Tree-inspired radially aligned, bimodal graphene frameworks for highly efficient and isotropic thermal transport

Highly-oriented, interconnected graphene frameworks have been considered as promising candidates to realize high-performance thermal management in microelectronics. However, the obvious thermal boundary resistance and anisotropic heat conduction still remain major bottlenecks for efficient heat dissipation. Herein, a biomimetic design enabled by radially aligned, bimodal graphene frameworks (RG-Fin) is proposed to achieve highly efficient and isotropic thermal transport. An interconnected RG skeleton is prepared via a radial ice-template method, serving as the primary expressway for isotropic heat conduction. Tree-leaf-like graphene nanofins are vertically grown on the RG surface to provide additional thermal pathways for bimodal phonon transportation, which can reduce the thermal boundary resistance without degrading the thermal properties of the skeleton. An RG-Fin composite exhibits a superior thermal conductivity of 4.01 W m^-1 K^-1 (almost 20 times that of a polymer) at an ultralow loading of 1.53 vol%, demonstrating an exceptionally large thermal conductivity enhancement efficiency of 1247%, which far exceeds those of graphene-based polymer composites. Further theoretical analysis and finite element simulations reveal the critical role of the nanofins in significantly decreasing the thermal boundary resistance (by almost 27-fold). Finally, the practical thermal management of running a CPU module is demonstrated, in which the heating-up rate of the RG-Fin composite is ∼2.0 times that of a pure polymer. This strategy provides an innovative avenue for designing radially aligned networks to realize isotropic and efficient thermoconductive composites for thermal management.