Impedance Spectroscopy Genetic Programming Research Articles

Quantifying the Resistive Losses of the Catalytic Layers in Anion-Exchange Membrane Fuel Cells.

The existing gap in the ability to quantify the impacts of resistive losses on the performance of anion-exchange membrane fuel cells (AEMFCs) during the lifetime of their operation is a serious concern for the technology. In this paper, we analyzed the ohmic region of an operating AEMFC fed with pure oxygen followed by CO2 -free air at various operating currents, using a combination of electrochemical impedance spectroscopy (EIS) and a novel technique called impedance spectroscopy genetic programming (ISGP). Presented here for the first time in this work, we isolated and quantified the individual effective resistance (Reff ) values occurring in the AEMFC and their influence on performance as operating conditions change. We believe that this first work is vital to help distinguish the influence of the individual catalytic and mass-transfer processes in this technology thereby providing valuable data to the AEMFC community, with potentially wider applicability to other electrochemical devices where individual physical processes occur simultaneously and need to be sequestered for deeper understanding.

Determining the Electrochemical Oxygen Evolution Reaction Kinetics of Fe3S4@Ni3S2 Using Distribution Function of Relaxation Times

AbstractWe designed a heterostructure of Fe3S4@Ni3S2, as a potent oxygen evolution reaction (OER) electrocatalyst in an alkaline medium. Intriguingly, Fe3S4@Ni3S2 exhibits low onset potential of 290 mV and overpotential of 360 mV at a current density of 10 mA cm−2. We examined the OER kinetics of Fe3S4@Ni3S2 using distribution function of relaxation times (DFRT), which are attained with the help of impedance spectroscopy genetic programming (ISGP). ISGP reveals the occurrences of three events of OER, manifested as peaks in the DFRT, such as active material or pores (P2), charge transfer (P1’), and production rate of intermediates (P1) in case of Fe3S4@Ni3S2 at different faradic overpotentials. The effective resistance of each phenomenon can be easily calculated. It decreases with an increase in conductivity at high overpotentials for all the three, which suggests the high performance of the as‐synthesized composite due to faster kinetics. Further, structural investigation of the catalyst employing x‐ray photoelectron spectroscopy is elaborated and it is suggested that the catalyst activation takes place by the constant exchange of anions between electrode and electrolyte during electrochemical oxidation.

Modeling of the impedance data of gadolinia doped ceria based actuators: a distribution function of relaxation times and machine learning approach

Gadolinia-doped ceria is one of the most extensively examined oxide ion conductors to exhibit large nonclassical electrostriction. The electromechanical response depends on the grain and grain boundaries which can be probed using electrochemical impedance spectroscopy. In this study, we have modeled the impedance spectra from buckled and free standing gadolinia doped ceria (Gd0.2Ce0.8O1.9) membrane in Al/Ti/Gd0.2Ce0.8O1.9/Ti/Al electromechanical device, at different AC excitation voltages (2, 4, 6, 8 and 10 V), and starting from room temperature to 100 °C. The analysis of impedance spectrum is commonly done by equivalent circuit modeling to obtain the resistors () and capacitors (). However, to overcome the inherent problems like non-uniqueness, over fitting, presently different approaches have been chosen such as impedance spectroscopy genetic programming (ISGP) and artificial neural networks (ANNs). ISGP finds an analytic form of the distribution function of relaxation times (DFRTs) using impedance spectra. The DFRT analysis reveals that the grain boundary capacitance for the membrane ∼10−8–10−9 F decreases with increasing temperature and excitation voltages. Besides, neural networks, which are optimized by Bayesian regularization, simulate both the real and imaginary parts of impedance following the pattern of experimental data up to several Hz. The DFRT analysis on this simulated impedance data shows an effect of grain boundaries. Indeed, ANNs as optimized by Levenberg-Marquardt method, can estimate the and ’s for present system with maximum relative errors of 24% and 22%, respectively.

Studies on effect of Ca-doping on structure and electrochemical properties of garnet-type Y3-xCaxFe5O12-δ

In this study, effect of Ca-doping on electrical and electrochemical properties of garnet structure Y3-xCaxFe5O12-δ (x ​= ​0, 0.05, 0.1, 0.3, 0.5 and 0.7) was investigated. Cubic-phase (Ia-3d) garnet was prepared through sol-gel method and sintered at 1100 ​°C for 2 ​h in air. Highest oxygen non-stoichiometry (δ ​= ​0.19) was found in x ​= ​0.3 member. X-ray absorption spectroscopy (XAS) confirmed the formation of hole carriers (Fe.Fe) due to Ca-substitution for Y in Y3Fe5O12. 4-Probe DC measurements showed that electrical conductivity increased with an increase in Ca amount until x ​= ​0.1 (1.58 ​S/cm at 750 ​°C) and then decreased due to decrease in the concentration of the charge carriers. Lowest area specific resistance (ASR) of 1 Ωcm2 was seen at 750 ​°C in air for the symmetrical cell with x ​= ​0.3 garnet-LSGM composite electrode. Studies on pO2 dependent ASR and impedance spectroscopy genetic programming (ISGP) analysis revealed that oxygen dissociation and partial reduction of adsorbed oxygen molecule co-limit the electrochemical performance for oxygen reduction reaction (ORR).

