Hierarchical fiber-reinforced soft-composites are composites made up of polymeric fibers (with specific material properties and hierarchical length-scales) embedded within a soft polymer matrix. Their emerging applications have highlighted the impending need to combine 3D printing (or additive manufacturing) technologies with the directed deposition of polymeric fiber networks. While the printing of multi-material polymer parts using droplet-deposition or melt-extrusion techniques is well-established, the 3D printing of hierarchical fiber-reinforced soft-composites is largely unproven. This award supports fundamental research directed towards developing 3D printing processes for these composites. The research findings will enable the development of a reliable and scalable 3D printing technology for such composites, leading to the creation of a new market-segment for 3D printers. It will also facilitate innovations in fields such as bio-inspired materials, embedded sensing, and 4D printing (3D printed products with shape-memory properties). These avenues collectively represent a multi-billion dollar world-wide market that affects key industries such as aerospace, healthcare, and defense. This award also supports educational outreach activities that will impact students in multiple institutions (including Rensselaer Polytechnic Institute and Hudson Valley community college) and the minority-serving middle/high-schools in the upstate New York area.
This research will investigate the fundamental manufacturing science and process-control problems unique to the 3D printing of hierarchical fiber-reinforced soft-composites. The PIs have recently invented a novel 3D printer that combines the conventional inkjet-based printing of ultraviolet curable polymers with the directed stamping of electrospun fiber networks. Using this 3D printing platform, the PIs will investigate the effect of key fiber and substrate properties on the fiber-transfer efficiencies and the physics of the fiber-droplet interactions encountered during the 3D printing process. On the experimental front, the research will focus on the manufacture of a diverse family of patterned fibers suitable for 3D printing, followed by process studies involving fiber-transfer efficiencies/material property characterization and high-speed imaging studies of fiber-droplet interactions. The modeling aspect of this research will focus on establishing novel control strategies tailored for 3D printing hierarchical fiber-reinforced soft-composites. The process studies will yield quantitative metrics that map the fiber-transfer efficiencies to critical process parameters such as stamping load, and fiber/substrate properties. These process maps will enable the selection of appropriate stamping load profiles while controlling the 3D printing process. The high-speed imaging study is expected to identify new droplet spreading regimes, droplet shapes and characteristic time-scales encountered during the 3D printing of hierarchical fiber-reinforced soft-composites.
