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This work characterizes a series of Ta and Nb co‐doped cobalt‐free perovskite oxides with the compositions of SrNb0.2‐xTaxFe0.8O3‐δ (x=0, 0.05, 0.1, 0.15, and 0.2) for intermediate‐temperature solid oxide fuel cell (IT‐SOFC) applications. Their electronic conductivities displayed semiconducting behavior (i. e. increase with temperature rise) between 300 and 500 °C and metallic behavior (i. e. decrease with temperature rise) from 500 to 900 °C. SrNb0.1Ta0.1Fe0.8O3–δ provided the highest electrical conductivity that reaches 300 S cm−1 at 500 °C. The thermal expansion coefficients for SrNb0.2‐xTaxFe0.8O3–δ were lower than those reported for cobalt‐containing perovskite cathodes. They varied from 12.83×10−6 to 16.31×10−6 K−1 between 30 and 810 °C. Among the five tested cathodes, SrNb0.1Ta0.1Fe0.8O3–δ exhibited the lowest area‐specific resistance between 550 and 750 °C, with a minimum of 0.046 Ω cm2 at 750 °C, when tested in its symmetric cell configuration of cathode|Sm0.2Ce0.8O1.9 (SDC)|cathode. A peak power density of 1223 mW cm−2 was achieved on a SrNb0.1Ta0.1Fe0.8O3‐δ|SDC|yttria‐stabilized zirconia (YSZ)|Ni‐YSZ anode‐supported fuel cell at 700 °C. This work highlights the opportunity to create new perovskite cathode compositions with improved electrochemical performance through a co‐doping strategy.

The comparison of the angular light-scattering method (ALSM) and the spectral extinction method (SEM) in solving the inverse problem of aerosol size distribution (ASD) are studied. The inverse problem is solved by a SPSO-DE hybrid algorithm, which is based on the stochastic particle swarm optimization (SPSO) algorithm and differential evolution (DE) algorithm. To improve the retrieval accuracy, the sensitivity analysis of measurement signals to characteristic parameters in ASDs is studied; and the corresponding optimal measurement angle selection region for ALSM and optimal measurement wavelength selection region for SEM are proposed, respectively. Results show that more satisfactory convergence properties can be obtained by using the SPSO-DE hybrid algorithm. Moreover, short measurement wavelengths and forward measurement angles are beneficial to obtaining more accurate results. Then, common monomodal and bimodal ASDs are estimated under different random measurement errors by using ALSM and SEM, respectively. Numerical tests show that retrieval results by using ALSM show better convergence accuracy and robustness than those by using SEM, which is attributed to the distribution of the objective function value. As a whole, considering the convergence properties and the independence on prior optical information, the ALSM combined with SPSO-DE hybrid algorithm provides a more effective and reliable technique to obtain the ASDs.

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