant gas species as a function of temperature and gas pressure.

Distinct from the proton defect, the hydride defect species may be present in certain perovskite materials in reducing environments such as in fuel electrodes of solid oxide cells (SOCs) or on the reducing side of ceramic membranes. A generalized defect thermodynamic model was developed for the triple-conducting perovskites (La,Ba)Fe_1−xM_xO_3−δ (M = Y and Zr) to allow inclusion of the hydride defect formation reaction in addition to the other three main defect reactions, namely, the oxygen vacancy formation, hydration, and charge disproportionation reactions. This comprehensive defect model also allows the incorporation of polynomial functional forms of oxygen nonstoichiometry δ to describe the defect reaction energies and entropies and to enable refinements of the defect reaction equilibrium constants in the defect thermodynamic analysis. As a first step, the developed model is applied to the Ba_0.95La_0.05FeO_3−δ material as an illustrative system to obtain its Brouwer diagrams with both the proton and hydride defects in relevant SOC conditions, particularly for more reducing environments. The results provide direct guidance on the influence of electronic and ionic defect concentrations upon thermodynamic properties and ultimately on the performance of Ba_0.95La_0.05FeO_3−δ and potentially other (La,Ba)Fe_1−xM_xO_3−δ perovskite materials involved in SOC applications.