Abstract
Direct Ink Writing (DIW), which is widely used for developing functional 3D scaffolds that have robust structural integrity for the growth of target tissues/cells, has emerged as an appealing method for biomedical applications. The production of 3D structures involves three separate but interconnected stages (material development, printing process, and post-printing treatment), whose effectiveness is influenced by several factors that therefore make it challenging to optimize the entire procedure. By studying the material processability and leveling the printing settings, this study proposes a three-step method to enhance the ink property design and the printer’s performance. The recommended approach is focused on the thorough study of alginate–gelatin hydrogel properties, which is a commonly used ink in biomedical applications, due to its natural origin through marine flora, as well as the development process parameters and their intercorrelations. Principal Component Analysis in comparison with K-means clustering was applied to reveal material properties that are highly correlated with additive manufacturing (AM) processability, and Taguchi’s Design of Experiments (DOE) determined the printing settings (primary and secondary) for achieving optimum printing accuracy. PCA results were affirmed by K-means clustering and showed that viscosity, m, G′ and G″ govern blends’ printing behavior while application of DOE led to 85% pore area printability.
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