RESUMO
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 Li3MCl6 [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. These findings suggest that a critical range or ordering of M exists in trigonal halides, and we showcase the achievement of high ionic conductivity by adjusting the simple M ratio (per Cl or Li). We provide general design criteria for superionic trigonal halide electrolytes.
RESUMO
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. We show that slab gliding plays a key role in trigger/initiating the structural disordering and consequent degradation of the anionic redox reaction. We further reveal that the 'concerted disordering mechanism' of slab gliding and transition-metal migration produces spontaneously irreversible/asymmetric lithiation and de-lithiation pathways, causing irreversible structural deterioration and the asymmetry of the anionic redox reaction. Our findings suggest slab gliding as a crucial, yet underexplored, method for achieving a reversible anionic redox reaction.
RESUMO
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. Moreover, prediction has often been far from accurate and has failed to offer general implications; thus it was practically inadequate as a selection criterion from a large material database, i.e. data-driven material discovery. Herein, we propose a new model for predicting the general reactivity and chemical compatibility among a large number of organic materials, realized by a machine-learning approach. As a showcase, we demonstrate that our new implemented model successfully reproduces previous experimental results reported on side-reactions occurring in lithium-oxygen electrochemical cells. Furthermore, the mapping of chemical stability among more than 90 available electrolyte solvents and the representative redox mediators is realized by this approach, presenting an important guideline in the development of stable electrolyte/redox mediator couples for lithium-oxygen batteries.
