The design of materials for electrochemical energy conversion is complicated by multifaceted property requirements: multi-carrier conductivity, stability, and catalytic activity are all necessary but rarely intersect. Meanwhile, the large search space of candidate materials, the influence of measurement conditions like temperature and atmosphere, and time-intensive electrochemical characterization further slow down materials discovery efforts. Here, we develop and evaluate a system, including hardware and software, for efficient screening of proton-conducting oxide electrodes for ceramic fuel cells and electrolyzers. Combinatorial thin-film microelectrode libraries are characterized with a joint time-/frequency-domain impedance measurement technique, which provides an order-of-magnitude acceleration relative to conventional impedance spectroscopy. The distribution of relaxation times is extracted from impedance data and analyzed without human intervention. These results feed a Bayesian active learning process that learns to predict electrochemical impedance as a function of material composition, measurement temperature, oxygen partial pressure, and electrical bias, which further reduces screening time by 10-fold with optimized experimental sequences. We apply this system to Ba(Co,Fe,Zr,Y)O3-δ combinatorial libraries and evaluate its effectiveness for learning materials property trends and optimizing expensive-to-evaluate properties like activation energy. Our results demonstrate the efficacy of the system for rapidly gathering information, but also highlight potential challenges of thin-film degradation and numerical instability in surrogate models.

The long-term stability of protonic ceramic electrolysis cell (PCEC) materials under high-steam operating conditions remains a critical barrier to device commercialization. Here, we investigate the fundamental degradation mechanisms of dense BaCe0.7Zr0.1Y0.1Yb0.1O3-delta (BCZYYb) electrolytes operated at 550 degrees C, 50% H2O in air. Over 1,000 h, the total electrolyte conductivity decreases by 11.1%, driven primarily by a >130% increase in grain-boundary resistivity. Post-mortem analyses reveal that damage is localized to near-surface grain boundaries extending similar to 50 mu m into the dense electrolyte pellet. This surface localization indicates that degradation is likely to be severe in thin, device-level electrolytes. Degradation is primarily attributed to chemo-mechanical grain-boundary weakening arising from hydration-induced chemical expansion, culminating in the formation of intergranular cracks oriented parallel to the pellet surface. These internal cracks subsequently react with steam and/or CO2, leading to the formation of nanoscale insulating phases, including Ba(OH)(2), nanocrystalline BaCO3, and amorphous Ce/Zr/Y/Yb-containing oxides or hydroxycarbonates. After an initial degradation period of approximately 200 h, the overall conductivity stabilizes. Incorporating NiO sintering aids reduces grain-boundary density by an order of magnitude under identical sintering conditions. Although addition of NiO increases the initial resistivity by >160% at 550 degrees C, it substantially suppresses grain-boundary instability and mitigates chemical degradation. These findings underscore the urgent need for chemical and/or physical stabilization of BCZYYb electrolytes and offer design guidelines to enable durable, high-performance PCECs.

Triple-conducting oxides (TCOs) are an emerging class of mixed ionic and electronically conducting materials that show great promise for oxygen reduction/evolution (ORR/OER) electrocatalysis-primarily in high-temperature ceramic electrochemical cells- but also in aqueous alkaline environments. Their high activity is attributed, at least in part, to their ability to incorporate and transport three mobile charge carriers: protons, oxygen vacancies, and electron-holes. Despite their promise, fundamental studies of TCOs are challenging, as transport dynamics from three charge carriers cannot be fully disentangled via traditional electrical measurement techniques. Characterizing proton dynamics in TCOs is particularly difficult as protons are generally the minority carrier, and their conduction response is typically obscured by the oxygen vacancies and electron holes. Here, we demonstrate successful isolation of the proton behavior in an archetypal TCO, BaCo0.4Fe0.4Zr0.1Y0.1O3-delta (BCFZY4411), using a combination of non-electrical techniques. We determine proton uptake and oxygen non-stoichiometry (delta) using thermogravimetric analysis (TGA). X-ray absorption near edge structure (XANES) and neutron diffraction (ND) are used to validate the oxidation state of Co and the delta values obtained through TGA. We apply H-1 solid-state magic-angle-spinning (MAS) nuclear magnetic resonance (NMR) to provide insights into local structure, dynamics, and proton kinetics. Finally, the proton transport properties are further quantified using tracer isotope exchange with time-of-flight secondary ion mass spectrometry (ToF-SIMS). Despite the very low proton concentrations in BCFZY4411 (<0.2 % under most conditions), our analysis suggests that the oxygen reduction and evolution reactions are nevertheless limited by the oxygen ion kinetics (e.g., oxygen surface exchange) rather than the proton kinetics at the reduced operating temperatures (<500 degrees C) that are targeted for electrochemical cell applications. These findings provide a comprehensive understanding of proton behavior in BCFZY4411 and pave the way for advancing the fundamental study of TCOs.

