Abstract
Disorder plays an increasingly important role in the design and development of high-performance battery materials and other clean energy materials like thermoelectrics and catalysts. However, conventional computational design approaches based on the thermodynamic properties of statistically averaged structures are unable to predict the accessible energy and power densities of such materials. Kinetic properties like ionic diffusion within locally resolved atomic structures is needed to perform longer time and length scale simulations like kinetic Monte Carlo in order to accurately estimate kinetic properties like power densities in battery electrodes. Here, we present and demonstrate a fast, on-the-fly, approach to calculate local diffusion barrier as a function of only the local atomic structure using machine learning and cluster expansion, particularly for Li-ions in lithium-rich transition metal oxyfluorides and the disordered rock salt (DRS) Li2−xVO2F electrodes.
Highlights
Lithium-rich transition metal oxyfluorides have garnered significant interest in recent years for their application as high energy density cathode materials for lithium-ion batteries
There are still several open questions that remain to be answered: How do we determine if the diffusing lithium atom will pass through upper or lower tetrahedron? How do non-local quantities such as the lithiation level influence the diffusion barrier? Can we develop a simple and fast computational framework to estimate diffusion barriers using descriptors that are easy to quantify? The main objective of this work is provide answers to the question above, thereby allowing one to incorporate on-the-fly estimation of lithium-ion diffusion barrier in disordered rock salt (DRS) transition metal oxyfluorides, e.g., to optimize and extend regions of high power operation
We report our work on estimating the diffusion path and the diffusion barrier using regression model fitted to the results obtained using the nudged elastic band (NEB) method based on density functional theory (DFT) calculations
Summary
Lithium-rich transition metal oxyfluorides have garnered significant interest in recent years for their application as high energy density cathode materials for lithium-ion batteries. These materials are typically synthesized using a high-energy ball-milling approach, which introduces a high degree of site disorder [1,2]. Lithium-rich transition metal oxyfluorides have a disordered rock salt (DRS) structure where lithium and transition metal occupy cationic sublattice, while oxygen and fluorine occupy the anionic sublattice. The inner workings of DRS oxyfluoride remain largely elusive, necessitating further research to gain a sufficient understanding of their thermodynamic and kinetic properties
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