Electrochemical impedance spectra of RuO2 during oxygen evolution reaction studied by the distribution function of relaxation times

In this work, the distribution function of relaxation times (DFRT) of a RuO2 catalyst is determined by Impedance Spectroscopy Genetic Programming (ISGP). The resulting DFRT plots contain three peaks that vary with the overpotential. This discloses the presence of various electrochemical phenomena at different relaxation times in the catalyst. The effective resistance to charge transfer during the oxygen evolution reaction (OER) is small at low overpotential but becomes dominant at high overpotential. Moreover, we can track the change in each peak after a stability test: the resistance to both the production rate of intermediates and charge transfer show an increase while the solution resistance is almost constant. Hence, ISGP opens a new avenue for analyzing catalysts and providing detailed information about the resistance contributed by various phenomena.

Determination of grain boundary conductivity using distribution function of relaxation times (DFRT) analysis at room temperature in 10 mol% Gd doped ceria: A non-classical electrostrictor

The electrical conductivity of Ce0.90Gd0.10O1.95 oxide ion conductor is studied, emphasizing distribution function of relaxation times (DFRT) analysis of impedance spectroscopy measurements. The corresponding powder has been prepared by co-precipitation method and sintered at 1300 °C. The formation of the fluorite phase is confirmed by X-ray diffraction. The temperature dependence of ionic conductivity has been studied at different bias voltages. The impedance spectra are analysed by impedance spectroscopy genetic programming (ISGP) that finds an analytic form of the DFRT. Interestingly, both the grain and grain boundary conductivities can be identified at room temperature by analysing the DFRTs. At higher temperatures and higher bias voltages, the grain boundary diffusion process of oxygen ions is identified. Both the grain and grain boundary activation energies are bias independent.

Structure and electrical conductivity of Ta doped La2Mo2O9 oxide ion conductors

In this work, we have investigated the crystal structure, thermal, vibrational, microstructural, and electrical properties of Ta doped La2Mo2O9 oxide ion conductors. The Rietveld refinements on the X-ray diffraction patterns confirm the α phase similar to that of undoped La2Mo2O9 at room temperature. α → β phase transition is confirmed by the differential scanning calorimetry analysis. The microcrystalline samples have grain sizes ∼10 μm along with well-defined grain boundaries. The infrared and Raman spectra mainly consist of MoO4 bands. The electrical conductivity of the highly dense pellets was analyzed by the impedance spectroscopy genetic programming method coupled with distribution function of relaxation times (DFRTs). Each DFRT consists of three main peaks conferring bulk, ionic, and electronic contributions of the grain boundary. The higher oxide ion conductivity in the β phase is identified due to the electronic contribution of the grain boundary for the samples. The capacitance for bulk and ionic parts of the grain boundary are almost temperature independent, whereas the electronic contribution varies turbulently. The incorporation reaction suggests that the sample with 5 wt. % Ta has the maximum oxide ion conductivity, which is further verified by the resistances obtained from the DFRT analysis.

Effect of isovalent doping on grain boundary conductivity for La2Mo2O9 oxide ion conductor: A distribution function of relaxation times approach

In this work we have studied the effect of grain boundary space charge on oxide ion conductivity of La2−xErxMo2O9 (0.05 ≤ x ≤ 0.25) ionic conductors. Microstructure is studied by scanning electron microscopy and high resolution transmission electron microscopy. Impedance spectra are analyzed in the frame work of impedance spectroscopy genetic programming method. A distribution function of relaxation times model is obtained, which is comprised of two peaks and correlated with the contribution from grain and grain boundary conductivities. The activation energies obtained for both grain and grain boundary conductivities confirm thermally activated hopping of oxygen. Theoretical analysis is carried out to estimate the grain boundary space charge potential at different temperatures for all compositions. The depletion of oxygen vacancies in the space charge layer is also determined. Despite the fact that Er is an isovalent dopant, both the space charge potential and oxygen vacancies are found to be composition dependent. The increase in space charge potential is related to decrease in grain boundary conductivity.

