Direct Ink Writing of Alginate–Gelatin Hydrogel: An Optimization of Ink Property Design and Printing Process Efficacy

Author:

Kaliampakou Christina1,Lagopati Nefeli23ORCID,Charitidis Costas A.1ORCID

Affiliation:

1. RNanoLab, Research Unit of Advanced, Composite, Nano Materials & Nanotechnology, School of Chemical Engineering, National Technical University of Athens, 9 Heroon, Polytechniou St., Zografos, 15780 Athens, Greece

2. Laboratory of Biology, Department of Basic Medical Sciences, Medical School, National and Kapodistrian University of Athens, 11527 Athens, Greece

3. Biomedical Research Foundation, Academy of Athens, 11527 Athens, Greece

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.

Funder

NTUA-supported PhD Scholarship

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

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