Crystal Structure Prediction for Battery Materials

Batteries have become an integral part of modern life, powering everything from mobile phones to electric vehicles. Their performance is governed by the materials used in their construction. Conventional experimental methods based on trial-and-error lead to low efficiency in the discovery of new materials for batteries. In this chapter, crystal structure prediction (CSP) is introduced as a computational tool to facilitate the discovery and design of battery materials. The fundamentals and theoretical framework of modern CSP is introduced, i.e., how new crystals are discovered by virtually placing atoms in computational methods. Representative methods are given as examples of the state-of-the-art in the CSP arena, showcasing their capabilities and limitations. The application of such methods in batteries is followed by a discussion of the key material requirements in real devices. In particular, a schematic pipeline for the discovery of novel cathodes, anodes, coatings, and solid electrolytes for batteries is presented, with examples.