Generalized projection optimization model for tomographic volumetric additive manufacturing

Abstract

As a recently developed 3D printing technique, tomographic volumetric additive manufacturing (VAM) enables rapid printing of freeform objects by parallelizing photopolymerization through tomographic exposure. In this tomographic exposure process, patterning resolution and conversion accuracy crucially depend on the design of tomographic projections. In this nascent field, there are only a few optimization algorithms and each proposed to cater certain special cases of the general inverse design problem. Yet, there is no comprehensive and rigorous treatment to simultaneously address the larger class of design problems involving a mix of greyscale targets, non-linear material response, spatially variant tolerance, arbitrary tomographic configuration, and complex propagation media. This paper outlines two contributions to the mathematical and computational foundation for volumetric 3D printing, namely, a general band constraint optimization model and a ray-tracing light propagation model. These advancements are crucial for VAM in creating accurate functionally graded objects in heterogeneous media. Beyond 3D printing, the findings in this work are relevant to synthesis of spatiotemporal irradiation profiles in other contexts, such as those in photografting of biological constructs, 3D neural photostimulation, and intensity-modulated radiation therapy (IMRT).