Abstract
Modern battery materials can contain many elements with substantial site disorder, and their configurational state has been shown to be critical for their performance. The intercalation voltage profile is a critical parameter to evaluate the performance of energy storage. The application of commonly used cluster expansion techniques to model the intercalation thermodynamics of such systems ab initio is challenged by the combinatorial increase in configurational degrees of freedom as the number of species grows. Such challenges necessitate the efficient generation of lattice models without overfitting and proper sampling of the configurational space under the requirement of charge balance in ionic systems. In this work, we introduce a combined approach that addresses these challenges by (1) constructing a robust cluster expansion Hamiltonian using the sparse regression technique, including -norm regularization and structural hierarchy; and (2) implementing semigrand-canonical Monte Carlo to sample charge-balanced ionic configurations using the table-exchange method and an ensemble average approach. These techniques are applied to a disordered rocksalt oxyfluoride (LMNOF) that is part of a family of promising earth-abundant cathode materials. The simulated voltage profile is found to be in good agreement with experimental data and particularly provides a clear demonstration of the and oxygen contributions to the redox potential as a function of content.
- Received 10 July 2023
- Revised 16 August 2023
- Accepted 30 August 2023
DOI:https://doi.org/10.1103/PRXEnergy.2.043005
Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI.
Published by the American Physical Society
Physics Subject Headings (PhySH)
Popular Summary
Disordered rocksalt (DRX) cathodes with earth-abundant transition metals offer an attractive alternative to expensive nickel-manganese-cobalt-based cathodes. However, the complex structure and redox behavior of DRX cathodes make it difficult to calculate their fundamental properties and expected performance with lithium cycling. Here, the authors introduce an approach that addresses these challenges with a combined method that uses sparse regression to construct a cluster-expansion Hamiltonian and semigrand-canonical Monte Carlo simulations to sample the energies of charge-balanced ionic configurations. These techniques are applied to DRX oxyfluoride LiMnNbOF to predict its voltage profile with lithium intercalation. The simulated profile agrees well with experimental data and provides a clear demonstration of the manganese and oxygen contributions to the redox potential as a function of Li content. The methods developed here for DRX cathodes will be useful for modeling other complex ionic materials with multiple redox-active species and a disordered structure.
