An improved method to increase the predictive accuracy of the ECR technique

The technique of electrical conductivity relaxation (ECR) is a widely utilized method for obtaining oxygen chemical surface exchange (k) and bulk diffusion (D) coefficients for mixed ionic electronic conductors. Although the technique is conceptually simple, its practical application does not frequently produce reliably accurate values of k and D, and many examples of poor agreement can be found in the published literature. In this present paper, methods for enhancing the accuracy of the ECR technique relative to data processing are described in detail. Physically accurate determination of the actual starting time (t0) and improved methods for data fitting of ECR measurements are discussed. To test the methods described, generated relaxation data sets are analyzed by using non-linear-least-square (NLLS) methods. The results showed that fixing t0 based on an ideally stirred reactor model improves the fitted results compared to treating t0 as a fitted parameter. Additionally, evaluation of the global minimum in the fitted error is made by analyzing multiple samples of varying thickness, which improves parameter evaluation compared to analysis of a single relaxation data set. The improved accuracy of the computed values of k and D is described in comparison to conventional methods.