A review of AC impedance modeling and validation in SOFC diagnosis

A-site-deficiency range identified for in situ exsolution from (La0.4Sr0.6)1-αTi0.95Ni0.05O3±δ electrodes for SOFC and SOEC

Modulating the A-site deficiency is a useful method to achieve the exsolution of nanoparticles on the surface of perovskite, improving the catalytic activity. However, rules for designing the deficiency value and its roles on the structure and performance remain unclear. In this study, a wide range of A-site deficiencies of (La0.4Sr0.6)1-αTi0.95Ni0.05O3±δ (LSTN, α = 0.00, 0.13, 0.15, and 0.18) titanate perovskite materials was designed to systematically investigate their crystal structure, binding energy, oxygen vacancy concentration, exsolution process, and electrochemical performance. An extremely high conductivity (e.g., 331.75 S cm-1@800 °C, 5% H2/Ar) was obtained in parallel with enhanced catalytical activity in SOFC and SOEC modes. The A-site-deficient samples displayed a higher conductivity, oxygen vacancy concentration, and power output than the stoichiometric samples (α = 0.00). The best maximum power density of 78.74 mW cm-2 and the highest population density of 25 particles per μm2 were obtained on the deficient LSTN with α = 0.13. These findings suggest that LSTN is an exceptionally promising material for solid oxide cell (SOC) electrodes.

Enriching Nano-Heterointerfaces in Proton Conducting TiO2-SrTiO3@TiO2 Yolk-Shell Electrolyte for Low-Temperature Solid Oxide Fuel Cells

A challenging task in solid oxide fuel cells (SOFCs) is seeking for an alternative electrolyte, enabling high ionic conduction at relatively low operating temperatures, i.e., 300-600 °C. Proton-conducting candidates, in particular, hold a significant promise due to their low transport activation energy to deliver protons. Here, a unique hierarchical TiO2-SrTiO3@TiO2 structure is developed inside an intercalated TiO2-SrTiO3 core as "yolk" decorating densely packed flake TiO2 as shell, creating plentiful nano-heterointerfaces with a continuous TiO2 and SrTiO3 "in-house" interfaces, as well the interfaces between TiO2-SrTiO3 yolk and TiO2 shell. It exhibits a reduced activation energy, down to 0.225 eV, and an unexpectedly high proton conductivity at low temperature, e.g., 0.084 S cm-1 at 550 °C, confirmed by experimentally H/D isotope method and proton-filtrating membrane measurement. Raman mapping technique identifies the presence of hydrogenated HO─Sr bonds, providing further evidence for proton conduction. And its interfacial conduction is comparatively analyzed with a directly-mixing TiO2-SrTiO3 composite electrolyte. Consequently, a single fuel cell based on the TiO2-SrTiO3@TiO2 heterogeneous electrolyte delivers a good peak power density of 799.7 mW cm-2 at 550 °C. These findings highlight a dexterous nano-heterointerface design strategy of highly proton-conductive electrolytes at reduced operating temperatures for SOFC technology.

Piezoresistivity and AC Impedance Spectroscopy of Cement-Based Sensors: Basic Concepts, Interpretation, and Perspective

Cement-based sensors include conductive fillers to achieve a sensing capability based on the piezoresistivity phenomenon, in which the electrical resistivity changes with strain. The microstructural characterisation of cement-based sensors can be obtained using a promising non-destructive technique, such as AC impedance spectroscopy (ACIS), which has been recently used by many researchers. This paper reviews the fundamental concepts of piezoresistivity and ACIS in addition to the comparison of equivalent circuit models of cement-based sensors found in the literature. These concepts include piezoresistivity theory, factors affecting piezoresistivity measurement, resistance measurement methodology, strain/damage sensing, causes of piezoresistivity, theories of conduction, AC impedance spectroscopy theory, and the equivalent circuit model. This review aims to provide a comprehensive guide for researchers and practitioners interested in exploring and applying different techniques to self-sensing concrete.

