RT Journal Article
T1 Computationally guided DIW technology to enable robust printing of inks with evolving rheological properties
A1 Lopez Donaire, Maria Luisa
A1 Aranda-Izuzquiza, Gonzalo de
A1 Garzón Hernández, Sara
A1 Crespo Miguel, Javier
A1 Fernandez-de la Torre, Miguel
A1 Velasco Bayón, Diego
A1 García González, Daniel
AB Soft multifunctional materials allow for mechanical sensing or actuation as a response to multiple physical stimuli, while providing material stiffness that mimic soft biological tissues (≈1–10 kPa). One of the main bottlenecks in the state of the art relates to the difficulty for manufacturing complex shapes when using inks whose properties significantly change over the printing time. To overcome this issue, the implementation of a hybrid (theoretical-experimental) framework that allows optimal printability of time-dependent viscosity inks by using the direct ink writing technology. Although the rheological properties of the ink vary during printing time, a combination of theoretical and experimental methods provides evolving printing conditions that ensure efficient and robust printability over the process. The method removes the need of introducing additives to the ink. To enable this technology, an in-house printer that provides flexibility to modulate the extrusion pressure over printing time is developed. The method is validated by manufacturing magnetorheological elastomers and conductive soft materials for specific bioengineering and soft electronics applications.
PB Wiley
SN 2365-709X
YR 2023
FD 2023-02-10
LK https://hdl.handle.net/10016/36846
UL https://hdl.handle.net/10016/36846
LA eng
NO M.L.L.-D., G.d.A.-I., and S.G.-H. contributed equally to this work. The authors acknowledge support from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement No. 947723, project: 4D-BIOMAP). The authors acknowledge support from Programa de Apoyo a la Realizacion de Proyectos Interdiscisplinares de I+D para Jovenes Investigadores de la Universidad Carlos III de Madrid and Comunidad de Madrid (project: BIOMASKIN). DGG acknowledges support from the Talent Attraction grant (CM 2018 - 2018-T2/IND-9992) from the Comunidad de Madrid.
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RD 17 jul. 2024