Triggering Reversible Intercalation-Conversion Combined Chemistry for High-Energy-Density Lithium Battery Cathodes.

Combining intercalation and conversion reactions maximizes the utilization of redox-active elements in electrodes, providing a means for overcoming the current capacity ceiling. However, integrating both mechanisms within a single electrode material presents significant challenges owing to their contrasting structural requirements. Intercalation requires a well-defined host structure for efficient lithium-ion diffusion, whereas conversion reactions entail structural reorganization, which can undermine intercalation capabilities.

Design of a trigonal halide superionic conductor by regulating cation order-disorder.

Lithium-metal-halides have emerged as a class of solid electrolytes that can deliver superionic conductivity comparable to that of state-of-the-art sulfide electrolytes, as well as electrochemical stability that is suitable for high-voltage (>4 volt) operations. We show that the superionic conduction in a trigonal halide, such as LiMCl [where metal (M) is Y or Er], is governed by the in-plane lithium percolation paths and stacking interlayer distance. These two factors are inversely correlated with each other by the partial occupancy of M, serving as both a diffusion inhibitor and pillar for maintaining interlayer distance.

Slab gliding, a hidden factor that induces irreversibility and redox asymmetry of lithium-rich layered oxide cathodes.

Lithium-rich layered oxides, despite their potential as high-energy-density cathode materials, are impeded by electrochemical performance deterioration upon anionic redox. Although this deterioration is believed to primarily result from structural disordering, our understanding of how it is triggered and/or occurs remains incomplete. Herein, we propose a theoretical picture that clarifies the irreversible transformation and redox asymmetry of lithium-rich layered oxides by introducing a series of global and local dynamic structural evolution processes involving slab gliding and transition-metal migration.

Predicting the chemical reactivity of organic materials using a machine-learning approach.

Stability and compatibility between chemical components are essential parameters that need to be considered in the selection of functional materials in configuring a system. In configuring devices such as batteries or solar cells, not only the functionality of individual constituting materials such as electrodes or electrolyte but also an appropriate combination of materials which do not undergo unwanted side reactions is critical in ensuring their reliable performance in long-term operation. While the universal theory that can predict the general chemical reactivity between materials is long awaited and has been the subject of studies with a rich history, traditional ways proposed to date have been mostly based on simple electronic properties of materials such as electronegativity, ionization energy, electron affinity and hardness/softness, and could be applied to only a small group of materials.