Statistical method to optimize the medium temperature solid oxide fuel cell electrode materials

Abstract

The research on intermediate-temperature solid oxide fuel cell materials has been largely focussed on three main areas: optimization of material porosity, introduction of nano-scale starting powders, and the search for new, electrochemically more active materials. However, regardless of the large number of papers published on the matter, only very few examples of statistically correct systematic optimization studies have been published. In this paper, the performance of electrolyte-supported Ni/Ce 0.9Gd 0.1O 2− δ |Ce 0.9Gd 0.1O 2− δ |Ln 0.6Sr 0.4CoO 3− δ , Ln = La, Pr, Gd, symmetric single-cells has been optimized for anode diffusion layer porosity, anode functional layer starting powder specific surface area ( S BET,powder), and cobaltite-based cathode material composition in a single designed experiment according to the so-called response surface methodology (RSM). The optimal cell was found to have either an La 0.6Sr 0.4CoO 3− δ or Pr 0.6Sr 0.4CoO 3− δ cathode, an anode active layer prepared of a starting powder of S BET,powder = 135 m 2/g, and a pore former content of 2 wt%. The combination of electrochemical impedance spectroscopy (EIS), equivalent circuit fitting, and mathematical statistics methods proved to be a powerful tool for interpreting solid oxide fuel cell data.