Modeling and spatio-temporal optimization of grayscale digital light processing 3D-printed structures with photobleaching resins

Abstract

Grayscale digital light processing (DLP) 3D printing modulates light intensity in each pixel through grayscale values, offering a promising approach for achieving high-resolution printed structures. However, existing theoretical models and optimization methods typically rely on the assumuption of a photo-invariant resin, for simplification. This study demonstrates that the curing depth varies even when the total accumulated dose remains constant, indicating a photo-variant effect. To address this, a spatio-temporal optimization method along with a model are developed, incorporating photobleaching effects, multilayer exposure, and Gaussian beam propagation. The model accurately predicts variations in curing depths at constant doses. Structures are optimized using this model, resulting in several significant improvements: channel heights are reduced to approximately one-fifth of the empirical minimum value with variations below 10 %; concave lenses are optimized with smooth surfaces; and the stair-stepping effect is notably reduced. Additionally, an asymmetric stair-stepping effect is identified between the left and right sides of objects printed at the corner, primarily caused by light divergence. The developed model and spatio-temporal optimization algorithm pave the way for high-fidelity grayscale DLP 3D printing.