Thermal conductivity of graphene polymorphs and compounds: from C3N to graphdiyne lattices
arXiv:1910.02929 · doi:10.1016/j.carbon.2020.02.007
Abstract
Tremendous experimental and theoretical attempts to find carbon based two-dimensional semiconductors have yielded a wide variety of graphene polymorphs, such as carbon-nitride, carbonboride, graphyne and graphdiyne 2D materials with highly attractive physical and chemical properties. In this study, by conducting extensive non-equilibrium molecular dynamics simulations, we have calculated and compared the thermal conductivity of thirteen prominent carbon-based structures at different lengths and two main chirality directions. Acquired results show that the structures of C3N, C3B and C2N exhibit the highest thermal conductivity, respectively, which suggest them as suitable candidates for thermal management systems in order to enhance the heat dissipation rates. In contrast, generally graphdiyne lattices and in particular 18-6-Gdy graphdiyne yields the lowest thermal conductivity, which can be a promising feature for thermoelectric applications. As a remarkable finding, we could establish connections between the thermal conductivity and density or Young's modulus of carbon based 2D systems, which can be employed to estimate the thermal conductivity of other polymorphs. Those results can provide a comprehensive viewpoint on the thermal transport properties of the nonporous and exceedingly porous carbon based 2D materials and may be used as useful guides for future designs in thermal management.
References in corpus (19)
- Electric Field Effect in Atomically Thin Carbon Films
- Van der Waals heterostructures
- Dimensional crossover of thermal transport in few-layer graphene materials
- Optimized Tersoff and Brenner empirical potential parameters for lattice dynamics and phonon thermal transport in carbon nanotubes and graphene
- Length-dependent thermal conductivity in suspended single-layer graphene
- Assessment of the Thermal Conductivity of BN-C Nanostructures
- Electron properties of fluorinated single-layer graphene transistors
- Ultra high stiffness and thermal conductivity of graphene like C3N
- Outstanding strength, optical characteristics and thermal conductivity of graphene-like BC and BCN semiconductors
- Enhancement in hydrogen storage capacities of light metal functionalized Boron Graphdiyne nanosheets
- Mechanical properties and thermal conductivity of graphitic carbon nitride: A molecular dynamics study
- Thermal Conductivity and Mechanical Properties of Nitrogenated Holey Graphene
- Boron-graphdiyne: superstretchable semiconductor with low thermal conductivity and ultrahigh capacity for Li, Na and Ca ions storage
- N-Graphdiyne two-dimensional nanomaterials: Semiconductors with low thermal conductivity and high stretchability
- N-, P-, As-triphenylene-graphdiyne: Strong and stable 2D semiconductors with outstanding capacities as anodes for Li-ion batteries
- Modulating the electronic properties of graphdiyne nanoribbons
- N-, B-, P-, Al-, As-, Ga-graphdiyne/graphyne lattices: First-principles investigation of mechanical, optical and electronic properties
- Anisotropic Elastic Modulus, High Poisson's ratio and Negative Thermal Expansion of Graphynes and Graphdiynes
- First-principles study of phononic thermal transport in monolayer C3N: a comparison with graphene
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