Perovskite Genomics: Optimizing the performance of large sets of perovskite materials with atomistic simulations

Perovskites are ideal candidates to be applied in two-step redox cycles to convert, store and utilize energy from concentrated solar radiation by heating the perovskite materials to high temperatures (up to 1,500 °C) and thus transferring them to an energy-rich state. In a second step at lower temperatures, this energy can be used for a variety of chemical processes. As the overall performance of such redox materials is dominated by the diffusion rate of oxide ions through the constituting lattice, tuning the redox thermodynamics of such materials through composition adjustment allows the design of ideal perovskite materials. For an enhanced insight into the diffusion properties of a large set of perovskite materials, Molecular Dynamics simulations are applied for an efficient funneling of up to 58,000 candidate oxides to a few hundred for subsequent intensive studies. A major challenge lies in the generalization of the force field generation for datasets including large numbers of different oxides involving the characteristic electrostatic properties to be known for each material. To this end, we use data obtained by DFT stored in the database of the Materials Project. In this way, we are able to suggest materials with optimized and tailored dynamic properties.