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Polymer-based nanocomposites emerged in the 1960s as a groundbreaking approach to advanced materials. By incorporating robust, durable, and multifunctional nanomaterials into a polymer matrix, the performance of nanocomposites has significantly surpassed that of the base polymers. However, over the past six decades, the challenges of achieving uniform nanomaterial dispersion and the resulting non-uniform properties have impeded further progress in this field. Here, we present a polymer-based nanocomposite with highly dispersed nanomaterials, achieved through aerosol-jet-based multi-material three-dimensional (AM3D) printing. This method allows precise programming of the nanocomposite's composition, structure, and dispersity. Numerical simulations in the design of AM3D printing system facilitate the avoidance of interfacial compatibility issue among heterogeneous aerosols, enabling distributed printing without nanomaterial agglomeration. As a result of this high level of dispersion and distribution, the 3D structured nanocomposite exhibits a uniform dielectric constant and low dielectric loss across the entire printed area. This work establishes an engineering framework for defect-free nanocomposites and significantly expands the range of polymer-based multi-material nanocomposite that can be designed and manufactured with complex architectures.

A single-stage transonic axial-flow fan is simulated using graphic processing unit (GPU)-accelerated wall-modeled large-eddy simulations. The computational meshes are generated using Voronoi diagram-based approach. Two types of mesh are employed for grid sensitivity study. The first type uses isotropic hexagonal close-packed (HCP) seeding whereas the second combines the background HCP mesh with anisotropic boundary-layer type of mesh around the blade surfaces. The effect of the rotor tip clearance is examined using a rotor-only configuration. The sweep of the performance curve at full rotation speed is carried out for both the rotor and the stage. The computational results are compared against the experimental measurement and excellent agreement is observed when adequate near-wall resolution is employed. The code performance of the GPU-accelerated solver is compared to the CPU-based version. The high throughput of the GPU solver significantly reduces the computational cost. On a mesh with 84 million control volumes, 10 rotor revolutions can be computed within 1 day using 20 GPUs.