Accelerating Cathode Material Discovery through Ab Initio Random Structure Searching
Bonan Zhu, Ziheng Lu, Chris J. Pickard, David O. Scanlon
The choice of cathode material in Li-ion batteries (LIBs) underpins their
overall performance. Discovering new cathode materials is a slow process, and
all major commercial cathode materials are still based on those identified in
the 1990s. Materials discovery using high-throughput calculations has attracted
great research interest, however, reliance on databases of existing materials
begs the question of whether these approaches are applicable for finding truly
novel materials. In this work, we demonstrate that ab-initio random structure
searching (AIRSS), a first-principles structure prediction methods that does
not rely on any pre-existing data, can locate low energy structures of complex
cathode materials efficiently based only on chemical composition. We use AIRSS
to explore three Fe-containing polyanion compounds as low-cost cathodes. Using
known quaternary LiFePO4 and quinary LiFeSO4F cathodes as examples, we easily
reproduce the known polymorphs, in addition to predicting other, hitherto
unknown, low energy polymorphs, and even finding a new polymorph of LiFeSO4F
which is more stable than the known ones. We then explore the phase space for
Fe-containing fluoroxalates, predicting a range of redox-active phases that
have yet to be experimentally synthesized, demonstrating the suitability of
AIRSS as a tool for accelerating the discovery of novel cathode materials.