Ionic conduction involves the movement of ions from one location to another inside a material. The ions travel through point defects, which are irregularities in the otherwise consistent arrangement of atoms known as the crystal lattice. This sometimes sluggish process can limit the performance and efficiency of fuel cells, batteries, and other energy storage technologies.
Before determining which underlying properties of solid materials are crucial for improving these applications, researchers must better understand the factors that control ionic conduction. To pursue this knowledge, a multidisciplinary team from the US Department of Energy’s (DOE’s) Oak Ridge National Laboratory (ORNL) developed a computational framework to process and analyze large datasets of ion-conducting solids.
Using a dataset containing over 80 different compositions of materials called perovskites, the researchers focused primarily on identifying and optimizing those with promising proton conduction capabilities. These novel materials could enable the production of more reliable and efficient proton-conducting solid oxide fuel cells—energy storage devices that convert chemicals into electricity for practical uses such as powering vehicles.