ABSTRACT
Mg-S batteries hold great promise as a potential alternative to Li-based technologies. Their further development hinges on solving a few key challenges, including the lower capacity and poorer cycling performance when compared to Li counterparts. At the heart of the issues is the lack of knowledge on polysulfide chemical behaviors in the Mg-S battery environment. In this Review, a comprehensive overview of the current understanding of polysulfide behaviors in Mg-S batteries is provided. First, a systematic summary of experimental and computational techniques for polysulfide characterization is provided. Next, conversion pathways for Mg polysulfide species within the battery environment are discussed, highlighting the important role of polysulfide solubility in determining reaction kinetics and overall battery performance. The focus then shifts to the negative effects of polysulfide shuttling on Mg-S batteries. The authors outline various strategies for achieving an optimal balance between polysulfide solubility and shuttling, including the use of electrolyte additives, polysulfide-trapping materials, and dual-functional catalysts. Based on the current understanding, the directions for further advancing knowledge of Mg polysulfide chemistry are identified, emphasizing the integration of experiment with computation as a powerful approach to accelerate the development of Mg-S battery technology.
ABSTRACT
Next-generation materials for fast ion conduction have the potential to revolutionize battery technology. Metal-organic frameworks (MOFs) are promising candidates for achieving this goal. Given their structural diversity, the design of efficient MOF-based conductors can be accelerated by a detailed understanding and accurate prediction of ion conductivity. However, the polycrystalline nature of solid-state materials requires consideration of grain boundary effects, which is complicated by challenges in characterizing grain boundary structures and simulating ensemble transport processes. To address this, we have developed an approach for modeling ion transport at grain boundaries and predicting their contribution to conductivity. Mg2+ conduction in the Mg-MOF-74 thin film was studied as a representative system. Using computational techniques and guided by experiments, we investigated the structural details of MOF grain boundary interfaces to determine accessible Mg2+ transport pathways. Computed transport kinetics were input into a simplified MOF nanocrystal model, which combines ion transport in the bulk structure and at grain boundaries. The model predicts Mg2+ conductivity in the MOF-74 film within chemical accuracy (<1 kcal/mol activation energy difference), validating our approach. Physically, Mg2+ conduction in MOF-74 is inhibited by strong Mg2+ binding at grain boundaries, such that only a small fraction of grain boundary alignments allow for fast Mg2+ transport. This results in a 2-3 order-of-magnitude reduction in conductivity, illustrating the critical impact of the grain boundary contribution. Overall, our work provides a computation-aided platform for molecular-level understanding of grain boundary effects and quantitative prediction of ion conductivity. Combined with experimental measurements, it can serve as a synergistic tool for characterizing the grain boundary composition of MOF-based conductors.