Cell reproducibility remains a significant challenge for emerging proton-conducting ceramic electrochemical fuel cell and electrolyzer technologies. This study investigates the factors contributing to cell-to-cell performance variation using a relatively large dataset of electrochemical data and machine learning models. Gaussian Process and Random Forest Regressor machine learning models were utilized to analyze 86 cells for fuel cell performance and 84 cells for electrolysis performance. The study focuses on BaCe 0.4 Zr 0.4 Y 0.1 Yb 0.1 O 3-δ (BCZYYb4411)+NiO | BCZYYb4411 | BaCo 0.4 Fe 0.4 Zr 0.1 Y 0.1 O 3-δ (BCFZY) material sets for the negatrode, electrolyte, and positrode, respectively. Key processing and morphological parameters impacting performance were identified. Machine learning models can elucidate the complex interrelationships between processing parameters, cell characteristics, and electrochemical performance. Machine learning models develop pattern recognition from prior data and attempt to minimize error in future predictions based on unseed input data, allowing the models to identify complex relationships that humans would not be able to independently determine. Gaussian Process models are probabilistic, non-parametric machine learning tools that predict probability distributions over potential outcomes rather than single target values. Random Forest Regressor models predict target values using an ensemble of decision trees. Both these models excel at fitting non-linear relationships with relatively low prediction error. The electrolyte thickness to grain size ratio emerged as a critical factor for both fuel cell and electrolysis performance, with maximum gains at ratios < 1. A NiO particle size threshold of ~6 μm was identified, below which performance increases markedly. Evaporating organics from the electrolyte spray or positrode application process before sintering may improve performance significantly, but the extent of this improvement remains uncertain. The optimal BCFZY positrode thickness for fuel cell performance is 20-25 μm. Higher ambient humidity levels in the laboratory are correlated with higher electrolysis performance. Fuel cell performance is primarily influenced by positrode microstructure and attributes, though the electrolyte morphology also has a significant impact. Optimizing the positrode microstructure can bring the largest benefit to fuel-cell performance through reduced polarization resistances. Electrolysis performance is strongly governed by electrolyte microstructure. Improving electrolyte microstructure and conductivity to reduce ohmic resistance greatly benefits electrolysis performance. When utilizing the same material sets across many proton-conducting ceramic electrochemical cells, ohmic and polarization resistance are uncorrelated with each other. Figure 1

Due to their high efficiency and versatility, solid oxide electrochemical cells (SOCs) are poised to play a significant role in future energy conversion and storage applications. In recent years, SOCs have bifurcated into two distinct categories: traditional oxygen-ion conducting SOCs that typically operate from similar to 650850 degrees C and the more recent proton-conducting ceramic (PCC) SOCs that typically operate from similar to 400650 degrees C. Current performance and lifetime of both oxygen-ion conducting SOCs and PCCs is primarily limited by the air/steam electrode, which facilitates the oxygen reduction reaction (ORR) during fuel cell operation and must also facilitate the oxygen evolution reaction (OER) during electrolysis operation. Here, we present a newly designed high-entropy double perovskite oxide suitable as a universal ORR/OER electrode for both oxygen-ion conducting SOCs and PCCs. Machine learning methods are applied to identify chemical descriptors for highly catalytic high-entropy double perovskite oxides (AA'B2O6) across a large compositional space. Based on the machine-learning guidance, we ultimately converge on Ba0.9Cs0.1(Ca0.2Gd0.2La0.2Pr0.2Sr0.2)Co1.5Fe0.5O6 (CsBaHEO) as a universal air/steam electrode. Structure stabilization is accomplished by an equimolar five-cation high-entropy composition on the A'-site, while cesium substitution on the A-site enhances the electrical conductivity and leads to a higher oxygen vacancy concentration. This material exhibits versatility and high performance in reversible oxygen-ion SOCs, reversible PCCs, and also large-scale tubular PCCs. For example, the CsBaHEO-based PCC reaches 1018 mW center dot cm(-2) at 600 degrees C, while a large-scale tubular PCC using CsBaHEO for electrolysis achieves a hydrogen production rate of 21.314 ML center dot min(-1) at 600 degrees C.

