Computational Understanding of Electrochemical Energy Storage Materials

Unfortunately, designing improved battery materials has proven a formidable challenge, especially since the lifetime and rate capability of Li-ion batteries depend strongly on interfacial stability and the structural order on the atomic scale. Examples are Li- and Ni-rich cathode materials that exhibit promising first-charge capacities but typically suffer from degradation in form of cation disordering and oxygen gas release.

Here, I will discuss predictive computational approaches for the modeling of disorder and reactions at electrochemical interfaces that have advanced our understanding of prospective next-generation battery materials. By combining first-principles calculations and lattice-model simulations, we obtained insight into the effects of cation disorder on the performance of Li-ion battery cathodes. First-principles surface phase diagrams reveal initial stages of cathode degradation and dynamic changes at the interface between electrodes and protective coatings. And recently we have made initial steps towards the engineering of battery recycling processes using machine-learning augmented first-principles calculations.