Modeling meso- and microstructure in materials patterned with acoustic focusing. (April 2021) - Melchert, Drew S.; Johnson, Keith; Giera, Brian; Fong, Erika J.; Shusteff, Maxim; Mancini, Julie; Karnes, John J.; Cobb, Corie L.; Spadaccini, Christopher; Gianola, Daniel S.; Begley, Matthew R.
Abstract: We conduct numerical simulations of acoustic focusing in dense suspensions to map the design space of acoustically patterned materials and understand the relationships between input parameters, structural features, and functional properties. We develop closed-form expressions for acoustic forces on particles, enabling rapid simulation of thousands of particles, and find excellent agreement with experimentally focused patterns over a range of conditions. We map the geometrical and microstructural features of focused particle patterns and their dependence on processing parameters. We find that mesostructural geometrical features (focused line height, width, and profile shape) can be controlled reliably over a broad range by modulating input parameters, and that while microstructural features are less readily modulated via input parameters, they are well-suited for various transport properties in functional materials. Notably, packing density nears the random close packing limit at 0.64, and particle contact density shows anisotropy favoring particle contacts along the focused lines. These results guide process design for controlling the properties of patterned materials, and outline the property ranges accessible via acoustic focusing. Additionally, we discuss the dependence of material functionalities, particularly electrical, thermal, and ionic transport properties, on the meso- and micro-structural features of patterned composite materials in the context of acoustic focusing. Graphical abstract: Unlabelled Image Highlights: Efficient models of acoustic forces on particles enable simulation of the acoustic assembly process in patterned composite compomaterials. These simulations elucidate the dependence of the materials' mesostructural properties on acoustic, material, and device parameters. Property maps enable design of material patterning processes for incorporation into fabrication, especially 3D printing techniques. Experimental validation shows excellent agreement with the modeled meso-structural properties. Dense packing and anisotropy in particle contact density are auseful for electrical, thermal, and ionic transport applications.