This study investigates the key factors influencing sintering behavior and grain growth in BaCe0.4Zr0.4Y0.1Yb0.1O3-delta$\mathrm{BaCe_{0.4}Zr_{0.4}Y_{0.1}Yb_{0.1}O_{3-\delta }}$ (BCZYYb4411)-NiO negatrodes and BCZYYb electrolytes for protonic ceramic electrochemical cells (PCECs). Elastic net machine learning models are applied to a dataset of nearly 200 individual PCEC button cells fabricated over the course of more than 3 years to identify the key processing parameters that significantly affect negatrode shrinkage and electrolyte grain growth. The shrinkage rate of the BCZYYb4411-NiO negatrode is primarily governed by the solid-state sintering behavior. Higher sintering temperatures, longer dwell times, and smaller NiO particle size are the primary determinants that lead to greater shrinkage. New or lightly-used setters and more compact negatrodes are also found to increase shrinkage. Electrolyte grain growth is chiefly controlled by the liquid-phase sintering of the BCZYYb phase. Increased cerium content on the B-site leads to the largest enhancement in grain size, followed by increasing maximum sintering temperature. We find that the parameters used to tune the spray deposition of the electrolyte layer are also critical, with wetter and more uniform sprays promoting grain enlargement. Finally, we find that the sintering environment (e.g. presence/absence of sintering neighbors or sacrificial powders and the ambient humidity level) also substantially impacts both shrinkage and grain growth. This work comprehensively analyzes data from nearly 200 PCECs without "success bias," meaning that poor performers and fabrication failures were included in the analysis. By doing so, the study provides valuable insight into the critical factors controlling shrinkage and grain growth in BCZYYb-based PCECs. The findings offer foundational guidance for processing optimization that could lead to better repeatability, increased yields, and higher performance.

Protonic ceramic electrochemical cells (PCCs) are clean energy-conversion devices designed to enable both electric power production and hydrogen generation at intermediate temperatures (400-600 degrees C). The electrolytes for PCCs are typically based on acceptor-doped barium cerate-zirconate perovskite oxides such as BaCe 0.4 Zr 0.4 Y 0.1 Yb 0.1 O 3-delta (BCZYYb4411). These materials suffer from intrinsic barium-evaporation issues under the high sintering temperatures required to achieve dense electrolytes. This study explores the use of sacrificial powders to compensate for barium evaporation from the electrolyte during the high-temperature firing process. Our thermodynamic modeling reveals that Ba evaporation from BaCe 1-x-y Zr x M y O 3-delta (M: Y or Yb) perovskites increase with increasing Ce content and finds that BCY20 powder indeed acts as a highly effective sacrificial sintering neighbor. To demonstrate the versatility of this approach, we apply it to the sintering of tubular PCCs, achieving a peak power density of 517 mW cm-2 in fuel-cell mode and a current density of 915 mA cm-2 (1.3 V) in electrolysis mode at 600 degrees C. Furthermore, we use the same technique to fabricate an 8-cm2 large-scale reversible tubular PCC. The large-scale tubular cell achieves 1249 mW at 550 degrees C under fuel- cell mode (H2/air), 1.4 An at 1.3 V under electrolysis operation with high faradaic efficiency (78-84 %) and durability 1000 h.

Proton-conducting ceramic electrochemical devices (PCCs) show promise for sustainable energy conversion, yet key challenges remain. This perspective highlights critical areas for advancing PCC research. The field requires standardized protocols for fabrication, testing, and results reporting. Improved electrolyte sintering techniques and minimized nickel-induced defects are imperative for stable, high-performing cells. Addressing materials criticality is essential for commercialization. A deeper understanding of electrolyte grain boundary properties, positrode-electrolyte interface characteristics, and distribution of relaxation times analysis has great potential to accelerate progress. The promising application of PCCs in electrolysis mode remains understudied and merits increased research attention.

