Thermal rectification in restructured graphene with locally modulated temperature dependence of thermal conductivity

We study thermal rectification (TR) in a selectively restructured graphene by performing deviational phonon Monte Carlo (MC) simulations with frequency-dependent phonon transport properties obtained from first principles. The restructuring is achieved by introducing vacancy defects in a portion of graphene. The defects significantly change phonon transport properties, which results in a modulation of temperature dependence of thermal conductivity. With this modulated temperature dependence, we predict TR ratio through an iterative scheme (IS), where heat flow through the system is analyzed by solving the Fourier’s law of heat conduction with spatially varying temperature-dependent thermal conductivity. To identify structure parameters for maximal TR ratio, we investigate the influence of defect size, volume percentage of defects, and system (consisting of defective and non-defective regions) length through IS analysis. As results, we find that TR ratio is mainly a function of length of defective and non-defective regions, and volume percentage of defect, whereas it is mostly independent of defect size. A longer (of the order 10 μm) non-defective side, coupled to a shorter (of the order 100 nm) defective side, can lead to large TR ratios. Finally, MC simulation for the restructured graphene (full system) is performed to verify the predictions from IS analysis. The full system calculations give similar trends but with enhanced TR ratios up to 70% for the temperature range of 200-500 K.