Prediction of impedance responses of protonic ceramic cells using artificial neural network tuned with the distribution of relaxation times

A deep-learning-based framework is proposed to predict the impedance response and underlying electrochemical behavior of the reversible protonic ceramic cell(PCC) across a wide variety of different operating conditions.Electrochemical impedance spectra(EIS) of PCCs were first acquired under a variety of opera ting conditions to provide a dataset containing 36 sets of EIS spectra for the model.An artificial neural network(ANN) was then trained to model the relationship between the cell operating condition and EIS response.Finally,ANN model-predicted EIS spectra were analyzed by the distribution of relaxation times(DRT) and compared to DRT spectra obtained from the experimental EIS data,enabling an assessment of the accumulative errors from the predicted EIS data vs the predicted DRT.We show that in certain cases,although the R^(2)of the predicted EIS curve may be> 0.98,the R^(2)of the predicted DRT may be as low as~0.3.This can lead to an inaccurate ANN prediction of the underlying time-resolved electrochemical response,although the apparent accuracy as evaluated from the EIS prediction may seem acceptable.After adjustment of the parameters of the ANN framework,the average R^(2)of the DRTs derived from the predicted EIS can be improved to 0.9667.Thus,we demonstrate that a properly tuned ANN model can be used as an effective tool to predict not only the EIS,but also the DRT of complex electrochemical systems.

Enhancing cathode performance for CO2 electrolysis with Ce0.9M0.1O2-δ（M=Fe, Co, Ni） catalysts in solid oxide electrolysis cell

Electrochemical conversion with solid oxide electrolysis cells is a promising technology for CO2 utilization and simultaneously store renewable energy.In this work,Ce0.9M0.1O2-δ(CeM,M=Fe,Co,Ni)catalysts are infiltrated into La0.6Sr0.4Cr0.5Fe0.5O3-δ-Gd0.2Ce0.8O2-δ(LSCr Fe-GDC)cathode to enhance the electrochemical performance for CO2 electrolysis.CeCo-LSCrFe-GDC cell obtains the best performance with a current density of 0.652 A cm^-2,followed by CeFe-LSCrFe-GDC and CeNi-LSCrFe-GDC cells with the value of 0.603 and 0.535 A cm^-2,respectively,about 2.44,2.26 and 2.01 times higher than that of the LSCrFe-GDC cell at1.5 V and 800℃.Electrochemical impedance spectra combined with distributions of relaxed times analysis shows that both CO2 adsorption process and the dissociation of CO2 at triple phase boundaries are accelerated by Ce M catalysts,while the latter is the key rate-determining step.

自组装FeRu双金属纳米催化剂在可逆固体氧化物电池中实现高效稳定的CO-CO_(2)相互转化

本文报道了一种适应于高效稳定的CO-CO_(2)相互转化的可逆固体氧化物电池(RSOC)相变燃料电极.该燃料电极由FeRu双金属纳米催化剂和Ruddlesden-Popper相Pr_(0.8)Sr_(1.2)Fe_(1-x-y)Ru_(x)Mo_(y)O_(4)氧化物复合而成(FeRu@PSFRM).固体氧化物燃料电池(SOFC)模式时,单电池800℃时的最大输出功率密度可以达到170 W cm^(-2);而在固体氧化物电解池(SOEC)模式下,800℃、1.3 V时电解池的电解电流密度达到-0.256 A cm^(-2).在SOFC-SOEC循环测试过程中,RSOC中CO-CO_(2)相互转化过程经历了“活化-稳定-衰退”三个明显阶段.幸运的是,性能衰退的燃料电极可通过“原位氧化-还原”处理实现性能再生,有效提升该电池的使用寿命.研究结果表明,原位脱溶形成的FeRu@PSFRM材料是一种极具应用潜力的燃料电极候选材料,以期实现高效稳定的CO-CO_(2)相互转化.

Electrochemical impedance spectroscopy analysis to accelerate electrocatalytic system innovation

Electrochemical impedance spectroscopy(EIS)is a well-established non-destructive characterization technique for assessing the efficacy of electrochemical energy storage and conversion systems.Electrocatalytic systems based on proton exchange membrane(PEM),including PEM fuel cells and PEM water electrolyzers,play a crucial role in renewable energy conversion through electricity–hydrogen interconversion.EIS,along with its derived analysis methods—equivalent circuit model(ECM),distribution of relaxation time(DRT),and dynamic EIS(DEIS),is widely utilized to extract valuable kinetics and impedance data.The acquired information affords critical insights into processes such as mass transfer,charge transfer,and proton transfer within PEM systems.This mini review surveys the role of EIS in optimizing components and investigating operational conditions to enhance the efficiency of PEM systems.In addition,it encapsulates the principles and applications of EIS-based methods like DRT and DEIS,highlighting their potential in the practical application of PEM systems.

New two-layer Ruddlesden-Popper cathode materials for protonic ceramics fuel cells

New two-layer Ruddlesden-Popper(RP)oxide La_(0.25)Sr_(2.75)FeNiO_(7-δ)(LSFN)in the combination of Sr_(3)Fe_(2)O_(7-δ) and La_(3)Ni_(2)O_(7-δ) was successfully synthesized and studied as the potential active single-phase and composite cathode for protonic ceramics fuel cells(PCFCs).LSFN with the tetragonal symmetrical structure(IMmmm)is confinned,and the co-existence of Fe^(3+)/Fe^(4+) and Ni^(3+)/Ni^(2+) couples is demonstrated by X-ray photoelectron spectrometer(XPS)analysis.The LSFN conductivity is apparently enhanced after Ni doping in Fe-site,and nearly three times those of Sr_(3)Fe_(2)O_(7-δ),which is directly related to the carrier concentration and conductor mechanism.Importantly,anode supported PCFCs using LSFN-BaZr_(0.1)Ce_(0.7)Y_(0.2)O_(3-δ)(LSFN-BZCY)composite cathode achieved high power density(426 mW·cm^(-2) at 650℃)and low electrode interface polarization resistance(0.26Ω·cm^(2)).Besides,distribution of relaxation time(DRT)function technology was further used to analyse the electrode polarization processes.The observed three peaks(Pl,P2,and P3)separated by DRT shifted to the high frequency region with the decreasing temperature,suggesting that the charge transfer at the electrode-electrolyte interfaces becomes more difficult at reduced temperatures.Preliminary results demonstrate that new two-layer RP phase LSFN can be a promising cathode candidate for PCFCs.