Effect of Weakened Bond Covalence on the Electronic, Thermal, and Elastic Properties of Disordered Graphite Monofluorides

Graphite monofluoride ((CF)n) has promising applications as a high-energy battery cathode and is known to possess a disordered structure. Despite many previous studies, the structure–property relationship is still not well understood due to challenges in determining the effects of structural disorder. In this work, we develop a machine learning interatomic potential (MLIP) with the NequIP architecture that predicts (CF)n properties at Density Functional Theory (DFT) level accuracy. We use this potential to study possible modes of structural disorder and find that both interlayer stacking disorder and intralayer fluorine conformation disorder are required to quantitatively reproduce the experimental X-ray diffraction (XRD) pattern. The (CF)n structure–property relationship is analyzed using disordered (CF)n structures predicted by MLIP. We find that the electronic band gap increases by 0.69 eV when the structure is 0.49 eV/CF less stable than the lowest-energy structure, owing to local fluorine conformation distortion and reduced C–F bond covalence. Thermal properties, including heat capacity and vibrational entropy, are only slightly affected by thermodynamic instability, by less than 15%. Both bulk and shear moduli decrease linearly by over 40% as the formation energy increases by 0.49 eV/CF. This increase in formation energy is also linearly correlated with elongation of the C–C and C–F bonds, which indicates a decrease in bond covalence. We believe that these correlations pave the way for a more thorough understanding of (CF)n, and could serve as a useful metric for designing (CF)n with a low electronic band gap and high elasticity.