Dataset Information

2.5D printing of a yield-stress fluid.

ABSTRACT: We report on direct ink writing of a model yield-stress fluid and focus on the printability of the first layer, the one in contact with the supporting substrate. We observe a diversity of deposition morphologies that depends on a limited set of operational parameters, mainly ink flow rate, substrate speed and writing density, and also on material properties (e.g., yield-stress). Among these morphologies, one of them does not depend on fluid properties (as long as the fluid displays some yield-stress) and consists of flat films whose thickness is controllable in a significant range, about [Formula: see text] mm, and tunable in real time during printing. We thus demonstrate the ability to print films with thickness gradients and prove that the printing fidelity is mainly due to a competition between yield-stress and capillarity.

SUBMITTER: Colanges S

PROVIDER: S-EPMC10060369 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

2.5D printing of a yield-stress fluid.

Colanges Simon S Tourvieille Jean-Noël JN Lidon Pierre P Leng Jacques J

Scientific reports 20230329 1

We report on direct ink writing of a model yield-stress fluid and focus on the printability of the first layer, the one in contact with the supporting substrate. We observe a diversity of deposition morphologies that depends on a limited set of operational parameters, mainly ink flow rate, substrate speed and writing density, and also on material properties (e.g., yield-stress). Among these morphologies, one of them does not depend on fluid properties (as long as the fluid displays some yield-st ...[more]

PMID: 36991085

Similar Datasets

Project description:Composite hydrogels have gained great attention as three-dimensional (3D) printing biomaterials because of their enhanced intrinsic mechanical strength and bioactivity compared to pure hydrogels. In most conventional printing methods for composite hydrogels, particles are preloaded in ink before printing, which often reduces the printability of composite ink with little mechanical improvement due to poor particle-hydrogel interaction of physical mixing. In contrast, the in situ incorporation of nanoparticles into a hydrogel during 3D printing achieves uniform distribution of particles with remarkable mechanical reinforcement, while precursors dissolved in inks do not influence the printing process. Herein, we introduced a "printing in liquid" technique coupled with a hybridization process, which allows 3D freeform printing of nanoparticle-reinforced composite hydrogels. A viscoplastic matrix for this printing system provides not only support for printed hydrogel filaments but also chemical reactants to induce various reactions in printed objects for in situ modification. Nanocomposite hydrogel scaffolds were successfully fabricated through this 3D freeform printing of hyaluronic acid (HAc)-alginate (Alg) hydrogel inks through a two-step crosslinking strategy. The first ionic crosslinking of Alg provided structural stability during printing, while the secondary crosslinking of photo-curable HAc improved the mechanical and physiological stability of the nanocomposite hydrogels. For in situ precipitation during 3D printing, phosphate ions were dissolved in the hydrogel ink and calcium ions were added to the viscoplastic matrix. The composite hydrogels demonstrated a significant improvement in mechanical strength, biostability, as well as biological performance compared to pure HAc. Moreover, the multi-material printing of composites with different calcium phosphate contents was achieved by adjusting the ionic concentration of inks. Our method greatly accelerates the 3D printing of various functional or hybridized materials with complex geometries through the design and modification of printing materials coupled with in situ post-printing functionalization and hybridization in reactive viscoplastic matrices.

Dataset Information

2.5D printing of a yield-stress fluid.

Publications

2.5D printing of a yield-stress fluid.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets