First-principles prediction of the thermal conductivity of two configurations of difluorinated graphene monolayer

文献情報

出版日 2023-11-25

DOI 10.1039/D3CP04923J

インパクトファクター 3.676

著者

Ao Chen, Hua Tong, Cheng-Wei Wu, Shi-Yi Li, Pin-Zhen Jia, Wu-Xing Zhou

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要旨

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.

掲載誌

Physical Chemistry Chemical Physics

CiteScore: 5.5

自己引用率: 10.3%

年間論文数: 3036

Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.