Materials
exhibiting outstanding ion transport properties have
been investigated for extensive applications, and there has been an
increasing demand for the rational design of ion-conductive materials.
δ-Bi2O3, which shows the highest reported
oxygen ionic conductivity, possesses a notoriously defective and disordered
structure, and this leads to make the initial guess of the atomic
coordinates difficult. Therefore, there is a lack of fundamental understanding
of the thermodynamic stability, doping effects, and surface reactions
of δ-Bi2O3. Herein, we suggest an accurate
and efficient way to describe the disordered nature of the δ-Bi2O3 oxygen sublattice, involving structure modeling
and structure sampling processes. Using a special quasirandom structure
method, we developed the disordered structure pool of δ-Bi2O3 and verified our modeling process by accurately
predicting its material properties. Subsequently, we introduced a
structure sampling process to efficiently determine the size of the
Bi2O3 structure pool based on the convergence
of the disorder variable while maintaining the prediction accuracy.