Connecting experimental synthetic variables with the microstructure and electronic properties of doped ferroelectric perovskites for solar cell applications using high-throughput frameworks

Doping remains as the most used technique to photosensitize ferroelectric oxides for solar cell applications. However, optimizing these materials is still a challenge. First, many variables should be considered, for instance dopant nature and concentration, synthesis method or temperature. Second, all these variables should be connected with the microstructure of the solid solution and its optoelectronic properties. Here, a computational high-throughput framework that combines Boltzmann statistics with DFT calculations is presented as a solution to accelerate the optimization of these materials for solar cells applications. This approach has two main advantages: i) the automatic and systematic exploration of the configurational space and ii) the connection between processing and electronic properties through the description of changes in the microstructure of the material. One of the most studied doped-ferroelectric systems, [KNbO3](1-x) [BaNi1/2Nb1/2O3-delta](x), is used as a study case. Our results not only agree with previous theoretical and experimental reports, but also explain the effect of some of the variables to consider when this material is synthesized in order to optimize their performance.