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Comparative analysis of the residues of granular support bath materials on printed structures in embedded extrusion printing.

Jinfeng ZengNozomi KasaharaZhengtian XieFiona LouisDonghee KangYasumasa DekishimaSetsuka KuwagakiNorihito SakaiMichiya Matsusaki
Published in: Biofabrication (2023)
Embedded extrusion printing facilitates the fabrication of complex biological structures using soft hydrogels that are challenging to construct using conventional manufacturing methods. While this targeting strategy is appealing, the residues of support materials on the printed objects have been overlooked. Here, we quantitatively compare the bath residues on fibrin gel fibers printed in granular gel baths that are conjugated with fluorescent probes for visualization, including physically crosslinked gellan gum (GG) and gelatin (GEL) baths and chemically crosslinked polyvinyl alcohol (PVA) baths. Notably, all support materials can be detected on a microscopic scale, even on structures without any visible residues. Quantitative results indicate that baths with nanoscale size or shear viscosity less than 360 Pa·s show more and deeper diffusion into the extruded inks, and the removal efficiency of support materials depends mainly on the dissolving property of the granular gel baths. The residual amount of chemically cross-linked support materials on fibrin gel fibers was 28-70 μg mm-2, which is tens of times higher than physically cross-linked GG (7.5 μg mm-2) and GEL (0.3 μg mm-2) baths. Meanwhile, cross-sectional images suggest that most gel particles are distributed around the fiber surface, but a small amount is in the fiber center. Such bath residues or the blank pores created by the removal of gel particles induce changes in product surface morphology, physicochemical and mechanical properties, impeding cell adhesion. This study will draw attention to the effects of residual support materials on printed structures and encourage the development of new strategies to diminish these residues or to take advantage of the residual support baths to improve product performances.
Keyphrases
  • hyaluronic acid
  • wound healing
  • high resolution
  • cross sectional
  • low cost
  • cell adhesion
  • deep learning
  • convolutional neural network
  • single molecule
  • atomic force microscopy
  • drug release