Ab initio random structure searching for battery cathode materials

TL;DR

This paper introduces a computational framework using ab initio random structure searching (AIRSS) to discover new and metastable battery cathode materials efficiently, expanding the chemical space beyond traditional methods.

Contribution

The paper presents a novel application of AIRSS for battery cathode discovery, including constraints and parameter optimization, and proposes new transition-metal oxalate cathodes with promising properties.

Findings

Successfully rediscovered known cathode structures.

Identified novel transition-metal oxalate cathodes with high energy density.

Demonstrated the efficiency of AIRSS in exploring metastable phases.

Abstract

Cathodes are critical components of rechargeable batteries. Conventionally, the search for cathode materials relies on experimental trial-and-error and a traversing of existing computational/experimental databases. While these methods have led to the discovery of several commercially-viable cathode materials, the chemical space explored so far is limited and many phases will have been overlooked, in particular those that are metastable. We describe a computational framework for battery cathode exploration, based on ab initio random structure searching (AIRSS), an approach that samples local minima on the potential energy surface to identify new crystal structures. We show that, by delimiting the search space using a number of constraints, including chemically aware minimum interatomic separations, cell volumes, and space group symmetries, AIRSS can efficiently predict both thermodynamically stable and metastable cathode materials. Specifically, we investigate LiCoO2, LiFePO4, and LixCuyFz to demonstrate the efficiency of the method by rediscovering the known crystal structures of these cathode materials. The effect of parameters, such as minimum separations and symmetries, on the efficiency of the sampling is discussed in detail. The adaptation of the minimum interatomic distances, on a species-pair basis, from low-energy optimized structures to efficiently capture the local coordination environment of atoms, is explored. A family of novel cathode materials based, on the transition-metal oxalates,is proposed. They demonstrate superb energy density, oxygen-redox stability, and lithium diffusion properties. This article serves both as an introduction to the computational framework, and as a guide to battery cathode material discovery using AIRSS.