An Innovative PEMFC Magnetic Field Emulator to Validate the Ability of a Magnetic Field Analyzer to Detect 3D Faults

An original non-invasive methodology of the fuel cell diagnosis is proposed to identify different positions of the faults in Proton Exchange Membrane Fuel Cell (PEMFC) stacks from external magnetic field measurements. The approach is based on computing the external magnetic field difference between normal and faulty PEMFC operating conditions. To evaluate the external magnetic field distribution, in this paper, we propose an improved design of the magnetic field analyzer. This analyzer amplifies the magnetic field around the cell to perform an accurate detection of the fault position. Moreover, the main contribution of this work is represented by conceiving and implementing a 3D multi-physical current distribution emulator of a proton exchange membrane fuel cell. The new concept of a proton exchange membrane fuel cell emulator has been specially designed to emulate the magnetic field of a real fuel cell stack. This emulator concept is also beneficial for a new model of the fuel cell, which implies a multi-physical coupling between electrochemical electric conduction and the generated magnetic field. Finally, finally, the numerical model and the emulator have been involved in the realization of numerical simulations and experimental analysis to prove the ability of the system to detect and localize 3D faults.

Medium-Entropy SrV1/3Fe1/3Mo1/3O3 with High Conductivity and Strong Stability as SOFCs High-Performance Anode

Perovskite oxides using solid oxide fuel cells (SOFCs) anodes should possess high chemical stability, adequate electronic conductivity and excellent catalytic oxidation for fuel gas. In this work, the medium-entropy SrV1/3Fe1/3Mo1/3O3 (SVFMO) with Fe, V and Mo co-existing in the B site of a perovskite structure was fabricated in reducing 5% H2/Ar mixed gas: (1) SVFMO demonstrates more stable physicochemical properties when using SOFCs anodes in a reducing environment; (2) the co-existence of Fe, V and Mo in SVFMO forms more small-polaron couples, demonstrating greatly enhanced electronic conductivity. With SVFMO in a porous structure (simulating the porous anode layer), its electronic conductivity can also reach 70 S cm−1 when testing at 800 °C in an H2 atmosphere; (3) SVFMO with more oxygen vacancies achieves higher catalytic ability for fuel gas, as an SOFCs anode layer demonstrates 720 mW cm−2 at 850 °C.

A Comparative Study of Equivalent Circuit Models for Electro-Chemical Impedance Spectroscopy Analysis of Proton Exchange Membrane Fuel Cells

Electrochemical impedance spectroscopy is one of the important tools for the performance analysis and diagnosis of proton exchange membrane fuel cells. The equivalent circuit model is an effective method for electrochemical impedance spectroscopy resolution. In this paper, four typical equivalent circuit models are selected to comprehensively compare and analyze the difference in the fitting results of the models for the electrochemical impedance spectroscopy under different working conditions (inlet pressure, stoichiometry, and humidity) from the perspective of the fitting accuracy, change trend of the model parameters, and the goodness of fit. The results show that the fitting accuracy of the model with the Warburg element is the best for all under each working condition. When considering the goodness of fit, the model with constant phase components is the best choice for fitting electrochemical impedance spectroscopy under different inlet pressure and air stoichiometry. However, under different air humidity, the model with the Warburg element is best. This work can help to promote the development of internal state analysis, estimation, and diagnosis of the fuel cell based on the equivalent circuit modeling of electrochemical impedance spectroscopy.

Recent progress in direct urea fuel cell

Direct urea fuel cell (DUFC) has attracted many researchers’ attention due to the use of wastewater, for example urine, which contains urea for the fuel. The main factor to improve the electrochemical oxidation performance of urea and further enhance the performances of DUFC is the use of a good anode catalyst. Non-noble metal catalyst, such as nickel, is reported to have a good catalytic activity in alkaline medium towards urea electro-oxidation. Besides optimizing the anode catalyst, the use of supporting electrode which has a large surface area as well as the use of H2O2 as an oxidant to replace O2 could help to improve the performances. The recent progress in anode catalysts for DUFC is overviewed in this article. In addition, the advantages and disadvantages as well as the factors that could help to escalate the performance of DUFC are discussed together with the challenges and future perspectives.

