Simon Daubner, Marcel Weichel, Martin Reder, Daniel Schneider, Qi Huang, Alexander E. Cohen, Martin Z. Bazant, Britta Nestler
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引用次数: 0
Abstract
Optimal microstructure design of battery materials is critical to enhance the performance of batteries for tailored applications such as high power cells. Accurate simulation of the thermodynamics, transport, and electrochemical reaction kinetics in commonly used polycrystalline battery materials remains a challenge. Here, we combine state-of-the-art multiphase field modelling with the smoothed boundary method to accurately simulate complex battery microstructures and multiphase physics. The phase-field method is employed to parameterize complex open pore cathode microstructures and we present a formulation to impose galvanostatic charging conditions on the diffuse boundary representation. By extending the smoothed boundary method to the multiphase-field method, we build a simulation framework which is capable of simulating the coupled effects of intercalation, anisotropic diffusion, and phase transitions in arbitrary complex polycrystalline agglomerates. This method is directly compatible with voxel-based data, e.g., from X-ray tomography. The simulation framework is used to study the reversible phase transitions in LiXNiO2 in dense and nanoporous agglomerates. Based on the thermodynamic consistency of phase-field approaches with ab-initio simulations and the open circuit potential, we reconstruct the Gibbs free energies of four individual phases (H1, M, H2 and H3) from experimental cycling data. The results show remarkable agreement with previously published DFT results. From charge simulations, we discover a strong influence of particle morphology on the phase transition behaviour, in particular a shrinking core-like behaviour in dense polycrystalline structures and a particle-by-particle mosaic behavior in nanoporous samples. Overall, the proposed simulation framework enables the detailed study of phase transitions in intercalation materials to enhance microstructure design and fast charging protocols.
期刊介绍:
npj Computational Materials is a high-quality open access journal from Nature Research that publishes research papers applying computational approaches for the design of new materials and enhancing our understanding of existing ones. The journal also welcomes papers on new computational techniques and the refinement of current approaches that support these aims, as well as experimental papers that complement computational findings.
Some key features of npj Computational Materials include a 2-year impact factor of 12.241 (2021), article downloads of 1,138,590 (2021), and a fast turnaround time of 11 days from submission to the first editorial decision. The journal is indexed in various databases and services, including Chemical Abstracts Service (ACS), Astrophysics Data System (ADS), Current Contents/Physical, Chemical and Earth Sciences, Journal Citation Reports/Science Edition, SCOPUS, EI Compendex, INSPEC, Google Scholar, SCImago, DOAJ, CNKI, and Science Citation Index Expanded (SCIE), among others.