Mechanistic investigations into the electrochemical performance of partially disordered LiNiO2

Cation-disordered oxides are attracting a great deal of attention as the next generation high energy Li-ion cathode materials given their exceptionally high capacities (~ 300 mAh g-1), and their high chemical versatility. Moreover, unlike common layered oxide cathodes, like LiNiO2 (LNO), the disordered arrangement of cations in the network enables isotropic, small volume changes for enhanced stability and electrochemical properties. Since its discovery in 1954, LNO has been thoroughly investigated as cathode for Li-ion batteries given its high operating voltage and electrochemical capacity. However, its commercial use has been hindered by its thermal instability at high degrees of de-lithiation as well as by its fast capacity fade upon consecutive cycles. We have recently developed a method to convert the layered (LNO) into a cation-disordered rock salt (DRS-LNO) via gradual introduction of disorder resulting in an improvement in its electrochemical performance. With this proposal we intend to unveil the structure of new partially disordered LNO (PD-LNO) cathode materials showing different capacity and stability depending on the degree of disorder in the system. Big-box modelling of this data will provide definitive information on the local atomic rearrangements and its effect on the O-redox and electronic structure of the material, to provide a fundamental understanding on the mechanism behind the differences in capacity and stability observed in these materials.

阳离子无序氧化物（cation-disordered oxides）凭借其极高的比容量（约300 mAh g⁻¹）与优异的化学可调性，作为下一代高能量密度锂离子电池正极材料受到广泛关注。此外，与常见的层状氧化物正极（layered oxide cathode），如LiNiO₂（LNO）不同，晶格中阳离子的无序排布可实现各向同性的体积小幅变化，从而提升材料稳定性与电化学性能。
自1954年被发现以来，LiNiO₂（LNO）因其高工作电压与电化学比容量，被广泛研究用作锂离子电池正极材料。然而，其商业化应用受到阻碍：在高脱锂（de-lithiation）程度下材料热稳定性极差，且连续循环过程中容量衰减迅速。
本团队近期开发了一种方法，通过逐步引入无序结构将层状LNO转化为阳离子无序岩盐结构（cation-disordered rock salt）的LNO（DRS-LNO），显著改善了其电化学性能。本项目旨在解析新型部分无序LNO（PD-LNO）正极材料的结构——这类材料的比容量与稳定性随体系内无序程度的不同而呈现差异。通过对本数据集开展大规模建模，可明确获取局域原子重排信息，及其对材料氧氧化还原（O-redox）与电子结构的影响，从而从根本上阐明这类材料比容量与稳定性差异背后的机制。