Predicting the optimal dopant concentration in gadolinium doped ceria: a kinetic lattice Monte Carlo approach

Abstract

Gadolinium doped ceria (GDC) is a promising alternative electrolyte material for solid oxide fuel cells that offers the possibility of operation in the intermediate temperature range (773–1073 K). To determine the optimal dopant concentration in GDC, we have employed a systematic approach of applying a 3D kinetic lattice Monte Carlo (KLMC) model of vacancy diffusion in conjunction with previously calculated activation energies for vacancy migration in GDC as inputs. KLMC simulations were performed including the vacancy repelling effects in GDC. Increasing the dopant concentration increases the vacancy concentration, which increases the ionic conductivity. However, at higher concentrations, vacancy–vacancy repulsion impedes vacancy diffusion, and together with vacancy trapping by dopants decreases the ionic conductivity. The maximum ionic conductivity is predicted to occur at ≈20% to 25% mole fraction of Gd dopant. Placing Gd dopants in pairs, instead of randomly, was found to decrease the conductivity by ≈50%. Overall, the trends in ionic conductivity results obtained using the KLMC model developed in this work are in reasonable agreement with the available experimental data. This KLMC model can be applied to a variety of ceria-based electrolyte materials for predicting the optimum dopant concentration.