Data-Driven Prognostics of the SOFC System Based on Dynamic Neural Network Models

Prognostics technology is important for the sustainability of solid oxide fuel cell (SOFC) system commercialization, i.e., through failure prevention, reliability assessment, and the remaining useful life (RUL) estimation. To solve SOFC system issues, data-driven prognostics methods based on the dynamic neural network (DNN), one of non-linear models, were investigated in this study. Based on DNN model types, the neural network autoregressive (NNARX) model with external inputs, the neural network autoregressive moving average (NNARMAX) model with external inputs, and the neural network output error (NNOE) were utilized to predict the degradation trend and estimate the RUL. First, the degradation trend prediction was executed to evaluate the correctness of the proposed DNN model structures in the first learning phase. Then, the RUL was estimated on the basis of the degradation trend of the NN models in the second inference phase. The comparison test results show the prediction accuracy of the NNARX model is higher and the RUL estimation can be given within a smaller relative error than the NNARMAX and NNOE models. The evaluation criteria of the root mean square error and mean absolute error of the NNARX model are the smallest among these three models. Therefore, the proposed NNARX model can effectively and precisely provide degradation trend prediction and RUL estimation of the SOFC system.

Synergistically enhanced performance of transition-metal doped Ni2P for supercapacitance and overall water splitting

Cost-effective and readily available catalysts applicable for electrochemical conversion technologies are highly desired. Herein, we report the synthesis of dithiophosphonate complexes of the type [Ni{S₂P(OH)(4-CH₃OC₆H₄)}₂] (1), [Co{S₂P(OC₄H₉)(4-CH₃OC₆H₄)}₃] (2) and [Fe{S₂P(OH)(4-CH₃OC₆H₄)}₃] (3) and employed them to prepare Ni₂P, Co-Ni₂P and Fe-Ni₂P nanoparticles. Ni₂P was formed by a facile hot injection method by decomposing complex 1 in tri-octylphosphine oxide/tri-n-octylphosphine at 300 °C. The prepared Ni₂P was doped with Co and Fe employing complexes 2 and 3, respectively, under similar experimental conditions. Doping Ni₂P with Co and Fe demonstrated synergistic improvement of Ni₂P performance as an electrocatalyst in supercapcitance, hydrogen evololution and oxygen evolution reactions in alkaline medium. Cobalt doping improved the Ni₂P charge storage capacity with a supercapacitance of 864 F g^-1 at 1 A g^-1 current density. Fe doped Ni₂P recorded the lowest overpotential of 259 mV to achieve a current density of 10 mA cm^-2 and a Tafel slope of 80 mV dec^-1 for OER, better than the undoped Ni₂P and the benchmark IrO₂. Likewise, Fe-doped Ni₂P electrode required the lowest overpotential of 68 mV with a Tafel slope of 110 mV dec^-1 to attain the same current density for HER. All catalysts showed excellent stability in supercapacitance and overall water splitting reactions, indicating their practical use in energy conversion technologies.

Exsolution of Ni Nanoparticles from A-Site-Deficient Layered Double Perovskites for Dry Reforming of Methane and as an Anode Material for a Solid Oxide Fuel Cell

Exsolution is a promising technique to design metal nanoparticles for electrocatalysis and renewable energy. In this work, Ni-doped perovskites, (Pr_0.5Ba_0.5)_1-x/2Mn_1-x/2Ni_x/2O_3-δ with x = 0, 0.05, 0.1, and 0.2 (S-PBMNx), were prepared to design exsolution systems as solid oxide fuel cell anodes and for catalysis applications. X-ray diffraction and transmission electron microscopy (TEM) analyses demonstrated that correlating A-site deficiency with Ni content can effectively induce exsolution of all Ni under H₂ atmosphere at T ∼ 875 °C, yielding the reduced (exsolved) R-PBMNx materials. On heating the exsolution systems in air, metal incorporation in the oxide lattice did not occur; instead, the Ni nanoparticles oxidized to NiO on the layered perovskite surface. The lowest area-specific resistance (ASR) under wet 5% H₂/N₂ in symmetrical cells was observed for R-PBMN0.2 anode (ASR ∼ 0.64 Ω cm² at 850 °C) due to the highest Ni particle density in the R-PBMNx series. The best performance for dry reforming of methane (DRM) was also obtained for R-PBMN0.2, with CH₄ and CO₂ conversion rates at 11 and 32%, respectively, and the highest production of H₂ (37%). The DRM activity of R-PBMN0.2 starts at 800 °C and is sustained for up to at least 5 h operation with little carbon deposition (0.017 g·gcat^-1·h^-1). These results clearly demonstrate that varying Ni-doping in layered double perovskite oxides is an effective strategy to manipulate the electrochemical performance and catalytic activity for energy conversion purposes.

Detection of pollutants in water bodies: electrochemical detection or photo-electrochemical detection?

