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In this paper, efficiency of defected graphene nano ribbon incorporating with additional nanoparticles on mass detection operations is studied via the Reverse Non Equilibrium Molecular Dynamics (RNEMD) method. Thermal conductivity management of this structure is challenging because of imposed losses in electrical conductivity and any procedure could manage the thermal conductivity of graphene will be useful. In this paper it is observed that on the mass detection operation, due to the porosity generation in the nano ribbon surface or even creation of external nanoparticles, thermal properties of graphene change considerably. This should be noted in calibration of graphene based mass sensors. In summary, results show that the graphene’s thermal conductivity would reduce by increasing the concentration of nanoparticles and thermal conductivity of graphene is higher when porosities and impurities are at the edges. This indicates that the location of vacancies and nanoparticles influences the thermal conductivity. For a better thermal management with the help of nanoparticles, wither respect to the porosities, addition of nanoparticles decrease the thermal conductivity more and more. By increasing the cavity’s diameter from 0.5nm to 4.4nm in a specific single layer graphene, thermal conductivity was reduced from 67 W/mk to 1.43 W/mk.

Keywords: Graphene, Thermal conductivity coefficient, Molecular Dynamics, defect, metallic nanoparticles additives

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