|dc.description.abstract||This dissertation focuses on the development of architected structures via direct additive manufacturing (AM) and novel template-assisted techniques for sensing and tissue engineering applications. Although AM technologies have eased the fabrication of architected structures, limitations arise while printing high-flex 3D complex shapes. To date, no feasible fabrication method has been introduced for high-flex electronics with architected complex geometries in a three-dimensional system. In the current thesis, employing a high-speed material jetting system for direct 3D printing of high-viscose silicone-based inks with carbon fiber additives is introduced. The 3D printed sandwich-like sensors with a silicone-carbon fiber layer (as the sensitive counterpart) and two silicone layers (as the protective and packaging layers) showed enhanced durability for biomonitoring applications. The carbon fiber content was optimized and set to 30 wt.% for printability, UV curability, and electrical conductivity so that high piezoresistive sensitivity (gauge factor in order of ∼400) was obtained.
However, due to the limitations of direct 3D printing, a novel template-assisted fabrication process is introduced for the development of elastomeric structures with complex-shape designs. The silicone prepolymer was engineered with additives allowing on-demand structural shrinkage upon solvent treatment, and consequently, fabrication of micrometer-size features was feasible. This enabled 3D printing at a larger scale compatible with extrusion 3D printer resolution followed by isotropic shrinkage. This procedure led to a volumetric shrinkage of up to ~70% in a highly controllable manner. In this way, pore sizes in the order of 500–600 μm were obtained.
The proposed low-cost fabrication method not only enabled the high-resolution fabrication of complex-shaped elastomeric structures but was adopted and modified for the fabrication of 3D flexible electronics. In this dissertation, a fabrication scheme based on accessible methods is introduced to surface-dope porous silicone sensors with graphene. The sensors are internally shaped using fused deposition modeling (FDM) 3D printed sacrificial molds. The presented procedure exhibited a stable coating on the porous silicone samples with long term electrical resistance durability over ∼12 months period and high resistance against harsh conditions (exposure to organic solvents). Besides, the sensors retained conductivity upon severe compressive deformations (over 75% compressive strain) with high strain-recoverability and behaved robustly in response to cyclic deformations (over 400 cycles), temperature, and humidity. The sensors exhibited a gauge factor as high as 10 within the compressive strain range of 2−10% and showed strong capability in sensing movements as rigorous as walking and running to the small deformations resulted by human pulse.
This dissertation also introduces a robust and scalable approach for forming 3D multilayered complexly architected perfusable networks within highly cellularized hydrogel constructs. Perfusable interconnected networks could assist in sustaining thick cellularized tissue constructs through uniform perfusion of body fluids. The hydrogel constructs were patterned through two-step sacrificial molding. The cell-laden hydrogel scaffolds showed high cell viability of over 90% and robust mechanical behavior.
Besides, conflicting design criteria in tissue engineering scaffolds necessitate investigating the structure-properties of the tissue engineering scaffolds and implants. This research shows that defining high local macroporosity at the implant/tissue interface improves the biological response. Gradually decreasing macroporosity from the surface to the center of the porous constructs provides mechanical strength. Furthermore, mechanical studies on the unit cell topology effects suggest that the bending dominated architectures can provide significantly enhanced strength and deformability, compared to stretching-dominated architectures in the case of complex loading scenarios.||en