Equilibrium Molecular Dynamics (MD) Simulation Study of Thermal Conductivity of Graphene Nanoribbon: A Comparative Study on MD Potentials

• Main Authors: Asir Intisar Khan, Ishtiaque Ahmed Navid, Maliha Noshin, H. M. Ahsan Uddin, Fahim Ferdous Hossain, Samia Subrina
• Format: Article
• Language: English
• Published: MDPI AG 2015-12-01
• Series: Electronics
• Subjects: thermal conductivity; graphene nanoribbon; equilibrium molecular dynamics; Green-Kubo; optimized Tersoff potential; 2nd generation REBO potential
• Online Access: http://www.mdpi.com/2079-9292/4/4/1109

The thermal conductivity of graphene nanoribbons (GNRs) has been investigated using equilibrium molecular dynamics (EMD) simulation based on Green-Kubo (GK) method to compare two interatomic potentials namely optimized Tersoff and 2nd generation Reactive Empirical Bond Order (REBO). Our comparative study includes the estimation of thermal conductivity as a function of temperature, length and width of GNR for both the potentials. The thermal conductivity of graphene nanoribbon decreases with the increase of temperature. Quantum correction has been introduced for thermal conductivity as a function of temperature to include quantum effect below Debye temperature. Our results show that for temperatures up to Debye temperature, thermal conductivity increases, attains its peak and then falls off monotonically. Thermal conductivity is found to decrease with the increasing length for optimized Tersoff potential. However, thermal conductivity has been reported to increase with length using 2nd generation REBO potential for the GNRs of same size. Thermal conductivity, for the specified range of width, demonstrates an increasing trend with the increase of width for both the concerned potentials. In comparison with 2nd generation REBO potential, optimized Tersoff potential demonstrates a better modeling of thermal conductivity as well as provides a more appropriate description of phonon thermal transport in graphene nanoribbon. Such comparative study would provide a good insight for the optimization of the thermal conductivity of graphene nanoribbons under diverse conditions.