Developing workflows for DFT + thermodynamics predictions of metal release from complex metal oxides under aqueous conditions | Poster Board #520

Improper disposal of lithium-ion batteries has become a growing environmental concern given that damaged batteries can leak various toxic substances. Specifically, metal cations can leach from oxides that comprise the battery cathode and form toxic aqueous species. The objective of this research is to develop a molecular-level understanding of the transformations that technologically in-use nanomaterials undergo in the environment. Physics-based modeling techniques such as Density Functional Theory (DFT) can be incorporated in high-throughput computational workflows to create and analyze large data sets while identifying trends to inform materials design, optimizing functionality and sustainability. We employ compositional tuning of Li(AxByCz)O2 structures, systematically altering the metal identities A, B, and C and their relative ratios in the complex, with the goal of discovering formulations that enhance properties like capacity, stability, and safety. For this project, 300+ ternary complex metal oxide materials (CMOs) have been designed using high-throughput approaches; the materials were modeled using DFT and studied for their metal release properties. Using electronic structure analysis, we identify changes in metal oxidation state that relate to material stability and performance, mapping material properties to the key chemical and electronic descriptors. One of the most important findings is that an enriched Mn or V surface significantly favors the release of MnOH meaning it can be more easily recyclable, yet more likely to solvate. The analysis also showed that Mn had the highest range of oxidation, while Al had the smallest. In conclusion, the results demonstrate that confluence of oxidation state, coordination environment, and aqueous chemistry govern metal release.