Abstract
Lattice thermal conductivity (κL) plays a crucial role in the thermal management of electronic devices. In this study, we systematically investigate the thermal transport properties of monolayer fluorinated graphene using a combination of machine learning-based interatomic potentials and the phonon Boltzmann transport equation. At a temperature of 300 K, we find that the κL values for chair-configured fluorinated graphene monolayers are 184.24 W m-1 K-1 in the zigzag direction and 205.57 W m-1 K-1 in the armchair direction. For the boat configuration, the κL values are 120.45 W m-1 K-1 and 64.26 W m-1 K-1 in the respective directions. The disparities in κL between these two configurations predominantly stem from differences in phonon relaxation times, which can be elucidated by examining the Grüneisen parameters representing the degree of anharmonicity. A more in-depth analysis of bond strengths, as assessed by the crystal orbital Hamiltonian population, reveals that the stronger in-plane CC bonds in chair-configured fluorinated graphene monolayers are the primary contributors to the observed variations in anharmonicity.
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