Abstract
Newly developed high thermal conductivity polymer composite 3D printing filaments are used to characterize the thermal properties as a function of print orientation. The thermal conductivity of a printed part is anisotropic and varies by 2-6 times depending on the print direction - demonstrating higher conductivity in the deposition direction (in-plane) than in the two directions perpendicular to the deposition direction (cross-plane and through-plane). Therefore, deposition path planning greatly affects the overall heat dissipation rate and the performance of the heat sink. Traditionally, 3D printing slicers generate deposition paths based solely on geometric constraints. This work investigates a new approach of deposition path planning assisted by computational predictions of the heat sink thermal performance. The proposed approach uses a thermal simulation of a 3D-printed part, accounting for the anisotropic thermal properties, and the orientation of the local material properties are assigned based on the deposition path in multiple print orientations. The performances predicted via the simulations are compared, and the optimal deposition path is determined. For the highest thermal conductivity 3D printing filament (~ 12 W/m- K in-plane), a heat sink printed with the print direction parallel to the fins z-axis had ~20% improved performance in comparison to a heat sink with print direction perpendicular to the fins z-axis. Moreover, a plastic 3D printed heat sink was able to perform within 7% of an extruded Aluminum heat sink with similar geometry under natural convection. The computational predictions show the same trend as experimental measurements using 3D printed heat sinks.