The massive discharge of pollutants including endocrine-disrupting chemicals (EDCs), heavy metals, pharmaceuticals and personal care products (PPCPs) into water bodies is endangering the ecological environment and human health, and needs to be accurately detected. Both electrochemical and photo-electrochemical detection methods have been widely used for the detection of these pollutants, however, which one is better for the detection of different environmental pollutants? In this feature article, different electrochemical and photo-electrochemical detection methods are summarized, including the principles, classification, common catalysts, and applications. By summarizing the advantages and disadvantages of different detection methods, this review provides a guide for other researchers to detect pollutants in water bodies by using electrochemical and photo-electrochemical analysis.

Performance Prediction Model of Solid Oxide Fuel Cell System Based on Neural Network Autoregressive with External Input Method

An accurate performance prediction model for the solid oxide fuel cell (SOFC) system not only contributes to the realization of the operating condition but also plays a role in long-term prediction performance. Accordingly, a research study has been developed to suitably deal with the time-series model and accurately build the performance prediction model of SOFC system based on neural network autoregressive with external input (NNARX) method. The architecture regressor parameters of the NNARX model were efficiently determined using the Taguchi orthogonal array (OA) method for optimal sets. The identified and evaluated optimal parameter levels were used to conduct an analysis of variance (ANOVA) to prove correctness. Moreover, a series of statistics criteria and multi-step prediction were also employed for investigating the uncertainty of the predicted model and solve the overfitting and under fitting problems; further. These criteria were also used to determine the performance of the proposed model architecture. The predicted results of the current study indicated that the developed optimal model level parameters consistently had the least statistics errors and reduced workload of the trial-and-error processes.

Solid Oxide Fuel Cell Performance Analysis through Local Modelling

Solid Oxide Fuel Cells (SOFC) are an emerging technology among different fuel cell types since they are successfully used in stationary cogeneration units to produce heat and electricity. Different scale applications are proposed as alternative energy sources for residential usage and industrial power plants, reducing the greenhouse gas emissions which characterize fossil-fuel-based processes. Their spread is favoured by the development of proper simulation tools that allow system design optimization and control in real-time operations. For this purpose, model building and validation, through comparison with experimental observations, are fundamental steps to guarantee the simulation validity. A single-anode-supported planar SOFC with two possible cathodic current collector designs is tested in common operating conditions, evaluating the performance through EIS analysis and characteristic curves. These provide a preliminary validation for the proposed 2D steady state simulation code. This model, implemented in Fortran, makes it possible to forecast the main SOFC local properties on both the anodic and cathodic sides. The key point of the code is the electrochemical kinetics, based on a semi-empirical approach where requested parameters, derived from fitting of experimental results, are introduced in physically based equations. In this way, the influence of specific cell design on system performance is evaluated.

Advanced Fuel Cell Based on New Nanocrystalline Structure Gd0.1Ce0.9O2 Electrolyte

Lowering the operating temperature is a universal R&D challenge for the development of low-temperature (<600 °C) solid oxide fuel cells (SOFCs) that meet the demands of commercialization. Regarding the traditional electrolyte materials of SOFCs, bulk diffusion is the main ionic conduction mechanism, which is primarily affected by the bulk density and operating temperatures. In this study, we report a new mechanism for the Ce_0.9Gd_0.1O_2-δ (GDC) electrolyte based on a nanocrystalline structure with surface or grain boundary conduction, exhibiting an extremely high ionic conductivity of 0.37 S·cm^-1 at 550 °C. The fuel cell with the nanocrystalline structure GDC electrolyte (0.5 mm in thickness) can deliver a remarkable peak power density of 591.8 mW·cm^-2 at 550 °C, which is approximately 3.5 times higher than that for the cell with the GDC electrolyte densified at 1550 °C. An amorphous layer enriched by oxygen vacancies was found at the surface of the nano-GDC particles in the fuel cell test atmosphere, which was attributed to the ion conduction channel of the grain boundary diffusion. The ionic conduction at the interfaces between the particles was discovered to be the dominant conduction mechanism of the nanocrystalline structure GDC electrolyte. Oxygen ions and protons were determined to be the charge carriers in this interfacial conduction phenomenon, and the conduction of oxygen ions was dominant.

A robust and repairable superhydrophobic Co5Zn21 alloy surface on a zinc substrate

Repairable Co₅Zn₂₁ superhydrophobic surface was successfully prepared on zinc substrate and showed good corrosion resistance and antifriction.

