Abstract
Doping and intercalation ion disordering complicate drastically computer modeling of cathode material properties and behavior during charge-discharge processes. For layered cathode material, parameters of the energetically favored entries of compositional/configurational spaces (CCS) are known to correlate well with the CCS mean values. For the CCS (20760 configurations) of commercially used Li1-xNi0.8Co0.15Al0.05O2, a comparative analysis of electrostatic energies and those obtained using first-principles calculations was performed. Based on the Coulomb energy values, the CCS subgroups containing energetically favorable configurations (ca. 25% of the total number of CCS entries) can be identified reliably for Li deficiencies x ≤ 0.5. Further delithiation results in discrepancies between the title methods demonstrating a limited applicability of the simplified selection procedure. The most apparent reason for this is dispersion interaction which can significantly influence structure behavior and shift energetic properties of the layered cathode materials at high lithium deintercalation levels.
Highlights
Comprehensive computer modeling approaches applied to investigations of compositional/configurational spaces (CCSs) of existing or hypothetic compounds allows one to distinguish the most relevant and reliable composition-structure-property correlations and, provides a tool for modifications of material properties, synthesis of new compounds, etc
Based on the DFT-vdW results for NCA, it was shown that the structural peculiarities and charge distributions of the most energetically favorable configuration are in a good consistence with the full CCS Boltzmann averages calculated at each delithiation level
The CCS complexity can be reduced by a factor of ca. 4 (27% configurations) using the Coulomb energy-based selection
Summary
Comprehensive computer modeling approaches applied to investigations of compositional/configurational spaces (CCSs) of existing or hypothetic compounds allows one to distinguish the most relevant and reliable composition-structure-property correlations and, provides a tool for modifications of material properties, synthesis of new compounds, etc. Such correlations can be effectively used to predict the stability and/or behavior of a functional material vs its chemical composition avoiding long-term synthesis, treatment and experimental measurement for a series of compounds [1]. The efficiency of reducing the number of independent configurations in the proposed scheme is investigated within the current research
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