An aluminum – ionic liquid interface sustaining a durable Al-air battery

A thorough study of a unique aluminum (Al)-air battery utilizing a pure Al anode, an air cathode, and hydrophilic room temperature ionic liquid electrolyte 1-ethyl-3-methylimidazolium oligofluorohydrogenate [EMIm(HF)2.3F] is reported. The effects of various operation conditions, both at open circuit potential and under discharge modes, on the battery components were discussed. A variety of techniques were utilized to investigate and study the interfaces and processes involved, including electrochemical studies, electron microscopy, spectroscopy and diffraction. As a result of this intensive study, the upon-operation voltage drop (“dip”) obstacle, occurring in the initial stages of the Al-air battery discharge, has been resolved. In addition, the interaction of the Al anode with oligofluorohydrogenate electrolyte forms an Al-O-F layer on the Al surface, which allows both activation and low corrosion rates of the Al anode. The evolution of this layer has been studied via impedance spectroscopy genetic programming enabling a unique model of the Al-air battery.

Evolutionary Programming Based Approach for SOFC Cathode Characterization: A Case Study on Co-Free Mixed Conducting Perovskites

Electrochemical impedance spectroscopy (EIS) is a powerful technique to characterize the performance of solid oxide fuel cells (SOFCs). Given a proper analysis technique, EIS data can shed light on the different contributions to the total impedance. The most common analysis technique is equivalent circuit modelling (ECM), where a combination of resistors, capacitors, constant phase elements, etc. represents the physical response of the sample. ECM has its known drawbacks, e.g. non-uniqueness and obscure physical meaning of the chosen model. Using impedance spectroscopy genetic programming (ISGP), based on evolutionary programming, those challenges are better tackled. Our analysis focuses on finding the distribution function of relaxation times (DFRT). The analysis procedure using ISGP yields a DFRT model comprised of known mathematical peaks. Each peak in the model is characterized by its height, width and relaxation time. It is possible to assign each peak to one or more process, and to calculate its area. Thus, we are able to determine the contribution of each process to the total impedance. By plotting the DFRT as a function of frequency it is possible to identify the different polarization processes and gain additional information, which may be convoluted and therefore undetected in other analysis techniques. Here, we report the electrochemical performance of perovskite-type Co-free cathodes such as Ba0.5Sr0.5Fe0.91Al0.09O3-δ, Ba0.5Sr0.5Fe0.8Cu0.2O3-δ, and Ba0.5Sr0.5Fe0.8Nb0.2O3-δ with oxide ion conducting La0.8Sr0.2Ga0.8Mg0.2O3-δ (LSGM) and proton conducting Ba0.5Sr0.5Ce0.6Zr0.2Gd0.1Y0.1O3-δ electrolytes have been investigated by ISGP. Composites of cathode with electrolytes were screen printed on both sides of electrolyte in order to get symmetrical cells for evaluating cathode performances. EIS of symmetrical cells at different experimental conditions were analyzed by ISGP. Thus, by changing parameters and monitoring corresponding changes in the peaks’ relaxation times and areas, in-depth understanding of the operation of various components of the symmetrical cells such as the oxygen reduction reactions, mass transfer limitations and the electrolyte ionic conductivity can be achieved.

Evolutionary Programming Based Approach for SOFC Cathode Characterization: A Case Study on Co-Free Mixed Conducting Perovskites

Cobalt-free perovskites were investigated in this work, in order to find more economical and chemically stable materials to serve as cathodes for intermediate temperature solid oxide fuel cells. The electrochemical performance of Ba0.5Sr0.5Fe0.91Al0.09O3-δ and Ba0.5Sr0.5Fe0.8Cu0.2O3-δ with oxide ion conducting La0.8Sr0.2Ga0.8Mg0.2O3-δ and proton conducting Ba0.5Sr0.5Ce0.6Zr0.2Gd0.1Y0.1O3-δ electrolytes was studied using non-destructive electrochemical impedance spectroscopy. The measured data was analyzed by impedance spectroscopy genetic programming (ISGP), which results in a unique model that requires no a-priori knowledge of the tested system. In-depth cathode operation mechanism is shown by finding the distribution function of relaxation times (DFRT) using ISGP. By monitoring the changes in the DFRT models at different temperatures, we are able to de-convolute the oxygen reduction reaction to its several polarization processes. Using our analysis approach it is possible to gain additional information, which may be convoluted and therefore undetected in conventional impedance analysis.

A novel approach for supercapacitors degradation characterization

Abstract A novel approach to analyze electrochemical impedance spectroscopy (EIS), based on evolutionary programming, has been utilized to characterize supercapacitors operation mechanism and degradation processes. This approach poses the ability of achieving a comprehensive study of supercapacitors via solely AC measurements. Commercial supercapacitors were examined during accelerated degradation. The microstructure of the electrode-electrolyte interface changes upon degradation; electrolyte parasitic reactions yield the formation of precipitates on the porous surface, which limit the access of the electrolyte ions to the active area and thus reduces performance. EIS analysis using Impedance Spectroscopy Genetic Programming (ISGP) technique enables identifying how the changing microstructure is affecting the operation mechanism of supercapacitors, in terms of each process effective capacitance and time constant. The most affected process is the transport of electrolyte ions at the porous electrode. Their access to the whole active area is hindered, which is shown in our analysis by the decrease of the capacitance gained in the transport and the longer time it takes to penetrate the entire pores depth. Early failure detection is also demonstrated, in a way not readily possible via conventional indicators. ISGP advanced analysis method has been verified using conventional and proven techniques: cyclic voltammetry and post mortem measurements.

