Highly flexible, deformable, and ultralightweight structures are required for advanced sensing applications, such as wearable electronics and soft robotics. This study demonstrates the three-dimensional (3D) printing of highly flexible, ultralightweight,… Click to show full abstract
Highly flexible, deformable, and ultralightweight structures are required for advanced sensing applications, such as wearable electronics and soft robotics. This study demonstrates the three-dimensional (3D) printing of highly flexible, ultralightweight, and conductive polymer nanocomposites (CPNCs) with dual-scale porosity and piezoresistive sensing functions. Macroscale pores are established by designing structural printing patterns with adjustable infill densities, while the microscale pores are developed by phase separation of the deposited polymer ink solution. A conductive polydimethylsiloxane solution is prepared by mixing polymer/carbon nanotubes with non-solvent and solvent phases. Silica nanoparticles are utilized to modify the rheological properties of the ink, making direct ink writing (DIW) feasible. 3D geometries with various structural infill densities and polymer concentrations are deposited using DIW. The solvent is evaporated during a stepping heat treatment, leading to non-solvent droplet nucleation and growth. The microscale cellular network is developed by removing the droplets and curing the polymer. Up to 83% tunable porosity is achieved by independently controlling the macro- and microscale porosity. The effect of macroscale/microscale porosity and printing nozzle sizes on the mechanical and piezoresistive behavior of the CPNC structures is explored. The electrical and mechanical tests demonstrate a durable, extremely deformable, and sensitive piezoresistive response without sacrificing mechanical performance. The flexibility and sensitivity of the CPNC structure are enhanced up to 900 and 67% with the development of dual-scale porosity. The application of the developed porous CPNCs as piezoresistive sensors for detecting human motion is also evaluated.
               
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