Anisotropic Thermally Conductive Composites Enabled by Acoustophoresis and Stereolithography. (17th May 2022) - Melchert, Drew S.; Tahmasebipour, Amir; Liu, Xin; Mancini, Julie; Moran, Bryan; Giera, Brian; Joshipura, Ishan D.; Shusteff, Maxim; Meinhart, Carl D.; Cobb, Corie L.; Spadaccini, Christopher; Gianola, Daniel S.; et al.
Abstract: Opportunities to improve thermal management in electronic devices are currently hindered by processing constraints that limit thermal conductivity in polymer‐matrix composites. Active patterning of filler particles is a promising route to improve conductivity while retaining processability by improving particle contact density and directing heat along optimized pathways. This study employs acoustic patterning to align and compact filler particles into stripes during stereolithographic 3D printing. This approach produces polymer‐based composite materials with highly efficient embedded heat transport pathways which reach 95 vol% particle utilization (relative to the parallel conduction upper limit). These composites exhibit anisotropic thermal conductivity up to 300% higher than unpatterned composites, with in‐plane anisotropy ratios of up to 350%. Combining this high conductivity with 3D printing enables materials with engineered heat networks that optimize transport from hot spots to heatsinks while maintaining low viscosity for fast particle patterning and for infiltration around electronic components. Finally, numerical simulations of acoustic assembly of particles with varied geometry, when compared to experimentally characterized particle packing, illuminate pathways for further improving conductivity by optimizing particle geometry for alignment and stacking of particles with maximum contact surface area. Abstract : Acoustic patterning of filler particles during 3D printing endows polymer matrix composites with high, anisotropic thermal conductivity. Conductivity is enhanced 300% over unpatterned materials, and in‐plane anisotropy reaches 350%. Mechanisms revealed by microstructural characterization paired with numerical modeling of acoustic forces on fiber‐ and flake‐like particles illuminate routes to optimize acoustic particle alignment and packing for further improved conductivity.