Effect of cation-disorder on lithium transport in halide superionic conductors
arXiv:2403.08237 · doi:10.1021/acsenergylett.4c00799
Abstract
LiZrCl (LZC) is a promising solid-state electrolyte due to its affordability, moisture stability, and high ionic conductivity. We computationally investigate the role of cation disorder in LZC and its effect on Li-ion transport by integrating thermodynamic and kinetic modeling. The results demonstrate that fast Li-ion conductivity requires Li/vacancy disorder, which is dependent on the degree of Zr disorder. The high temperature required to form equilibrium Zr-disorder precludes any equilibrium synthesis processes for achieving fast Li-ion conductivity, rationalizing why only non-equilibrium synthesis methods, such as ball milling, lead to good conductivity. Our simulations show that Zr disorder lowers the Li/vacancy order-disorder transition temperature, which is necessary for creating high Li diffusivity at room temperature. These insights raise a challenge for the large-scale production of these materials and the potential for the long-term stability of their properties.
References in corpus (4)
- Multicomponent multisublattice alloys, nonconfigurational entropy and other additions to the Alloy Theoretic Automated Toolkit
- Active learning of reactive Bayesian force fields: Application to heterogeneous hydrogen-platinum catalysis dynamics
- Stacking Faults Assist Lithium-Ion Conduction in a Halide-Based Superionic Conductor
- Modeling intercalation chemistry with multi-redox reactions by sparse lattice models in disordered rocksalt cathodes
Cited by in corpus (3)
- Benchmarking CHGNet Universal Machine Learning Interatomic Potential Against DFT and EXAFS: Case of Layered WS2 and MoS2
- Machine-Learning-Guided Insights into Solid-Electrolyte Interphase Conductivity: Are Amorphous Lithium Fluorophosphates the Key?
- Data-driven Prediction of Ionic Conductivity in Solid-State Electrolytes with Machine Learning and Large Language Models