Electron-Donor and -Acceptor Agents Responsible for Surface Modification Optimizing Electrochemical Performance

The electrochemical roles of electron-donor and -acceptor agents in surface reforming of magnesium alloy were investigated via plasma electrolysis. The surface modification was performed in an aluminate-based electrolyte, having urea and hydrazine with inherent molecular structures, which might act as electron acceptor and donor during plasma-assisted electrochemical reaction. The presence of hydrazine working as donor would promote the formation of magnesium aluminates in the oxide layer, resulting in superior compactness of the oxide layer to that when urea was used as the working as acceptor since the precipitation of MgCO₃ was favored in the electrolyte with urea. The thickness of the oxide layer formed by a combination of urea and hydrazine was higher than urea, while the porosity was higher than hydrazine. The electrochemical performance was enhanced in the order of hydrazine, urea and hydrazine combined, and urea, which was discussed on the basis of impedance interpretation.

Electrochemical impedance spectroscopy (EIS) study on the degradation of acrylic polyurethane coatings

Degradation of acrylic polyurethane coatings with different NCO/OH values was evaluated by EIS technology.

A Gd0.2Ce0.8O1.9 impregnated Pr0.4Sr0.6Co0.2Fe0.7Nb0.1O3−δ nanofiber-structured composite anode in solid oxide fuel cells

The PSCFN–GDC nanofiber-structure composite anodes have excellent electrochemical performance and thermal cycling stability.

Effect of Surface Modification on Nano-Structured LiNi(0.5)Mn(1.5)O4 Spinel Materials

Fine-tuning of particle size and morphology has been shown to result in differential material performance in the area of secondary lithium-ion batteries. For instance, reduction of particle size to the nanoregime typically leads to better transport of electrochemically active species by increasing the amount of reaction sites as a result of higher electrode surface area. The spinel-phase oxide LiNi0.5Mn1.5O4 (LNMO), was prepared using a sol-gel based template synthesis to yield nanowire morphology without any additional binders or electronic conducting agents. Therefore, proper experimentation of the nanosize effect can be achieved in this study. The spinel phase LMNO is a high energy electrode material currently being explored for use in lithium-ion batteries, with a specific capacity of 146 mAh/g and high-voltage plateau at ∼4.7 V (vs Li/Li(+)). However, research has shown that extensive electrolyte decomposition and the formation of a surface passivation layer results when LMNO is implemented as a cathode in electrochemical cells. As a result of the high surface area associated with nanosized particles, manganese ion dissolution results in capacity fading over prolonged cycling. In order to prevent these detrimental effects without compromising electrochemical performance, various coating methods have been explored. In this work, TiO2 and Al2O3 thin films were deposited using atomic layer deposition (ALD) on the surface of LNMO particles. This resulted in effective surface protection by prevention of electrolyte side reactions and a sharp reduction in resistance at the electrode/electrolyte interface region.

Effects of cobalt addition on the catalytic activity of the Ni-YSZ anode functional layer and the electrochemical performance of solid oxide fuel cells

The effects of cobalt (Co) addition in the Ni-YSZ anode functional layer (AFL) on the structure and electrochemical performance of solid oxide fuel cells (SOFCs) are investigated. X-ray diffraction (XRD) analyses confirmed that the active metallic phase is a Ni(1-x)Co(x) alloy under the operation conditions of the SOFC. Scanning electron microscopy (SEM) observations indicate that the grain size of Ni(1-x)Co(x) increases with increasing Co content. Thermogravimetric analyses on the reduction of the Ni(1-x)Co(x)O-YSZ powders show that there are two processes: the chemical-reaction-controlled process and the diffusion-controlled process. It is found that the reduction peak corresponding to the chemical-reaction-controlled process in the DTG curves moves toward lower temperatures with increasing Co content, suggesting that the catalytic activity of Ni(1-x)Co(x) is enhanced by the doping of Co. It is observed that the SOFC shows the best performance at x = 0.03, and the corresponding maximum power densities are 445, 651, and 815 mW cm(-2) at 700, 750, and 800 °C, respectively. The dependence of the SOFC performance on the Co content can be attributed to the competing results between the decreased three-phase-boundary length in the AFL and the enhanced catalytic activity of the Ni(1-x)Co(x) phase with increasing Co content.