Electrochemical production of commodity chemicals via H2O electrolysis or H2O-CO2 co-electrolysis using solid oxide electrolysis cells (SOECs) offers a way to utilize excess renewables to address hard-to-decarbonize industrial sectors. Recently, proton-conducting SOECs (PCECs) have emerged as a promising type of SOEC in such applications, due to their unique properties of lower operating temperatures and flexible coupling with other chemical processes. However, the Faradaic efficiency (FE), i.e., the ratio of the experimentally produced H2 to that which could be theoretically generated, of PCECs is less than 100 % and their stability, particularly under coelectrolysis operation, has yet to be verified. In this work, a systematic investigation of the variation of FE under different operating conditions and the stability of PCECs in both H2O electrolysis and H2O-CO2 co-electrolysis is conducted. It is shown that the operating parameters have a significant effect on the apparent FE. During shortterm stability testing, H2O-CO2 co-electrolysis mode presents much less favorable operating characteristics than H2O electrolysis or H2-CO2 thermochemical conversion, with both FE and the catalytic activity of the negatrode (Ni-based fuel electrode) degrading gradually. Opportunities are identified to optimize operating parameters to maximize effectiveness and minimize degradation.

Triple-conducting perovskite oxides are well-known for their outstanding electrocatalytic activity, thermal and chemical stability, and remarkable simultaneous ionic and electronic conduction rendering them exceptionally valuable for serving as cathodes in solid oxide fuel cells (SOFCs) and protonic ceramic fuel cells (PCFCs/H-SOFcs). The perovskite BaCo0.4Fe0.4Zr0.1Y0.1O3-δ (BCFZY4411) has garnered heightened interest due to its triple conducting capability, convenient synthesis, compatibility with many electrolytes, and stability. Recent studies emphasize that the electronic/O2-/H+ transport behavior and electrocatalytic activity of BCFZY4411 can be tailored through the Co/Fe composition. Here, we present a structural and O2-/H+ transport study of the BCFZY solid solution series (BaCoxFe0.8−xZr0.1Y0.1O3− δ; x = 0.1, 0.2, 0.4, 0.6, 0.7). Neutron total scattering data was collected on both neat and deuterated/hydrated samples at 100 K, 300 K, and 500 K. Analysis of the diffraction and pair distribution function (PDF) data demonstrate that Co/Fe substitution results in short-range ordering, maintaining the average cubic perovskite for all compositions. Rietveld refinements with associated Fourier difference and bond valence sum analyses were applied to quantify lattice vacancies, locate proton positions, and calculate oxygen/proton transport pathways and energy barriers for migration. With increasing Co content, oxygen vacancy concentration increases, with associated expansion in free volume, and a reduction in oxygen diffusion barriers. The Fourier difference maps reveal that protons incorporated into BCFZY partially occupy four positions surrounding each oxygen atom, accommodated through hydrogen bonding, and facilitating both rotational (around a single oxygen position) and hopping (between positions adjacent to neighboring oxygens) diffusion mechanisms. Calculated activation energy barriers show a minimal impact of Co/Fe content on proton diffusion. Our studies reveal that while oxygen ion dynamics is closely linked to Co concentration, proton dynamics in BCFZY appear to be dominated by other factors.

Electrochemistry enables reversible storage and release of hydrogen gas in a metal hydride.

