Thermal conductance bottleneck of a three dimensional graphene–CNT hybrid structure: a molecular dynamics simulation

Literature Information

Publication Date 2019-12-02
DOI 10.1039/C9CP05228C
Impact Factor 3.676
Authors

Zepei Yu


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Abstract

Three dimensional (3D) graphene–CNT hybrid structures (GCNTs) are promising materials for applications including capacitors and gas storage and separation devices, however until now their thermal conductance mechanism has scarcely been studied. These hybrid nanomaterials are particularly suitable as next-generation thermal interface materials due to the excellent thermal properties of carbon nanotubes and single atomic layer graphene. In this paper, the out-of-plane thermal conductivities of GCNTs, graphene nanomesh (GNM), and graphene sheets are investigated using molecular dynamics (MD) simulations which apply the Green–Kubo method. Distinct from GNMs and graphene sheets, the GCNTs exhibit a relatively high out-of-plane thermal conductivity, stemming from the CNTs’ ability to accelerate the energy flow. However, the GCNT out-of-plane thermal conductivity is still far lower than that of pristine graphene due to extreme phonon localizations, which are concentrated on the graphene–CNT junction regions as evidenced by the participation ratio, phonon vibrational density of states, and overlap energy. This study provides microscopic insight into the GCNT heat transfer mechanism and offers design guidelines for application of GCNTs in thermal management devices.

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Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics
CiteScore: 5.5
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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.

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