Vibrational and impedance spectroscopic analyses of semi-interpenetrating polymer networks as solid polymer electrolytes.

Semi-interpenetrating polymer networks (semi-IPNs) with significant ionic conductivity (10-4 S cm-1 at ambient temperature) were studied by vibrational and impedance spectroscopies coupled with advanced analysis procedures. Vibrational spectroscopy recognized the numbers of free ions, ion pairs, ion-polymers and hydrogen bonds within the solid polymer electrolyte matrices (SPE). Electrochemical impedance spectroscopy (EIS) was used to quantify the bulk resistance and bulk relaxation time. The analyses used discrepancy-complexity plots to assess the number of free parameters properly, and EIS was further analyzed using impedance spectroscopy genetic programming (ISGP). Four compositions of PEO-polyurethane/poly(ethylene glycol) dimethyl ether (PEO-PU/PEGDME) were examined with LiClO4 salt. The polymer electrolyte composition of 30/70 PEO-PU/PEGDME resulted in the lowest relaxation times and the highest ionic conductivity. The best salt concentration was observed at an EO/Li ratio of 30 for the PEO-PU/PEGDME : LiClO4 (30/70) semi-IPN matrix. Several lithium salts of different anions were examined at an EO/Li ratio of 10, and the ionic conductivity achieved varied in the order -N(CF3SO2)2- > -ClO4- > -(CF3SO3)- > -I-/I3-.

Impedance spectroscopy analysis inspired by evolutionary programming as a diagnostic tool for SOEC and SOFC

Impedance spectroscopy (IS) is an effective tool for the analysis of solid oxide fuel cell (SOFC) and solid oxide electrolysis cell (SOEC) performance. The challenge using this characterization tool lies within the analysis method. Impedance spectroscopy genetic programming (ISGP) is a novel analysis technique for impedance spectroscopy data. The ISGP utilizes evolutionary programming techniques for finding the most suitable distribution function of relaxation times (DFRT). This approach leads toward a better analysis of impedance spectroscopy results as compared to other analysis tools such as equivalent circuits or deconvolution techniques.In this work, SOFC and SOEC were examined during operation by IS measurements and the results were analyzed using ISGP. The aim of this work is to show examples of DFRT models which reflect the physical processes occurring during the operation. It is demonstrated that despite the low impedance (in the mΩ range) and the narrow available bandwidth, ISGP can provide consistent DFRT models.

Analysis of impedance spectroscopy of aqueous supercapacitors by evolutionary programming: Finding DFRT from complex capacitance

Electrochemical impedance spectroscopy (EIS) of aqueous-electrolyte supercapacitors can shed light on the physical processes occurring within the cell, given a proper analysis technique. Impedance Spectroscopy Genetic Programming (ISGP) is a novel technique to analyze EIS data. ISGP finds a functional form of the distribution of relaxation times utilizing genetic algorithm and offers a detailed quantitative analysis.In this work, EIS data of aqueous-electrolyte supercapacitors were analyzed by transforming the data to complex capacitance representation. A distribution function of relaxation times (DFRT) model was obtained, comprised of two peaks, each correlated with a different physical process (diffusion and EDLC formation). Two cell configurations were examined and the differences regarding capacitance distribution and diffusion rates are presented.

Electrochemical Impedance Analysis of SOFC Cathode Reaction Using Evolutionary Programming

AbstractInvestigation of the cathode reaction in solid oxide fuel cells (SOFC) by impedance spectroscopy (IS) measurements using evolutionary‐based programming analysis is demonstrated. In contrast to the conventional analysis methods used for impedance spectroscopy measurements, e.g., equivalent circuits, the impedance spectroscopy genetic programming (ISGP) program seeks for a distribution of relaxation times that has the form of a peak or a sum of several peaks, assuming the Debye kernel. Using this method one finds a functional (parametric) form of the distribution of relaxation times. A symmetric cell configuration of Pt|LSCF|GDC|LSCF|Pt was examined using IS measurements combined with I–V measurements. Different samples at different temperatures and different oxygen partial pressures were examined in order to investigate their influence on the oxygen reduction reaction. The resulting IS data was analyzed using the ISGP program and the resulting peaks constructing the distribution of relaxation times were assigned for the different processes that occur at the cathode side. The activation energies as well as the dependence of the processes on the oxygen partial pressure were also evaluated.