DIW theoretical-experimental framework to print multifunctional soft materials
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4D printing technologies have opened new opportunities for the design and manufacturing of responsive structures. There has been a considerable interest in soft multifuncional materials, which are composed of a soft polymeric matrix filled with particles that provide a mechanical response to external stimuli, e.g., magnetic or electric actuation. These materials can mimic soft biological tissues (≈ 1−10kPa) and their mechanical behaviour can be modulated remotely, making them ideal in the bioengineering field [1]. The 3D printing of these soft materials uses reactive inks whose properties change significantly over the time. These inks are provided in a pure liquid-phase that transitions to a solid-phase. Therefore, flexibility to modulate the printing parameters during the manufacturing process is essential. To overcome this issue, other authors had proposed the inclusion of additives to enhance the printability of the material. However, these solutions do not keep the matrix and filler phases intact. In this work, we propose a new methodology that ensures optimal printability of time-dependent viscosity inks by using the direct ink writing technology (DIW) [2]. To this end, we developed an in-house printer that provides flexibility to modulate the extrusion pressure over printing time. In addition, a hybrid (theoretical-experimental) framework is proposed to predict the variation of the rheological properties of the ink during printing time. This approach provides the temporal evolution of the printing conditions that ensure efficient and robust printability over the process. This method is validated by manufacturing magnetorheological elastomers and conductive soft materials for specific bioengineering and soft electronics applications. Acknowledgment: 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). S. Garzon-Hernandez acknowledges support from the Talent Attraction grant (CM 2022 - 2022-T1/IND-23971) from the Comunidad de Madrid