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Acoustic patterning of 3D printed composites for anisotropic conductivity and multifunctionality


A versatile class of composite materials composed of functional filler particles in polymer matrices are increasingly used in high-performance applications that leverage their adaptable mechanical, electrical, thermal, and other functional properties. The choice of constituent materials largely determines these properties: for example, long fibers redistribute stress efficiently, highly conductive filler particles impart their conductivity to the material, and combinations of ionic and electrically conductive fillers with energy storage materials increase the capacity of battery electrodes. The performance of these composites, however, is highly dependent on the internal arrangement of particles. Consequently, controlling this internal structure enables property improvements and novel functionalities. In particular, combining microstructure control with the design freedom of 3D printing presents opportunities to maximize the performance of functional components by spatially modulating properties and their directionality (e.g. reinforcing high-stress regions, prescribing electrical interconnects, or directing heat away from hot spots), as well as introducing novel combinations of properties.

To develop this structural control in printed materials, this work utilizes pressure fields to assemble filler particles into patterns within composites during 3D printing. Particle patterns are engineered to improve material properties by leveraging microscopic acoustic forces on particles, tailoring the particle arrangement for improvements in the functionality of the material. This acoustic patterning technique is integrated into 3D printing with attention to processing constraints (e.g. component and feature sizes, material properties, cost, throughput rate, etc.) required in existing and emerging technological applications. In particular, 3D printed composites with high electrical or thermal conductivity, which are simultaneously mechanically flexible or strain-tolerant, are targeted for advancing the emerging fields of flexible electronics and soft robotics, and for alleviating the bottleneck in cooling of electronic devices.

Acoustically patterned composites exhibit increased electrical and thermal conductivity (by many orders of magnitude under some conditions) compared to conventional, unpatterned composites via concentrated particle contact density and optimized transport pathways. Simultaneously, patterning enhances mechanical flexibility by reducing the required loading of filler particles and encapsulating conductive particle networks in thick sheathes of strain-absorbing polymer. The magnitude and directionality of electrical and thermal transport is configurable over a wide range via manipulation of the orientation and connectivity of filler particles, introducing processing routes for printing components with embedded electrical interconnects or directional cooling networks.

Computational modeling of acoustic forces probes the design space of possible particle structures, which are compared to detailed particle-level material characterization to understand and then optimize the patterning process for desired microstructures. These structural details inform the physics of electrical and thermal conduction between particles in the material as well as particle rearrangements during mechanical deformation. Finally, this work investigates methods for expanding control over composite microstructure, including patterning hierarchically structured particles and manipulating particles with multiple external fields.

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