Obtaining a cohesive understanding of performance in protonic-ceramic electrolysis cells is difficult due to the wide operating space coupled with low-throughput diagnostic techniques, sluggish system dynamics, and cell degradation. In this work, design of experiments (DOEs) methods are implemented to provide an efficient framework for understanding the phenomena that most strongly dictate cell performance. In addition to a more robust description of cell-level phenomena, mathematical equations are generated that accurately describe the complex relationship between the cell operating variables and cell performance metrics such as faradaic efficiency, cell potential, resistances, and energy conversion efficiency. Here, DOE is realized without the need to pre-select the most important operating variables based on a priori rationalizations. This is particularly valuable for system-level and technoeconomic analyses where the accurate prediction of cell/stack response over many operating conditions is required. The demonstrated experimental framework consists of a screening design and subsequent optimization design. The Plackett-Burman factor-screening design identifies temperature, current density, and steam content as having the largest impacts on cell performance, particularly faradaic efficiency. Increasing the electrolytic current density from 0.2 to 0.5 A cm-2 decreases polarization resistances by 74% due in large part to a negative-capacitance element that dominates at low frequency and high electrolysis bias. Impedance data highlights the connection of this negative feature to electronic leakage through the electrolyte and gas diffusion limitations. Additionally, increasing cell temperature from 500 to 600 degrees C is shown to decrease faradaic efficiency by 9% due to electrolyte dehydration and oxygen incorporation at high temperatures. The Box-Behnken optimization design then enables generation of regression equations to be used in response surfaces for data visualization and cohesive, multivariate analysis of cell operation.

Electrochemical impedance spectroscopy (EIS) is widely used in electrochemistry, energy sciences, biology, and beyond. Analyzing EIS data is crucial, but it often poses challenges because of the numerous possible equivalent circuit models, the need for accurate analytical models, the difficulties of nonlinear regression, and the necessity of managing large datasets within a unified framework. To overcome these challenges, non-parametric models, such as the distribution of relaxation times (DRT, also known as the distribution function of relaxation times, DFRT), have emerged as promising tools for EIS analysis. For example, the DRT can be used to generate equivalent circuit models, initialize regression parameters, provide a time-domain representation of EIS spectra, and identify electrochemical processes. However, mastering the DRT method poses challenges as it requires mathematical and programming proficiency, which may extend beyond experimentalists’ usual expertise. Post-inversion analysis of DRT data can be difficult, especially in accurately identifying electrochemical processes, leading to results that may not always meet expectations. This article examines non-parametric EIS analysis methods, outlining their strengths and limitations from theoretical, computational, and end-user perspectives, and provides guidelines for their future development. Moreover, insights from survey data emphasize the need to develop a large impedance database, akin to an impedance genome. In turn, software development should target one-click, fully automated DRT analysis for multidimensional EIS spectra interpretation, software validation, and reliability. Particularly, creating a collaborative ecosystem hinged on free software could promote innovation and catalyze the adoption of the DRT method throughout all fields that use impedance data.

For protonic ceramic fuel cells, it is key to develop material with high intrinsic activity for oxygen activation and bulk proton conductivity enabling water formation at entire electrode surface. However, a higher water content which benefitting for the increasing proton conductivity will not only dilute the oxygen in the gas, but also suppress the O-2 adsorption on the electrode surface. Herein, a new electrode design concept is proposed, that may overcome this dilemma. By introducing a second phase with high-hydrating capability into a conventional cobalt-free perovskite to form a unique nanocomposite electrode, high proton conductivity/concentration can be reached at low water content in atmosphere. In addition, the hydronation creates additional fast proton transport channel along the two-phase interface. As a result, high protonic conductivity is reached, leading to a new breakthrough in performance for proton ceramic fuel cells and electrolysis cells devices among available air electrodes.

Stability of proton-conducting ceramic fuel cells (PCFCs) is not well understood. Many stable cells are reported in the literature. However, unstable cells generally go unstudied. This paper explores and identifies sources of instability, and suggests fabrication methods that promote cell stability. We find that fuel cells that lack gas-tight electrolytes breakdown over time at rates exceeding 75% of the cell overpotential per 1000 h. Oxygen leakage through electrolyte pinholes gives rise to nickel re-oxidation at the negatrode, advancing performance degradation. Nickel redox cycling decreases the catalytic activity and leads to mechanical cleaving of the negatrode. The nickel oxidation increases high-frequency polarization resistance which is evident in the distribution of relaxation times (DRT). Nickel separation and cleaving from the electrolyte phase within the cermet negatrode increases ohmic resistance. Three sintering strategies aid the formation of gas-tight electrolytes, including two-step sintering, sintering neighbors, and positrode functional layers (PFLs). Stability rates of gas-tight cells are as low as 2.6% of the overpotential per 1000 h. Fabricating cells with thicker electrolytes also improves stability. Hybrid-DRT polarization mapping during stability testing reveals that PCFCs have four main DRT peaks, and thus four main electrochemical processes, at 550 °C.

