Object-Space Optimization of Tomographic Reconstructions for Additive Manufacturing.

ABSTRACT: Volumetric 3D printing motivated by computed axial lithography enables rapid printing of homogeneous parts but requires a high dimensionality gradient-descent optimization to calculate image sets. Here we introduce a new, simpler approach to image-computation that algebraically optimizes a model of the printed object, significantly improving print accuracy of complex parts under imperfect material and optical precision by improving optical dose contrast between the target and surrounding regions. Quality metrics for volumetric printing are defined and shown to be significantly improved by the new algorithm. The approach is extended beyond binary printing to grayscale control of conversion to enable functionally graded materials. The flexibility of the technique is digitally demonstrated wi

SUBMITTER: Rackson CM 

PROVIDER: S-EPMC8656269 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature