Bioinspired fluidic design for additive manufacturing

Abstract While resin 3D printing affords designers unprecedented geometric complexity, currently the technology struggles to find real-world adoption in manufacturing settings due to slow print speeds, poor reliability, and cumbersome support structures. The last of these are not user-friendly in numerous ways; they are materially wasteful, human labor-intensive, time-consuming to remove, damaging to surface finish, and often unreliable in ensuring printability in the first place. These limitations are fundamentally related to adhesion forces and a lack of control of fluid flow during the printing process. Current design for additive manufacturing (DfAM) industry standards do not seek to offset such forces; instead, they empirically call for reducing printing speeds and/or imposing cumbersome supporting structures. Injection continuous liquid interface production (iCLIP) is a recent approach capable of effectively nullifying such forces by injecting resin into the deadzone. The method has been demonstrated to date for the case of a single channel running through an object formed of rigid material. However, the possibility of innervating the growing object with multiple channels -- possible to engineer into the CAD design uniquely for every print by this fabrication approach -- remains unexplored. Inspired by the complex three-dimensional fluidic distribution networks engineered by biological systems across scales, in this work we define and evaluate a qualitatively new bioinspired DfAM approach to accompany iCLIP, optimally innervating the part with channels to infuse resin into the deadzone. We detail our modeling approach for both single and multiple injection sites, and for Newtonian and non-Newtonian resins. After describing our hardware implementation to evaluate our approach, we provide experimental validation for our simulation-driven injection scheme, including using both rigid and elastomeric resins. We demonstrate such a bioinspired design approach can significantly increase print speed and reduce the need for supports in a user’s 3D model. In doing so, our approach promises to enhance the scalability of resin 3D printing to hasten its adoption in real-world manufacturing settings.