Solid oxide cells (SOCs), capable of interconverting electrical and chemical energy, have emerged as one of the key technologies for the future multi-energy complementary grid. However, the commercialization of SOCs is hindered by poor long-term stability, attributed in large-part to the microstructural evolution of the electrodes, which results in the loss of active reaction sites, blockage of gas transport pathways, and degradation of mechanical properties. Owing to recently developed three-dimensional (3D) microstructure reconstruction techniques, the microstructural evolution of SOC electrodes can now be investigated quantitatively. This review highlights insights gained from studies of the microstructural evolution of porous cermet SOC electrodes during long-term operation and redox cycling, and the corresponding effects on electrochemical and mechanical performance, with particular attention to investigations using 3D reconstruction technologies. The influencing parameters and the possible strategies to mitigate microstructure evolution-induced degradation are also summarized. The challenges and opportunities for the future development of stable and active SOC electrode microstructures are analyzed, and the corresponding prospects for commercial application are provided.

Solar thermochemical hydrogen is one of the few potential routes towards direct fuel production from renewable energy sources, but the thermodynamic boundary conditions for efficient and economic energy conversion are challenging. Success or failure of a given oxide working material depends on the subtle balance between enthalpy and entropy contributions in the redox processes. Developing a mechanistic understanding of the behavior of materials on the basis of atomistic models and first-principles calculations is an important part of advancing the technology. One challenge is to quantitatively predict thermochemical equilibria at high concentrations when the redox-active defects start to interact with each other, thereby impeding the formation of additional defects. This problem is of more general importance to applications that rely on high levels of off-stoichiometry or doping, including, for example, batteries, thermoelectrics, and ceramic fuel cells. To account for such repulsive defect interactions, we introduce a statistical mechanics approach, defining an expression for the free energy of defect interaction based on limited sampling of defect configurations in density functional theory supercell calculations. The parameterization of this energy contribution as a function of defect concentration and temperature allows on-the-fly simulation of thermochemical equilibria. The approach consistently incorporates finite temperature effects by including the leading contributions to the temperature-dependent free energy for the case at hand, i.e., the ideal gas and configurational enthalpies and entropies. We demonstrate the capability and utility of the approach by simulating the water splitting redox processes for Sr1−xCexMnO3−δ alloys.Received 1 September 2023Revised 2 December 2023Accepted 19 December 2023DOI:https://doi.org/10.1103/PRXEnergy.3.013008Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI. Open access publication funded by the National Renewable Energy Laboratory (NREL) Library, part of a national laboratory of the U.S. Department of Energy.Published by the American Physical SocietyPhysics Subject Headings (PhySH)Research AreasDefectsHydrogen productionSolar energyPhysical SystemsOxidesTechniquesFirst-principles calculationsStatistical methodsCondensed Matter, Materials & Applied PhysicsEnergy Science & TechnologyStatistical Physics & Thermodynamics

Doping monovalent alkali metals with high basicity into barium containing perovskite materials facilitates high proton conduction pathways through the exsolution of barium oxides at humidified air conditions, boosting oxygen reactions activities.

Protonic ceramic fuel cells (PCFCs) are emerging as a promising technology for reduced temperature ceramic energy conversion devices. The BaCe _0.4 Zr _0.4 Y _0.1 Yb _0.1 O _3− _δ (BCZYYb4411) electrolyte is notable for its high proton conductivity. However, the tendency of barium to volatilize in BCZYYb4411 during high-temperature sintering compromises its chemical stability and performance. This study investigates the effects of intentionally incorporating excess barium into BCZYYb4411, formulated as Ba _1+ _x Ce _0.4 Zr _0.4 Y _0.1 Yb _0.1 O _3− _δ (where x = 0, 0.1, 0.2, and 0.3), with the aim of compensating barium evaporation and enhancing the physical and chemical properties. We find that excess barium results in a greater shrinkage rate, facilitating a denser electrolyte structure. This barium-enriched electrolyte demonstrates improved electrochemical performance by effectively counteracting the deleterious effects of barium evaporation. Applying this strategy to tubular PCFCs, we achieved a peak power density of 480 mW∙cm ^−2 at 600 °C. This unique approach provides a simple, tunable, and easy-to-implement processing modification to achieve high-performance tubular PCFC.